Stdc 2014 proceedings book

Symposium on Sustainable Technology

and Development

STDC -2014 Proceedings

One Day National Symposium

21st April, 2014

Organized by

Department of Engineering

Al Musanna College of Technology, Sultanate of Oman

Editors

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“STDC 2014- Proceedings” Edited by Mr. James Joseph and Dr. C Ravichandran

© Al Musanna College of Technology, Oman ,April 2014

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About the Symposium

Sustainable development is often interpreted as meeting the needs of the present

without compromising the ability of future generation to meet their own need. In order for a country to be sustainable it must meet the environmental, economic, and social needs of its citizens. In order to achieve a sustainable life, a balance and equal distribution of natural resources is necessary throughout the world so that basic needs of each and every living being may be fulfilled. Sustainable Development as a norm has been accepted in the literature ever since the publication of the Brundtland Commission report in 1987. It is a pattern of social and structured economic transformations that optimizes the economic and societal benefits available in the present, without jeopardizing the likely potential for similar benefits in the future.

There is growing concern nationally and internationally about environment, energy, climate change, biodiversity, water and industrial development. It is important to view sustainable efforts from global perspective that addresses socio-economic and environmental issues. In the long term, responsible use of natural resources now will help ensure that there are resources available for sustained industrial growth far into the future.

Sustainable development must be taken up by society at large as a principle guiding the many choices each citizen makes every day, as well as the big political and economic decisions that have. This requires profound changes in thinking, in economic and social structures and in consumption and production patterns. This symposium will provide an in-depth discussion on environment, biodiversity, energy and other issues related to sustainable development.

The main thrust of this one-day symposium is to provide a forum to scientific community to interact and exchange information for accomplishment of new horizon in sustainable development.

Mr. James Joseph/Dr. C Ravichandran

Conveners - STDC2014

Al Musanna College of Technology

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Content List

About The College Vision Mission About The Department Of Engineering Symposium Objective Symposium Topics Message from the Dean Message from the Head, Department of Engineering 1. Carbon Dioxide Capture, Transport and Sequestration to Abate Global Warming

Ammera Salim Al Sharji, Badriya Mohammed Al Hatmi, Maryam Mohammed Al-Roshdi, Taimoora Nasser

Al Hasani and S. Murthy Shekhar

2. Prediction of Excess Air Requirement Using ANN for the Improvement of Boiler Efficiency

Arun. S. Gopinath and N. Sreenivasa Babu

3. Investigation of Sustainable Development in Omani Manufacturing Firms: Evidence from Industrial

Company

Ibrahim Garbie, Zuwaina Al Bahri, Jamila Al Yahmedi and Najia Al Shandudi

4. Design and development of an infrared heater for waste plastic gasification

Zuhair E. M. Haruon

5. Study of Microwave Radiation on Transesterification of Jatropha Oil in Presence of Acid Catalyst

Nadira Hassan Mohammed Al Balushi and Priy Brat Dwivedi

6. Microwave assisted Trans-esterification of waste cooking oil in presence of Alkali Catalyst

Hasna Khalfan AlSuleimani, and Priy Brat Dwivedi

7. A review of optimum sizing techniques for off-grid Hybrid PV-Wind Renewable Energy Systems

Ahmed Said Al Busaidi, Hussein A Kazem, and Mohammad Farooq Khan

8. E-Waste: An Emerging Problem of Innovative Society

Rahila N. Gadi, and Nabeel Ahmed N.Gadi

9. Using a New Programme to Predict Thermal Comfort as a Base to Design Energy Efficient Buildings

Hanan Al-Khatri, and Mohamed B. Gadi

10. Trend Analysis of Climate Variability in Salalah, Oman

Mohammed Al-Habsi, Luminda Gunawardhana, and Ghazi Al-Rawas

Papers/Carbon%20Dioxide%20Capture,%20Transport%20and%20Sequestration%20to%20Abate%20Global%20Warming.pdf

Papers/Prediction%20of%20Excess%20Air%20Requirement%20Using%20ANN%20for%20the%20Improvement%20of%20Boiler%20Efficiency.pdf

Papers/Investigation%20of%20Sustainable%20Development%20in%20Omani%20Firms.pdf

Papers/Investigation%20of%20Sustainable%20Development%20in%20Omani%20Firms.pdf

Papers/Design%20and%20Development%20of%20An%20Infrared%20Heater%20For%20Waste%20Plastic%20Gasification.pdf

Papers/Study%20of%20Microwave%20Radiation%20on%20%20Transesterification%20of%20Jatropha%20Oil%20in%20Presence%20of%20Alkali%20Catalyst.pdf

Papers/Microwave%20Assisted%20Trans-esterification%20of%20Waste%20Cooking%20Oil%20in%20Presence%20of%20Alkali%20Catalyst.pdf

Papers/A%20Review%20of%20Optimum%20Sizing%20Techniques%20for%20Off-Grid%20Hybrid%20PV-Wind%20Renewable%20Energy%20Systems.pdf

Papers/E-Waste%20An%20Emerging%20Problem%20of%20Innovative%20Society.pdf

Papers/Using%20a%20New%20Programme%20to%20Predict%20Thermal%20Comfort%20as%20a%20Base%20to%20Design%20Energy%20Efficient%20Buildings.pdf

Papers/Trend%20Analysis%20of%20Climate%20Variability%20in%20Salalah,%20Oman.pdf

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11. Wadi Flow Simulation Using Tank Model in Muscat, Oman

Mohammed Al-Housni, Luminda Gunawardhana , and Ghazi Al-Rawas

12. An Assessment of Temperature and Precipitation Change Projections in Muscat, Oman from

Recent Global Climate Model Simulations

Abdulaziz Al-Ghafri, Luminda Gunawardhana , and Ghazi Al-Rawas

13. Assessment of Embodied Energy in the Production of Ultra High Performance Concrete (UHPC)

Aysha. H, T. Hemalatha, N. Arunachalam, A. Ramachandra Murthy and Nagesh R. Iyer

14. Investigation of Mechanical Properties of Aluminium 6061 Alloy Friction Stir Welding

J. Stephen Leon and V. Jayakumar

15. Effect of Fiber Length on the Short-Term Flexural Creep Behavior of Polypropylene

C.Subramanian, Abdulrahman Khalfan Hassan Al Mamari and S.Senthilvelan

16. Exergy Analysis of Vapor Compression Refrigeration System Using R12 and R134a as Refrigerants

Mohan Chandrasekharan

17. Activity concentrations of natural radionuclides in soils of rainforest sites in Western Ghats

P.K.Manigandan and K.K.Natrajan

18. Optimization of Hybrid Renewable Energy System for a Remote Village in Bataan, Philippines

Eugene V. Vega and Nelson S. Andres

Papers/Wadi%20Flow%20Simulation%20Using%20Tank%20Model%20in%20Muscat%20Oman.pdf

Papers/An%20Assessment%20of%20Temperature%20and%20Precipitation%20Change%20Projections%20in%20Muscat%20Oman%20from%20Recent%20Global%20Climate%20Model%20Simulations.pdf

Papers/An%20Assessment%20of%20Temperature%20and%20Precipitation%20Change%20Projections%20in%20Muscat%20Oman%20from%20Recent%20Global%20Climate%20Model%20Simulations.pdf

Papers/Assessment%20of%20Embodied%20Energy%20in%20the%20Production%20of%20Ultra%20High%20Performance%20Concrete%20(UHPC).pdf

Papers/Investigation%20of%20Mechanical%20Properties%20of%20Aluminium%206061%20Alloy%20Friction%20Stir%20Welding.pdf

Papers/Effect%20of%20Fiber%20Length%20on%20the%20ShortTerm%20Flexural%20Creep%20Behavior%20of%20Polypropylene.pdf

Papers/Exergy%20Analysis%20of%20Vapor%20Compression%20Refrigeration%20System%20Using%20R12%20and%20R134a%20as%20Refrigerants.pdf

Papers/Activity%20Concentrations%20of%20Natural%20Radionuclides%20in%20Soils%20of%20Rainforest%20Sites%20in%20Western%20Ghats.pdf

Papers/Optimization%20of%20Hybrid%20Renewable%20Energy%20System%20for%20a%20Remote%20Village%20in%20Bataan%20Philippines.pdf

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About The College Al Musanna College of Technology (ACT) is one of the seven technological colleges affiliated to the Ministry of Manpower and was established in the year 1993. At present, there are three academic departments in the college namely: Engineering, Business Studies, and Information Technology. There are two centers in the college to prepare and support students' career formation – English Language Centre and Educational Technology Centre. With the proven years of service, ACT is still growing, and offering quality education to the youth of Oman. ACT has an intense commitment to build a sustainable infrastructure, skilled human resource, and excellent student body to meet the changing demands of education and is thriving forward with its vision to be a leading technological institution, providing high quality teaching and learning to prepare and empower Omani professionals of the future, so that they can contribute to national socio-economic development. ACT is ever reminded of its mission to deliver high quality student-centered education that produces competitive graduates who enter the labor market with confidence, strong technological and personal skills, and are prepared for a life of contribution and success. Vision We will be a leading technological institution, providing high quality teaching and learning to prepare and empower the Omani professionals of the future so that they can contribute to national socio-economic development. Mission To deliver high quality student centered education that produces competitive graduates who enter the labor market with confidence, strong technological and personal skills, and are prepared for a life of contribution and success.

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About The Department Of Engineering The Department of Engineering has three sections namely: Mechanical & Industrial Engineering, Electrical & Electronics Engineering and Civil & Architectural Engineering. The department is equipped with well qualified & experienced faculty members, and modern laboratory facilities catering to the course requirements and to provide for the various training programs. The department is continuously striving to achieve academic excellence through its state - of - the – art laboratory facilities, well planned course delivery and student training programs.

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Symposium Objective STDC 2014 is aimed to provide a common platform for academicians, researchers, industrial personnel and scholars to share their innovative ideas and research results to review and identify gaps that we need to address and emerging issues, where we need to surge ahead towards sustainability of technology & development. The conference is intended in reinvigorating discussions on sustainable development to identify shortcomings, replicate successes, and to avail ourselves of new science, information and the technologies to make real advancements towards achieving sustainable development. Symposium Topics ● Green Energy ● Energy Audit & Management ● Energy Efficient Processes ● Solid Waste Management & Recycling ● Water Treatment ● Pollution Management ● Global Warming ● Eco System Management ● Energy Efficient Buildings ● Green Information and Communication Technologies (ICT) ● Socio- Political & Economic Aspects of ● Sustainable Development ● Green Chemistry ● Materials for Sustainable Development

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Message from the Dean

On behalf of Al-Musanna College of Technology (ACT) and the Symposium Committees of Sustainable Technology and Development, it is my great pleasure to extend a warm welcome to all the participants of STDC2014 scheduled to take place at ACT, Al Musanna, Sultanate of Oman on April 21, 2014.

"Sustainable development is development that meets the needs of the present without compromising the ability of future generations to meet their own needs

- U.N. Brundtland Commission”

STDC2014 provides a platform for engineers, academicians as well as industrial professionals from all

parts of the Sultanate of Oman to present their research results and development activities related to

sustainable Technology and development. This symposium is aimed at dissemination of knowledge on

methods, policies and technologies for sustainable development in the fields of Science Engineering and

Technology. Sustainability and sustainable development provides a perfect field for interdisciplinary

deliberations, as well.

Al Musanna College of Technology continues to grow in many different ways and our graduates are

excelling in their professional and personal lives. Our faculty and staff are committed in providing the

best possible education and I am sure that this symposium will enrich each one of us, in striving towards

excellence.

Finally, I would like to extend my thanks to all the participants who will present their papers and the

keynote speakers who will share their knowledge and experiences. I am confident that the professional

contacts you make at this event, the presentations, and the proceedings will provide ideas and insights

that you can apply to your areas of research.

Dr. Qasim Murtadha Al Mar'ashi

Dean, Al Musanna College of Technology

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Message from the Head, Department of Engineering

Welcome to STDC-2014 at Al Musanna College of Technology.

The Department of Engineering has been organizing Technical Conferences since 2012. The objective of

these conferences is to provide academicians, students and industrial personnel the opportunity to

listen to and interact with experts from all around the Sultanate. It also provides a forum to share

experiences and recommend ways to improve standards of engineering education in the country. The

symposium also provides distinctive opportunity to the professionals to present their research work.

This year the theme is ‘Sustainable Technology and Development’ as sustainable development is the

backbone of the philosophy of Omani renaissance and development plans. The long-range development

strategy outlined in `Economic Vision Oman 2020' embodies an action plan that stresses sustainability

through the diversification of economy, so as to satisfy the demands of a growing population and

development.

I would like to acknowledge the efforts of the Organizing Committees for conducting this event. I would

also like to thank the editorial board of GIAP Journals for publishing the papers in its special edition of

IJSRTM.

My sincere thanks and appreciation is to all participants for their outstanding contributions and in particular the members of the Technical Committee and Steering Committee for their competent evaluation.

Mr. Abdulhamid Al Hinai

Head of Department

Department of Engineering

Al Musanna College of Technology

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Proceedings of Symposium on Sustainable Technology & Development (STDC - 2014) [ISBN 978-81-925781-9-4], April 2014, pg. 1-7

http://www.giapjournals.org/stdc-2014-oman.html 1

Carbon Dioxide Capture, Transport and Sequestration to Abate Global Warming Ammera Salim Al Sharji, Badriya Mohammed Al Hatmi, Maryam Mohammed Al-Roshdi,

Taimoora Nasser Al Hasani & S. Murthy Shekhar

Mechanical& Industrial Engineering Section

Higher College of Technology, Muscat [email protected]; [email protected]

Abstract- Climate change is one of the primary environmental concerns of the 21st century. Without changes in energy policies, environmental policies, and oh technologies, global carbon emission are also forecast to increase nearly 70% from 1990 levels. The green houses gases viz., carbon dioxide, methane have been identified as major threat to environment. With the above changes the United Nations Framework Convention on Climate Change has brought into force CCS methods to be adopted by carbon intensive industries. The present work covers the occurrence and effect of global warming, CO2 capture technologies viz., post-combustion, pre-combustion and oxy-fuel combustion methodologies. The CCS method encompasses CO2 separation methods viz., absorption, adsorption, membrane techniques followed by transportation and storage of co2 using geographical, deep ocean and mineralization techniques.

Keywords- Global warming, CO2 emission, capture technologies, carbon sequestration, CO2 transport

I. INTRODUCTION

The atmosphere is a complex dynamic natural gaseous system that is essential to support life on planet “EARTH”.

The atmospheric air consists of oxygen, nitrogen, argon, helium, hydrogen and water vapor, which are vital for completion of various cycles on the surface of the earth. Fossil Fuels have been a major contributor to the high standard of living enjoyed by the industrial world. By 2020, the world‟s appetite for energy is likely to be about 75%

higher than what it was in 1990.[1] With passage of time, increase in the human population, has lead to excessive use of fossil fuels causing “Air pollution”. The effect of air pollution is related to health of humans. According to World Health Organization, both indoor and outdoor air pollution have caused approximately 3.3 million deaths worldwide.[2] Children aged less than five years who are living in developing countries are the most vulnerable population in terms of total deaths attributable to indoor and outdoor air pollution. Hence, greater responsibility need to be taken by individuals, organizations, societies and nations to control pollutants as they are considered as environmental threat not only to humans near to the source and also getting dispersed into atmosphere causing climate change leading to global warming, acid rain etc.

II. GLOBAL WARMING

The environmentalists identify, the phenomena of Global Warming has resulted from anthropogenic sources viz., emission of flue gas or smoke from power plants, manufacturing facilities (factories) and waste incinerators, furnaces, other types of fuel-burning or heating devices, traditional biomass burning viz., wood, crop waste and dung.

A. Occurrence of Global Warming

The occurrence of global warming has been shown in Fig. 1. The pollutants emitted by industrial sources have been hindering escape of heat from earth‟s surface resulting in heating of earth causing „Global Warming‟. The gases which are responsible for above effect are known as „Green House Gases (GHG)’. Few gases which are widely accepted as GHG‟s are Carbon dioxide (CO2), Methane (CH4), Chloroflurocarbons (CFC), Sulfur hexafluoride(SF6), Nitrous oxide (NO) etc.

B. Carbon Dioxide Emission

Although various GHG‟s exists in atmosphere, the

emission of CO2 is alarmingly high. CO2 is being added by natural processes viz., gas exhaled by all living organisms by breathing and fermentation and decay of organic matter and anthropogenic sources viz., emissions of flue gas in large quantity after combustion of fossil fuels by energy intensive industries like steel, cement and paper, power plants, petroleum and petrochemical industries. In summary, the contribution of the above industries to the emission of green house gases are as shown in Fig.2. It has been reported that, at the beginning of industrial revolution the level of CO2 in the atmosphere was around 280 parts per million by volume (ppmv) and at present it has risen to around 380ppmv due to burning of fossil fuels. With tremendous rise in CO2 (about 35% rise) attention towards global warming scenario has escalated. Recent study by Pires et al.[3], report CO2 emissions from power plants alone to 23Gton CO2/year which is about 26% of the total emissions . An another study by Takeshi Kuramochi et al.[4] report Petroleum and Petroleum refineries were together emitted more than 11



https://en.wikipedia.org/wiki/Power_plant



Gton CO2 directly and indirectly accounting for nearly 40% of total global CO2 emissions.

Fig. 1: Utilization of Solar energy [2]

C. Effect of Global Warming

The effect of global warming is not just on individuals and nation(s) and is on planet earth itself. The major effects have been identified as polar ice cap melting and raise of sea levels, increased probability and intensity of droughts and heat waves, warmer waters and more hurricanes, spread of disease and economic consequences.

With effect of global warming reaching its pinnacle, various international agencies have made a road map to abate global warming and UN committee‟s have been urging the

global community to take urgent steps to minimize the effect of global warming by cutting the emission of greenhouse gases. A road map for reduction of CO2 has been drawn by international organizations involving UN, developed and developing nations is as given in Fig.3, to reduce the concentration of GHG viz., CO2 gradually within next 10 to 20 years and get concentration below pre-industrial revolution level by 2050.

D. Control of CO2

To meet the target laid, a serious effort to look into various avenues to control emission of CO2 into atmosphere is essential. In general, five ways to reduce the CO2 emissions viz., Reduction of Population, Decline of economy output, Increase of energy efficiency and Change of fossil fuel to non carbon forms of energy (renewable and nuclear energy) and increasing the CO2 sink. Out of the above five only three options suitable to implement are (i) reduce CO2 concentration in the atmosphere, (ii) energy saving and (iii) switching from carbon to non-carbon energy source. But on the other hand, rise of population, increased demand for cheaper energy, and reliable processes based on fossil fuels thereby increasing CO2 level.

With different methods to control CO2 with their own merits and demerits, one of the promising technology available to control of CO2 has been found in “Carbon Sequestration” or “Carbon Capture and Storage (CCS)”

technology. The carbon sequestration technology involves removal of GHG, either directly from the exhaust streams of industrial or utility plants or indirectly from the atmosphere, separation of CO2, Transporting CO2 and storing CO2 for long term so that they cannot interact with the climate system. Further verification of feasibility and adoptability of the CCS method, majority of international organizations and carbon intensive industries like power plants and cement manufacturing plants, iron and steel industries, petroleum refining and petrochemical industries are on way to adopting it.

III . CARBON CAPTURE TECHNOLOGIES[7]

Capturing CO2 from flue gas streams is an essential parameter for the carbon management for sequestration of CO2 from our environment. The three different technologies available for reduction of CO2 emissions are Post-combustion CO2 capture, Pre-combustion CO2 capture and Oxy-fuel combustion technologies. The suitability of particular technology depends on concentration of CO2 in the gas stream, the pressure of the gas stream and type of fuel viz., solid, liquid or gas.

A. Post-combustion CO2 capture

Post combustion CO2 capture technology involves separating CO2 from the flue gas produced by fuel combustion. Post-combustion capture is a downstream process and in many respects is analogues to Flue Gas



Desulphurization (FGD), which is widely used to capture SO2 from flue gas in coal and oil fired power plants

Fig. 2 Greenhouse gas emissions by various sectors [2]

The method requires separating the CO2 from other flue gases because sequestration of combustion gases is not feasible due in part to the cost of gas compression and storage.

The characteristic features of technology are (i) adoptable to majority of existing coal fired power plants (ii) low CO2 partial pressure conditions (iii) higher performance or circulation volume requirement for high capture level and (iv)

availability of retrofit technology option. The method is adoptable for concentration of CO2 in flue gas between 4-14%. A large volume of flue gas to large equipment sizes and high capital costs. The challenges faced by Post-combustion Technology are design of equipment for capture of higher temperature and low partial pressure CO2 of flue gas. The method also require chemical solvents for CO2 separation and release of CO2 requires large amount of energy.

Fig .3 International organization and the activities planned and for reduction of CO2 [2]



Fig. 4 Process flow diagram for Post-combustion Technology[5]

The application of above technology with biomass gas involves steam reforming, partial oxidation and auto thermal reforming. After shift reaction, gas mixture is cooled and Selexol acid gas removal unit separates CO2 and sulphur compound steams.

The characteristic features of pre-combustion are (i) transformation of carbon fuel to carbonless fuel (ii) combustion of hydrogen does not emit sulphur dioxide (iii) application of hydrogen generated in gas boiler, gas turbines, fuel cell etc. The concentration of CO2 and pressure higher than encountered in post-combustion process leading to small size equipment.

Further it is considered as one of more potential technology to be adopted among all the CO2 capture technologies. The Challenge encountered is mainly high total capial cost of equipment required for the creation of facility.

B. Oxy-fuel combustion

Oxy-fuel combustion technology, is actually modified post-combustion method. In this method, Fuel is burnt with pure oxygen instead of air, which results in high concentration of CO2 in flue gases. If fuel is burnt in pure oxygen, the flame temperature is excessively high, so some CO2-rich flue gas would be recycled to the combustor to make the flame temperature similar to that in normal air-blown combustor.

The characteristic features of oxy-fuel combustion technology are (i) depends on physical separation processes for O2 production (ii) product of combustion being CO2, it does not require any reagent /or solvents (iii) no operating

cost due to separation and regeneration stages (iv) no issues related to environmental disposal of solid or liquid wastes (v) direct compression of CO2 for transportation.

The advantages the process offers are increased CO2 concentration over 80% in flue gas thereby eliminating purification or separation of components from flue gas, minimum NOx formation and elimination of gas desulphurization stages. The disadvantage of process are need for a large quantity of oxygen, which is expensive, both in terms of capital cost and energy consumption. [5]

The condition of CO2 separation in pre-combustion capture processes will be quite different from those in post-combustion capture. Although good number of technologies show feasibility only few of them have till date have been proved commercially feasible. The CO2 capture cost contributes 75% to the overall cost and CCS increase the electricity production cost by 50%[5]. The cost of capture depends also on separation techniques from a flue gas.

IV. CO2 SEPARATION

There are many options for CO2 separation viz., absorption, adsorption, membrane and cryogenics and chemical combustion looping and adoptability depends on the characteristics of the flue gas stream. The accepted technologies in post combustion CO2 capture are chemical solvent absorption, adsorption and membrane while for pre-combustion CO2 capture are physical absorption, adsorption, membrane viz., H2/CO2 membrane, water-gas shift membrane respectively. Out of the above methods each of them have their own merits and are as listed in Table-1.



Fig. 5 Process Flow Diagram for Pre-combustion Technology[5]

The optimum CO2 capture scheme could be determined by analyzing costs. Before the transport, the CO2 stream is conditioned to remove impurities and compressed into supercritical form. Some of the impurities that may be present in the capture CO2 such as water vapor, H2S, Methane, O2 and hydrocarbons need to be either eliminated or brought down to permissible levels before transporting capture gas

The optimum CO2 capture scheme could be determined by analyzing costs. Before the transport, the CO2 stream isconditioned to remove impurities and compressed into supercritical form. Some of the impurities that may be present in the capture CO2 such as water vapor, H2S, Methane, O2 and hydrocarbons need to be either eliminated or brought down to permissible levels before transporting capture gas

Fig. 6 Process Flow diagram for Oxy-fuel combustion [5]

V. CO2 TRANSPORTATION



The CO2 transport plays an important role as CO2 is not stored in the same place where it is captured. The captured CO2 needs to be transported to a safe destination for further usage or disposal. The method depend on distance between two places viz., pipe line , ship or tanker trucks . The transport of CO2 is a mature technology as the technical requirements are similar to those applied to other gases transport. The energy requirement depends on composition and pressure of CO2 rich stream and selected transport process. Mccoy and Rubin[6] report transport of large volumes of CO2 using pipe lines due to its effectiveness and reliability. The cost of pipeline transport varies depending on construction, operation and maintenance, and other factors like right-of-way costs, regulatory fees and more. The cost of transportation depends on quantity, distance and whether pipeline is onshore or offshore, level of congestion along the route etc. At present, several million tons of CO2 are being transported using pipelines for enhanced oil recovery in oil fields. The concept that can be adopted for transportation is the linking of pipelines of several industrial regions which can be shared, thereby reducing cost of emission reduction. But, on the other hand for large distance and overseas, transport by ship is considered economical method.

TABLE I ADVANTAGES OF CO2 SEPARATION PROCESSES [5]

Separation Process Advantages

Chemical Absorption using Ammonia

Lower heat of regeneration than monoethanol amine

Higher net co2 transfer capacity than MEA

Stripping steam not required

Offers multi-pollutant control

Amine Scrubbing Applicable to co2 partial pressure

Recovery rates of up to 95% and product

Purity > 99% vol.% can be achieved

Physical Absorption Low utility consumption

Cheaply available methanol /polyethylene glycol is used

Simultaneous dehydration of the gas stream.

Membrane No regeneration energy is required

Simple modular system

No waste streams

VI. CO2 STORAGE

The storage of CO2 forms the last stage of CCS. Till date, natural CO2 cycle uses the widely popular sinks viz., Oceans and land biosphere as CO2 sinks, which absorbs about 50% of emissions. The efficiency of the above sinks have been decreased due to Global warming. The CCS approach, to abate global warming have identified based on IPCC, three modes to store captured CO2 viz., geological storage, ocean storage and mineralization. With Carbon dioxide storage gaining importance the criteria for storage of CO2 are (i) storage must be safe; (ii) the environmental impact should be minimal (iii) storage must be verifiable and (iv) storage liability is indefinite.

A. Geological Formations

Three main types of geological formations are being considered for carbon sequestration (i) depleted oil and gas reservoirs (ii) deep saline reservoirs and (iii) unminable coal seams. The IEA report[7] indicates capacity of depleted oil and gas reservoirs, deep saline reservoirs and coal seems as 920, 400-10,000, and above 150 billion tons respectively. In each case, CO2 is injected in a supercritical state a relatively dense liquid below ground into a porous rock formation that holds or previously held fluids. By injecting CO2 at depths greater than 800 m in a typical reservoir, the pressure keeps the injected CO2 in a supercritical state and thus less likely to migrate out of the geological formations. Injection of CO2 into geological formation is viewed as the most viable option by Celia and Nordbotten[8]. The geological storage options are: oil and gas reservoirs (depleted, in combination with EOR or in line combination with enhanced gas recovery); saline aquifers; and unminable coal seams (in combination with enhanced coal bed methane recovery). The requirements for geological storage are (i) adequate porosity and thickness (storage capacity) and permeability (injectivity) (ii) a satisfactory sealing cap rock; and (iii) a stable geological environment to avoid compromising the integrity of storage site according to Solomon et al.[9] .

The saline aquifers are also being considered due to their high storage capacity than other geological storage options. These saline aquifers sedimentary basins containing saline brines or brackish water unsuitable for agriculture or drinking, which exists both onshore and offshore. These are also being used by oil and gas industry to inject brines produced during oil production. But these aquifers capacity vary greatly due to lack of storage capacity measurement techniques.

The unminable coal seams, are permeable and can trap gases such as methane. After extraction of methane, carbon dioxide can be injected into permeable coal seams . The CO2 capture capacity depends on depth permeability and coal bed geometry.

B. Deep Ocean Sequestration



The ocean is considered as the largest store of CO2. It is estimated that the ocean contains 40,000 Gton of carbon, contrasting with 750 Gton in the atmosphere and 2200 Gton in the terrestrial biosphere. The ocean storage consists of CO2 injection at great depths where it dissolves or forms hydrates or heavier than water plumes that sinks at the bottom of the ocean. This process accelerates the transfer of CO2 to the ocean that occurs naturally with an estimated rate of 2Gton/year based on study by Khoo and Tan [10]. Some of the techniques used to transfer into ocean are vertical injection, inclined pipe, pipe towed by ship and dry ice. However, the increase of co2 concentration in the ocean can have serious consequences in marine life as CO2 leads to the ocean acidification, affecting the growth rate of corals,

C. Mineralization

The most recent sequestration method that seems adoptable is the mineralization technique., which aims at conversion of CO2 to solid inorganic carbonates using chemical reactions. The natural occurrence of the above process is called weathering and take millions of years. The process can be accelerated by reacting a high concentration of CO2 with minerals viz., olivine and serpentine. This option offers an opportunity for safe and long period storage of CO2.. The only disadvantage being high cost of the process.

VII. CCS CONSEQUENCES

The other factor of much concern is the leakage of CO2 after storage to the atmosphere, which could render CCS ineffective as climate change reduction option. The CO2 leakage has several consequences (i) asphyxiation, death of low lying and small animals living in low level enclosed areas where the CO2 can be accumulated (ii) change of the water pH which may affect marine life( if leakage occurs in the bottom of the ocean). Moreover the injection of CO2 in geological formations can acidify the potable ground water present nearby, which causes the dissolution heavy metals. This effect reduced the quality of the drinking water obtained from these sources.

The captured CO2 is used for various industrial and commercial processes e.g. urea production, fertilizer production, foam blowing, carbonation of beverages and dry ice production.

VIII. ECONOMICS

The implementation of CCS needs a huge capital and operating capital. The studies covering economic aspects of industries adopting CCS in a power plant indicate increase in electricity production cost by 50%. Although these numbers may vary with different CCS schemes, reducing the capture cost is the most important issue for the CCS process to be acceptable to the energy industry.

IX. CONCLUSIONS

With increase in population and demand for economic development for progress of nations, CCS methodology seems to be only alternative to keep the progress alongside reduction of CO2 emissions. Further CCS steps although achieved success in few stage further research and development needs improvement in CO2 separation methods, analysis and consequences of CO2 storage in various options.

REFERENCES

[1] Lawrence.K.Wang, Norman C. Pereria, and Yung-Tse Hung, Ed., Advanced Air and Noise Pollution control

[2] (2013) The solar energy website [Online]. Available: http://en.wikipedia.org/wiki/Air_Pollution

[3] J.C.M.Pires, F. G. Martin, M.Cm. alvim-Ferrar, M.Simoes, “ Recent Developments on carbon capture and storage: An overview” Chemical Engineering Research and Design, Vol.89, pp1446-1460, 2011

[4] Takeshi Kuramochi, Andrea Ramirez, wim Turkenburg, Andre Faaji, “Comparative assessment of CO2 capture technologies for carbon-intensive industrial processes”,

Progress in Energy and combustion science, Vo.38, pp 87-112, 2012

[5] Abass A. Olajire, “CO2 capture and separation technologies for end-of-pipe applications – A review”,

Energy, Vo. 35, pp2610-2628, 2010

[6] McCoy, S. T., Rubin E.S., “An engineering economic model of pipeline transport of CO2 with applications to carbon capture and storage” Int. J. Greenh. Gas Con. Pp 219-229, 2008

[7] Cheltenham, “Putting Carbon back in the ground” IEA,

Greenhouse Gas R & D Programme, UK,2001

[8] Celia M. A., Nordbotten, J.M., “Practical modeling

approaches for geological storage of carbon dioxide” Ground

water, Vol. 47, pp627-638, 2009

[9] Soloman, S., Carpenter, M., Filach, T. A., “Intermediate

storage of carbon dioxide in geological formations: a technical perspective‟ Int. J. Greenh. Gas Con., Vol.2, pp502-510, 2008

[10] Khoo, H.H., Tan R. B.H., “Life cycle investigation of

CO2 recovery and sequestration”, Environ.Sci. Technol.

pp4016-4024, 2006

http://en.wikipedia.org/wiki/Air_Pollution

Proceedings of Symposium on Sustainable Technology & Development (STDC - 2014)

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Prediction of Excess Air Requirement Using ANN for the Improvement of Boiler Efficiency

Arun. S. Gopinath#1, N. Sreenivasa Babu*2

Engineering Department, Shinas College of Technology Sultanate of Oman

[email protected] [email protected]

Abstract—An improvement in the efficiency on converting fuel energy to useful thermal energy could result in significant fuel saving for industrial Sector. In this paper artificial intelligence concept using Artificial Neural Network (ANN) is used to predict the optimized excess air requirement using real time and calculated data. This work determines the excess air requirement for complete combustion corresponding to theoretical CO2 in flue gases and real-time values obtained from remote measurements of CO2 (actual) in flue gases.

Keywords— ANN, Flue gas Analysis, Excess Air Control, Boiler Efficiency, Losses

I. INTRODUCTION

The operating efficiency of industrial boilers is one of the critical concerns in National Energy Consumption.The improvement in boiler efficiency will increase the steam input to the turbine and hence the alternator output power as well. Improvement in boiler efficiency can be done by optimizing the combustion with excess air control. Moreover Optimized combustion directly minimizes the emission of hazardous pollutants into the atmosphere like CO, Oxides of Sulphur and Nitrogen etc. which will minimize air pollution.

II. FUELS, COMBUSTION & FORMULATION

Coal is one among the prominent fuel using in the power generation industry. For the Complete combustion of Coal as fuel, air is required. Normally Oxygen (O2) is required for the combustion. It is obtained from the air which is supplied to the furnace. The amount of air required to supply sufficient Oxygen for the complete combustion of fuel is the Theoretical air. Excess Air is the amount of air required in addition to the stoichiometric air to make sureof complete oxidation during burning of fuel.

Among the types of fuels ,Natural gas requires less and coal requires the maximum amount of excess air for the complete

combustion[1].A typical 210 MW natural circulation , dry Bottom , tangentially fired , balanced draft and radiant Reheat type with direct fired pulverized coal system boiler is considered for this analysis. Data from the Proximate and Ultimate analysis of Coal used in the boiler is as shown in Table1&2. In situ Measurements from 210MW Boiler is shown in Table 3 & 4.

TABLE I SAMPLE OF PROXIMITY ANALYSIS RESULT OF COAL

Content Percentage

1 Ash 38

2 Volatile Matter 20

3 Moisture 7.1

4 Fixed Carbon 34.6

GCV of Coal : 4210 K Cal/kg

TABLE-2 SAMPLE OF ULTIMATE ANALYSIS OF COAL FROM PROXIMITY ANALYSIS

Sl. No Content Percentage

1 Carbon 45.957

2 Hydrogen 2.835

3 Nitrogen 0.935

4 Sulphur 0.3

5 Oxygen 4.873


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TABLE-3 PERFORMANCE DATA FROM 210MW BOILER

Sl. No

Parameter Unit Test value

1 Load MW 210 2 PA In Temp.to APH A 0 C 42 3 PA In Temp.to APH B 0 C 42 4 SEC. AIR TEMP.TO APH A 0 C 42 5 SEC. AIR TEMP.TO APH B 0 C 42 6 Flue Gas TEMP APH A INLET 0 C 147.7 7 Flue Gas TEMP APH B INLET 0 C 159.0 8 Flue Gas TEMP. APH A OUTLET 0 C 333 9 Flue Gas TEMP. APH B OUTLET 0 C 331 10 SEC.AIR TEMP. APH A OUTLET 0 C 262.5 11 SEC.AIR TEMP.APH B OUTLET 0 C 280 12 PA OUTLET TEMP.APH A 0 C 292 13 PA OUTLET TEMP.APH B 0 C 282 14 TOTAL SEC. AIR FLOW T/Hr. 405 15 TOTAL PA FLOW T/Hr. 340 16 TOTAL AIR FLOW T/Hr. 705

TABLE IV IN SITE MEASUREMENTS

Sl. No Parameters Quantity in % 1 O2 INLET 3.585 2 O2 OUTLET 5.115 3 CO2 INLET 15.715 4 CO2 OUTLET 14.185 5 CO OUTLET 0.005

An Indirect Method is followed in this analysis for evaluating boiler efficiency. In Indirect method the following losses are considered [2];

Percentage heat loss due to dry flue gas, L1 Percentage heat loss due to evaporation of water

formed, L2 Percentage heat loss due to moisture present in fuel,L3 Percentage heat loss due to moisture present in air, L4 Percentage heat loss due to Partial Conversion of C to

CO , L5 Percentage heat loss due to Radiation & Convection,

L6 Percentage heat loss due to Un burnt carbon in Fly ash,

L7 Percentage heat loss due to Unburnt carbon in Bottom

Ash, L8

Boiler Efficiency =

[100 – (L1+ L2+ L3+ L4+ L5+ L6+ L7+ L8)]

III. ALGORITHM & RESULT ANALYSIS

The Excess air required for the complete combustion is calculated by comparing the actual CO2measured from insitu and the theoretical CO2 value derived from the theoretical air required for complete combustion [6].

The steps followed for the calculation is as follows:

Step 1: Fuel Parameters after Proximity Analysis and Ultimate Analysis should be given as input Step 2: Boiler parameters & Ambient parameters from the In site measurements to be given as input Step 3: Calculate the Theoretical Air required for the Combustion of Fuel Step 4: Calculate the Theoretical CO2 Required for the complete Combustion of fuel Step 5: Actual CO2 from the Flue gas is taken from in site measurements Step 6: Excess Air required for the complete combustion was calculated by comparing the theoretical CO2 and Actual CO2 Step 7: After calculating the Excess Air Required for different combinations of theoretical CO2 and Actual CO2for different grades of coal, a neural network was trained to predict the values of excess air required.

A. ANN for Prediction of Excess Air Requirement

A feed forward neural network trained with back propagation is used for this prediction.

The steps followed for creating the Artificial Neural Network is as follows:

Step 1: Theoretical CO2 from different grades of coal and their Measured Actual CO2 where given as Input vectors.

Step 2: Corresponding Excess air Requirement calculated were assigned as the target values for their input vectors.

Step 3: The 2 layer feed forward Neural Network was created with 3 neurons in each hidden layer.

Step 4: TheNetwork was trained and created with the Data samples

Step 5: Weight values and the biasing is adjusted iteratively to improve the network performance function.

Step 6: Mean square error between the network outputs and the target outputs is the performance function

Step 7: Trained network can be applied to simulate output corresponding to any new set of input data


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Fig. 1 Excess Air Requirement for Different CO2 actual measurements of coal using indirect method

Neural Network Training data is shown in Table 5. The CO2 actual is taken from in site measurements for different grades of pulverized coal with different compositions. The training algorithm used in neural network is Levenberg -Marquardt algorithm which works better on function fitting problems with small networks [3]. CO2theoretical is derived from the details of ultimate analysis of the coal [4-5]. The performance function for the feed forward network is its mean square error between the network output and targets.

The resulting graph with test data, validation data and training is shown in Fig 2.

Fig 2 Training plot showing Mean Square Error (MSE) of the network

TABLE V RESULTS OF INDIRECT METHOD USED FOR TRAINING NETWORK IN ANN

CO2Theoretical %

CO2 Actual % Excess air % by Indirect method

22.32 15.6 43.81

21.5 15.83 36.04

20.67 14 47.44

18.25 15.76 15.27

15.5 10 51.42

TABLE VI RESULTS OF SIMULATION FROM ANN

CO2Theore-tical %

CO2 Actual

%

Excess Air % from

ANN

Excess air % by Indirect

method

Error %

20.5 15.2 39.68 34.69 14.38

21 14.8 44.55 41.89 6.3

22 13.6 71.53 62.55 14.3

22.5 15.8 42.2 43.23 2.5

23 16 42.38 44.88 5.5

IV. CONCLUSIONS

The Excess air requirement predicted by the ANN is in good understanding with the values using indirect method. As the CO2 actual from the flue gas reduces, the excess air Requirement is increasing. The Errors can be minimized in this prediction if more training data’s are added for training. This

Prediction method can be incorporated with the control mechanism of primary and secondary induced/Forced draft fans to give excessair control in boilers which in turn will increase the combustion efficiency as well as the boiler efficiency.

ACKNOWLEDGMENT

We acknowledge our friends and colleagues of Shinas College of Technology who helped in collecting information to finish this paper. We here by showing our gratitude towards our college management for their constant support and encouragement.

0

10

20

30

40

50

60

1 3 5 7 9 11 13 15 17 19 21

Exce

ss A

ir P

erc

en

tage

CO2 _Actual in Percentage

CO2_Actual

Excess Air


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REFERENCES

[1] Henry CopeteLópez and Santiago Sánchez Acevedo., An Approach to Optimal Control of the Combustion System in a Reverberatory Furnace, RevistaTecnologicas No. 23, December 2009.

[2] Yoshitaka and Akihiro Murata., Optimum Combustion control by TDLS200 Tunable Diode Laser Gas Analyser, Yokogawa Technical Report English Edition, Vol.53, No.1, 2010.

[3] Mark Hudson Beale, Martin T Hagan and Howard B Demuth., Neural Network Tool BoxTM –User’s Guide, R2013b.

[4] JigishaParikha, S.A. Channiwalab and G.K. Ghosalc., A correlation for

calculating HHV from proximate analysis of solid fuels, Science Direct, Fuel84, pp. 487-494, 2005.

[5] James G. Speight., Hand Book of Coal Analysis, John Wiley & Sons, Inc. Publications, Hoboken, New Jersey, 2005.

[6] Viktor Placek, Cyril Oswald and Jan Hrdlicka., Optimal Combustion Conditions for a Small-scale Biomass Boiler, ActaPolytechnica, Vol. 52, No. 3, 2012.


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Investigation of Sustainable Development in Omani Manufacturing Firms: Evidence from

Industrial Company Ibrahim Garbie#*1, Zuwaina Al Bahri#, Jamila Al Yahmedi#, Najia Al Shandudi#

#Department of Mechanical and Industrial Engineering, Sultan Qaboos University, Muscat, Sultanate of Oman 1Corresponding author E-mail [email protected]

*Department of Mechanical Engineering, Helwan University, Cairo, Egypt

Abstract- Sustainable development (SD) is always emphasizing on the life of people to satisfy their basic needs and enjoy a better quality of living without compromising future generations. Sustainability or sustainable development is based on and used to balance between the three pillars/dimensions: economy, society and environment. The SD means making decisions that recognize the long-term impacts of actions on economy, society, and environment. In this paper, one case study will be analyzed and evaluated regarding sustainability through the three dimensions/pillars of sustainable development based on presented approach published by [1]. This approach is validated by designing a computer programming using Microsoft Visual Studio program (C++). This program is helpful for manufacturing enterprises to evaluate the sustainability or sustainable development level. Keywords: Sustainability, sustainable development, manufacturing enterprises.

I. INTRODUCTION

Sustainability concept is the development to meets the needs of the present without affecting the ability of future generations to meet their own needs. To achieve sustainability, manufacturing enterprise changes the products or process and many tools are used to ensure long term productivity and social well-being. To reach the sustainability, manufacturing enterprises face many challenges which are: related to impacts outside their direct control including supply chain, standard measure of sustainability performance, life cycle of product design which includes manufacturing, distribution, processes, end of life, materials extraction, and develop end-of–use-product management strategies which should focus in „inventory‟ to recycle and remanufacturing processes [1]. To reduce the environmental impact across the life cycle, the green design will be introduced and then the green manufacturing processes will require little energy and emit zero waste. To extend product life, preventive maintenance should be

employed.

Sustainable value creation has a lot of drivers. These drivers are numerous such as: risk reduction. Applying the activities of sustainability reduces the risks in the enterprise and increases its reputation. Reputation can make a positive relationship with the stakeholders and increase the loyalty of the customers, growth in economics. The company has to be developed through the innovation in product and process, increasing the market share and motivating employees. The firms can reduce the level of material and water consumption and scrape rate. Firms have to work with a great level of transparency that creates a good relationship with society.

II. LITERATURE REVIEW

Reference [2] presented sustainability terms, definitions and interconnections for understanding and better communication in the process toward sustainable development. Sustainable engineering was recommended to be studied as a new educational course in Engineering Schools [3]. Reference [4] analyzed sustainability information in the print press journals, periodicals and textbooks to provide the development of sustainability science. A fully detailed discussion about sustainable manufacturing showing the importance of sustainable manufacturing as one of the most important issues regarding sustainable development was presented [5]. Challenges, perspectives and recent advances in support of sustainable production operations decision-making through sustainable design, sustainable manufacture and sustainable supply chain management was reviewed [6]. The requirements of manufacturing systems in a wide scope with clarifying their limitations and bottlenecks were discussed [7]. The importance of integrating sustainability with manufacturing and along different objectives (function, competitiveness, profitability and productivity) was investigated [8]. The key requirements for



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engineering sustainability including resources, processes, increased efficiency and reduced environment impact were identified [9]. A brief explanation and an analysis of sixteen of the most widely initiatives to embed sustainability into companies‟ systems were provided [10].

III. SUSTAINABILITY ANALYSIS

A. Economic Sustainability Analysis

1) Business and finance: It is very important to increase the business and finance returns of the enterprises. In order to ensure that appropriate and timely decisions and plans can be made. Because the sales and profit are the main drivers or motivations to run the business, companies have to focus on developing this aspect.

2) Employees: The productivity of the employees has to be monitored and they have to be motivated by different things. It should be recognized that different people are motivated by different things. The use of indicators like money, job security, and a comfortable workspace, for motivating employees, it includes the accessibility of their skills.

3) Customer: Customers are the target for any enterprise. They are resources that help the success of the company. It is known that customers help to provide revenue and certainty for a company. Ignoring customer satisfaction and loyalty may lead to lose them and reduce the company revenue.

4) Development expenditure: Research and development (R&D) increase the creativity of the product and servicers in the companies. In addition, the (R&D) helps the enterprises to compete and sustain in the market.

5) Production operation: Production operation includes activities related to manufacturing production such as the efficiency and maintenance of the machines. Also, it contains delivery precision of the products and lead time of the manufacturing processes.

6) Suppliers: Suppliers have a major role in the success of the global enterprise. They offer the raw materials, equipment and so on to the enterprises. Delivery precision of the supplier is very important for customers (manufacturing enterprises) satisfaction.

B. Social sustainability analysis

1) Health and safety: The provision of health care services and the promotion of health are equally important. Basically, they are both achieved in a healthy environment - clean air and water, a safe food supply and adequate housing. This investment in health benefits must cover the entire population.

2) Education and training: Educational aspects depend on

level of education, training hours and participation ratios in improvement group. Measurement of the improvement in human capital and skill levels by knowing training hours.

3) Labor management relations: The study of labor-management relations (LMR) means the rules and policies which govern and organize employment. It is more about how these rules and policies are established and implemented, and how they affect the needs and interests of employees and employers.

4) Diversity and equal opportunity: Understanding equality means understanding the differences between individuals‟

cultural, social and intellectual contribution to the factories.

5) Human capital: Human capital aspect represents the value of the workplace and manufactures enterprises to the community. The SME are found in specific regions, leading to generation of many permanent and casual jobs. Human capital describes the features of social organization, such as networks, and cooperation for mutual benefit.

C. Environmental Sustainability Analysis

1) Natural Resources: Natural resources aspects have five indicators which are land, water consumption, recycled water, purification of waste water and share of reuse. The availability of these resources plays a major role for any manufacturing enterprises especially for those who have the plan of expanding.

2) Energy: The manufacturing sector is a major consumer of energy. Also, there is a high consumption of fossil fuels, of which the most significant are emissions of greenhouse gases. In order to improve energy efficiency and protecting the environment, you can reduce t h e fossil fuel consumption, greenhouse gas emissions and related air pollution emissions, and by increasing the percentage of renewable energy usage.

3) Material: The available resources for the raw material is mainly extracted from the earth which some of them will be limited in supply. Therefore, the reduction of material usage can be achieved by adapting many technologies like recycling and remanufacturing.

4) Waste and Emission: Waste and emission represent that there is inefficiencies in the production process. Environment protection needs new techniques and processes for treatment and disposal of wastes. Manufacturing companies can achieve sustainability only by waste elimination, which leads to reduce the extraction from nature (earth), eliminating disposal and improving economic efficiency

5) Environmental Legal and standard compliance: Environmental Legal and standard compliance is measured by four indicators which are environmental accidents, cost for EHS


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compliance (time, liabilities, worker compensation, and waste disposal), compliance with ISO 14001/ EMAS and environmental impact assessment.

IV. SUSTAINABILITY ASSESSEMENTS

The purpose of designing questionnaire is to suggest a framework for any manufacturing firms that are planning to measure the existing level of sustainability. The aspects of each dimension was chosen and filtered after looking through different references. This framework initially designed through [11], and in this paper, it is modified to be suitable with the proposed sustainability assessment approach [1]. Then, the indicators for each aspect were determined according to its effectiveness on that dimension with an appropriate measuring unit. The measuring unit of each indicator is designed to be either quantitative or qualitative. The proposed sustainable framework is based on determining the existing performance and the target value for each indictor. This procedure assists manufacturing enterprise in understanding the difficulties with an existing manufacturing system and defining objectives towards sustainable manufacturing enterprises. In addition, this procedure can be used to increase the knowledge of the companies in sustainability. The questionnaire includes matrix that reflects the relative weights representing the relationship between all aspects of sustainable manufacturing enterprises. These relations also indicate the importance of each aspect relative to other aspects. Then, the relative weight of each aspect can be measured using analytical hierarchy process (AHP). The proposed questionnaire and the matrix of each dimension are shown as following in Tables (1-3). Mathematical model for measuring the sustainability indexes is developed by [1] and it suggested measuring the proposed framework. It‟s contains a set of equations that used to calculate the sustainability index of each dimension/pillar through calculating each aspect/issue.

Visual studio program (C++) was used to build a computer programming software package to measure the economic, social and environmental sustainability using the mathematical model that mentioned through E quations (1-3). Then, the program was justified to check it is workability. The program is a user- friendly. It was designed to measure all aspects of each dimension separately. Also, it calculates the sustainability index for economic, social and environmental dimension. The program helps the companies to identify which aspect that needs more effort (time and cost) that is needed towards sustainability compared to the existing one. The program allows the user to choose between the three dimensions: economy,

society, environment or exit for finish the program. These steps which were programmed in C++ as are shown in The following Figures (1-3). In the program, the user has to enter the existing and target value of each indicator as shown in Figure 2. These values are used to calculate the sustainability of aspects/issues. After the user has to enter the weight for each aspect with respect to the other aspects as shown in the Figure 3, the program is built to calculate the relative weight using analytical hierarchy process (AHP) which includes these operations: calculating the summation of each column in the matrix, dividing each value in the column by its summation and calculating the summation of the values in each raw. These values are the relative weights for each aspect. Equations (1-3) are programmed to measure the sustainability index for each aspect and dimension (see Figure 4). Also, the program calculates the level of sustainability in each value. These procedures are repeated for each dimension. In this paper, the program will be used to measure easily the sustainability index for the real life case study.

V. CASE STUDY

XYZ Company was established in 1984. The XYZ Company is one of the leading companies of aluminum manufacturing in the Gulf Countries Cooperation (GCC). It was located in the Al-Rusail Industrial Estate, Muscat, the Sultanate of Oman, the XYZ Company benefits from the Sultanate's liberal economic policies. Keeping up with global competition, The XYZ Company has established itself as a reliable source of high quality extrusions from the Gulf to World Markets by conforming to international standards. According to the survey of The XYZ Company, the data is analyzed as in Tables (4-6).

The XYZ Company needs 1.309 times (130.9%) more than the existing effort towards economic sustainability compared with existing value. The results of the program indicate that from social point of view, the social sustainability for the XYZ Company has almost 7.30 times (730 %) than existing one in order to achieve social sustainability. In addition, this value means that the social aspects are need for improvement especially in labor management relations and human capital. The XYZ Company also needs 44.449% more than the existing effort towards environmental sustainability compared with existing value. The overall sustainability index for the XYZ Company equals almost 3 times (2.98689) based on Equation (3) with equal relative weights between the pillars/dimensions of sustainability.


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TABLE I

ECONOMIC SUSTAINABILITY SURVEY

TABLE II

SOCIAL SUSTAINABILITY SURVEY


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TABLE III

ENVIRONMENT SUSTAINABILITY SURVEY

Fig. 1: Selecting the dimension

Fig. 2 Entering the values of existing and target

Fig. 3 Entering relative weights

Fig. 4 The sustainability index for aspects, and dimension

TABLE IV PERFROMANCE MEASURES FOR ECONOMICAL DIMENSION

Indicator Performance measures Existing Target

A11 3.37 4 A21 70 90 A22 YES YES A23 YES YES A23 2 2.25 A31 0.1 0 A32 2 5 A41 10 20 A42 5 7 A51 80 87 A52 10 15 A53 86 93 A54 75 81 A55 90 100 A56 2 1.6 A57 60 80 A58 1 0.8 A61 NO NO


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TABLE V

PERFROMANCE MEASURES FOR SOCIAL DIMENSION

Indicator Performance Measures

Existing Target B11 7 0 B12 7 0 B13 YES YES B21 7 9 B22 5 7 B23 2 3 B31 N/A N/A B32 0 5 B41 YES YES B42 10/350 15/350 B43 5 7 B44 NO NO B51 80 90 B52 10 12 B53 80 95 B54 YES YES B55 20 10 B56 YES YES B57 YES YES B58 YES YES

TABLE VI

PERFROMANCE MEASURES FOR ENVIRONMENTAL DIMENSION

Indicator Performance Measures Existing Target

C11 49000 55000 C12 3650 3500 C13 65 70 C14 0 0 C15 1 2 C21 N/A N/A C22 1260950 1386825 C23 600 250 C31 1500 1700 C32 35 20 C33 80 90 C34 2 3 C41 1000 850 C42 50 20 C43 0.05 0.01 C44 N/A N/A C45 3 1 C46 5 4 C51 7 0 C52 30000 50000 C53 NO NO C54 NO NO

VI. CONCLUSIONS

This paper is about the sustainability which means meets the needs of the present without compromising the ability of future generations to meet their own needs and there are three dimensions of sustainable development (SD): economy, society and environment. Manufacturing enterprises are striving to achieve sustainability through changes in products, processes, and system. Decisions support tools and methods are rooted not only in improving environmental aspects of manufacturing, but also in ensuring long term productivity and social well-being. Refocused efforts on the development of sustainable technologies can further aid continues improvement and stimulate revolutionary advancements industry-wide. A framework was proposed to measure the sustainability in a huge different number of manufacturing enterprises. The proposed framework measures each dimension individually with it different aspects and indicators.

REFERENCES

[1] I.H.Garbie, I.H., “DFSME: design for sustainable manufacturing enterprises (an economic viewpoint),” International Journal of Production Research, vol.51, no.2, pp. 479-503m 2013.

[2] P. Glavic, and R. Lukman, “Review of sustainability terms and their definitions,” Journal of Cleaner Production, vol. 15, pp. 1875-1885, 2007.

[3] C.I. Davidson, C.T. Hendrickson, H.S. Matthews, M.W. Bridges, D.T. Allen, C.F. Murphy, B.R. Allenby, J.C. Crittenden, and S. Austin, “Preparing future engineers for challenges of the 21st Century: sustainable engineering,” Journal of Cleaner Production, vol. 18, no. 7, pp. 698-701, 2010.

[4] A.M. Hasna, “Sustainability classifications in engineering: discipline and approach,” International Journal of Sustainable Engineering, vol. 3, no. 4, pp. 258-276, 2010.


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[5] M. Garetti, and M. Taisch, “Sustainable manufacturing: trends and research challenges,” Production Planning and Control, vol. 23, no. 2-3, pp. 83-104, 2012.

[6] S. Liu, M. Leat, and M. H. Smith,”State-of-the-art sustainability analysis methodologies for efficient decision support in green production operations,” International Journal of Sustainable Engineering, vol. 4, no. 3, pp. 236-250, 2011.

[7] Z. Bi, “Revisiting system paradigms from the viewpoint of manufacturing sustainability,”

Sustainability, vol. 3, pp. 1323-1340, 2011. [8] M.A. Rosen, and H.A. Kishawy, “Sustainable

manufacturing and design: concepts, practices and needs,” Sustainability, vol. 4, pp. 154-174, 2012.

[9] M.A. Rossen, “Engineering sustainability: a technical approach to sustainability,” Sustainability, vol. 4, pp. 2270-2292, 2012.

[10] R. Lozano, “Towards better embedding sustainability into companies‟ systems: an analysis of voluntary

corporate initiatives,” Journal of Cleaner Production, vol. 25, pp. 14-26, 2012.

[11] M. Winroth, P. Almstrom, and C. Andersson, “Sustainable indicators at factory level-a framework for practical assessment,” Proceedings of the 2012 Industrial and Systems Engineering Research Conference, May 18-23, 2012, New Orland, Florida, USA, 2012.


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Design and Development of An Infrared Heater For Waste Plastic Gasification

Zuhair E. M. Haruon

Department of Electrical Engineering, Cape Peninsula University of Technology [email protected]

Abstract— This paper outlines the design, manufacture and analysis of a far infrared ceramic heater for plastic gasification purposes. The study includes the theoretical overview of the mathematical modelling of the far infrared ceramic heater. This study gives a novel energy conversion system of waste plastic materials. In this system, waste plastics are converted into gaseous fuel by gasification using infrared gasifier system. The derived gaseous fuels can then be used in fuel cell for purposes of electricity production. In this study two types of waste plastics (high density polyethylene, low density polyethylene) have been used as feedstock for the infrared gasifier. Analysis of the spectral properties of the waste plastics has been performed. Gasification of plastic waste as carbonaceous material, basic reactions during the gasification of plastics and gasification results has been analysed. The ceramic infrared heaters developed in this research are fully functional and all test results obtained are accurate to a very fair degree. The results obtained from the gasification experiment shows that using infrared heaters on gasification is practically sound because of significant advantages of infrared heating compared to the landfill and incineration. The work is intended to develop a low-cost ceramic infrared heater solution to be used in plastic waste gasification.

Keywords — Gasification, Infrared heater, Plastic waste, LabVIEW.

I. INTRODUCTION

The energy demand has been increasing, and the combustion of fossil fuel to cover energy demand is associated with serious environmental problems through the emission of CO2. The researchers have been researching for clean and reliable energy source that could substitute fossil fuel. Hydrogen gas is clean fuel with no CO2 emission used in fuel cell for electricity generation. It is valuable gas as clean fuel, it has high energy content, 122kj/g [1], therefore, demand on hydrogen has increased considerably in recent years. Hydrogen production methods include electrolysis of water, steam reforming of hydrocarbons and auto-thermal process.

With the modern lifestyle, the consumption of plastics continues to increase every year and therefore the amount of plastic waste has also increased. Traditional ways of plastic waste disposal have been either to bury or burn them in landfill incinerators, respectively. Landfills and incinerations

however are associated with serious environmental concerns. There are different technologies such as gasification and pyrolysis which transform waste plastic to useful fuels or petrochemicals. One of these technologies is infrared radiation heating which is often said to be more efficient and cost effective. The use of infrared radiant heating in the gasification of waste plastic is performed because infrared radiation does not emit harmful fumes and do not require air movement [2]. This project is concerned with the use of infrared energy in the disposal of plastic waste.

II. BACKGROUND REVIEW

Waste plastics are one of the most promising resources for fuel production because of useful gases that it contains. Plastic recycling can be divided into three methods; mechanical recycling, chemical recycling and energy recovery. Chemical recycling which, converts plastic materials into useful chemicals have been recognized as an advanced technology process [3]. In recent years the gasification of plastics has been intensively conducted and some useful results have been seen in different studies [4], [5]. Two types of fuel-coal and polyethylene, were gasified in a 250mm across 3.4m high drop tube furnace, the study conclude that the gasification of coal has produce H2, CO with concentrations of 15% and 25% respectively. Gasification is a process that converts carbonaceous materials such as plastic, coal and petroleum into carbon monoxide and hydrogen. The gas yield from the gasification process is called syngas. Equation 1 and 2 represent the raw material decomposition and reaction with oxygen during gasification.

A two-stage thermal gasification process for plastics has been studied and developed by Tashiro [6], [7]. Polyethylene (PE), polypropylene (PP) and polystyrene (PS) have been gasified using two stage thermal degradation. Plastics have been transformed to liquid and then to gas during gasification. A gasification process which converted waste plastics to synthetic gases (CO, H2), at a high temperatures (over 1600K) has also been studied by Takatoshi [8].


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III. METHODOLOGY

A. Overview of Methodology

The plastic samples were washed with hot water prior the gasification tests to remove dirt and any possible contaminants on the surface of the samples. Samples were also weighed using measuring scale to measure the mass of each sample before and after gasification. Samples of High density polyethylene (HDPE) and Low density polyethylene (LDPE) from municipal solid waste were collected and cut into squares.

The methodology used within this study;

Mathematical modeling of an infrared ceramic heater Wavelength measurements of waste plastics using

Fourier Transform Infrared Spectroscopy (FTIR). The design of a data acquisition system to verify results.

Using Quadrupole Mass Spectrometer 200 gas analyser for gas analysis.

IV. MODELLING AND DESIGN

The design of a ceramic infrared heater which has a surface temperature lower than 800℃ shall be considered. The heater is made of a ceramic body with resistance wire (filament) embedded in it. A fibre blanket placed behind the filament to avoid heat loss from the back of the heater. Ceramic infrared heaters are designed to emit wavelengths in the far infrared range at certain operational temperatures. As voltage is applied, a current and resistive loss in the filament that translates to heat build-up. The higher the temperature the higher the filament resistivity, with a reduction in the amount of current and power consumed. The rise in filament temperature results in heat transfer by means of conduction to the ceramic body and then radiation to the environment. The passage of electric current through the filament when voltage is applied is given by

( )

[ √

]

Where is constant.

⁄

⁄

⁄

Where U is energy storage.

The mechanism involved in the heat transfer in ceramic heaters is conduction from the filament to the ceramic body. A Fourier equation can be used to calculate the rate of heating and cooling of the heater:

Where ( ).

Where are the running temperature of the surface of the heater after the time , the initial temperature of the heater, and the temperature of the medium respectively, a is the diffusivity, equal to the product of the heat capacity of the heater, its density and the thermal conductivity of the insulating sheath, N is the heat transfer coefficient characterizing heat exchange with the medium, r is the depth of penetration of the heat pulse. The heating element reliability and stability are determined by the extent to which the heater remains constant over it is service life. The relation in equation (5) describes the rate of degradation.

[

]

Where is a constant dependent on the composition and method of production of the material of the conducting phase, the electrical insulator, or the casing, Q is the energy of activation of the aging process, which depends on the ambient conditions and the thermo-mechanical stability of the material of the heater, T is the working temperature of the heater.

A. Energy Balance Energy balance is when the rate at which energy is

transferred from the heater surface to the surface of the target is equal, given mathematically as follows:

Considering ceramic heaters as having a resistance wires of diameter D and length L initially at thermal equilibrium with the ambient air and its surroundings, this equilibrium condition is only distributed when an electric current I is passed through the wire. An equation that could be used to compute the variation of the wire temperature with time during the passage of the current is developed using the first law of thermodynamics, often used for determining unknown temperatures. Relevant terms involve heat transfer by radiation from the surface of the heater, internal energy generation due to electrical current passage through the wire, and a change in internal energy storage. For determining the rate of change of temperature and applying the first law of thermodynamics to a system of length L of the wire, it follows that:


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Where the energy generation due to the electric resistant heating is given by:

Energy outflow due to net radiation leaving the surface is given by:

The change of energy storage due to the temperature change is:

Where and are the density and specific heat, respectively of the wire material and is the volume of the

wire (

)

Substituting the rate equations into the energy balance, it follows that:

(

)

Hence the time rate of change of the wire temperature is:

(

)

The heat transfer is defined as one dimensional conduction in the reflector which itself is considered as an opaque body. The equation in the reflector is defined as:

Since there is an insulation blanket, the boundary condition at the back of the heater is:

The boundary conditions at the front surface of the heater involve radiation and it is represented as follows:

V. TESTING AND MEASUREMENTS

Testing of the manufactured heaters has been conducted by connecting the heater leads to the wall socket, which normally gives 220 to 230 volts, and the temperature sensor has been mounted in front of the heater to sense the temperature of the heater surface. The maximum values of temperature recorded were as follows: 187.8 ℃ and 234.9 . “Table 1” shows the

manufactured heaters specifications including temperatures and calculated wavelength.

The wavelength of the manufactured heaters is calculated using Wien's displacement law. The wavelength of the emitter is inversely proportional to the temperature, and is given by:

Where b is a constant.

Different samples of plastic waste have been tested in terms of absorbtivity and transmitivity in order to determine the exact wavelengths at which high density polyethylene, low density polyethylene, teraphthalate perfectly absorb infrared radiation. The results showed that the absorption of the infrared radiation by any sample of plastics strongly depends on the thickness of the sample: the thinner the sample the better and stronger the absorption, while the opposite also held true - the thicker the sample the poorer the absorption.

Transmittance measurements of LDPE and HDPE using FTIR spectroscopy were conducted and the results are shown in “Fig. 1 and 2”. A sample wavelength measurement was implemented to determine the infrared absorption wavelength of LDPE and HDPE. Peak absorption values shown in “Table 2” were calculated after conversion from cm-1 to m.

TABLE 1

MANUFACTURED HEATER SPECIFICATIONS

Parameter Heater 1 Heater 2

Size (mm) 265×198 216×122

Typical operating temperature

187.8 234.9

Wavelength (μm) 6.2 5.70

TABLE 2

MEASURED WAVELENGTH VALUES

Sample Measured Peak Value Absorption Wavelengths (m)

LDPE 3.3 6.6 12

HDPE 3.3 4.5 6.6

VI. GASIFICATION OF PLASTICS

The manufactured ceramic infrared heaters were carefully placed inside the gasifier before establishing the electrical connections. The input voltage to the gasifier was 230 volts


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and the rated current was 4.2A. The gasification tests then conducted on each sample separately.

Fig 1: Transmittance spectrograph of LDPE

A. Sample Preparation The plastic samples were washed with hot water prior to

the gasification tests to remove dirt and any possible contaminants that stick on the surface of the samples. Samples were also weighted using measuring scale to determine the mass of each sample before and after gasification, “Table 3” shows the measured mass of samples.

TABLE 3

MASS OF SAMPLES

Sample Mass (grams)

LDPE 153.9

HDPE 190.05

Fig 2: Transmittance spectrograph of HDPE

VII. RESULTS

In order to test and validate the manufactured ceramic infrared heaters for the gasification process and the production of syngas, gasification experiments were conducted. The infrared gasifier was left for 20 minutes to reach an operating temperature of 457 . The gasifier was heated to reach

temperature of 457 before feeding the samples to the gasifier. After feeding the LDPE sample and during the gasification, the emission of gases started after 10 seconds. Gases continue to yield for 12 minutes before it stops completely, results of gasification tests are shown in “Table 4”

below. The temperature measurements inside and outside the gasifier and the temperature of the samples during gasification were performed using a Fluke Ti20 (Thermal imager). The total gas yield of LDPE and HDPE were 96.7wt% and 95 wt% each at a temperature of 457 . The formation of carbonaceous residue or coke was 3.3wt%, 5.2wt% for LDPE and HDPE respectively. After taking all the plastic samples, the test run is considered finished and the gasification then concluded.

TABLE 4

GASIFICATION RESULTS

Sample

Mass (a)

(Grams)

Duration

(Minute)

Mass (b)

(Grams)

temperature

(˚C)

yield

Wt%

LDPE 153.9 10 5.06 457 96.7

HDPE 190.5 12 9.95 457 95

Fig 3: LDPE gas spectrum analysis

CO2 CO

H2


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Fig 4: HDPE gas spectrum analysis

VIII. ANALYSIS OF RESULTS

The comparison of the wt% of coke residue and the wt% of the feed reveals the fact that the carbonaceous residue is very low, less that 5%, which makes the use of ceramic infrared heaters efficient. The plastics started react at 457˚C, the

wavelength emitted by the manufactured infrared heaters was successfully absorbed by the plastic samples. The short period gasification time of the plastic sample during gasification confirms the high thermal efficiency of the infrared gasifier and therefore the validity of infrared technology used in gasification of plastics. Whereas in this experiments the difference of gasification residence time between samples referred to the difference in the samples thickness. Gasification process shows that the amount of the produced gases increased when gasification temperature increased. Gasification results derived from this project were compared to other models (Toshiro, 2009) (Takatoshi, 2001). The comparison has shown that the production of syngas is comparable to models and the designed gasifier has low coke formation less than 5wt%. Gasification time and formation of residue needs further modification in the infrared gasifier compared to the two stage gasification procedures.

IX. GAS ANALYSIS

Quadrupole Mass Spectrometer 200 gas analyser was used to further analyse the resultant gas derived from the gasification of plastic samples. Analog scan mode has been chosen for analysis, it is the spectrum analysis mode common to all gas analisers. X-axis represents the atomic mass range chosen in the mass spectrometer. The Y-axis represents the amplitude of every mass increment measured.

Atmospheric scan inside the gasifier was performed and set as reference for any increase in gas yield. The experiments

concentrated in the production of H2, CO and CO2. Gases derived from the gasification of the two plastic samples then carefully injected to the gas analyser. Gas sample analyses have shown increase in hydrogen production for LDPE. Increase in CO2 was also observed for HDPE. In all samples,

TABLE 5

GAS ANALYSIS RESULTS

Sample Gasification temperature (˚C)

H2 production

CO production

CO2 production

LDPE

457

Increased

No change

No change

HDPE

457

No change

No change

Increased

the production of CO stayed unchanged during the analysis. “Figure 1and 4”shows the gas analysis of chosen samples, where “Table 4” summarises the gas analysis results.

X. CONCLUSION

Gasification results derived from this project were compared to other models, the comparison of the coke residue and the feedstock reveals that carbonaceous residue is very low, which makes the use of ceramic infrared heaters very efficient. The plastics reacted at 457 because of the good match of the heaters wavelength and the absorption characteristics of the samples. The short gasification times of the plastic samples during gasification confirms the high thermal efficiency of the infrared gasifier and therefore the validity of infrared use in the gasification of plastics. In this experiment the difference in gasification time between samples referred to the difference in samples thickness. Gasification process shows that the amount of the produced gases increased when gasification temperature increased. The comparison has shown that the production of syngas is comparable to models and the designed gasifier has low coke formation less than 5wt%.

REFERENCES

[1] M. Hamai, M. Kondo, M. Yamaguchi, G. Piao, Y. Itaya and S. Mori. “Gasification of organic waste materials for power

generation using fuel cell”, In environmentally conscious design and inverse manufacturing, pp. 103-106, IEEE., 2001.

[2] K. Kathiravan and K. H. Kaur and S. Jun and I. Joseph and D. Ali, “Infrared heating in food processing: An overview”, Comprehensive reviews in food science and food safety, Vol. 7, N. 1, pp. 2-13, 2008.

[3] P. Martin, T. Norbert, J. Eberhard, W. Ernst, “Recycling of

plastics in Germany” ,Resources, Conservation and Recycling

Vol. 29, N. 1, pp. 65-90, 2000. [4] V. Cornelia, A. B. Mihai, K. Tamer, Y.J ale, D. Hristea,

“Feedstock recycling from plastics and thermosets fractions of

used computers II Pyrolysis oil upgrading”, Fuel, Vol. 86, N. 2,

pp. 477-485, March 2007.

H2 CO2

CO


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[5] K. Peter, M.A.Barlaz, R. P. Alix, A. Baun, A. Ledin, T. H. Christensen,“Present and Long-Term Composition of MSW Landfill Leachate: A Review”, Critical review in environmental

science and technology, Vol. 32, N. 4, pp. 297-336, 2002. [6] T. Tashiro, Yoshikitanaka, S. Toshiharu, U. Osamu, I. Hironori,

“Two stage thermal gasification of plastics”, Proceedings of the

1st ISFR, Tohoku University Press, Sendai, pp. 211-214, 1999. [7] T. Toshiro, H. Akito, “Gasification of waste plastics by steam

reforming in fluidized bed”, Journal of Material Cycle and Waste Management, Vol. 11, No. 2 pp. 144-147, 2009.

[8] T. Shoji, K. Shindoh, Y. Kajibata , A. Sodeyama, “Waste

plastics recycling by an entrained flow gasifier”, Journal of

Material Cycles and Waste Management, Vol.3, No.2, pp. 75-81, 2001.

Principal Author:

Zuhair Hauron holds a BSc (Hons) degree in Electronics and Computational physics from Al-Neelain University of Technology and is a Master’s student at the Cape Peninsula

University of Technology.

http://www.springerlink.com/content/?Author=Takatoshi+Shoji

http://www.springerlink.com/content/?Author=Kenjiro+Shindoh

http://www.springerlink.com/content/?Author=Atsushi+Sodeyama


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Study of Microwave Radiation on Transesterification of Jatropha Oil in Presence

of Alkali Catalyst Nadira Hassan Mohammed Al Balushi#1, Priy Brat Dwivedi*2

1Student, 2Project Guide, Mechanical & Industrial Engineering Department

Caledonian College of Engineering, Muscat, Oman

Corresponding author: [email protected]

Abstract— The objectives of this study is to produce biodiesel

from Jatropha oil using microwave radiation in presence of alkali

catalyst and designing suitable batch reactor for lab scale

production. Cost effectiveness of the project is also being studied.

This paper outlines studies done to find the optimal method for

converting Jatropha oil to useable biodiesel using microwave

irradiation. The amount of acid catalyst is 0.4w % and ratio of

methanol to oil is 6:1 w/w for the optimal trans-esterification.

Keywords: Jatropha oil, Biodiesel, Catalyst, Microwave radiation,

Trans-esterification

I. INTRODUCTION

Oil is running out. In the short term it will continue to go up in price and in the middle distant future it will be too expensive to burn. As the world energy demand and consumption increases every day, we need to focus on the use of biofuels that will help extend the lifetime of our oil supply, but eventually we will need to replace oil. Whatever that replacement is it needs to be sustainable.

By 2030, global energy consumption is projected to grow by 36% [1] and, in our view; demand for liquid transport fuels will rise by some 16 million barrels more a day. With the world’s population projected to reach 8.3 billion by then, an

additional 1.3 billion people will need energy. To meet this demand a diverse energy mix is needed. This is where biofuels can help; in the next two decades, biofuels is expected to provide some 20% (by energy) of the growth in fuel for road transport [2]. The possibility of deriving bioduesel from locally grown sources and using them as alternatives to petro diesel products is attractive for many countries, including the

Sultanate of Oman, that currently depend largely on fossil fuels.

Biodiesel is fuel that is similar to diesel fuel and is derived from usually vegetable sources. Biodiesel refers to a vegetable oil- or animal fat-based diesel fuel consisting of long-chain alkyl (methyl, ethyl, or propyl) esters. Biodiesel is typically made by chemically reacting lipids (e.g., vegetable oil, animal fat (tallow) with an alcohol producing fatty acid esters (FAE).

Biodiesel helps reduce greenhouse gas emissions (GHGs) because it comes from animal or plant biomass with a lifecycle of a few years. On the other hand, petro diesel is a fossil fuel that releases into the atmosphere carbon that has been tied up for hundreds of millions of years, and all of it adds to GHGs. Fossil fuels also release more tailpipe emissions than does biodiesel. Biodiesel is a liquid which varies in color between golden and dark brown depending on the production feedstock. It is slightly miscible with water, has a high boiling point and low vapor pressure. The flash point of biodiesel (>130 °C, >266 °F) is significantly higher than that of petroleum diesel (64 °C, 147 °F) or gasoline (−45 °C, -52 °F). Biodiesel has a density of ~ 0.88 g/cm³, higher than petrodiesel (~ 0.85 g/cm³). Most diesel engines are warranted to run on anywhere between B5 (5% biodiesel) to B20 (20% biodiesel). [3] Have discussed few chemical and physical properties of jatropha oil. (Table 1).

Kapilan [5] has used microwave radiation for two step transesterification in his work and reported successful production of biodiesel from jatropha oil grown in Indian soil. Antony Raja, et al. [6] reported that Jatropha oil is converted into jatropha oil methyl ester known as (biodiesel) prepared in the presence of homogeneous acid catalyst. The same characteristics study was also carried out for the diesel fuel for obtaining the base line data for analysis.



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TABLE I

CHEMICAL AND PHYSICAL PROPERTIES [4]

Parameter Value

% FFA as oleic acid

Iodine value

Saponification value

Peroxide value

Percentage oil content (kernel)

Density at 20° C (g/ml)

Viscosity at room temperature (cp)

Physical state at room temperatur

2.23±0.02

103.62±0.07

193.55±0.61

1.93±0.012

63.16±0.35

0.90317

42.88

Liquid

A Value is mean ± standard deviation of triplicate determinations.

Marchetti, et al. [7] concluded that there are different ways of production, with different kinds of raw materials: refine, crude or frying oils. Also with different types of catalyst, basic ones such as sodium or potassium hydroxides, acids such as sulfuric acid and ion exchange resins. One of the advantages of this fuel is that the raw materials used to produce it are natural and renewable. Also of this process, the free fatty acid will be changed completely in to esters. Bojan, et al. [8] carried out his work to produce biodiesel from crude Jatropha Curcas oil (CJCO) with a having high free fatty acid (HFFA) contents (6.85%) and also the crude Jatropha Curcas oil was processed in two steps. During the first step the free fatty acid content of crude Jatropha Curcas oil was reduced to 1.12% in one hour at 60°C using 9:1 methanol to oil molar ratio. The second step was alkali catalyzed transesterification using methanol to oil molar ratio of 5.41:1 to produce biodiesel from the product of the first step at 60°C.The maximum yield of biodiesel was 93% v/v of crude Jatropha Curcas oil which was more than the biodiesel yield (80.5%) from the one step alkali catalyzed transesterification process. Temu, et al. [9] reported that the quality of biodiesel is influenced by the nature of feedstock and the production processes employed. The physico-chemical properties of jatropha and castor oils were assessed for their potential in biodiesel. The properties of jatropha and castor oils were compared with those of palm from literature while that of biodiesel were compared with petro-diesel. Results showed that high amounts of FFA in oils produced low quality biodiesel while neutralized oils with low amounts of FFA produced high quality biodiesel.

In current study locally grown jatropha oil was taken as feed stock and two step transesterification was done by microwave radiation.

Antony, et al. [10] reported that all countries are at present heavily dependent on petroleum fuels for transportation and agricultural machinery. The fact that a few nations together produce the bulk of petroleum has led to high price fluctuation and uncertainties in supply for the consuming nations. This in

turn has led them to look for alternative fuels that they themselves can produce. Among the alternatives being considered are methanol, ethanol, biogas and vegetable oils. Vegetable oils have certain features that make them attractive as substitute for Diesel fuels. Vegetable oil has the characteristics compatible with the CI engine systems. Vegetable oils are also miscible with diesel fuel in any proportion and can be used as extenders. Ronnie, et al. [11] concluded that the benefits of jatropha as biodiesel include the reduction of greenhouse gas emissions, as well as the country’s oil imports. Local production of jatropha is also practical because as a non-food crop, it will not compete with food supply demands. It can also grow on marginal degraded land, leaving prime agricultural lots for food crops while at the same time restoring the marginal and degraded land’s fertility.

All of these benefits can possibly be achieved by the presence of this locally fabricated high efficiency jatropha oil extractor equipment.

This mixture was heated in LG make domestic microwave oven with occasional shaking for 60 seconds. Power level was set at 160 W. This pretreatment was done with every set before mixture was set for transesterification. This pre-treated jatropha oil was used in base catalysed second-step transesterification.

In the second step, transesterification was carried out at with various methanol-to- oil ratio, at various catalyst strength, and various time duration. In this step also power supply 160 W. Results of variations are summarized in table 2. After the reaction, the excess methanol was removed by vacuum distillation and then the trans-esterification products were poured into a separating funnel for phase separation. After phase separation, the top layer (biodiesel), was separated and washed with distilled water in order to remove the impurities. Then the biodiesel was heated above 1000C, to remove the moisture.

Fig 1: Conventional Heating


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II. MATERIALS

For current study, Jatropha oil was purchased from local market in Salalah, Oman. This oil was filtered and then used for the production of biodiesel. Sulphric acid (H2SO4) is used as acid catalyst in first step and KOH was used as catalyst in second step. In our study we used Methanol for transesterification. Because methanol is cheaper and has better physical and chemical properties (polar and shortest chain alcohol). Potassium hydroxide, methanol and sulphuric acid were purchased from Schalau, Chemie S.A, Spain. All the chemicals used for transesterification were of analytical reagent grade. Study was done in LG domestic microwave oven at 160 W power levels.

Fig 2: Microwave-assisted biodiesel production units.

III. BIODIESEL PRODUCTION

Acid value of Jatropha oil was determined by standard method and it was found as 9 mg KOH per g of oil. Since acid value is higher than 1 mg KOH, acid catalyzed trans-esterification is necessary in first step. Acid catalyzed trans-esterification is good if oil is having high free fatty acid content. It avoids possibility of soap formation like in case of alkali catalyst. In this pretreatment, methanol-to-oil ratio was taken as 4:1 w/w and 0.4 w% of H2SO4 was

IV. RESULTS AND DISCUSSION

Conventional heating set was also studied (Figure 1) with 5g of jatropha oil, 40 ml methanol and 5 hrs of refluxing. Biodiesel yield was 3.09g. From table 2 it is clear that microwave radiation is one of the best tools for transesterification of Jatropha oil. During experiment various ratios of methanol to jatropha oil was tested. Results are summarized in table 2 (entries 1, 2 and 3). Optimum yield was found when methanol to oil ratio was 6:1. Later yield was decreasing with increasing the amount of methanol. More

study is required in this area to find the reasons behind this observation. In case of alkali catalyst variation, (entries 4, 5 and 6 in table 2) biodiesel yield was increasing with increase in alkali catalyst concentration. But due to of possibility of soap formation and difficulty in product separation, catalyst ratio was not studied beyond 0.8 w%. During this study, effect of time was also studied and results are summarized in table 2 (entries number 7, 8, and 9). Yield of biodiesel was found to be increasing with time. But to avoid bumping and overheating, no study was done after 200 seconds.

Biodiesel production by microwave irradiation was due to direct adsorption of the radiation by the polar group (OH group) of methanol. It is speculated that the OH group is directly excited by microwave radiation, and the local temperature around the OH group would be very much higher than its environment. Hence, microwave assisted transesterification is a way of reducing the reaction time, the electrical energy and labor costs as compared to the conventional method.

TABLE II

SUMMARY OF MICROWAVE HEATING VARIATION

No. Oil(g) Methanol (g)

Catalyst (g)

Time(s) Yield (g)

1 5g 30g 0.02g 80s 4.8 2 5g 40g 0.02g 80s 4.68 3 5g 50g 0.02g 80s 3.97 4 5g 40g 0.01g 140s 4.06 5 5g 40g 0.02g 140s 4.10 6 5g 40g 0.04g 140s 4.21 7 5g 50g 0.02g 80s 3.9 8 5g 50g 0.02g 140s 4.18 9 5g 50g 0.02g 200s 4.26 After variation, biodiesel properties were tested as per

ASTM D 6751, for various parameters as given in table 3.

TABLE III

FUEL PROPERTIES

Property ASTM D6751 Biodiesel Diesel Flash point (◦C) > 130 128 68

Pour point (◦C) - – 7 −15 Calorific Value (MJ/kg)

- 39.9 42.71

Viscosity at 40 ◦C (mm2/sec)

1.9–6 4.20 2.28

Density at 15 ◦C (kg/m3)

– 901 846

Water content (mg/kg)

< 500 99 102

Acid number (mg KOH/g)

< 0.50 0.80 0.34

Copper strip corrosion

>No. 3 1 1

Ash Content (%) < 0.02 0.01 0.01


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Table III compares the properties of jatropha biodiesel produced in this study with the properties of diesel. The flash point of biodiesel satisfies the fuel standards and is better than the flashpoint diesel. This is an important safety consideration when handling and storing flammable materials. The important cold flow properties of biodiesel are the cloud and pour point.

According to ASTM standard D 6751, no limit is given for pour point and suggested “report” in the fuel standard. The calorific value is an important property of biodiesel that determines its suitability as an alternative to diesel. As per European standard, EN 14214, the approved calorific value for biodiesel is 35 MJ per kg. The table shows that the calorific value of jatropha biodiesel is close to that of diesel. According to the ASTM standards, the acceptable viscosity range for biodiesel is between 1.9–6.0 mm2/s at 400C, and jatropha biodiesel satisfies the biodiesel standard. The density of jatropha biodiesel is close to that of diesel and satisfies the ASTM standard. ASTM standard approves a maximum acid value for biodiesel of 0.5 mg KOH/g, but jatropha biodiesel produced in this study has acid value 0.80 mg. The degree of tarnish on the corroded copper strip correlates to the overall corrosiveness of the fuel sample. The copper strip corrosion property of jatropha biodiesel is within the specifications of ASTM. Another important factor of biodiesel is the ash content estimation. The ash content of jatropha biodiesel satisfies the ASTM standard.

V. CONCLUSIONS

In this work, biodiesel was produced from jatropha oil using microwave radiation and with the help of two-step transesterfication. It was observed that microwave radiation helps the synthesis of methyl esters (biodiesel) from non-edible oil, and higher biodiesel conversion can be obtained within a few minutes, whereas the conventional heating process takes more than 5 hrs.

In the current investigation, it has confirmed that Jatropha oil may be used as resource to obtain biodiesel. The experimental result shows that alkali catalyzed transesterification is a promising area of research for the production of biodiesel in large scale. Effects of different parameters such as time, reactant ratio and catalyst concentration on the biodiesel yield were analyzed. The best combination of the parameters was found as 6:1 w/w ratio of Methanol to oil, 0.8 w% of KOH as catalyst and 200 seconds of reaction time. The viscosity of Jatropha oil reduces substantially after transesterification and is comparable to diesel. Biodiesel characteristics like density, viscosity, flash point, and pour point were studied and are found as comparable to diesel.

ACKNOWLEDGEMENT

Authors are thankful to Caledonian College of Engineering, Muscat,

for supporting this work.

REFERENCES

[1] (2013) Annual Energy Outlook 2013 website. [Online]. Available: http://www.eia.gov/forecasts/aeo/IF_all.cfm.

[2] (2013) BP Outlook 2030 website. [Online]. Available: http://www.bp.com/sectiongenericarticle.do?categoryId=9030039&contentId=7055156.

[3] (2014) The wikipedia website. [Online]. Available: http://en.wikipedia.org/wiki/Biodiesel.

[4] E. Akbar, Z. Yaakob, S. K. Kamarudin, M. Ismail and J. Salimon, “Characteristic and Composition of

Jatropha Curcas Oil Seed from Malaysia and its Potential as Biodiesel Feedstock, ” European Journal of Scientific Research., vol. 29, pp. 396-403, Nov. 2009.

[5] N. Kapilan, “Production of Biodiesel from Vegetable Oil Using Microware Irradiation,” Acta Polytechnica., vol. 52, pp. 46-50, Nov. 2010.,” Research Journal of Chemical Science., vol. 1, pp. 81-87, Nov. 2011.

[6] S. Antony, D.S. Robinson and C. Lee, “Biodiesel

production from jatropha oil and its characterization Oil by A Two Step Method- An Indian Case Study, ”

Journal of Sustainable Energy & Environment., vol. 3, pp. 63-66, Dec. 2012.

[7] J.M. Marchetti, V.U. Miguel and A.F. Errazu, “Possible methods for biodiesel production,”

Renewable and Sustainable Energy Reviews., vol. 11, pp. 1300-1311, Nov. 2007.

[8] S.G. Bojan and S.K. Durairaj, “Producing Biodiesel from High Free Fatty Acid Jatropha Curcas Oil by A Two Step Method- An Indian Case Study, ” Journal of Sustainable Energy & Environment., vol. 3, pp. 63-66, Nov. 2012.

[9] A. Okullo, T. Ogwok and J.W. Ntalikwa, “Physico-Chemical Properties of Biodiesel from Jatropha and Castor Oils, ” International Journal of Renewable Energy Research., vol. 2, pp. 47-52, Nov. 2012.

[10] S. Antony, D. Robinson and C. Robert, “Biodiesel

production from jatropha oil and its characterization, ”

Research Journal of Chemical Sciences., vol. 1, pp. 81-87, Apr. 2011.

[11] P. Ronnie, D. Robinson and C. Robert, “Jatropha Oil

Extractor Equipment, ” Research Journal of Chemical

Sciences., vol. 3, pp. 238-243, Apr. 2010.

http://www.eia.gov/forecasts/aeo/IF_all.cfm

http://www.bp.com/sectiongenericarticle.do?categoryId=9030039&contentId=7055156

http://www.bp.com/sectiongenericarticle.do?categoryId=9030039&contentId=7055156

http://en.wikipedia.org/wiki/Biodiesel


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Microwave Assisted Trans-esterification of Waste Cooking Oil in Presence of Alkali Catalyst

Hasna Khalfan AlSuleimani#1, Priy Brat Dwivedi#2

Student#1 , Project Guide#2 Mechanical & Industrial Department,

Caledonian College of Engineering, Oman

#1 [email protected] #2 [email protected]

Abstract— Depletion of world petroleum resources and air pollution has led to a search for alternative sources for fossil fuel, including diesel. Because of the similarity with petro-diesel, biodiesel fuel (fatty acid methyl ester) from vegetable oils, animal fats and recycled cooking oil is considered as the best candidate for diesel fuel substitute in diesel engines. Biodiesel helps in extending engine life, improving fuel economy, decreasing air pollution and reducing reliance on foreign and fossil fuel. In this paper the effect of microwave radiation on trans-esterification of waste cooking oil (from restaurants and from industrial food processors) in presence of alkali catalyst in batch process was studied. For optimal yield ratio of oil to methanol was 1:6, 0.4 w% KOH for 200 seconds in domestic microwave oven. Later on results were compared with conventional heating process of trans-esterification. From this work it is concluded that biodiesel can be produced from waste cooking oil using microwave radiation with significant reduction in production time.

Keywords— WCO, Trans-esterification, microwave, biodiesel, alkali catalyst

I. INTRODUCTION

Biodiesel (biological oil) is one of the alternative fuels that are produced from renewable sources. It is also called as mono alkyl ester of long chain fatty acid and it can be derived from various biological sources such as vegetable oil and animal fats. It can be made from a diverse mix of feed stocks including Waste cooking oil. Hundred years ago, Rudolf Diesel tested vegetable oil as fuel for his engine. In 1930s and 1940s vegetable oils (VOs) were used as diesel fuels, but only in emergency situations [1]. Alternative fuels for diesel engines are becoming increasingly important due to diminishing petroleum reserves and the environmental consequences of exhaust gases from petroleum fuelled engines [2]. Although the calorific value of VOs is as good as diesel fuel but the low volatility and high viscosity of VOs prohibits its direct application as fuel for diesel engines. However, this technical problem of higher viscosity of VOs has been overcome by

trans-esterification [3]. Trans-esterification is the process of reacting triglyceride (vegetable oils) with alcohol in presence of catalyst. During the transesterification process, triglycerides are first converted to diglycerides, which in turn are converted to monoglycerides, and then to glycerol. Each step produces a molecule of an ester of a fatty acid [4].

Waste cooking oil is taken as feed stock for production of Biodiesel; it offers a triple fact solution: economic, environmental and waste management. The term “waste

vegetable oil” (WVO) refers to vegetable oil which has been used in food production and which is no longer viable for its intended use. It is can be collect from variety of sources, e.g., food industry, restaurants or houses. Production of biodiesel from Waste cooking oil to partially substitute petroleum diesel is an alternative way for environment protection and energy security.

Trans-esterification is a process in which the glycerin is separated from WVO. It refers to catalyzed chemical reaction involving vegetable oil and an alcohol to yield fatty acid alkyl esters (i.e. Biodiesel) and glycerol.

Fig 1.1: A schematic representation of the Trans-esterification of triglycerides (vegetable oil) with methanol to produce fatty acid methyl esters (Biodiesel) (R=CH3).




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This process can convert oil to biodiesel up to 80 to 94% in 30 min to 2 hr [5]. The yields were dictated by molar ratio of the oil to alcohol, reaction time, temperature, catalyst type, catalyst concentration, triglyceride properties, and mixing intensity.

An alternative to conventional heating trans-esterification is the microwave-assisted trans-esterification. This means that microwave radiation for biodiesel synthesis is more efficient in reducing the time required for the reaction and separation of the products and offers a better way to synthesize biodiesel when compared to conventional mode of heating as well as improve product yields under atmospheric conditions [6] [7]. It is due to the fact that microwave radiation activates the smallest degree of variance of polar molecules and ions such as alcohol with the continuously changing magnetic field.

The use of vegetable oils as alternative fuels has been around for one hundred years when the inventor of the diesel engine Rudolph Diesel first tested peanut oil, in his compression-ignition engine. In 1970, scientists discovered that the viscosity of vegetable oils could be reduced by a simple chemical process and that it could perform as diesel fuel in modern engine. Considerable efforts have been made to develop vegetable oil derivatives that approximate the properties and performance of the hydrocarbon-based diesel fuels. Bio-diesel production is a very modern and technological area for researchers due to the relevance that it is winning every day because of the increase in the petroleum price and the environmental advantages. Trans-esterification is the most common method and leads to mono-alkyl esters of vegetable oils and fats, now called bio-diesel when used for fuel purposes [8].

The diesel fuel has a closer properties, biodiesel fuel (fatty acid methyl ester) from vegetable oil is considered as the best candidate for diesel fuel substitute in diesel engines. Biodiesel is the fastest growing alternative fuel in the country. Biodiesel’s

has ability to extend engine life, improve fuel economy, decrease air pollution and reduce reliance on foreign fuel. The use of waste cooking oil to produce biodiesel reduced the raw material cost [9].

II. MATERIALS

Waste Cooking Oil was collected from the local restaurant in Muscat, Oman. This oil was filtered and used for the production of biodiesel. In this work, Potassium hydroxide was used as alkali catalyst. In comparison with other alcohols, methanol is cheaper and has better physical and chemical properties (polar and shortest chain alcohol), and it was used as a reactant. Potassium hydroxide, methanol and sulphuric acid were purchased from Schalau Chemie S.A, Spain. Other

required chemicals purchased from local market were of analytical reagent great. In this study domestic oven was used of LG company make. Total work was done at fixed power of 160 wt.

III. BIODIESEL PRODUCTION

Waste cooking oil was used in this study. Waste Cooking Oil contains an initial acid value of 2.3 mg which is >1 mg KOH per gram of oil. Therefore, biodiesel production was performed in two-step reaction mechanisms:

Acid-Catalyzed Esterification.

Base-Catalyzed Trans-esterification.

A. Acid Catalyzed esterification The Waste Cooking Oil used in this study had an initial acid

value of 2.3 mg KOH/g corresponding to a free fatty acid (FFA) level of 3.1%, which is above the 1% limit for a satisfactory trans-esterification reaction using an alkaline catalyst [10]. In this pretreatment, methanol-to-oil ratio was taken as 4:1 w/w and 0.4 w% of H2SO4 was used. This mixture was heated in LG make domestic microwave oven with occasional shaking for 60 seconds. Power level was set at 160 W. This pretreatment was done with every set before mixture was set for trans-esterification.

B. Base-Catalyzed Trans-esterification The method applied for the production of biodiesel from

WCO in this study is base-catalyzed trans-esterification in a laboratory-scale setup. The reaction was performed using methanol as alcohol and KOH as catalyst. The trans-esterification process was studied at three KOH catalyst loadings (0.01, 0.02 and 0.04 g), three oil to methanol w/w ratios (1:6, 1:8, and 1:10) and three time variations. Results are listed in table. After the reaction, the excess methanol was removed by vacuum distillation and then the trans-esterification products were poured into a separating funnel for phase separation. After phase separation, the top layer (biodiesel), was separated and washed with distilled water in order to remove the impurities. Then the biodiesel was heated above 1000C, to remove the moisture.

IV. RESULT AND DISCUSSION

Conventional heating set was also studied for methanol, catalyst and time variation and results are given in table 1. Maximum yield of biodiesel yield was 3.1g with 50g methanol in 5 hrs refluxing set. In table 2, 3 and 4 results of methanol, time and catalyst variation are summarized. It is clear that microwave radiation is one of the best tools for trans-esterification of waste cooking oil. Optimum yield was found


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when methanol to oil ratio was 6:1. As clear from table 2, biodiesel yield was decreasing with increasing the amount of methanol. More study is required in this area to find the reasons behind this observation.

In case of alkali catalyst variation biodiesel yield increased with increase in alkali catalyst concentration. But due to soap formation and difficulty in product separation, yield decreased as catalyst amount increased to 0.4 w%. During this study, effect of time was also studied. Yield of biodiesel was found to be increasing with time. But to avoid bumping and overheating, no study was done after 200 seconds.

Biodiesel production by microwave irradiation was due to direct adsorption of the radiation by the polar group (OH group) of methanol. It is speculated that the OH group is directly excited by microwave radiation, and the local temperature around the OH group would be very much higher than its environment. Hence, microwave assisted trans-esterification is a way of reducing the reaction time, the electrical energy and labour costs as compared to the conventional method. And Gas Chromatography analysis of biodiesel from waste cooking oil is given in table 5.

TABLE 1

MEOH: OIL (CONVENTIONAL HEATING)

MeOH : Oil (w/w)

Time (hr) Catalyst (g) BD Yield (g)

20:5 3 0.15 No Result 20:5 3 0.02 2.9 50:5 5 0.02 3.1

TABLE 2

MEOH: OIL VARIATION

MeOH : Oil (w/w)

Time (s) Catalyst (g) BD Yield (g)

30:5 80 0.02g 4.7 40:5 80 0.02g 4.5 50:5 80 0.02g 4.2

TABLE 3

CATALYST VARIATION

Catalyst (g) Time (s) MeOH : Oil (w/w)

BD Yield (g)

0.01 140 40:5 4.2 0.02 140 40:5 4.5 0.04 140 40:5 4.1

TABLE 4

TIME VARIATION

Time (s) MeOH: Oil

(w/w)

Catalyst

(g)

BD Yield

80 50:5 0.02 4.2

140 50:5 0.02 4.3

200 50:5 0.02 4.4

TABLE 5

GC RESULT OF BIODIESEL FROM WCO

Component % Concentration

9-Octadecenoic acid 40.898 %

Pentadecanoic acid 40.779 %

8,11-octadecadienoic acid 10.052 %

Heptadecanoic acid 3.699 %

9-Octadecenoic acid 1.125 %

n-Hexadeecanoic acid 1.094 %

V. CONCLUSION

In this work, biodiesel was produced from Waste cooking oil using microwave radiation and with the help of two-step trans-esterification. It was observed that microwave radiation helps the synthesis of fatty acid methyl esters (biodiesel) from waste cooking oil, and higher biodiesel conversion can be obtained within a few minutes, whereas the conventional heating process takes more than 5 hrs.

In the current investigation, it has confirmed that Waste cooking oil may be used as resource to obtain biodiesel. The experimental result shows that alkali catalyzed trans-esterification is a promising area of research for the production of biodiesel in large scale. Effects of different parameters such as time, reactant ratio and catalyst concentration on the biodiesel yield were analyzed. The best combination of the parameters was found as 6:1 w/w ratio of Methanol to oil, 0.4 w% (0.02g) of KOH as catalyst and 200 seconds of reaction time. The viscosity of Waste cooking oil reduces substantially after trans-esterification and is comparable to diesel. Biodiesel characteristics like density, viscosity, flash point, and pour point were studied and are found as comparable to diesel.

I take this opportunity to express my profound gratitude and deep regards to my guide Dr. Priy Brat Dwivedi and Ms. Shah


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Jahan for their exemplary guidance, monitoring and constant encouragement throughout this work. I thank almighty, my parents, sisters and friends for their constant encouragement without which this assignment would not be possible. I am also thankful to Caledonian College of Engineering, Muscat Oman for providing me all facilities in lab.

REFERENCES

[1] Schumacher LG, Peterson CL, Grepen JV. 2001. Fuelling direct diesel engines with 2 % biodiesel blend. Written for presentation at the 2001 annual international meeting sponsored by ASAE.

[2] Ghobadian B, Rahimi H. 2004. Biofuels-past, present and future perspective. International Iran and Russian congress of agricultural and natural science.Shahre cord university. Shahrekord. Iran.

[3] Ma F, Hanna MA. 1999. Biodiesel production: a review. Bioresource technology, 70: 1-15.

[4] Freedman B, Butterfield RO, Pryde EH.1986.Transesterification kinetics of soybeen oil. JAOCS 63, 1375–1380.

[5] Encinar J, Gonzalez J, Rodriguez J, Tejedor A. 2002. Biodiesel Fuels from Vegetable Oils: Transesterification of Cynara c ardunculus L.

[6] Dasgupta A, Banerjee P, Malik S. 1992. Use of microwave irradiation for rapid transesterification of lipids and accelerated synthesis of fatty acyl pyrrolidides for analysis by gas chromatography-mass spectrometry: study of fatty acid profiles of olive oil, evening primrose oil, fish oils and phospholipids from mango pulp. Chemistry and physics of lipids, 62: 281-291.

[7] Lertsathapornsuk V, Pairintra R, Krisnangkura K, Chindaruksa S. (Eds.) 2003. Proceeding of the 1st International Conference on Sustainable Energy and Green Architecture, Bangkok, SE091.

[8] Balat, M. and Balat, H. 2008. A critical review of bio-diesel as a vehicular fuel. Energy conversion and management, 49 (10), pp. 2727--2741.

[9] Mistry, M. and Khambete, A. Extraction of Biodiesel from waste vegetable oil.

[10] Freedman B, Butterfield RO, Pryde EH. Transesterification kinetics of soybean oil 1. J Am Oil Chem Soc (JAOCS) 1986;63(10):1375–80.


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A Review of Optimum Sizing Techniques for Off-Grid Hybrid PV-Wind Renewable Energy Systems

Ahmed Said Al Busaidi, Hussein A Kazem, Mohammad Farooq Khan

Lecturer , Nizwa College of Technology, Oman Professor, Sohar University, Oman

Lecturer, Nizwa College of Technology, Oman

Presenting author email: [email protected]

Abstract – Hybrid renewable energy power systems have proven their ability to address limitations of single renewable energy system in terms of power stability, efficiency and reliability while running at minimum cost. In the present decade, lots of research and practical experiences have been done. This paper will present an overview of the different hybrid solar (PV)- wind renewable energy systems for power generations. Different criteria of selecting the right sizing of different component of hybrid renewable energy power plant at the most preferable economical, logistical environmental considerations will be discussed. In some cases when the weather data are not available, this paper will discuss some optimization approaches which are used to compare the performance and energy production cost of different system configurations using simulation techniques. Based on the fact that, potential of the wind and solar energy is not equal in Oman, this paper will discuss the optimum sizing process of two proposed hybrid solar-wind plants in Oman. Key Words: Hybrid Energy, wind, solar, sizing and optimization.

I. INTRODUCTION

Hybrid Renewable Energy Systems are defined as an electric energy system which is made up of one renewable and one conventional energy source or more than one renewable with or without conventional energy sources, that works in off-grid (stand alone) or grid connected mode [1]. The main feature of hybrid renewable energy systems is to combine two or more renewable power generation and so they can address efficiency, reliability, emissions and economical limitations of single renewable energy source [2].

Hybrid Renewable Energy Systems are becoming popular for stand-alone power generation in isolated sites due to the advances in renewable energy technologies and power electronic converters [3]. Based on the availability of the natural local resources, there are some advantages of the hybrid system. Higher environmental protection, especially CO2 and other emissions reduction is expected due to the

lower consumption of fuel. The cost of wind energy, and also solar energy can be competitive with nuclear and the diversity and security of natural resources who are abundant, free and inexhaustible [4]. Most of these appliances can be easily installed and they are rapidly deployed. Financially, the costs are predictable and not influenced by fuel price fluctuations [5-8]. However, because of the solar-wind unpredictable nature and dependence on weather and climatic changes, a common drawback to solar and wind power generations is that both would have to be oversized to make their stand- alone systems completely reliable for the times when neither system is producing enough electric power [9].

Many areas are concerned with the applications of the hybrid renewable energy generation. Researches [1, 10] have focused on the performance analysis of demonstration systems and the development of efficient power converters, such as bi-directional inverters and the Maximum power point trackers [11-12]. Other researches focused on the storages devices and the battery management units [6].

In the last decade, various hybrid energy systems have been installed in many countries, resulting in the development of systems that can compete with conventional, fuel based remote area power supplies [13]. However, there are several combinations of hybrid energy system which mainly depend on the natural available resources, the wind or the solar energy practically represents one source of the hybrid renewable energy systems.

With the advance development of the hybrid solar-wind systems for electrical power generation, the target to achieve efficient and reliable performance became complicated task. So the need to select and configure the right sizing of all components is important in order to obtain the initial minimum capital investment while maintaining system reliability [14-15]. This paper will overview three common used sizing methods for hybrid solar-wind systems. Beside



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that, the paper will discuss some optimization approaches of the solar-wind hybrid renewable energy systems. These approaches are used to compare the performance and energy production cost of different system configurations using simulation techniques.

This work will focus on the off-grid solar (PV)-wind hybrid energy systems as both solar and wind has the highest potential in Oman compared to the others [16-17]. Two research cases will be discussed as a practical implementation of the right sizing and optimization of the Masirah Island and Al-Halaniyat Island proposed hybrid renewable energy plants.

II. HYBRID SOLAR- WIND ENERGY

In fact, the use of small isolated hybrid energy systems is expected to grow tremendously in the near future [18], both in industrialized and developing countries. Solar and wind are naturally complementary in terms of both resources being well suited to hybrid systems [19]. Hybrid electric systems combine solar-wind systems to make the most of the area's seasonal wind and solar resources; with wind relatively more available in winter months and at night time, and solar relatively more available in summer months and during winter's sunlit days [13].

These hybrid systems provide a more consistent year-round output than either wind-only or solar-only systems and can be designed to achieve desired attributes at the lowest possible cost [20]. Most hybrid systems have backup power through batteries and/or and diesel engine generator.

Moreover, Fig 1 compares PV system capital costs of

three common PV types. The cost of electricity of the three

PV types has dropped 15- to 20 times; and grid-connected PV

systems currently sell for about $5-$10 per peak Watt (20 to

50¢/kWh), including support structures, power conditioning,

and land. In contrast, the system efficiency of the three types

has increased for about 10-13% [21].

Fig 1 PV system capital cost

The wind capital cost of class 4 and 6 wind turbines is shown in Fig 2. The cost of both systems has dropped by 180$ per KW in the last two decades.

Fig 2 Wind capital cost

However both Fig 1 and Fig 2 show promised figures for the real investments of the PV and wind renewable energies, the optimum design of hybrid system becomes complicated through uncertain renewable energy supplies uncertain load demand, non-linear characteristics of the resources with the increased complexity, the need for practical sizing and optimum configuration becomes an issue [22].

Researcher and industries faces some challenges in the

developments of the hybrid solar-wind energy systems. The

following may be considered, poor efficiency of the solar PV

sources as the efficiency cannot reach more than 17.5 % , high

manufacturing cost which leads to longer payback time [16-

17].

Beside all of the technical considerations there are other factors which must be included such as the financial investment, social aspects, local infrastructure and the whole system durability. Furthermore, references [1, 10] has presented some steps which must be taken into account before installing PV-wind hybrid systems. They include selecting the most suitable location for installation, acquiring data on the local natural potential of available wind energy and solar energy and the annual energy consumption must be determined. Then the right sizing of the whole system can be set as it will discuss in the following section.

III. SIZING METHODS OF SOLAR -WIND HYBRID SYSTEMS

Before setting up or installation of a new hybrid renewable energy system, it is essential to do the right sizing of the individual components to obtain the initial capital investment[18]. Unit sizing is basically a method of determining the right practical sizing of the hybrid system components by minimizing the system cost [14] while


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maintaining system reliability. The right sizing is to determine the wind generator capacity (number and size of wind turbines), the number of PV panels and number and capacity of battery needed for the stand-alone system. Note that it is important to maintain optimum resource management in a hybrid generation system in order to avoid wrong sizing. Over sizing the system components will increase the system cost whereas under sizing can lead to failure of power supply [14]. References have presented three methods of sizing.

A. The Yearly Monthly Average Sizing Method

The PV panels and wind generators size are measured from the average annual monthly values of energies statement. This calculates is basing on the average annual monthly data of sunning and the wind.

B. The Most Unfavorable Month Method

The PV and wind generators are being calculated in the most unfavorable month. Generally the month most unfavorable in wind is favorable in irradiation. Here the system must be dimensioned in two most unfavorable months (unfavorable irradiation month and unfavorable wind month). When the system functioned in this month it’s automatically functioned in the author month.

C. Loss of Power Supply Probability (LPSP) Method

The LPSP is the probability that an insufficient power supply results when the hybrid system is not able to satisfy the load demand [23-24]. This method consists in determining the optimal number of the batteries and the photovoltaic modules according to the optimization principle knowing: the reliability, which is based on the concept of the probability of loss of energy [25-26], and on the cost of the system. This method presents the advantage that the introducing of the wind generator permits to minimize the cost of the photovoltaic stand-alone system, by the minimizing the size of the photovoltaic generator and the storage number of battery [27]. Two methods can be used for the application of the LPSP in designing a grid-off hybrid solar–wind system. The first one is based on chronological simulations. The second approach uses probabilistic techniques to incorporate the fluctuating nature of the resource and the load, thus eliminating the need for time-series data.

IV. OPTIMIZATION METHODS OF SOLAR -WIND HYBRID

SYSTEMS

Optimization approaches of the solar-wind hybrid renewable energy systems are used to set up the optimum configuration of renewable energy configuration. Simulation techniques are used to compare the performance and energy production cost of different system configurations. Several

software tools [28] are available for designing of hybrid systems, such as homer, hybrid2, hoga and hybrids [29]. Depends on the availability of the metrological data, two approaches are followed to achieve the right optimum sizing. The conventional techniques are based on the energy balance and reliability of supply and they make use of the metrological weather data. If the weather data are not available, the system must be optimized using different methods as will be discussed in this section.

A. Graphic Construction Technique

This technique can configure the optimum combination of PV array and battery for a stand-alone hybrid solar–wind system based on using long-term data of solar radiation and wind speed recorded for every hour of the day for very long years [2]. For given load and a desired LPSP, the optimum sizing of the hybrid PV-wind can be achieved by assuming that the total cost of the system is linearly related to both the number of PV modules and the number of batteries. The minimum cost will be at the point of tangency of the curve that represents the relationship between the number of PV modules and the number of batteries.

B. Probabilistic approach

The effect of variation of the solar radiation and wind speed are the main factors in the system design of this method. Reference [29] has proposed a sizing method treating storage energy variation as a random walk. The probability density for daily increment or decrement of storage level was approximated by a two-event or three- event probability distribution. This method was extended to account for the effect of correlation between day to day radiation values.

Other applications presented the probabilistic approach based on the convolution technique. The fluctuating nature of the resources and the load is incorporated, thus eliminating the need for time-series data for the assessment [30].

C. Iterative Technique

Reference [31] proposed a Hybrid Solar–wind System Optimization (HSWSO) model, which utilizes the iterative optimization technique following the LPSP model and Levelised Cost of Energy model for power reliability and system cost respectively. Three sizing parameters are considered, i.e. the capacity of PV system, rated power of wind system, and capacity of the battery bank. For the desired LPSP value, the optimum configuration can be identified finally by iteratively searching all the possible sets of configurations to achieve the lowest Levelised Cost of Energy.

Similarly, in [32] an iterative optimization method was presented by to select the wind turbine size and PV module


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number using an iterative procedure to make the difference between the generated and demanded power (DP) as close to zero as possible over a period of time. From this iterative procedure, several possible combinations of solar–wind generation capacities were obtained. The total annual cost for each configuration is then calculated and the combination with the lowest cost is selected to represent the optimum mixture.

D. Artificial intelligence methods

There are different artificial intelligence methods which are widely used to optimize a hybrid system in order to maximize its economic benefits [32], such as Genetic Algorithms, Artificial Neural Networks and Fuzzy Logic. Genetic Algorithms are also widely used in the design of large power distribution systems because of their ability to handle complex problems with linear or non-linear cost functions. [33] Proposed one optimum sizing method based on Genetic Algorithms by using the Typical Meteorological year data, while desired LPSP with minimum Annualized Cost of System is maintained. Two optimization variables that are not commonly seen, PV array slope angle and turbine installation height have been considered. Such algorithms are applicable for the conventional optimization methods such as dynamic programming and gradient techniques [33]. Ref [18] has compared between all optimization techniques and listed all advantages and disadvantages.

V. DISCUSSION OF SOLAR- WIND ENERGIES IN OMAN

Study [17] has discussed and addressed all renewable energy resources in Oman, solar and wind energy present the highest potential for applicability in the country. The following sections overview these energies and their potential applications.

A. Solar Energy

In Oman, solar energy is the main renewable energy resource which is currently utilized in Oman for some local small applications. Oman is one of the highest solar energy densities in the world, the received solar radiation ranging from 5,500-6,000 Wh/m2 a day in July to 2,500-3,000 Wh/m2 a day in January[17].

A solar energy evaluation study [34] covered several years in order to estimate the long term average solar energy resources. The average global isolation data which is the sum of direct and diffuse radiation from 1987 to 1992 for six locations in Oman is depicted in Fig 3.

Fig 3 Global average radiation for 1987-1992 for the stations included in this study.

As shown in Fig 3, the solar isolation varies from 4.5 to 6.1 kWh/m2 per day which corresponding to 1640– 2200 kWh per year per square meter. Salalah and Sur have a significant lower insolation compared with other stations; this is due to the summer rain period in Salalah and the frequent period with fog in Sur. Relatively high solar energy density is available in all region of Oman. The total solar energy resources in Oman are enormous and can cover all energy demands as well as could provide export [17].

The consumption of energy is higher during the summer time due to the need for air conditioning. During the winter time the surplus production can be exported to Europe where the need for energy is highest [17]. For real solar PV energy investment in Oman, the following points must be considered [8]:

The solar PV technology is suitable for use in northern parts of Oman.

The solar PV technology is also suitable for electricity generation in off-grid power plants in rural desert areas where the solar energy can reduce diesel fuel use. The efficiency of PV cells is influenced by high air temperature and dust contamination.

It was found that highly suitable land for PV applications in Oman can provide more than 600 times the current electric energy demand if Thinfilm PV technology is used [8].

A research paper [35] has investigated the economical

prospect of the solar PV in Oman for a 25 location assuming a 5MW plant as shown in Fig 4.

Global solar radiation. Average 1987-1992. kWh/m2 per day

4.51 4.53

5.38 5.485.69

6.09

0.00

1.00

2.00

3.00

4.00

5.00

6.00

7.00

Salalah Sur Buraimi Seeb Fahud Marmul

kWh

/m2

per

day


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Fig 4 The COE for 25 locations in Oman

The research results revealed the following:

The renewable energy produced each year from 5MW PV power plant vary between 9000 MWh at Marmul to 6200 MWh at Sur while the mean value is 7700 MWh of all the 25 locations.

The capacity factor of PV plant varies between 20% and 14% and the cost of electricity varies between 210 and 304 US$/MWh for the best location to the least attractive location.

The study has also found that the PV energy at the best location is competitive with diesel generation without including the externality costs of diesel.

An average of about 6000 tons and 5000 tons of GHG emissions can be avoided for each implementation of PV station that is currently using diesel and natural gas, respectively.

Theoretically, it is possible to power Oman by utilizing

about 280 km2 of desert from solar collectors, corresponding to 0.1% of the area of the country [35].

B. Wind Energy

Wind power has become a major source of energy today, it is free, clean, and inexhaustible source of energy. In 2007, wind power capacity increased by a record-breaking 20,000MW, bringing the world total to 94,100MW, which is sufficient to satisfy the residential electricity needs of 150 million people. Existing wind power capacity grew by 29% in 2008 to reach 121GW, more than double the 48GW that existed in 2004 [36].

The assessment of the wind energy resources in Oman is based on the hourly wind speed data measured at twenty one stations in 2005 under the responsibility of Directorate General of Civil Aviation & Meteorology (DGCAM) [34]. The wind data is measured at 10 m and estimated at 80 m above ground level to represent a hub height of a modern large

wind turbine (capacity 2-3 MW). Five stations with the highest wind speeds were identified and the annual mean wind speed is shown in Fig 6.

Fig 5 Annual mean wind speed at 10m and at 80 m above ground level at five

meteorological stations

Fig 6 Energy content in the wind at 80 m above ground level at five meteorological

stations

Further assessment was done to estimate the annual energy content at each of the five stations. The energy is specified as kWh per year through a vertical area of one m2, kWh/year/m2. The maximum expected energy is at Thumrat for an almost 4.5 kWh/m2/year. The assessment results are shown in Fig 6.

The main findings of the study are:

The high wind speeds are found along the coast from Masirah to Salalah. The highest wind speeds are in the Dhofar Mountain Chain north of Salalah. The low wind speed areas are in the north and western part of Oman.

The highest wind energy speeds are observed during the summer period. The summer period is also the period with the highest electricity demand in Oman.

The study reveals that at the present gas price of 1.5 US$/MMBtu wind energy is not economical. The wind energy at Quiroon Hariti, the highest wind

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potential in Oman, becomes marginally economical at a gas price of 6 US$/MMBtu [34].

This clearly shows that wind application for large wind farms is not presently economical. However, the wind energy remains a suitable option for hybrid applications.

VI. HYBRID SOLAR- WIND ENERGY SYSTEMS IN OMAN

Study [13] has investigated different combinations of hybrid systems of diesel generator, wind turbine, PV array, battery, and power converter for Masirah Island in Oman. The wind and the solar assessment for Masirah Island are presented in Fig 7 & Fig 8 respectively.

Fig 7 Masirah monthly average wind speed in m/s and monthly load in MW (2008)

Fig 5 & Fig 7 show that the average yearly wind speed is 4.99 m/s and the measured wind speed happens to be quite high when the electrical load requirement is also high. Moreover, wind speeds are generally higher during the months of April to September compared to other months. The average monthly solar radiation between 2004- 2008 is shown Fig 8.

Fig 8 Masirah monthly average solar radiation between 2004- 2008

TABLE 1

TECHNICAL DETAILS OF THE LOAD AND DIFFERENT SOURCES AT MASIRAH ISLAND

Item Details Remark Site information (Masirah Island )

Area of about 649 km2 population estimated to 12,000

Scattered in 12 villages

Average wind speed

4.99 m/s

1997-2008 At 10-m height

Solar average daily radiation

6.4 kWh/m2 from 2004 till 2007

Annual electrical energy demand

43,624,270 kWh Year 2011 minimum load 550kW maximum load 9530 kW

Using the above metrological weather background and the technical details given Table 1, the optimum sizing of the system components was selected based on the monthly

average sizing approach. The optimum sizing results are

illustrated on table 2.

TABLE 2 OPTIMUM SIZING CONFIGURATION FOR THE PROPOSED MASIRAH ISLAND

HYBRID PLANT

Proposed Diesel generator details

10 units Capacity between 200kW to 3300kW

The actual diesel price for Masirah Island is 0.468 US$/L

Number of the PV panels

1.6 MW PV, Cost = 3000 US$/kW O & M cost=10US$/year/kW

Proposed Wind turbine

Rated power=250kW @ Height= 31m Rated wind speed =13m/s

Batteries Type 6CS25P, Nominal voltage 6V, Nominal capacity 1156 Ah Nominal energy capacity of Each battery (VAh/1000) 6.94 kWh

Converter Cost=900US$/kW Efficiency=90%

Level of RE penetration

25%

Furthermore, a comparison of cost of energy of different hybrid solar –wind- battery- diesel systems was developed as shown in table 3.


[ISBN 978-81-925781-9-4], April 2014, pg. 33-42


TABLE 3 A COMPARISON OF COST OF ENERGY FOR DIFFERENT SYSTEMS

COE

Battery unit

PV–diesel hybrid system

Wind–diesel

hybrid system

PV–Wind- diesel hybrid

system

Yes

0.186 US$/kWh with 28 minutes battery system

0.189 US$/kWh with 28 minutes battery system.

0.182 US$/kWh with the presence of 28 minutes battery unit

No

0.189 US$/kWh without batteries and the annual diesel consumption will increase by 1%

0.187 US$/kWh with no battery system used

0.185 US$/kWh if the battery unit is removed from the hybrid system

It is shown here that using PV–wind–diesel hybrid system

with a battery unit will produce the lowest COE (0.182 US$/kWh) compared to other hybrids. It can be noticed that the combination and the ratio of the types of energy depending greatly on the resources locally available in each geographical area ref.

The second study is presented in for Al Hallaniyat Island in Oman [37]. The technical and economic viability of utilizing different configurations of hybrid system (Wind, PV, diesel) was investigated using the weather data from 2004-2008. Al Hallaniyat’s annual electrical energy demand for the year 2008 was 1,303,290 kWh with a minimum load of 50kW and a maximum load of 320kW . The average wind speed at 10m height was 5.19 m/s and the yearly average daily value of solar radiation was 6.8 kWh/m2 [37].

Fig 9 Monthly average wind speed at Al Hallaniyat Island

The wind assessment at Al Hallaniyat Island shows that wind speeds are generally higher during the months of May to August when compared with other months. The wind duration analysis indicated that the wind speeds are less than 4 m/s for about 40% of the time during the year, as shown in

Fig 9.

The monthly average solar radiation for the 2004–2007 is plotted in Fig 10. The insolation level is high during the high electrical load season (March–May) when compared with other months. The yearly average daily value of solar radiation is 6.8 kWh/m2.

Fig 10 Monthly average daily global radiation at a site near Al Hallaniyat Island

The technical details of the site and the load are summarized in table 4. Since both wind and PV are promising systems in this location, a hybrid system was considered in the analysis consisting of the following combinations: wind–PV–

diesel with batteries and wind–PV–diesel without batteries. Fig 11 shows the proposed hybrid system which can be implemented Al Hallaniyat Island. Using the above metrological weather background and the technical details given Table 1, the optimum sizing of the system components was selected based on the monthly average sizing approach. The optimum sizing results are illustrated on table 5.

TABLE 4

TECHNICAL DETAILS OF THE LOAD AND DIFFERENT SOURCES AT AL

HALANIYAT ISLAND

Item Details Remark Site information (Al Hallaniyat Island )

Area of about 56 km2 population estimated to 150

Among five the Khuriya Muriya Islands

Average wind speed 5.19 m/s at 10m height

Average daily value of solar radiation

6.8 kWh/m2 from 2004 till 2007

Annual electrical energy demand

1,303,290 kWh Year 2008 minimum load of 50kW and a


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maximum load of 320kW

Fig 11 Proposed hybrid solar-wind- diesel system for AL Halaniyat

TABLE 5 OPTIMUM SIZING CONFIGURATION FOR THE PROPOSED AL HALANIYAT

ISLAND HYBRID PLANT

Proposed Diesel generator details

10 units Capacity 1080.8 kW

Diesel Price : US$0.508 l−1

Number of the PV panels

70 kW with 30 min storage capacity

A standard cost of $3000kW−1 Lifetime 25 years O&M cost US$10 per kW per year

Proposed Wind turbine

Rated power=60kW@ 11.3 m/s Height= 10m Rated speed =11.3m/s

capital cost US$60,000 Replacement cost US$40,000 Lifetime 30 years

Batteries Type US305HC, Nominal voltage 6V, Nominal capacity 305 Ah Nominal energy capacity of Each battery (VAh/1000) 1.83 kWh

Converter Cost=900US$/kW Efficiency=90%

Level of RE penetration

From 10 -25%

This study has investigated the technical and economic

viability of utilizing different configurations of a hybrid system. The main finding is that potential site for deployment of a PV and wind power station, especially with the diesel fuel price $0.5081 − 1. The simulation results showed that for a hybrid system composed of 70kW PV, 60 kW wind, 324.8kW diesel generators together with a battery storage, with

renewable energy penetration of 25%, the total COE was found to be $0.222 kWh−1. Moreover, removing the 30 min battery unit from the hybrid system will increase the COE to $0.225 kWh−1.

VII. CONCLUSION

This paper addresses the concepts of off-grid hybrid renewable energy sources for electrical power generation. Hybrid renewable energy system allows high improvement in the system efficiency, power reliability and reduce the system requirements for storages devices. Most of the advantages of the hybrid PV-Wind hybrid systems were given and the difficulties which faces these industries were also discussed. The paper has also presented different methods of sizing off-grid hybrid solar PV-wind renewable energy sources. Right sizing of a new hybrid renewable energy system can significantly help to determine the initial capital investment while maintaining system reliability at minimum cost. The optimization techniques of the hybrid solar-wind renewable energy systems were also discussed. The optimization approaches compare the performance and energy production cost of different system configurations and that will help to set up the optimum configuration of renewable energy configuration using simulation techniques.

Two proposals for optimum sizing of off-grid hybrid solar-wind power system are discussed. The first was for Masirah Island 12 MW hybrid PV-wind solar plant and the other one was for Al Halaniyat Island.

Optimum sizing analysis showed using PV–wind–diesel hybrid system with a battery unit will produce the lowest COE (0.182 US$/kWh) compared to other hybrids for Masirah Island. For AL Halaniyat Island, the analysis showed that for a hybrid system composed of 70kW PV, 60 kW wind, 324.8kW diesel generators together with a battery storage, with renewable energy penetration of 25%, the total COE was found to be 0.222 US$/kWh.

ACKNOWLEDGMENT

The research leading to these results has received Research Project Grant Funding from the Research Council of the Sultanate of Oman, Research Grant Agreement No. ORG/EI/13/011. The authors would like to acknowledge support from the Research Council of Oman.

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E-Waste: An Emerging Problem of Innovative Society

Rahila N. Gadi#1, Nabeel Ahmed N.Gadi*2 #Dept of E&CE-Al-Musanna’s College of Technology, Oman

*Dept of Community Medicine MM institute of Medical Science &Research Mullana, Haryana, India [email protected]

[email protected]

Abstract– In the past few years there is a revolution in electronic industry, which increases the volume and varieties of both solid and hazardous wastes. Urbanization Industrialization, fast changes in technologies leave a negative impact on health of human beings. Also increases the pollution in air, land and water. A growing municipal waste contains hazardous electrical and electronics products. When dumped in landfill will pollute the environment badly. This waste is usually named as E-waste (Electrical an Electronics Waste).In the absence of suitable techniques and protective measures, recycling e-waste can result in toxic emissions to the air, water and soil and pose a serious health and environmental hazard-waste is assuming serious proportions in developing countries and urgent steps need to be taken to mitigate this problem. This paper highlights the problem posed by e-waste and its hazards on environment and health

Keywords– E-waste (Electrical &Electronic waste), carcinogen, landfills

I. INTRODUCTION

During the last few years, there is an increasing acknowledgment of our impact on the environment due to our lifestyle, while the need to adopt a more sustainable approach concerning our consumption habits emerges as of particular significance. This trend regards industrial sector affecting the consumption habits and especially electronic industry where the short life cycles and the rapidly developing technology have led to increased E-waste volume [3]

Electrical and Electronics waste, also known as Electronic waste or waste electrical & electronics equipment (WEEE), or in short called E-waste, is used to describe obsolete or end of life electrical & electronics equipment [4]. There is no generally accepted definition of E-waste around the world[2].According to the European Union directive WEEE means Electrical or Electronic Equipment which is waste within the meaning of article1(a) of directive75/442/EEC ,including all components, subassemblies and consumables which are part of the product at the time of discarding .However E-waste most often misunderstood as comprising only computers related IT equipment or email spam[5].It is universally understood as electronic waste disposed of by end

users and a wide range of products, from simple devices to complex goods .Therefore E-waste comprises both white goods such as refrigerators ,washing machines and microwaves ,and brown goods which consists of TV ,Radios and Computers that have reached their ends for their current holder[6].

E-waste mainly comes from several sources:

Residue or leftover materials from electronic products manufacturing process

.Leftover parts or materials or discarded EEE generated from a repair shop

Obsolete EEE coming from all sector of society like government offices, Companies, Education institutes, Household etc

Obsolete electrical or electronic products brought in by smuggling [7].

The production of electrical & electronic equipment (EEE) is one of the fastest growing global manufacturing activities. Rapid economic growth, coupled with urbanization and a growing demand for consumer goods has greatly increased both the consumption and the production of EEE [8][9][10]

II. MAGNITUDE OF PROBLEM

The magnitude of the problem is really huge and scary. According to UNEP, global E-waste generation is growing by about 40 million tons a year, and predicts that by 2020 in South Africa & china E-waste from old computers will jump by 200 to 400% from 2007 levels and by 500% in India [2].Developing countries are the major dumping grounds for E-waste. By 2020 there will be increase by 400 to 500%.The spectrum of hazardous E-waste Mountain looms large especially for developing countries with serious consequences for the environment and public health[11].The global E-waste production is accessed at 20-50 million ton/year, equal to 1-



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3% of the estimated global urban waste production. Personal computers, Cell phones and TV will contribute 5.5 Mt in 2010 and will increase to 9.8Mt in 2015.In developed countries E-waste will stand for 8% of the urban waste volume[3].Each item‟s participation in the annual E-waste production(kg/year),depends on each electronics‟ item‟s mass

M(Kg),its quantity (number) in the market and consumption(N) and its Average life cycle L (year).

Estimated Life E = MN/L

For computers with an average 3 years life cycle contributes to a greater extent to the total E-waste flow compared to refrigerators and electric stoves, having an average of 10-12 years [12].Certain electrical & electronics equipment‟s which form the major part of the E-waste generation along with their mass and estimated life cycle are summarized in Table 1.

TABLE 1

ELECTRICAL & ELECTRONICS EQUIPMENTS & THEIR ESTIMATED LIFE

Items Mass(Kg) Estimated Life(Yrs)

Personal Computer 25 3

Cell Phones 0.1 2

Television 30 5

Fax Machines 3 5

AC 55 10

Photo copier 60 8

Washing Machine 65 8

Refrigerator 35 10

Microwave 15 7

Vacuum Cleaner 10 10

III. IMPACT ON HEALTH & ENVIRONMENT

E-waste cannot be considered or treated like any kind of waste, because it contains hazardous and toxic substances such as heavy metals or others such as dioxins and furans (produced when E-waste is incinerated).For instance, lead represent 6% of the total weight of a computer monitor. It is been reported that nearly 36 chemical elements are incorporated in electronic equipment‟s [13].Electronic wastes

can cause widespread environmental damage due to the use of toxic materials in the manufacture of electronics goods. Hazardous metals such as lead (Pb) ,Mercury(Hg) and hexavalent chromium[Cr(VI)],in one form or the other are present in such wastes primarily consisting of cathode ray tubes(CRTs),PCB, capacitors, mercury switches ,relays .batteries etc. Liquid Cr tetardants on PCB, LCD, cartridges from photocopying machines, selenium drums etc. Land filling of E-waste can lead to the leaching of lead (Pb) into the groundwater and leads to un-portability of water. If the CRT is crushed and burned, it emits toxic fumes into the air cause air pollution, which are very hazardous to human being as well as animals. A rechargeable battery which contains toxic substances that can contaminate when burned in incinerators or disposed of in landfills .E-waste is much more hazardous than many other municipal wastes. Long term exposure to these substances damages the nervous system, kidney, reproductive system, endocrine system and bones. It also leads to carcinogen (cancer).Workers in E-waste recycling or disposal sector are poorly protected against the risk of it. They dismantle E-waste, often by hand in very unhealthy conditions. The hazardous substances found in the E-waste are considered dangerous to health. Inhaling or handling such substances and being in contact with them on a regular basis can damage the main organs of the human body. Working in poorly-ventilated enclosed areas without masks and technical expertise result in exposure to dangerous and slow poisoning chemicals. Due to lack of awareness, workers are risking their health [15][14].Scientist who examined Guiyu, China(one of the popular destinations of E-waste recycling activities) have determined that because of waste, the location has the highest level of cancer causing dioxins in the world. Pregnant women are six times more likely to suffer a miscarriage, and seven out of ten kids have too much lead (Pb) in their blood [17]. E-waste is not alone factor in causation of environmental and health problems but its inadequate management which plays as a catalyst in the magnitude of the problem.

IV. STRATEGIES FOR REDUCTION OF E- WASTE

The best option for dealing with E-waste is to reduce the volume. Designers should ensure that the product is built for re-use and/or upgradability. Stress should be laid on use of less toxic, easily recoverable and recyclable materials which can be taken back for refurbishment, remanufacturing, disassembly and reuse. Recycling and reuse of material are the next level of potential options to reduce E-waste. Recovery of metals, plastic, glass and other materials reduces the magnitude of E-waste. These options have a potential to conserve the energy and keep the environment free of toxic materials that would otherwise have been released. It is high time the manufactures, consumers, regulators, municipal authorities and policy makers take up the matter seriously so that the different critical elements are addressed in an integrated manner. It is need of the hour to have an “E-waste policy “and national regulatory framework for promotion of


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such activities. An E-waste policy is best created but those who understand the issues. So it is best for industry to initiate policy formation collectively, but user involvement. Sustainability of E-waste management system has to be ensured by improving the effectiveness of collection and recycling system (e.g: public-private partnership in setting up buy back or drop off center) and by designing in advance funding [1][15].The E-waste generated every year globally is 40-50 million ton out of which 15 to 20 % is recycled and remaining is dumped in landfills/incinerators. If we have a good and effective recycling system and good policies to carry recycling process than we can sustain our natural resources which is depleting very fast

V. E-WASTE MANAGEMENT

To have a better management of E-waste the end user should be aware of the hazardous affects of E-waste. Proper awareness should be given and in turn survey should be conducted to find what people are doing with their E-waste. Is they are just dumping in the store room or selling to scrap people or they are giving back to the company .Find the amount of E-waste generated, by surveys from all sector of society, awareness program to educate the people how to reuse the existing Electrical & Electronics products. Next step will be the design of a proper E-waste management system to reduce and to recycle the E-waste generated. The first in the process is to collect the E-waste from all sector of the society i.e from companies, institution, residential, hospitals etc.

The second step involved to manage the E-waste is to apply the principle of three R i.e. Reduce, Reuse and Recycle. As the duty of the user is that try to minimize the E-waste generation by up grading the system or repair it. If those things will not give the expected output then try to resale or recycle it. Many companies have take back schemes. Segregation & dismantling of the various equipment or components is the third step where under proper environment this process is carried out. In the recycling process we can recovery many valuable materials and metals. Which can be reused? The last part is the hazardous materials disposal that has to be done with at most cares.[1][2][16]

VI.NEED FOR E-WASTE POLICY AND REGULATION

The policy should address all issues ranging from production and trade to final disposal, including technology transfer for the recycling of electronics waste. Clear regulatory instruments, adequate to control both legal or illegal exports and imports of E-waste and ensuring their environmentally sound management should be in place. According to the EU the designers and the manufactures have to obey the RoHS directive which bans or restrict the use of certain hazardous substances like lead and its compound, Cadmium and ,its compound, Mercury, hexavalent chromium, polybrominated biphenyls[1].The regulations should prohibit the disposal of E-waste in municipal landfills and encourage owners and generators of E-waste to properly recycle the

waste. Manufactures of products must be financially, physically and legally responsible for their products. Better management of hazardous substances may be implemented through measures such as

Specific product take back obligations for industry.

Financial responsibility for actions and schemes

Greater attention to the role of new product design. Follow RoHS directives.

Greater scrutiny of cross border movements of electrical & electronic products and E-waste

Increasing public awareness by labeling products as “Environmental Hazard”

Personal protection measures (masks, Gloves, shields, protective glasses etc) should be made available to all the workers who are engaged with E-waste management.

The key questions about the effectiveness of legislation would includes

What is to be covered by the Term Electronic Waste

Who pays for disposal is the producer responsibility the answer.

What would be the benefits of voluntary commitments

How can sufficient recovery of materials be achieved to guarantee recycling firms a reliable and adequate flow of secondary materials [18].

A. Benefits of E-Waste

Conservation of natural resources

Preventing soil, water and air contamination by toxic chemicals.

By back offers for consumers

Creates new jobs in the market

Creates new markets for secondary materials and components

B. Energy Efficiency [19][16]

Reduction of energy requirement, cost involved in E-waste recycling is comparatively less than the cost involved in mining and processing of new materials from scratch. Recycling of Aluminum can save 95% of energy than production from basic ore. Recycling of plastic can save 70% of energy and glass up to 40%.Recovering of metals from recycling process generates only a fraction amount of co2 emission compared from natural process. Innovation in E-


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waste treatment should focus on the major needs to improve overall sustainability [1][18].Some of the policies in place globally for effectively managing E-waste are mention in table 2.

TABLE 2 REGULATORY MODEL

Producers Responsibility

Government Responsibility

Model Commonly known as EPR Manufacturers financially responsible beyond point of sale. Take back Schemes & recycle them up to a defined percentage by the manufacturers Funding model for this activity varies from company to company

End consumer taxed a recycling fee on the purchased product. This Tax/Fees is used to fund the E-waste collection & recycling activity Government is responsible to monitor & collect the E-waste

Current Examples European Union Japan, South Korea, Taiwan

Switzerland California(USA)

Likely Implications Pressure on manufacturers to follow RoHS directive

No incentives for manufacturer to create cleaner design.E-waste not likely to reduce as manufacturers do not have any liability

VII. CONCLUSION

The Electronic market has revolutionized the whole world over last decades as Electrical & Electronics products

increasingly capture the major part of our lifestyle. While no one can give the exact figures how much E-waste is presently generated or how much of this is hazardous, what is definite is that if we the people living in the innovative society don‟t try

to manage the E-waste properly then E-waste have the potential of threatening human health and its environment.

Initiatives are been taken to reduce the volume of generation and to have an effective recycling techniques, which can

sustain the natural resources as well as conserve the energy. E-waste in developing countries is a menace. There is lack of

awareness among the people about E-waste. This paper highlights some of the problems, their impact on human health and environment, briefly explains how to have an

effective E-waste management system with examples

REFERENCES

[1] Dejo Olowu Article „Menace of E-Wastes in Developing CountriesAn Agenda for Legal and Policy Responses‟, Lead Journal-ISS1746-58938/1 Law, Environment and Development Journal (2012), p.59, available at http://www.lead- journal.org/content/12059.pdf

[2] Sustainable Innovation & Technology Transfer Industrial Sector studies Recycling from E-waste to resources, July 200 UNEP-STEP

[3] G. Gaidajis*, k. Angelakoglou and d. Aktsoglou, e-waste: environmental problems and current management, journal of Engineering science and technology review 3 (1) (2010) 193- 199

[4] Y. C. Jang and h. Yoon, 2006. The practice and challenges of electronic waste recycling in korea with emphasis on extended producer responsibility (EPR). Anweshaborthaku, pardeepsingh international journal of environmental sciences volume 3 no.1, 2012

[5] Deepalisinhakhetriwal, philippkraeuchi, rolfwidmer, 2007. Producer responsibility for ewaste management: key issues for consideration – learning from the swiss experience.Journal of environmental management, 2007. Xx: 1–1

[6] Shah alam, selangor, electrical and electronic waste management practice by households in , malaysia,2010, international journal of environmental sciences volume 1, no 2 ,2010

[7] Ramesh babu b, parandeak, ahmedbasha c. Electrical and electronic waste: a global environmental problem. Waste manag res. 2007;25:307–18. [pubmed].

[8] Sinha s. Downside of the digital revolution. Published in toxics link, 28/12/2007. Accessed 13 feb/96/ec . 2013. Available: http://www.toxicslink.org/art-view.php?id=124

[9] V. O. Akinseye, electronic waste components in developing countries: harmless substances or potential carcinogen, 2013, annual review & research in biology, 3(3): 131-147 , 2013

[10] Bina rani et al, j advscient res, 2012, 3(1): 17-21 17 [11] K. Betts, producing usable materials from e-waste,

environ sci technol. 42, pp. 6782–6783 (2008) [12] Musson se, jangnyc, townsendtg, chungih.

Characterization of lead leachability from cathode ray tubes using the toxicity characteristic leaching procedure. Environmental science & technology. 2000;34(20):4376-4381

http://www.lead-/


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[13] Ajeetsaojie-waste management: an emerging environmental and health issue in india,national journal of medical research,volume 2 issue 1 jan – march 2012 issn 2249 4995

[14] India together: un report spotlights india‟s e-waste pile up – 31 march 2010. Available from: http://www.indiatogether.org/2010/mar/env-unewaste.htm

[15] Electronic waste: where does it go and what happens to it? By michellecastillo: january 2011. Available from: http://techland.time.com.

[16] Environment, energy and transportation program; electronic waste. National conference of state legislatures [cited june 10, 2006]; available from http://www.ncsl.org/programs/environ/cleanup/ elecwaste.

[17] Waste wise update: electronics reuse and recycling. Environmental protection agency 2000 [cited july 14, 2006]; available from: http:// www.epa.gov/wastewise/wrr/updates.htm.

[18] Article on Benefits of E-waste Recycling by Drew Hendricks in Growing Green Jobs August 6, 2012 Available from www.ewaste.htm

http://techland.time.com/

http://www.ncsl.org/programs/environ/cleanup/elecwaste

http://www.ncsl.org/programs/environ/cleanup/elecwaste

http://www.epa.gov/wastewise/wrr/updates.htm

http://www.ewaste.htm/


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Using a New Programme to Predict Thermal Comfort as a Base to Design Energy Efficient

Buildings Hanan Al-Khatri # ¹, Mohamed B. Gadi*²

# Civil and Architectural Engineering Department, Sultan Qaboos University, Oman

* Department of Architecture and Built Environment, University of Nottingham, UK

¹[email protected]

²[email protected]

Abstract---- A strong relationship relates the thermal comfort and the consumption of energy, especially in the hot arid climate where the installation of HVAC systems is unavoidable. In fact, it has been reported that the HVAC systems are responsible for consuming huge amounts of the total energy used by the buildings that can globally reach up to 40% of the total primary energy requirement. The future estimations indicate that the energy consumption is likely to continue growing in the developed economies to exceed that of the developed countries in 2020. Under these situations, it seems that the shift towards more energy efficient buildings is not an option. Because part of any successful environmental design is to understand the potentials of the site, the proposed programme (THERCOM) assists in weighing the indoor and outdoor thermal comfort in different climates in order to provide better understanding of the site environment as well as testing the thermal comfort chances of the initial concepts. Keywords---- energy efficient buildings, indoor thermal comfort, outdoor thermal comfort, passive design, arid climate, equatorial climate, warm temperate climate

I. INTRODUCTION

The current records indicate that the buildings sector is responsible for consuming 40% approximately of the total primary energy requirements [1]. For any typical building, around 80% of this amount is consumed as an operational energy from which huge amounts are consumed for the HVAC systems alone [2]. This pattern of consumption is forecasted to grow as the future estimations predict that in 2020, the energy consumption of the developed economies are likely to exceed that of the developed countries [1].

The associated negative influences for these consumption patterns on the ecological systems of the planet impose their regulation. Hence, the concept of the energy efficient

buildings is an attractive option. The energy efficient buildings can be characterised by their ability to satisfy both the proposed design requirements and the operational demands using the possible minimum energy compared with other buildings in the same design category [3]. This is mainly attained via applying the passive environmental design strategies in addition to utilising the renewable energy technologies.

In this regard, it may worth mentioning that the thermal comfort opportunities are defined to a large extent by the passive design strategies which in turn are mostly defined by the early design decisions. Thus, it is crucial to analyse and appreciate the thermal comfort demands in the early stages of the design in order to satisfy them passively as much as possible. Under the unavoidable conditions when the HVAC systems are required to modify the thermal conditions, the analysis of the thermal demands is still of benefit as it can be related to control the set points in order to achieve the optimal efficiency which will be reflected in potential savings.

However, in constructing such buildings, it is crucial to ensure that the proposed efficiency during the design stages is reflected in the operational stages as well. In fact, it has been reported that some of the energy efficient buildings tend to consume huge amounts of energy in order to keep them running properly, regardless of the apparent efficiency in the design stage [3].

The excess consumption of the operational energy may be partially due to the nature of the method by which the performance of these buildings is assessed. Frequently, a simulation approach is implemented to compare the intended scenario of the energy consumption with an ideal one. Although the patterns of the occupants' behaviour are often included, it is difficult to predict the actual patterns.


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Therefore, and taking into consideration that most of the operational energy is consumed to achieve the thermal comfort, it may be advantageous to view the thermal comfort demands from the approach of the adaptive models instead of applying the analytical ones. The former models are tailored towards specific groups of people in harmony with certain types of climates and they intensively consider the behavioural adaptations patterns [4]. As a result, most likely their predictions will resemble the actual patterns of consuming the energy in order to achieve the required thermal comfort.

Additionally and based on the characteristics of the energy efficient buildings, it can be understood that, at least in certain periods of the year, these buildings encompass the concept of the free running buildings that satisfy the heating and cooling demands passively. In a comparison with the buildings that depend on the HVAC systems, the free running buildings reduce the operational energy by around 50% [5]. However, in the attempt to use less energy, the risk of achieving poor quality of the indoor environment is obvious. This situation can partially be avoided by the comprehensive analysis of both the buildings thermal demands and the site potentials which leads to defining the periods at which the buildings can be operated on the free running mode. Inversely, in the situations of the uncomfortable conditions, the results of this analysis can be utilized to define adaptive set points that achieve the maximum potential savings.

II. THERCOM PROGRAMME

Based on the Visual Basic programming language, the proposed programme (Thermal Comfort in Different Climates - THERCOM) has been developed to measure and predict the thermal comfort in the free running buildings (to download a trial version of the programme, kindly visit: http://www.nottingham.ac.uk/~lazmbg/MScREA/). It does so by means of measuring the wet bulb globe temperature index, the adaptive model for thermal comfort, and the tropical summer index. In addition, it assess the thermal comfort in the outdoor environments by means of measuring the wet bulb globe temperature index, the wind chill index, the discomfort index, and the heat index.

THERCOM can measure the thermal comfort in twelve different cities located in three climates based on the Koppen-Geiger climate classification. Based on the integrated data, the predictions can be calculated for 24 hours in each month for all the integrated indices, except those of the adaptive model for thermal comfort. This exception was due to the nature of the integrated formula which is based on the outdoor monthly mean temperature. The integrated climates are: the equatorial, arid, and warm temperate climates. The exclusion of the remaining two climates, i.e. snow and polar, was due to the relatively low populations in regions where

these climates are dominant [6]. More details about the programme can be obtained from [7].

By predicting the interior thermal conditions, THERCOM assists in facilitating the selection of the most optimum design among the different design alternatives through comparing the thermal performance [5], [8]. In addition, by defining the periods at which the interior thermal conditions are comfortable, the programme in fact defines the periods at which the HVAC system can be switched off in the examined building. On the other hand, predicting the outdoor thermal conditions is crucial in order to design the exterior environments properly as they affect the indoor environments [9].

III. METHODOLOGY

The concept of the energy efficient buildings implies the good matching between the site environment and the used materials and equipment [3]. Based on this, and for the purpose of the study at hand, four mock-up models were constructed with different construction materials for the roof. The thermal performance of these models was investigated based on the effectiveness of the roof materials in contributing towards providing the comfortable thermal conditions.

A. Constructional Details

Despite the construction of the roof, the four models share identical dimensions, properties, and construction materials of the other parts of the models. They are basically a 3 m x 3 m x 3 m models with one 40 mm foam core plywood door (1 m x 2.2 m) located at the east facade and a single pane of glass with aluminium frame window (1.5 m x 1.5 m) located at the west facade. Brick concrete blocks with total thickness of 340 mm were used for the walls and a 100 mm concrete slab placed on the ground for the floor. The construction of these elements is detailed in Table 1.

For the roof, the investigated four construction systems are:

- Cinder concrete with insulation - Hardboard slab with insulation - Timber slab without insulation - Concrete roof with asphalt cover

The detailed components and their properties are displayed in Table 2.

The models are assumed to be located in Colombo city. It has been found that the west wind is dominant according to a previous analysis study of the city climate.

Therefore, the window was positioned on the west facade in order to encourage the natural ventilation. The wind velocity was modified based on the wind power low and based


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on Melaragno method to account for the changes in the wind velocity inside the buildings [10].

TABLE 1 CONSTRUCTIONAL DETAILS OF THE MODELS ELEMENTS EXCEPT THE ROOF

Layer Width (mm)

Density (kg/m³)

Specific heat

(J/kg.ºC)

Conductivity (W/m.ºC)

Wall Brick Masonry Medium

110 2000 836.8 0.711

Concrete Cinder

220 1600 656.9 0.335

Plaster Building (Molded Dry)

10 1250 1088 0.431

Floor Concrete 100 3800 656.9 0.837

Door Plywood 3 530 1400 0.140 Polystyrene Foam

34 46 1130 0.008

Plywood 3 530 1400 0.140 Window

Glass Standard

6 2300 836 1.046

B. Selected Thermal Index

THERCOM programme was used to compute the thermal comfort for the explored models by means of calculating the Tropical Summer Index. This model was selected for the study at hand based on the coincidence of its climatic boundaries and the climatic conditions of the chosen city [7]. The investigated period includes 288 hours distributed as 24 hours from each month.


A. Periods of Switching-off HVAC

For each model, the dominant thermal conditions over the examined period are presented in their percentages of thermal sensation as depicted in Figure 1. As can be noted from the pie chart of the first model, a comfortable thermal sensation was dominant in 83% of the investigated hours followed by slightly warm sensation with a percentage of 16%. In 1% of the investigated hours, the dominant sensation was slightly cool.

For the second model, the pie chart indicates that in 78% of the examined hours, the thermal conditions were considered as comfortable. In 21% and 1% of the investigated hours, slightly warm and slightly cool sensations were

presented respectively. For the third model, the thermal sensation of 76% of the tested hours was comfortable. In the remaining hours, a slightly cool sensation was present.

TABLE 2 DETAILS OF THE ROOF CONSTRUCTION

Layer Width (mm)

Density (kg/m³)

Specific heat (J/kg.ºC)

Conductivity (W/m.ºC)

Case 1: Cinder concrete with insulation Aggregate 10 2240 840 1.8 Rubber natural 2 930 2092 0.138 Polystyrene foam

50 46 1130 0.008

Polyethylene 1 950 2301 0.502 Concrete cinder 100 1600 656.9 0.335 Plaster ceiling tiles

10 1120 840 0.38

Case 2: Hardboard slab with insulation Aggregate 10 2240 920 1.3 Rubber Polyurethane elastomer

2 1250 1674 0.293

Hardboard slab 10 1000 1680 0.29 Wool, fibrous 10 96 840 0.043 Board 10 160 1890 0.04 Coat 10 2300 1700 1.2

Case 3: Timber slab without insulation Sand 10 2240 840 1.74 Rubber 2 1100 2092 0.293 Slab 10 300 960 0.055 Plaster Board 10 1250 1088 0.431

Case 4: Concrete roof with asphalt cover Asphalt cover 6 900 1966 0.088 Concrete lightweight

150 950 656.9 0.209

Plaster 10 1250 1088 0.431

The fourth model has a different thermal scenario as demonstrated from the Figure. The comfortable conditions were dominant in only 52% of the examined hours, with the slightly warm and warm sensations forming the remaining percentages as 42% and 6% respectively.

Based on these percentages, it can be concluded that the longest period in which the mechanical ventilation systems can be switched off is of the first model followed by the second, third, and fourth with percentages of 83%, 78%, 76%, and 52% respectively.

For the rest of the investigated hours, it may be necessary to use the HVAC systems to achieve the required comfortable thermal conditions with an obvious need for cooling in the four cases.


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Fig. 1 Percentages of the thermal sensations of the examined models

A detailed examination of the thermal conditions distributions as depicted in Figure 2 shows that for the first model, the mechanical ventilation can be switched off in about 14 hours from 20 to 10. Although an identical scenario is applicable for models 2 and 3 as can be noted from the Figure, the scope of switching off the HVAC systems in the hours from 10 to 20 is greater for the first model in comparison with the other models. In the fourth model, the hours at which the HVAC system can be switched off are limited to around 9 hours in each of January and February, 6 hours in each of May, June, November, and December, and the maximum is 13 hours in each of the months from July to October including both.

Nevertheless, it should not be forgotten that it is possible to expand the comfortable thermal conditions through the implementation of the passive design strategies. These strategies include the proper selection of the materials of the building envelope, the proper proportion of the openings to the solid area of the envelope, the orientation, the aspect ratio,

Fig. 2 Hours distribution of thermal sensations of the examined models

Periods of Switching HVAC off


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the integration of the shading devices, etc. Additionally, it should be mentioned that the use of the fans is permitted [12] as they consume negligible amount of energy compared with the HVAC systems to achieve an identical extension of the comfortable conditions.

B. Selecting the Optimum Roof System

From other perspective, the statistical variance of the tropical summer index temperatures was calculated for the four models to show values of 1.92, 2.54, 3.11, and 3.89, where the means of the index temperatures were 28.59 ºC, 28.69 ºC, 28.91 ºC, and 30.29 ºC in sequence.

The narrowest spread of the index temperatures of the first model from its mean value, in addition to its longest comfortable period and consequently shortest uncomfortable periods especially those with slightly warm conditions in comparison with other models, indicate that the first model may be considered as the optimum option within the investigated alternatives.

Table 3 shows the thermal resistance of the four examined roofs. It is clear from the table that the first model has the best thermal performance as it has the highest thermal resistance. A closer look clarifies that this resistance is mainly due to the presence of the thick insulation layer (layer 3: Polystyrene foam) which alone contributes of about 95% of the total roof resistance.

TABLE 3

DETAILS OF THE ROOF CONSTRUCTION

Resistance of Model 1 Model 2 Model 3 Model 4 Layer 1 0.006 0.008 0.006 0.068 Layer 2 0.014 0.007 0.007 0.718 Layer 3 6.250 0.034 0.182 0.023 Layer 4 0.002 0.233 0.023 - Layer 5 0.299 0.250 - - Layer 6 0.026 0.008 - - Total 6.597 0.532 0.218 0.809

Nonetheless, the relatively good thermal performance of the first model may additionally be partially due to the combined effect of the high thermal mass of the concrete deck in addition to the position of the insulation layer where it was located above the structural deck close to the outer surface. This according to [11] is the optimum position for the insulation to insure the most comfortable thermal conditions in the hot periods. For the first model, the order of the construction materials with the insulation closer to the outer surface insures that most of the heat is being prevented from passing through conduction to the interior layers of the roof. The permitted amount is absorbed and stored in the thermal mass of the concrete and thus delayed from affecting the interior conditions.

Although a fibrous wool thermal insulation was used in the second model, its thinness and position towards the inner side of the roof, in addition to the low thermal mass of the hard board deck, might contributed towards the lower thermal performance of this model in comparison with the first model.

Moreover, the lack of the insulation layer had an influence on the much lower thermal performance of the remaining models. However, the lower thermal mass of the timber slab of the third model had a relatively positive impact on the interior thermal conditions as it has a shorter time lag. This insures that the indoor temperature follows the exterior temperature. On the other hand, the high thermal mass of the concrete deck had contributed in the continuous heat stress during the night period as it can be noted from Figure 2.

IV. CONCLUSION

Under the current rates of energy consumption, it is important to consider the occupants' behaviour from the early stages of design as most of the operational energy is consumed to achieve the thermal comfort. This consideration is crucial for the energy efficient buildings as the risk of having poor quality of indoor environment is possible under the attempts to reduce the consumption of the operational energy.

Although calculating the thermal resistance may give an impression about the thermal performance of the examined roofs, the effect of the different construction systems and materials on the actual thermal conditions remains unclear. Hence, it is important to consult tools such as THERCOM to understand the predicted thermal comfort experience of the users by means of computing the thermal comfort indices suitable for the cases under consideration.

THERCOM is of great importance as it helps in better understanding and good appreciation of the available thermal comfort opportunities and the deviation from the required conditions. This understanding helps in making decisions about selecting the appropriate equipment, materials, amenities and possibly adjusting the operating patterns which eventually will increase the efficiency of the buildings.

In the study at hand, four mock-up models were tested to explore the thermal performance of the roof construction system and materials. The thermal comfort conditions were investigated using the tropical summer index. The aim of this examination was to define the periods at which the HVAC systems can be switched off and to select the most optimum construction system among the explored roofs. The first model, cinder concrete with insulation, had the optimum thermal performance. Possible factors incorporated to achieve this performance include the position of the insulation layer, its high thermal resistance, and the high thermal mass of the concrete deck.


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Furthermore, and in order to extent the comfortable conditions of the first model further, it is recommended to select the construction systems of the other parts of the building envelope based on their thermal properties, in particular the thermal mass. However, careful planning of the buildings layouts should be maintained to ensure the continuity of the natural ventilation.

Finally, it is recommended to perform further investigations to explore the extent at which the comfortable thermal conditions may be extended by means of using fans as a step before the unavoidable use of the HVAC systems.

REFERENCES

[1] L. Yang, H. Yan, and J. C. Lam, “Thermal comfort and

building energy consumption implications - A review,” Applied Energy, vol. 115, pp. 164-173, 2014.

[2] M. K. Singh, S. Mahapatra, and S. K. Atreya, “Adaptive thermal comfort model for different climatic

zones of North-East India,” Applied Energy, vol. 88,

pp. 2420-2428, 2011. [3] A. Meier, T. Olofsson, and R. Lamberts, “What is an

Energy-Efficient Building?,” in Proc. ENTAC, 2002, p.

3. [4] R. de Dear and G. S. Brager, “The adaptive model of

thermal comfort and energy conservation in the built environment,” International Journal of Biometeorolgy,

vol. 45, pp. 100-108, 2001. [5] M. A. Humphreys, H. B. Rijal, and J. F. Nicol,

“Updating the adaptive relation between climate and

comfort indoors; new insights and an extended database,” Building and Environment, vol. 63, pp. 40-55, 2013.

[6] A. K. Mishra and M. Ramgopal, “Field studies on human thermal comfort - An overview,” Building and

Environment, vol. 64, pp. 94-106, 2013. [7] H. Al-Khatri and M. B. Gadi, “Development of a new

computer model for predicting thermal comfort in different climates using Visual Basic programming language,” in Proc. People and Buildings, 2013, paper

MC2013-P24. [8] N. Djongyang, R. Tchinda, and D. Njomo, “Thermal

comfort: A review paper,” Renewable and Sustainable

Energy Reviews, vol. 14, pp. 2626-2640, 2010. [9] L. Shashua-Bar, I. X. Tsiros, and M. Hoffman,

“Passive cooling design options to ameliorate thermal

comfort in urban streets of a Mediterranean climate (Athens) under hot summer conditions,” Building and

Environment, vol. 57, pp. 110-119, 2012. [10] F. Allard, Natural ventilation in buildings: a design

handbook, Ed., London, UK: James & James, 1998. [11] I. C. d'Energia, Ed., Sustainable building: Design

manual, New Delhi, India: The Energy and Resources Institute, 2004, vol. 2.

[12] F. Nicol and M. Humphreys, “Derivation of the

adaptive equations for thermal comfort in free-running buildings in European standard EN15251,” Building

and Environment, vol. 45, no. 1, pp. 11 - 17, 2012.


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Trend Analysis of Climate Variability in Salalah, Oman

Mohammed Al-Habsi #1, Luminda Gunawardhana #2, Ghazi Al-Rawas #3 # Department of Civil and Architectural Engineering, Sultan Qaboos University

P.O. Box 33, Postal code 123, Al-Khoud, Sultanate of Oman 1 [email protected]

2 [email protected] 3 [email protected]

Abstract—The frequency and intensity of weather events are expected to change as climate change, which may result in more frequent and intensive disasters such as flash floods and persistent droughts. Subsequent impacts will affect regions in different ways, but projected to worsen conditions in water scares countries like Oman. In Oman, changes in precipitation and temperature have already begun to be detected, although a comprehensive analysis to determine long-term trends has yet to be conducted. We analyzed daily precipitation and temperature records in Salalah city of Oman, mainly focusing on extremes. A set of climate indices, defined in the RClimDex software package, were derived from the longest available daily series (precipitation over the period 1943-2011 and temperature over the period 1991-2011). Results showed significant changes in daily minimum and maximum temperatures associate with cooling as well as warming. The annual number of cold nights (percentage of days when daily minimum temperature (TN) less than 10th percentile of that during base period: 1991-2000) decreased by 8 days per decade (p-value = 0.3). On the other hand, the annual number of warm nights (percentage of days when daily minimum temperature (TN) larger than 90th percentile of that during base period) increased by 10 days per decade (p-value = 0.3). In contrast, the annual occurrence of cold days increased by 11 days per decade (p-value = 0.25), while the annual occurrence of warm days decreased by 4 days per decade (p-value = 0.62). The significant trends apparent in minimum temperatures reveal that Salalah area has become less cold rather than hotter. Moreover, contrary trends in minimum and maximum temperatures indicate that, in long-term, daily temperature range has decreased in this area.

Annual total precipitation averaged over the period 1943-2011 is 95 mm, which shows a statistically weak negative trend with a -2 mm/10 yr rate. There is also a tendency for precipitation extremes according to many indices. The contribution from very wet days to the annual precipitation totals steadily increases with significance at 87% level. The positive trend in simple daily intensity index is also clear and reasonably significant (p-value = 0.29). Results of all these indices lead us to conclude that precipitation intensity in Salalah has increased while mean precipitation changes are less marked.

I. INTRODUCTION

Extreme weather events are causing extensive damage to economy, environment and human life. For example, the

supper cyclone, hurricane gonu in 2007 caused extensive damage along coastline cities, with total rainfall reached 610 mm near the coast. The cyclone caused about 4 billion in damage (2007 USD) and 49 deaths (Rafy and Hafez, 2008). Many studies show that these extreme events that used to be rare in more than 60 years before are becoming frequent in many parts of the world in recent decades. Alexander et al. (2006) assessed changes in daily temperature and precipitation extremes. They found that the trends in minimum temperature are more significant, implying that many regions become less cold rather than hotter. Easterling et al. (2000) revealed the heavy precipitation change in Siberia and northern Japan while mean precipitation changes are less marked. Therefore, greater understanding of occurrence of past extremes is prime important to avoid or at least to reduce the damages such as catastrophic floods and prolonged period of droughts (Beniston et al. 2007; Fowler et al. 2005).

In Oman, changes in precipitation and temperature have already detected (Al Rawas and Valeo, 2010), although a comprehensive analysis to determine long-term trends has yet be conducted. With efforts to build a long-term database, the Sultan Qaboos University now possessed quality controlled records of daily temperature over the period 1991-2011 and daily precipitation over the period 1943-2011. The objective of this research is to use these data to evaluate the trends of extreme temperature and precipitation change in Salalah.

II. STUDY AREA

Salalah, the second largest city in the Sultanate of Oman, located in southern of Oman and on the edge of the Indian Ocean (Fig. 1). Annual total precipitation averaged over the period 1943-2011 is 95 mm, which shows statistically weak negative trend of a 2 mm/10-years. Mean annual temperature during 1980-2008 warms at a rate of 0.12°C/10-years, which is relatively small compared to warmings recorded in northern cities such as Sur and Khasab (1.03 and 0.5°C per decade, respectively). Salalah costal plain serves one of the intense agricultural fields in the Sultanate of Oman. Consequently, over the time, saline water intrusion has become one of the major issues for the management of sustainable groundwater



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resource. By the end of 2003, a main project was operated to treat wastewater and re-inject 20000 m3 daily in the coastal wells in Salalah in order to stop seawater intrusion. In past, severe cyclones have occurred in Salalah area in 1959, 1963 and 1966. In 2002, a tropical storm affected Salalah city which brought 58.6 mm rain in the city area and 250.6 mm rain in adjoining mountains.

Fig. 1. Study area in Oman

III. METHODOLOGY

In this study, maximum and minimum temperatures, and precipitation trends were analysed using a selection of 27 indices. These indices were calculated using RClimDex software, which was developed by the Expert Team on Climate Change Detection, Monitoring and Indices (ETCCDMI) to analyse many aspects of a changing climate (Alexander et al. 2006). The quality control procedure in RClimDex was applied to identify errors in data processing. Both minimum and maximum daily temperatures were considered as missing values if daily minimum temperature is greater than daily maximum temperature. Daily maximum and minimum temperature records were defined as outliers if they lye outside the range of four standard deviations (STDEV) from the mean of the records (Mean ± 4 × STDEV). Negative precipitation records were also considered as missing values. Homogeneity test was conducted using RHtest software package to identify abrupt changes in data series. However, no artificial step changes were detected.


The set of 27 indices used in this study includes 16 temperatures related and 11 precipitation related indices which describe changes in intensity, frequency and duration of temperature and precipitation events. For space reason, we present specific indices with significant impacts, together with combined indices, if the thresholds represent to values of

hydrological significance. A trend is said to be detected when a test of the null hypothesis that no trend is present is rejected at a high significance level, such as 5% or 10%.

We found no significant changes in most of precipitation indices (Table 1). However, consecutive wet days (CED) shows negative trend with a confidence 89% (Fig. 2). On the other hand, consecutive dry days (CDD) increases but exhibits only a statistically weak relationship with standard error larger than the slope of the fitted linear regression line. The simple

TABLE I TEST STATISTICS OF PRECIPITATION INDICES

Index Slope Standard

error P-value

Significant at

5% 10% CDD 0.253 0.38 0.507 No No CWD -0.031 0.020 0.113* No No

PRCPTOT -0.194 0.535 0.718 No No RX1day 0.018 0.211 0.933 No No RX5day -0.157 0.284 0.581 No Yes

R95P 0.153 0.466 0.744 No No R95P/

PRCTOT 0.0027 0.0017 0.130* No No

SDII 0.015 0.014 0.285 No No *Significance level < 25%

Fig. 2. Trend of consecutive wet days (CWD)

Fig. 3. Trend of simple daily intensity index (SDII)

Salalah


[ISBN 978-81-925781-9-4], April 2014, pg. 54-57


Fig. 4. Contribution from very wet days to total precipitation

daily intensity index (SDII), which is the ratio of annual precipitation and number of wet days, shows a reasonably positive trend with a confidence of 71% (Fig. 3). Figure 4 depicts that the contribution from very wet days to the annual precipitation total steady increases with a reasonable high confidence of 87%. In other words, the probability of the null hypothesis (no contribution from extreme precipitation) becomes true is less than 0.13. These results lead us to conclude that precipitation intensity in Salalah has increased while the annual total precipitation slightly decreases.

Both absolute temperature indices: TNn (annual minimum value of daily minimum temperature) and TXx (annual maximum value of daily maximum temperature) in Table II exhibit no statistically significant change. However, the trends of TNx (annual maximum value of daily minimum temperature, Fig. 5) and TXn (annual minimum value of daily maximum temperature, Fig. 6) are relatively significant. The absolute magnitude of the gradients of two curves is higher than standard errors, even though none of them are statistically significant at 10% level. The extreme temperature range (ETR) index calculated from the difference between TXn and TNx indicates a reasonably strong upward trend (Fig. 7) with a confidence of 86%. In practical point of view, these changes indicate that the temperature of warmest nights increases while the temperature of coolest day times decreases. When the percentile based indices were considered, the annual number of cold nights (percentage of days when daily minimum temperature (TN) less than 10th percentile of that during base period: 1991-2000) decreased by 8 days per decade (p-value = 0.3). On the other hand, the annual number of warm nights (percentage of days when daily minimum temperature (TN) larger than 90th percentile of that during base period) increased by 10 days per decade (p-value = 0.3). In contrast, the annual occurrence of cold days increased by 11 days per decade (p-value = 0.25), while the annual occurrence of warm days decreased by 4 days per decade (p-value = 0.62).

V. CONCLUSIONS

In this study, precipitation and temperature extremes in Salalah, Oman were investigated using a set of climate indices. The significant trends apparent in minimum temperatures reveal that Salalah area has become less cold rather than hotter. Moreover, contrary trends in minimum and maximum temperatures indicate that, in long-term, daily temperature range has decreased in this area.

Many precipitation indices show no statistically significant trend. However, there is a tendency for precipitation extremes according to some indices. The contribution from very wet days to the annual precipitation totals steadily increases with a confidence of 87%. The positive trend in simple daily intensity index is also clear and reasonably significant (p-value = 0.29). However, the annual total precipitation averaged over the period 1943-2011 shows a weak negative trend with a -2 mm/10 yr rate. Results of all these indices lead us to conclude that precipitation intensity in Salalah has increased while mean precipitation changes are less marked

TABLE III TEST STATISTICS OF TEMPERATURE INDICES

Index Slope Standard error

P-value

Significant at

5% 10% TNn -0.016 0.027 0.562 No No TXx -0.077 0.105 0.472 No No TNx 0.024 0.024 0.338 No No TXn -0.056 0.052 0.299 No No CSDI -0.353 0.270 0.206* No No DTR -0.02 0.008 0.025* No No

TN10P -0.217 0.202 0.296 No No TN90P 0.282 0.266 0.302 No No TX10P 0.313 0.265 0.253 No No TX90P -0.120 0.239 0.622 No No ETR 0.079 0.051 0.137* No No

*Significance level < 25%

Fig. 5. Trend of annual maximum value of daily minimum temperature (TNx)


[ISBN 978-81-925781-9-4], April 2014, pg. 54-57


Fig. 6. Trend of annual minimum value of daily maximum temperature (TXn)

Fig. 7. Trend of extreme temperature range index (ETR)

ACKNOWLEDGMENT

Authors wishes to acknowledge Prof. Xuebin Zhang and Prof. Feng Yang at the Climate Research Branch of Meteorological Service of Canada for providing RClimDex.

REFERENCES

[1] M. E. Rafy, and Y. Hafez, ―Anomalies in meteorological fields over northern Asia and its impact on Hurricane Gonu,‖ 28th Conference on Hurricanes and Tropical Meteorology, pp. 1–12, 2008.

[2] L. V. Alexander, et al., ―Global observed changes in daily extremes of temperature and precipitation,‖

Journal of Geophysical Research, 111, D05109, doi:10.1029/2005JD006290, 2006.

[3] D. R. Easterling, T. R. Karl, K. P. Gallo, D. A. Robinson, K. E. Trenberth and A. Dai, ―Observed climate

variability and change of relevance to the biosphere,‖

Journal of Geophysical Researches vol. 105, pp. 101–

114, 2000. [4] G. A. Al-Rawas and C. Valeo, ―Relation between Wadi

drainage characteristics and peak flood flows in arid northern Oman,‖ Hydrological Sciences Journal,vol. 55, pp. 377-393, 2010.

[5] M. Beniston et al., ―Future extreme events in European climate: an exploration of regional climate model projections,‖ Climatic Change, vol. 81, pp. 71–95, 2007.

[6] H. J. Fowler, M. Ekstrom, C. G. Kilsby and P. D. Jones, ―New estimates of future changes in extreme rainfall across the UK using regional climate model integrations, 1. Assessment of control climate,‖ Journal of Hydrology, vol. 300, pp. 212–233, 2005.


[ISBN 978-81-925781-9-4], April 2014, pg. 58-62


Wadi Flow Simulation Using Tank Model in Muscat, Oman

Mohammed Al-Housni #1, Luminda Gunawardhana #2, Ghazi Al-Rawas #3 # Department of Civil and Architectural Engineering, Sultan Qaboos University

P.O. Box 33, Postal code 123, Al-Khoud, Sultanate of Oman 1 [email protected]

2 [email protected]

3 [email protected]

Abstract— In Oman, changes in precipitation intensity and

frequency have already begun to be detected, although the attributed impacts, such as, flash flooding is poorly understood. For example, the supper cyclonic storm, hurricane Gonu in 2007 led to the worst natural disaster on record in Oman, with total rainfall reached 610 mm near the cost. The cyclone and flash flood caused about $4 billion in damage (2007 USD) and 49 deaths. The objective of this study is to develop a Wadi-flow simulation model to understand precipitation-river discharge relationship in Muscat. A lumped-parameter, non-linear, rainfall-runoff model was used. The Food and Agriculture Organization (FAO-56) modified Hargreaves equation was used for estimating reference evapotranspiration (ET0). Precipitation and temperature data during 1996-2003 were obtained from the Muscat-airport meteorological station. Observed river discharges during 26-30, March 1997 were used to calibrate the model and observations during 1997-2003 were used to verify our simulations. Simulated water discharges agreed with the corresponding observations, with the Nash–Sutcliffe model efficiency coefficient equals to 0.88. This developed model will later be used with a set of General Circulation Model scenarios (GCM) to understand the Wadi-flow variations under changing climate conditions.

I. INTRODUCTION

Oman, located in south-Eastern corner of the Arabian Peninsula, encompasses a diverse range of topography, including mountain ranges, low land, coastal areas and arid deserts. The coastal line of Oman extends over 3165 km and experiences very severe tropical cyclones. The supper cyclonic storm, hurricane Gonu in 2007 led to the worst natural disaster on record in Oman, with total rainfall reached 610 mm near the cost. The cyclone and flash flood caused about $4 billion in damage (2007 USD) and 49 deaths (Rafy and Hafez, 2008). Recently changes in intensity and frequency of the weather events and subsequent impacts demand countermeasures to adopt with these changes in future. Hydrological model is an effective tool that could provide river discharge response attributed to the changes in weather variables and can be used for planning countermeasures to cope with the potential impacts.

The tank model developed by Sugawara (1984) is a lumped parameter, non-linear rainfall- runoff model. The tank

model is composed one, two, three or four tanks laid vertically in series. Various coefficients represent different hydrological processes such as surface and subsurface runoff and infiltration. The different in magnitude of these coefficients in different catchments reflects the geographical features of the watersheds. Gunawardhana and Kazama (2012) used the tank model to study water availability and low-flow analysis of the Tagliamento River discharge in Italy under changing climate conditions. Also, this tank model has been used for river discharge simulations in 12 catchment areas in Japan (Yokoo et al., 2001). Both studies were done in humid regions, but in this research, we test the performances of the tank model to simulate wadi flow in arid region in Oman.

The objective of this study is to develop a Wadi-flow simulation model to understand precipitation-river discharge relationship in Muscat (Al-Khoud catchment area). The developed model is expected to use for climate change scenarios in future studies to predict wadi flow variations under changing climate conditions.

II. STUDY AREA

Wadi Al-Khoud in Oman is located in the northern part of Oman and at the western-north part of Muscat. The downstream of catchment area is towards northeast Gulf of Oman (Fig1). The total catchment area approximately is about 1740 km2. The elevation in the catchment area ranges from 41 m at the catchment outlet in Al-Khoud to 2339 m in the inland mountain area. The climate is arid and it is important for the water resources, especially for agriculture and domestic purposes. The annul precipitation occurs in November, December, March and April as observed from previous data. The average annual rainfall in Muscat is around 63mm (Al-Khoud station) to 210 mm (JabalBani Jabir). According to the meteorological records from 1984 to 2003, the annual average maximum and minimum temperatures near the catchment outlet were approximately 33 and 24C°, respectively. The geology of the catchment area mainly consists of 55% of igneous and volcanic rocks, whereas, 3% of metamorphic rocks, 16% of sedimentary rocks and 26% of recent deposits.



[ISBN 978-81-925781-9-4], April 2014, pg. 58-62


III. THEORY

The tank model is a simple non-linear rainfall-runoff model composed of one or several tanks (Fig. 2). The coefficients represented for different hydrological processes (surface and subsurface runoff and infiltration) are generally obtained by matching observed and simulated data. Magnitude differences of these coefficients in different catchments reflect the geographical features of the watersheds. The rainfall summed to put into the first tank at the top. Evapotranspiration is directly subtracted from the top tank. Among the four tanks in the model, first tank at the top account for rapid runoff near the ground surface and second tank models the shallow subsurface runoff process. Other two tanks at the bottom delayed surplus water from the top two tanks.


This phenomenon represents hydrological role of the deep aquifers that accumulate the infiltrating water from the ground

surface and released in to the downstream with certain time delays (Todini, 2007). Representative mathematical model for the water exchange between tanks and daily runoff generation can be expressed as follows.

(1)

(2)

(3)

4

1,

xnxn RQ (5)

where x: number of tanks counted from top n: number of days from the beginning (1/d) Δt: length of time step A(x): runoff coefficient of xth tank (1/d) B(x): infiltration coefficient of xth tank (1/d) H(x,n): water depth in xth tank at nth day (mm) Z(x): height of runoff hole of xth tank (mm) R(x,n): runoff from xth tank at nth day (mm/d) I(x,n): infiltration in xth tank at nth day (mm/d) T(n): total input to first tank at nth day (mm/d) Evt(n): evapotranspiration at nth day (mm/d) Q(n): total runoff at nth day (mm/d) P(n): precipitation at nth day (mm/d)

Fig. 2. Tank model structure for runoff generation

I(x,n) = B(x)× H(x,n)

T(n) = P(n) – Evt(n)

R(x,n) = A(x)× [H(x,n)-Z(x)] H(x,n) > Z(x) 0 H(x,n) ≤ Z(x)

H(x,n)-[R(x,n)×Δt]-[I(x,n)×Δt]+[T(n+1)×Δt] x=1 H(x,n)-[R(x,n)×Δt]-[I(x,n)×Δt]+[I(x–1, n)×Δt] x≠1

H(x,n+1)=

(4)


[ISBN 978-81-925781-9-4], April 2014, pg. 58-62


TABLE I TANK MODEL COEFFICIENTS

* based on 12 catchments in southern Japan from Yokoo et al.

The Food and Agriculture Organization (FAO-56)

modified Hargreaves equation, one of the widely used temperature based method, was used for estimating reference evapotranspiration (ET0).

aRTTTT

ET

minmax

minmax0 8.17

2

0023.0

(6)

where Tmax(°C) is the maximum daily air temperature,

Tmin(°C) is the minimum daily air temperature, Ra (MJ/m2/d) is the extra-terrestrial solar radiation and λ is the latent heat of

vaporization (2.45 MJ/m2/d). Actual evapotranspiration was estimated by matching observed river discharge with simulations. Precipitation and temperature data during 1996-2003 were obtained from the Muscat-airport meteorological station. The Nash–Sutcliffe model efficiency coefficient is used to assess the predictive power of hydrological models. It is defined as:

T

t

tm

to

T

t

tm

to

QQ

QQE

1

2

1

2

1

where Qo is observed discharge, and Qm is modelled

discharge. Qot is observed discharge at time t. The closer the

model efficiency is to 1, the more accurate the model is. If the simulated discharges obtained from the tank model and historical discharges have a trend and significant correlations, the simulation is considered successful and the tank model can be used to evaluate the flow phenomena for the concerning watersheds.

IV. RESULTS AND DISCUSSIONS

Model calibration was done by matching observed river discharges at gage station at the outlet of the catchment area in 1997 and the model verification was done according to data observed in 1997, 1999, 2000 and 2003 (Fig.3). Simulated wadi flow agreed with the corresponding observations, with Nash-Sutcliffe model efficiency coefficient of 0.88. Table 1

shows the calibrated model parameters in Al-Khoud catchment area. These model parameters in Al-Khoud were compared with the derived parameters in 12 catchment areas in Japan for understanding parameter dependency on different geographical and climatic settings.

The coefficients of the tank model represent different hydrological processes of the catchment. As example, larger A1 coefficient produces higher rapid surface runoff near the ground surface, while larger B1 coefficient stands for higher infiltration capacity. According to Table 1, A11 coefficient in Al-Khoud catchments is smaller than that in Japanese catchments. This is because top soil layer in Oman catchments generally has very low soil moisture content due to extreme dry condition in air and high evaporation throughout the year. Therefore, infiltration potential is higher and runoff potential in very shallow subsurface layer is low in catchments in Oman than them in Japan. For this reason, Al-Khoud catchments generate smaller A11 coefficients for the tank models than in Japanese catchments. In contrast, A12 coefficient for Al-Khoud catchment area is greater than Japanese catchment area. This can be attributed to the high representative gradient (RG) of the catchments in Oman than in Japan. Steep slope in Al-Khoud catchment area increases the runoff potential in the shallow subsurface layers. Therefore, infiltrated water from the top soil surface rapidly flows to downstream areas rather than recharging deep aquifers. For the same reason, Al-Khoud catchment area has small storage capacities (Z11, Z12 and Z2) than the Japanese catchments. Moreover the land-use types in the catchment area have a significant effect in retaining water in shallow subsurface layers. Absence of full grown trees with deep spread roots in Oman facilitates rapid subsurface flow which attenuates groundwater recharge and subsurface storage. This phenomenon replicate with small Z coefficients in Oman than in Japan. B1 coefficients between two catchments also depict significant differences. These variations indicate that the Al-Khoud catchment has higher infiltration capacity than the Japanese catchments, which may also be attributed to the low soil moisture content in Al-Khoud than in Japanese catchments.

V. CONCLUSIONS AND RECOMMENDATIONS

The objective of this study was to develop a rainfall-runoff model to simulate Wadi flow in Muscat, Oman. Wadi Al-

Catchment area Model parameter

A11 A12 B1 A2 B2 A3 B3 A4 Al-Khoud 0.14 0.35 0.37 0.05 0.05 0.02 0.03 0.0003 Southern Japan* 0.4 0.2 0.15 0.1 0.05 0.02 0.03 0.003 Z11 Z12 Z2 Z3 H4 H3 H2 H1 Al-Khoud 1 0.1 5 10 0 0 0 0 Southern Japan* 40 15 20 10 200 40 2 1

(7)

http://en.wikipedia.org/wiki/Hydrology


[ISBN 978-81-925781-9-4], April 2014, pg. 58-62


Khoud catchment area was selected. Model calibration was carried out with observations in 1997. The simulated Wadi flow model was verified with observation in 1997, 1999, 2000 and 2004. The Nash–Sutcliffe model efficiency coefficient of 0.88 could be obtained. The calibrated tank model parameters in Wadi Al-koud catchment area were compared with the parameters calibrated in several catchments in Japan. Physical meaning of the tank model parameters in arid environment could be successfully interpreted. It was found that the differences of model parameters of two catchment areas depend on vegetation cover, topography (RG) and soil moisture content.

The tank model performance highly depends on input data quality. Lack of long-term quality controlled rainfall and river discharge records was a major constrain. Respective authorities are therefore encouraged to maintain a long-term data base to facilitate academic community.

The results of this study showed the ability of the tank model to simulate Wadi flow with a reasonable accuracy and therefore will be applicable for climate impact predictions. In the next step of this study, downscaled GCMs scenarios from several models for different climate variables will be used with the developed tank model to simulate wadi flow variations in future.

REFERENCES [1] M. E. Rafy, and Y. Hafez, “Anomalies in meteorological fields over

northern Asia and its impact on Hurricane Gonu,” 28th Conference on Hurricanes and Tropical Meteorology, pp. 1–12, 2008.

[2] M. Sugawara, “On the analysis of runoff structure about several Japanese River,” Japanese Journal of Geophysic, vol. 4, pp. 1-76, 1961.

[3] L. N. Gunawardhana and S. Kazama, “A water availability and low-flow analysis of the Tagliamento river discharge in Italy under changing climate conditions,” Hydrology and Earth System Sciences, vol. 16, pp. 1033-1045, 2012.

[4] Y. Yokoo, S. Kazama, M. Sawamoto and H. Nishimura, “Regionalization of lumped water balance model parameters based on multiple regression,” Journal of Hydrology, vol. 246, pp. 209-222, 2001.

[5] E. Todini, “Hydrologigal catchment modeling: past, present and future,” Hydrology and Earth System Sciences, vol. 11, pp. 468-482, 2007.


[ISBN 978-81-925781-9-4], April 2014, pg. 58-62


Fig. 3. Observed and simulated wadi flows


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An Assessment of Temperature and Precipitation Change Projections in Muscat, Oman from Recent

Global Climate Model Simulations Abdulaziz Al-Ghafri #1, Luminda Gunawardhana #2, Ghazi Al-Rawas #3

# Department of Civil and Architectural Engineering, Sultan Qaboos University P.O. Box 33, Postal code 123, Al-Khoud, Sultanate of Oman

1 [email protected] 2 [email protected] 3 [email protected]

Abstract— Oman is vulnerable to the impacts of climate

change, the most significant of which are increased temperature, less and more erratic precipitation, see level rise (SLR) and desertification. The objective of this research is to investigate the potential variation of precipitation and temperature in Muscat, the capital city of Sultanate of Oman in future. We used the MIROC general circulation model (GCM) output (maximum and minimum temperatures and precipitation) from the Representative Concentration Pathways (RCPs) 2.6, 4.5, 6.0 and 8.5 scenarios of the Fifth Assessment Report (AR5) of the Intergovernmental Panel on Climate Change (IPCC) for assessing changes in climate in the period of 2080-2099 compared to the baseline period of 1986-2005. The spatial mismatch between GCM grid scale and local scale was resolved by applying the LARS stochastic Weather Generator (WG) model. The results obtained for 4 scenarios indicate a significant warming in future, which ranges from 0.93ᴼC (minimum temperature by 1.1ᴼC and maximum temperature by 0.86ᴼC) for the lowest scenario, RCP 2.6, to 3.1ᴼC (minimum temperature by 3.2ᴼC and maximum temperature by 3.0ᴼC) for the highest one, RCP 8.5, relative to baseline level. The differences in the precipitation projections between the scenarios are much greater compared to consistent warming depicted in temperatures. The results reveal -36.4% and -36.0% decreases in precipitation for the RCP 2.6 and RCP 4.5 scenarios, respectively, while, RCP 6.0 and RCP 8.5 scenarios predict increase in precipitation in a range from 9.6% to 12.5%, respectively during 2080-2099 compared to 1986-2005 period. These results need to be further improved by adopting more GCMs, which will provide potential changes in a consistent range.

I. INTRODUCTION

Observed and projected increases in temperature and precipitation variability are perhaps the most influential climate driven changes to impact water systems (Parry et al., 2007). Located in an arid region, the climate of Oman is vulnerable to the potential impacts of climate change, the most significant of which are increased average temperatures, less and more erratic precipitation, sea level rise (SLR) and desertification. Oman is primarily concerned due to its chronic water stress and lack of resilience (institutional, infrastructure and social) against climate change.

Groundwater represents about 78% of the water supply in Oman. Owing to a lack of data and the very slow reaction of groundwater systems to changing recharge conditions, impacts of climate change on groundwater are poorly understood. Groundwater resources are related to climate change through hydrologic processes, such as precipitation and evapotranspiration, and through interaction with surface water. With increased evapotranspiration as a result of higher air temperature and decreased precipitation, the impact of climate change will result in declining groundwater recharge (Eckhardt and Ulbrich, 2003; Brouyere et al., 2004) and alter the associate temperature distribution in the subsurface. For example, in the Ogallala Aquifer region, projected natural groundwater recharge decreases more than 20% in all simulations with warming of 2.5°C or greater (Rosenberg et al., 1999).

Integrating climate change mitigation and adaptation in development strategies and policies is a must for Oman which is at the early stage of economic and industrial development. Thus far in Oman, the scientific knowledge about the climate change and its impacts on the hydro-meteorological extremes has not been fully studied thereby making it difficult to assess future risks. Therefore, the main objective of this research is to investigate the potential variation of precipitation and temperature in Muscat, the capital city of Sultanate of Oman in future.

II. STUDY AREA

Oman located in south-Eastern corner of the Arabian Peninsula, encompasses a diverse range of topography, including mountain ranges, low land, coastal areas and arid deserts. The coastal line of Oman extends over 3165 km and experiences very severe tropical cyclones. The supper cyclonic storm, hurricane Gonu in 2007 led to the worst natural disaster on record in Oman, with total rainfall reached 610 mm near the cost. The cyclone and flash flood caused about $4 billion in damage (2007 USD) and 49 deaths (Rafy and Hafez, 2008). The climate of the country is mainly arid or semiarid, which receives less than 100 mm in annual rainfall



[ISBN 978-81-925781-9-4], April 2014, pg. 63-66


on average compared to annual global average of 1123 mm. Muscat, the capital city of Oman is a coastal city (Fig.1), which accommodates 29.5% of the total population in Oman in 2010. The average precipitation of Muscat is 81 mm over the period 1977-2011 and it shows statistically weak increasing trend at an average rate of 6 mm/10 yr. The rainfall pattern proved to be irregular, averaging rain on only around 7 days per year. Consequently, number of consecutive days of no rainfall is relatively high, which was estimated to be about 225 days per year over the period 1977-2011. The daily maximum temperature in Muscat fluctuates between 17 and 49C, and the daily minimum temperature is between 10 and 40C over the period 1986-2011.


III. METHODOLOGY

Observed precipitation and temperature data in the Muscat airport meteorological station for the period of 1986-2005 were obtained. For the future climates, we used the MIROC general circulation model (GCM) output (maximum and minimum temperatures and precipitation) from the Representative Concentration Pathways (RCPs) 2.6, 4.5, 6.0 and 8.5 scenarios in the periods of 1986-2005 and 2080-2099. The four RCPs are based on multi-gas emission scenarios. They are being used to drive climate model simulations planned as part of the World Climate Research Programme’s

Fifth Coupled Model Intercomparison Project (CMIP5) (Taylor et al. 2009).

The spatial mismatch between GCM grid scale and local scale was resolved by applying statistical downscaling method. A stochastic weather generator (LARS-WG) used in this study serve as a computationally inexpensive tool to produce multiple-year climate change scenarios at the daily time scale which incorporate changes in both mean climate and in climate variability (Semenov & Barrow, 1997). LARS-WG

can be used for the simulation of weather data at a single site under both current and future climate conditions. These data are in the form of daily time-series for a suite of climate variables, namely, precipitation (mm), maximum and minimum temperature (°C) and solar radiation (MJm-2day-1). The simulation of precipitation occurrence is based on distributions of the length of continuous sequences, or series, of wet and dry days. To developed future scenarios, the mean of the empirical distributions for wet and dry spell length from the baseline (1986-2005) and future time period (2080-2099) were calculated for each month. The relative change in length of wet (or dry) series was calculated as follows.

Relative change in length = length2080-2099 / length1986-2005 (1)

Similarly, the relative change in standard deviation

(St.dev.) of minimum and maximum temperatures and the mean change in precipitation amount were calculated as follows.

Relative change in St.dev = St.dev.2080-2099 /

St.dev.1986-2005 (2) Relative change in Precipitation = pre.2080-2099

/pre.1986-2005 (3) For monthly mean changes in maximum and minimum

temperatures, the monthly mean changes in these values between the future and baseline periods were considered.


We used the MIROC model output of maximum and minimum temperatures and precipitation from the RCPs 2.6, 4.5, 6.0 and 8.5 scenarios for assessing changes in climate in the period of 2080-2099 compared to the baseline period of 1986-2005. An example of the scenario file developed for the RCP4.6 is shown in Fig. 2.

The scenario files developed for each scenario were used with the observations during 1986-2005 to produce time series of weather variable for the period of 2080-2099. Table 1 shows a summary of weather variables and their relative change in future compared to baseline time period. Figure 3 depicts accumulative probability distributions of three variables in baseline period and four scenarios in the future. According to figures 3 a) and b), there is a consistent warming in both minimum and maximum temperatures with different magnitudes for all scenarios during 2080-2099 compared to observations in 1986-2005 period. RCP8.5, which is representative of the high range of non-climate policy scenarios (subsequent radiative forcing of 8.5Wm-2 in 2100), predicts the highest warming of 3.2 and 3.05C for minimum and maximum temperatures, respectively. Similarly, RCP2.6, which assumes drastic policy interventions to reduce greenhouse gas emissions (subsequent radiative forcing of 2.6 Wm-2 by 2100), predicts the lowest warming of 1.01 and


[ISBN 978-81-925781-9-4], April 2014, pg. 63-66


0.86C for minimum and maximum temperatures, respectively. Warming predicts by two other scenarios varies between RCP8.5 and RCP2.6 in similar magnitudes.

Fig. 2. A scenario file developed to use in the LARS-WG for the MIROC global climate model for the RCP4.6 scenario for the time period 2080–2099

at Muscat.

The differences in the precipitation projections between the scenarios are much greater compared to consistent warming depicted in temperatures. The results reveal -36.4% and -36.0% decreases in precipitation for the RCP 2.6 and RCP 4.5 scenarios, respectively, while, RCP 6.0 and RCP 8.5 scenarios predict increase in precipitation in a range from 9.6% to 12.5%, respectively during 2080-2099 compared to 1986-2005 period. Figure 3 c) depicts that the RCP8.5 scenario predicts the potential of very extreme precipitation events in future, which may increase the risk of floods in our study area.

V. CONCLUSIONS AND RECOMMENDATIONS

This study was conducted to investigate the potential variation of precipitation and temperature in Muscat, the capital city of Sultanate of Oman in future. We used the MIROC general circulation model output (maximum and minimum temperatures and precipitation) from the RCPs 2.6, 4.5, 6.0 and 8.5 scenarios of the IPCC Fifth Assessment Report for assessing changes in climate in the period of 2080-2099 compared to the baseline period of 1986-2005. LARS-

WG was used for the simulation of weather data under both current and future climate conditions.

Fig.3 Probability distributions of weather variables in the baseline and future time periods

The results obtained for 4 scenarios indicate a significant

warming in future, which ranges from 0.93ᴼC (minimum temperature by 1.1ᴼC and maximum temperature by 0.86ᴼC) for the lowest scenario, RCP 2.6, to 3.1ᴼC (minimum temperature by 3.2ᴼC and maximum temperature by 3.0ᴼC) for the highest one, RCP 8.5, relative to baseline level.

// Columns are: // [1] month // [2] relative change in monthly mean rainfall // [3] relative change in duration of wet spell // [4] relative change in duration of dry spell // [5] absolute changes in monthly mean min temperature // [6] absolute changes in monthly mean max temperature // [7] relative changes in daily temperature variability // [8] relative changes in mean monthly radiation [VERSION] LARS-WG5.5 [NAME] Muscat_RCP46 [BASELINE] 1986 [FUTURE] 2080 [GCM PREDICTIONS] Jan 0.68 0.94 1.06 1.09 1.09 0.86 1 Feb 1.40 0.80 0.66 1.09 1.09 0.71 1 Mar 0.34 0.86 3.99 1.09 1.09 1.04 1 Apr 1.62 0.84 1.51 1.09 1.10 0.94 1 May 0.41 1.11 1.39 1.09 1.08 0.86 1 Jun 0.58 0.74 0.84 1.06 1.05 0.78 1 Jul 3.69 0.81 1.28 1.04 1.02 0.97 1 Aug 4.47 1.70 0.52 1.03 1.02 0.77 1 Sep 1.34 0.76 1.17 1.03 1.02 0.93 1 Oct 9.27 1.54 1.12 1.05 1.05 1.00 1 Nov 0.08 0.68 2.06 1.06 1.06 0.80 1 Dec 0.50 0.78 1.55 1.09 1.09 0.70 1 [END]

a)

b)

c)


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TABLE I A SUMMARY OF WEATHER VARIABLES CHANGE DURING 2080-2099 COMPARED TO 1986-2005 PERIOD

Data

Minimum Temperature Maximum Temperature Rainfall

Annual average value

(°C)

Relative change (°C)

Annual average value

(°C)

Relative change (°C)

Annual total (mm)

Relative change (%)

Observations 23.89 32.99 79.79

RCP 2.6 24.9 1.01 33.85 0.86 50.75 -36.40

RCP 4.5 25.57 1.68 34.74 1.75 51.09 -35.97

RCP 6.0 25.81 1.92 34.83 1.84 89.76 12.50

RCP 8.5 27.09 3.2 36.04 3.05 87.41 9.55

The results reveal -36.4% and -36.0% decreases in precipitation for the RCP 2.6 and RCP 4.5 scenarios, respectively, while, RCP 6.0 and RCP 8.5 scenarios predict increase in precipitation in a range from 9.6% to 12.5%, respectively during 2080-2099 compared to 1986-2005 period. RCP8.5 scenario alone predicts the probability of very extreme precipitation events in future which may have implications for planning and decision making for flood mitigation infrastructures, land-use regulations and building codes. The differences in the precipitation projections between the scenarios are much greater compared to consistent warming depicted in temperatures. These results need to be further improved by adopting more GCMs, which will provide potential changes in a consistent range. The results of this study can be integrated with hydrological and flood models so that risk scenarios can be constructed for future time periods.

ACKNOWLEDGMENT

Authors wishes to acknowledge Prof. M. Semenov in Rothamsted Research Center for providing LARS-WG model. We are also grateful to the National Center for Atmospheric Research, Colorado for providing us the NCAR command Language (http://dx.doi.org/10.5065/D6WD3XH5).

REFERENCES [1] M. Parry, O. Canziani, J. Palutikof, P. V. Linden and C. Hanson,

“Climate change 2007: Impacts, Adaptation and Vulnerability. Summary for policymakers”, Cambridge University Press, New York, 2007.

[2] K. Eckhardt and U. Ulbrich, “Potential impacts of climate change on

groundwater recharge and streamflow in a central European low mountain range,” Journal of Hydrology, vol. 284, pp. 244-252, 2003.

[3] S. Brouyere, G. Carabin and A. Dassargues, “Climate change impacts

on groundwater resources: modelled deficits in a chalky aquifer, Geer basin, Belgium,” Hydrogeology Journal, vol. 12, pp.123-134, 2004.

[4] N. J. Rosenberg, D. J. Epstein, D. Wang, L. Vail, R. Srinivasan and J. G. Arnold, “Possible impacts of global warming on the hydrology of

the Ogallala Aquifer region,” Climatic Change, vol. 42, pp. 677–692, 1999.

[5] M. E. Rafy, and Y. Hafez, “Anomalies in meteorological fields over

northern Asia and its impact on Hurricane Gonu,” 28th Conference on Hurricanes and Tropical Meteorology, pp. 1–12, 2008.

[6] K. Taylor, R. J. Stouffer and G. A. Meehl, “A summary of the CMIP5 Experiment Design” [Online]. Available: http://cmip-pcmdi.llnl.gov/cmip5/docs/Taylor_CMIP5_design.pdf

[7] M. A. Semenov and E. M. Barrow, “Use of a stochastic weather generator in the development of climate change scenarios,” Climatic Change, vol. 35, pp.397-414, 1997.

http://cmip-pcmdi.llnl.gov/cmip5/docs/Taylor_CMIP5_design.pdf

http://cmip-pcmdi.llnl.gov/cmip5/docs/Taylor_CMIP5_design.pdf


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Assessment of Embodied Energy in the Production of Ultra High Performance Concrete (UHPC)

Aysha. H^, T. Hemalatha*, N. Arunachalam**,

A. Ramachandra Murthy* and Nagesh R. Iyer*

^project Student, *CSIR-SERC, Chennai, Tamil Nadu, India – 600113.

** Dean - Bannari Amman Institute of Technology, Sathy, Tamil Nadu, India – 638 503.

Presenting author email: [email protected]

ABSTRACT - There is a growing interest towards quantifying the direct and indirect emission of carbon (embodied energy) in the production and utilization of new types of concrete. Advanced technological development of concrete and demand for high strength and high performance construction materials have lead to the evolution of Ultra High Performance Concrete (UHPC). This material is primarily characterized with high strength and durability and when reinforced with steel fibers or steel tubes exhibits high ductility. Existing UHPC preparation methods involve costly materials and classy technology. This may increase the embodied energy of UHPC, which is not in favor of green environment for a sustainable technology and development.

Embodied energy is the energy required to produce any goods or services, which is incorporated or embodied in the product itself. Embodied energy assessment aims in finding the sum of total energy necessary for an entire product life-cycle. To make UHPC an eco-friendly material, the embodied energy involved in its production should be reduced by the application of simple technology. Many research works are being done in replacing certain amount of cement with silica fume (SF), fly ash (FA), ground granulated blast furnace slag (GGBS) etc. in order to achieve an environmental friendly UHPC of high strength of more than 150 MPa and an elevated level of durability. This study is focused on the assessment of embodied energy involved in the production of UHPC with alternate cementitious material. With the knowledge of embodied energy for UHPC, implications can be deliberated by varying the constituents and replacing cement with certain amount of eco-friendly materials, so as to reduce the environmental impact of construction with UHPC.

Key Words - embodied energy, fly ash, GGBS, sustainable concrete, UHPC.

I. INTRODUCTION

The net cement production in the world has increased from about 1.4 billion tonnes in the year 1995 to almost 2 billion tonnes in the year 2010. This has lead to the emission of about 2 billion tonnes of CO2 in the atmosphere every year [1]. The global cement industry has reduced its specific net CO2 emissions per tonne of product by 17 % since 1990, from 756 kg/tonne to 629 kg/tonne. Meanwhile, cement production increased by 74 % between 1990 and 2011, according to the World Business CSI, which released

its 2011 data update to the project Council for Sustainable Development’s Cement Sustainability Initiative (CSI).

“Getting the Numbers Right” or GNR, which tracks global CO2 emissions for participating companies in the cement industry, reports the evidence of significant reduction of CO2 emissions and improved efficiency. According to CSI, the four main drivers for the reduction in emissions are (i) investment in more efficient kiln technology, (ii) increasing the use of alternative fuels such as biomass, (iii) reduction in clinker content and (iv) 8 % decrease in electricity use per tonne of cement since 1990. Between 2010 and 2011, cement production volume covered by the GNR increased from 840 million tons to 888 million tons, and specific net CO2 emissions decreased from 638 kg/ton to 629 kg/ton of product.

As a building material, concrete is the most used man-made material in the world, utilized at double the rate of all other building materials, according to CSI. There are several essentials which can reduce the environmental impact factor and CO2 intensity of concrete used for construction, which include maximizing the concrete durability, conservation of materials, use of waste and supplementing cementing materials and recycling of concrete [3]. Partial replacement of cement with waste and supplementary cementitious materials such as fly ash, GGBS, silica fume, rice husk ash and metakaolin not only improves the concrete durability and reduce the risk of thermal cracking in mass concrete but also emits less CO2 than cement. By doing so, it ensures the proper utilization of such waste materials in an effective manner which otherwise are being dumped creating hazard to the environment.

II. RESEARCH SIGNIFICANCE

Ultra high performance concrete belongs to the family of engineered cementitious composites (ECC) and is defined as cement based concrete with compressive strength equal to or greater than 150 MPa. The ductility of UHPC is attained by adding steel fibres to it and these generally transform the developed cracks into larger number of small width cracks, which increases the strength and durability of UHPC



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members. It is a high strength ductile material formulated from a special combination of constituent materials which include Portland cement, silica fume, quartz powder, fine sand, high range water reducer, water and steel fibres. With the present focus on sustainability, green concrete is achieved by optimizing the mixture proportions and material substitutions, so that energy and CO2 impact can be reduced

Replacement of certain amount of cement with silica fume and other cementitious materials in the production of UHPC itself leads to lesser consumption of cement. UHPC, being a highly efficient material with good mechanical and durability characteristics is used in the production of thinner elements which in turn consumes less volume of cement. Hence, UHPC employs lesser volume of cement both in the production and utilization phases. The present study focuses on the assessment of embodied energy of UHPC, with partial replacement of cement with eco friendly materials like silica fume, fly ash, GGBS etc. Also, an optimum UHPC mix proportion with less embodied energy, without compromising the strength and durability criteria are obtained.

III. SUSTAINABLE CONSTRUCTION

The principles of sustainable development and green buildings have penetrated the construction industry at an accelerating rate in recent years. The concrete industry in particular, because of its enormous environmental footprint, has a long way to go to shed its negative image [4]. Sustainability is given prime importance in the field of construction for the social progress which recognises the needs of everyone, effective protection of the environment, prudent use of natural resources and maintenance of high and stable levels of economic growth and employment. The use of GGBS or fly ash in concrete, either as a mixer addition or through a factory made cement can significantly reduce the overall greenhouse gas emissions associated with the production of concrete, and thereby reducing the embodied energy.

A. Embodied Energy

Embodied energy is an accounting method which aims to find the sum of the energy necessary for an entire product life-cycle, which constitutes assessing the relevance and extent of energy into raw material extraction, transport, manufacture, assembly, installation, disassembly, deconstruction and/or decomposition as well as human and secondary resources as shown in Fig. 1. Materials that have a lower embodied energy are more sustainable than those with a higher embodied energy. Energy inputs usually entail greenhouse gas emissions in deciding whether a product contributes to or mitigates global warming. Different methodologies produce different understandings of the scale, scope of application and the type of energy embodied. Typical embodied energy units used are MJ/kg (mega joules of energy needed to make a kilogram of product).

Fig. 1 Breakdown of embodied energy calculations

1) Embodied Energy Methodologies: Different methodologies use different scales of data to calculate the energy embodied in products and services of nature and human civilization. International consensus on the appropriateness of data scales and methodologies is still pending. This difficulty can give a wide range in embodied energy values for any given material. In the absence of a comprehensive global embodied energy public dynamic database, embodied energy calculations may omit important data. Such omissions can be a source of significant methodological error in embodied energy estimations. The following are the widely used methodologies, 1. Input-Output embodied energy analysis and 2. Process life cycle assessment.

2) Standards on Embodied Energy: The UK Code for Sustainable Homes and USA LEED are methods in which the embodied energy of a product or material is rated along with other factors, to assess a building's environmental impact. Embodied energy is a concept for which scientists have not yet agreed absolute universal values because there are many variables to take into account, but most agree that products can be compared to each other to see which has more and which has less embodied energy.

B. Supplementary Cementitious Materials

There are some materials obtained as industrial by-products, which is actually a waste, but can be used as a supplementary cementitious material, by partially replacing the cement. In this study, the analysis of embodied energy of UHPC is undertaken, by partial replacement of cement with silica fume, fly ash and ground granulated blast furnace slag (GGBS).

1) Silica Fume: This siliceous material is a by-product of the semiconductor industry. When added to concrete, this greatly improves both strength and durability, and hence modern high performance concrete mix designs as a rule call for the addition of silica fume. There have been several research works, which have identified the benefits of silica fume both as a pozzolanic and a filler material [5], [6]. Nowadays silica fume is produced specifically for the

Site to grave

Cradle to Site


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concrete industry, apart from that available as an industrial by-product due to its massive usage. The beneficial aspect of silica fume is the presence of around 98 % of SiO2.

2) Fly Ash: The utilization rates of fly ash vary greatly from country to country, from as low as 3.5% in India to as high as 93.7% in Hong Kong [7]. Fly ash, an important pozzolanic material has numerous advantages when compared with regular Portland cement. Firstly, lesser heat of hydration makes it a popular cement substitute for mass structures, resulting in the development of high volume fly ash concrete mixes. Perhaps, the most significant advantage of fly ash is that it is a byproduct obtained from coal combustion, which otherwise involves the greater cost for disposal of the waste product. Moreover, concrete produced with fly ash can have better strength and durability. After all, the cost of fly ash is lesser than Portland cement. The main disadvantage of fly ash is its slow rate of strength development and hence accelerators are used to speed up the hydration rates of fly ash concrete mixes. The quality of fly ash is an important issue, because of considerable variation in the physical and chemical properties, since the primary source of coal varies widely. In recent years, after the increased usage of fly ash, technologies have developed to separate the unburned residues for the quality improvement.

3) Ground Granulated Blast Furnace Slag: This is a glassy granular material, which is a by-product of the steel industry, formed when molten blast furnace slag is rapidly chilled, when immersed in water [8]. Like fly ash, GGBFS improves mechanical and durability properties of concrete and generates less heat of hydration. GGBFS is not only used as a partial replacement for portland cement, but also as an aggregate. The optimum cement replacement level is often quoted to be about 50% and even sometimes as high as 70% to 80%. The cost of slag is generally same as that of portland cement, but is being extensively used due to its beneficial properties [5]. Many suggest that the concrete industry offers ideal conditions for the beneficial use of such slag and ashes because the harmful metals can be immobilized and safely incorporated into the hydration products of cement.

IV. METHODOLOGY

For the assessment of embodied energy of UHPC, initially a base mix with quartz powder (40% of cement) designated as UHPC-I is taken into consideration, whose mix proportions are given in Table I. The optimum mix proportion of the base mix is obtained from various trials at the laboratory, satisfying the criteria of UHPC. The main constituents of the base mix are cement, silica fume, quartz powder, sand, water, superplasticizers and steel fibres. The mix developed is a kind of reactive powder concrete, whose material proportions are determined in part by optimizing the granular mixture.

The basic idea is to completely eliminate the coarse aggregate to attain greater homogeneity. The cost effective optimal dosage of steel fibres is 2% by volume of concrete. The fine sand used in this case acts as a filler material and superplasticizer is added to improve the workability of the mix. The compressive strength of this base mix with silica fume (25% of cement) is found to be 196 MPa with hot air curing at 200°C. The embodied energy of the base mix is ascertained by replacing 25% of cement with silica fume (SF), fly ash (FA) and ground granulated blast furnace slag, GGBS (BS).

Also, in order to arrive at the optimum value of embodied energy of UHPC with varying percentage of silica fume, fly ash and GGBS, several literature [9]-[16] are identified to obtain the mix proportions of UHPC with higher strength and durability criteria. Out of those literature, three are finally chosen [10], [15] & [16], and the mix proportions of UHPC taken from those literatures are presented in TABLE II

(UHPC-II), TABLE III (UHPC-III) and TABLE IV (UHPC-IV) respectively. The mixes are so identified, that one set of mix contained steel fibres but no coarse aggregate; the other set contained coarse aggregate but no steel fibres and the third set contained neither steel fibres nor coarse aggregate. All the three sets of mixes had varying percentage of silica fume, fly ash, GGBS and quartz powder, to achieve several mix proportions having higher strength and durability, satisfying the UHPC norms. The embodied energy of all the three set of mixes with varying combinations of silica fume, fly ash and GGBS are ascertained. A comparative analysis is made with the embodied energy and compressive strength of all the mixes, and the influence of the compressive strength on the embodied energy of a particular mix is also studied.

V. MATERIAL DESCRIPTION

The supplementary cementitious materials silica fume, fly ash and GGBS are abbreviated as SF, FA and BS respectively. Three mix proportions of UHPC-I with silica fume, fly ash and GGBS are designated as UHPC-I-SF, UHPC-II-FA and UHPC-III-BS respectively.

UHPC-II mixes have 6 different mix proportions containing varying percentage of fly ash and GGBS, which are given in TABLE II. In addition to the basic materials, it contained steel fibres, silica fume and quartz powder, but no coarse aggregate. The mix denoted as BS0FA0 contained neither GGBS nor fly ash; BS10FA10 contained 10% GGBS as well as 10% fly ash; BS10FA20 contained 10% GGBS, 20% fly ash; BS10FA30 contained 10% GGBS and 30% fly ash; FA20 contained no GGBS but 20% fly ash and BS40 contained 40% GGBS but no fly ash.


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TABLE I

MIX PROPORTION of BASE MIX UHPC-I WITH DIFFERENT % of SILICA FUME, FLY ASH and GGBS

S. No Material

Embodied energy

(MJ/kg)

Quantity (kg/m3) Total Embodied energy (MJ/m3)

UHPC-I-SF

UHPC-I-FA

UHPC-I-BS

UHPC-I-SF

UHPC-I-FA

UHPC-I-BS

1 Cement 5.50 788.00 788.00 788.00 4334.00 4334.00 4334.00

2 Fly ash 0.10 0.00 197.00 0.00 0.00 19.70 0.00

3 GGBS 1.60 0.00 0.00 197.00 0.00 0.00 315.20

4 Silica fume 0.036** 197.00 0.00 0.00 7.09 0.00 0.00

5 Quartz powder 0.850* 315.00 315.00 315.00 267.75 267.75 267.75

6 Coarse aggregate 0.083 0.00 0.00 0.00 0.00 0.00 0.00

7 Fine aggregate 0.08 866.80 866.80 866.80 70.21 70.21 70.21

8 Water 0.01 173.00 173.00 173.00 1.73 1.73 1.73

9 Superplasticizer 9.00** 14.77 14.77 14.77 132.93 132.93 132.93

10 Steel fibres 36.00*** 157.00 157.00 157.00 5652.00 5652.00 5652.00

Total value of each mix (MJ/m3) 10465.71 10478.32 10773.82

* Green Building Challenge Handbook, 1995.

** Minerals Products Association, The Concrete Industry Sustainability Performance Report, 1st Report

*** Steel Wires (Virgin) from ICE Database.

Others – The Inventory of Carbon & Energy Database (ICE)

TABLE II

MIX PROPORTIONS of UHPC-II WITH DIFFERENT % of FLY ASH and GGBS (WITH STEEL FIBRES and WITHOUT COARSE AGGREGATES)

S. No Material (kg/m3) BS0FA0 BS10FA10 BS10FA20 BS10FA30 FA20 BS40

1 Cement 830.00 664.00 581.00 498.00 664.00 498.00

2 Fly ash 0.00 83.00 166.00 249.00 166.00 0.00

3 GGBS 0.00 83.00 83.00 83.00 0.00 332.00

4 Silica fume 291.00 205.00 157.00 141.00 195.00 173.00

5 Quartz powder 244.00 260.00 266.00 264.00 257.00 269.00

6 Coarse aggregate 0.00 0.00 0.00 0.00 0.00 0.00

7 Fine aggregate 733.00 781.00 800.00 794.00 773.00 810.00

8 Water 151.00 151.00 151.00 151.00 151.00 151.00

9 Superplasticizer 55.00 35.00 34.00 33.00 38.00 35.00

10 Steel fibres 234 234.00 234.00 234.00 234.00 234.00


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TABLE III

MIX PROPORTION of UHPC-III WITH DIFFERENT % of SILICA FUME and GGBS (WITHOUT STEEL FIBRES and WITH COARSE AGGREGATES)

S. No Material (kg/m3) 1-SF10 2-SF10 3-SF10 SF10BS20 SF10BS40

1 Cement 450.00 630.00 810.00 630.00 450.00

2 Fly ash 0.00 0.00 0.00 0.00 0.00

3 GGBS 0.00 0.00 0.00 180.00 360.00

4 Silica fume 50.00 70.00 90.00 90.00 90.00

5 Quartz powder 0.00 0.00 0.00 0.00 0.00

6 Coarse aggregate 1195.00 1073.00 923.00 923.00 923.00

7 Fine aggregate 797.00 715.00 616.00 616.00 616.00

8 Water 90.00 126.00 162.00 162.00 162.00

9 Superplasticizer 18.00 18.00 18.00 18.00 18.00

10 Steel fibres 0.00 0.00 0.00 0.00 0.00

TABLE IV

MIX PROPORTION of UHPC-IV WITH DIFFERENT % of FLY ASH and GGBS (WITHOUT STEEL FIBRES and COARSE AGGREGATES)

S. No Material (kg/m3) FA0BS0 FA20 FA40 FA60 FA80 BS20 BS40 BS60 BS80

1 Cement 850.00 680.00 510.00 340.00 170.00 680.00 510.00 340.00 170.00

2 Fly ash 0.00 170.00 340.00 510.00 680.00 0.00 0.00 0.00 0.00

3 GGBS 0.00 0.00 0.00 0.00 0.00 170.00 340.00 510.00 680.00

4 Silica fume 260.00 260.00 260.00 260.00 260.00 260.00 260.00 260.00 260.00

5 Quartz powder 212.00 212.00 212.00 212.00 212.00 212.00 212.00 212.00 212.00

6 Coarse aggregate 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00

7 Fine aggregate 850.00 787.00 724.00 661.00 598.00 838.00 826.00 814.00 802.00

8 Water 170.00 170.00 170.00 170.00 170.00 170.00 170.00 170.00 170.00

9 Superplasticizer 45.00 45.00 45.00 45.00 45.00 45.00 45.00 45.00 45.00

10 Steel fibres 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00


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UHPC-III mixes have 5 different mix proportions containing varying percentage of silica fume and GGBS, which are given in TABLE III. In addition to the basic materials, it contained coarse aggregate but no steel fibres, fly ash and quartz powder. The mix represented as 1-SF10, 2-SF10 and 3-SF10 comprised only 10% silica fume with varying quantity of cement as presented in Table III. The mix symbolized as SF10BS20 consisted of 10% silica fume, 20% GGBS and SF10BS40 comprised 10% silica fume, 40% GGBS.

UHPC-IV mixes have 9 different mix proportions containing varying percentage of fly ash and GGBS, which are given in TABLE IV. In addition to the basic materials, it contained silica fume and quartz powder, but no coarse aggregate and steel fibres. The mix symbolized as FA0BS0 has neither fly ash nor GGBS; FA20 included 20% fly ash; FA40 included 40% fly ash; FA60 included 60% fly ash; FA80 included 80% fly ash; BS20 included 20% GGBS; BS40 included 40% GGBS; BS60 included 60% GGBS and BS80 contained 80% GGBS.


The embodied energy of the UHPC mixes are calculated based on the embodied energy values of each constituent material in terms of Mega Joules per kilogram (MJ/kg). These embodied energy values for different constituents are taken from three different sources for this study [17]-[19]. The quantity of the constituent materials in terms of kilogram per cubic metre (kg/m3) is multiplied with the basic embodied energy values to get the total embodied energy of the constituent material in MJ/m3. The sum of all the embodied energy values of the constituent materials in the mix would represent the final embodied energy of the mix in terms of MJ/m3. The embodied energy value for steel fibres is not found in any source, and hence the value of steel wires (virgin) from ICE database is taken as the embodied energy value for steel fibres, as far as this study is concerned.

The embodied energy values of UHPC-I mixes presented in TABLE I, represents that the embodied energy is lesser for the mix with silica fume with superior strength of 196 MPa than the mix with GGBS with comparatively lesser strength. This is because the embodied energy value of GGBS is higher than that of silica fume.

From Figs. 2, 3 and 4, it is evident that the embodied energy as well as the compressive strength of UHPC-II mixes is very high when compared with the other two mixes. This is obvious due to the presence of steel fibres in the mix, for which the embodied energy is very high about 36 MJ/kg (Steel wires – ICE data base). The steel fibres are included in the mix to impart ductility, because it is certain that the high strength

mixes are very brittle in nature. This type of ultra high performance mix is used for specific purpose, where strength and durability are the governing factors.

Fig. 2 Embodied energy Vs Compressive strength for UHPC mix with steel fibres and without coarse aggregates

The embodied energy of the other two mixes UHPC-III and UHPC-IV without steel fibres is in the range of 1500 to 5000 MJ/m3depending upon the mix proportions. Their compressive strength is in the range of 70 MPa to 140 MPa, which is less compared to UHPC-II mixes, whose compressive strength is more than 200 MPa. These mixes satisfy the criteria of UHPC and also have a less embodied energy, which can be termed as “high strength green concrete”.

From Fig. 2 and TABLE II (with steel fibres and without coarse aggregate), it is recognized that the embodied energy is highest of about 13763 MJ/m3 for the mix without fly ash and GGBS and the compressive strength is highest of about 212 MPa for the mix with 20% fly ash and 10% GGBS. The optimum mix among the UHPC-II mixes would be the mix with 10% GGBS and 30% FA, having an embodied energy of 11913 MJ/m3 and a compressive strength of 206 MPa. Similar strength of 202 MPa is achieved with the mix without fly ash and GGBS but with the highest embodied energy of 13763 MJ/m3, which is actually not a good proportioning in embodied energy perception. Hence, this mix would require partial replacement of cement with optimum levels of fly ash and GGBS.

From Fig. 3 and TABLE III (without steel fibres and with coarse aggregates), it is apparent that the embodied energy as well as the compressive strength is highest for the mix with 10% of silica fume (with 810 kg/m3 of cement) of about 4748


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MJ/m3 and 137 MPa respectively, which is due to the presence of high cement content. The optimum mix among the UHPC-III mixes would be the mix with 10% of silica fume (with 450 kg/m3 of cement), having an embodied energy of 2803 MJ/m3 and compressive strength of 131 MPa. The weakest mix would be the mix with 10% SF and 40% GGBS, having the least compressive strength of about 110 MPa and high embodied energy of 3345 MJ/m3.

Fig. 3 Embodied energy Vs. Compressive strength for UHPC mix without steel

fibres.

From Fig. 4 and TABLE IV (without steel fibres and coarse aggregate), it is evident that the embodied energy is highest for the mix without fly ash and GGBS of about 5340 MJ/m3 and the compressive strength is highest for the mix with 40% fly ash and no GGBS of about 126 MPa. The optimum mix among the UHPC-IV mixes would be the mix with the highest compressive strength of 126 MPa and an embodied energy of 3494 MJ/m3

containing 40% fly ash and no GGBS. The mixes which would require a re-proportioning are, 1) The mix containing 80% of GGBS, with an embodied energy of 2684 MJ/m3 and a low compressive strength of 82 MPa and 2) The mix with the highest embodied energy of 5340 MJ/m3 and a compressive strength of 113 MPa having no fly ash and GGBS, because the same strength of 113 MPa is achieved with a lesser embodied energy of 2570 MJ/m3 with the mix containing 60% of fly ash. This reduction in embodied energy with considerable strength can be due to the replacement of high volume of cement with fly ash.

Fig. 4 Embodied energy Vs. Compressive strength for UHPC mix without steel

fibres and coarse aggregates.

V. CONCLUSIONS

Basically, all the UHPC mixes contain silica fume as a base material, which has very low embodied energy value of 0.036 MJ/kg, when partially replaced for cement produces a high strength low embodied energy ultra high performance concrete. An efficient mix is identified as the mix with partial replacement of cement by 10-25% of silica fume, 20-40% of GGBS and 30-60% of fly ash, which results in the reduction of cement usage and in turn results in lesser embodied energy without compromising the strength. To obtain the most favorable UHPC mix, the proportioning of the cementitious materials needs to be taken utmost care, because higher percentage of replacement of supplementary cementitious materials can lead to a poor mix having higher embodied energy and lower strength. Hence, the optimum levels of cementitious materials as a replacement for cement can be arrived by trial and error only.

ACKNOWLEDGEMENT

We acknowledge with thanks the technical support provided by the Computational structural mechanics group (CSMG), CSIR-SERC. This paper is being published with the kind permission of the Director, CSIR-SERC, Chennai, India.


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different curing regimes”, Construction and building materials, Vol. 23, pp. 1223-1231, 2009.

[11] Ming-Gin Lee, Yung-Chih Wang, Chui-Te Chui, “A

preliminary study of reactive powder concrete as a new repair material”, Construction and building materials, Vol. 21, pp. 182-189, 2007.

[12] Bassam A. Tayeh, B. H. Abu Bakar, M. A. Megat Johari, Yen Lei Voo, “Mechanical and permeability properties of the interface between normal concrete substrate and ultra high performance fibre concrete overlay”, Construction and building materials, Vol. 36, pp. 538-548, 2012

[13] Eduardo N. B. S. Julio, Fernando A. B. Branco, Vitor D. Silva, Jorge F. Lourenco, “Influence of added concrete

compressive strength adhesion to an existing concrete substrate”, Building and environment, Vol. 41, pp. 1934-1939, 2006.

[14] F. A. Farhat, D. Nicolaides, A. Kanellopoulos, B. L. Karihaloo, “High performance fibre reinforced cementitious composite – Performance and application to retrofitting”, Engineering fracture mechanics, Vol. 74, pp. 151-167, 2007.

[15] Chong Wang, Changhui Yang, Fang Liu, Chaojun Wan, Xincheng Pu; “Preparation of ultra high performance

concrete with common technology and materials”, Cement and concrete composites, Vol. 34, pp. 538-544, 2012.

[16] Halit Yazici, “The effect of curing conditions on

compressive strength of ultra high strength concrete with high volume mineral admixtures”, Building and environment, Vol. 42. pp. 2083-2089, 2007.

[17] Hammond G. P. and Jones C. I., “Inventory of (embodied) Carbon & Energy Database (ICE)”, Version 2.0, UK - University of Bath, 2011.

[18] “Minerals Products Association; the Concrete Industry Sustainability Performance Report”, 1st Report, 2009.

[19] Green Building Challenge Handbook, 1995.


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Investigation of Mechanical Properties of Aluminium 6061 Alloy Friction Stir Welding

J. Stephen Leon1 and Dr. V. Jayakumar2

Faculty of Mechanical and Engineering, Department of Engineering

Ibri College of Technology, Ibri, Sultanate of Oman

[email protected]

Abstract– Aluminium 6061 alloy is commonly used for construction of aircraft structures, such as wings and fuselages, more commonly in homebuilt aircraft than commercial or military aircraft. Aluminium 6061 alloy generally present low weldability by traditional fusion welding process. The development of Friction Stir Welding (FSW) has provided an alternative improved way of satisfactorily producing weld joint in aluminium 6061 alloy. In FSW, the welding tool motion induces frictional heating and severe plastic deformation and metal joining process is done in solid state results, which results in defect free welds with good mechanical properties in aluminium alloy 6061. Unlike in traditional fusion welding, friction stir welds will not encounter problems like porosity alloy segregation and hot cracking, and welds are produced with good surface finish. In this paper, an attempt was made to investigate the impact of process parameters of FSW in the mechanical properties of the joint. The tensile properties, microstructure, hardness of the FSW joints were investigated in the weldment and heat affected zone. The changes of mechanical properties are compared with the parental metal. The welding parameters such as tool rotational speed and welding speed plays a major role in deciding the joint characteristics. This paper focusses on optimization of all these parameters. From this investigation it was found that the joint made from the FSW yielded superior tensile properties and impact strength due to the higher hardness and fine microstructure. Key Words– FSW, welding speed, axial force, mechanical properties, microstructure.

I. INTRODUCTION

In recent years, demands for aluminium alloy 6061 have steadily increased in aerospace, aircraft and automobile applications because of their excellent strength to weight ratio, good ductility, corrosion resistance and cracking resistance in adverse environment. Welding of these alloys, however, still remains a challenge. Apart from softening in the weld fusion zone and heat affected zone, hot cracking in the weld can be a serious problem [1]. Thus, the solid state bonding process is

highly recommended to solve these problems. FSW is an innovative solid state welding process in which the metal to be welded is not melted rather the two parts of weld joints are brought into contact and the interface is strongly forged together under the effect of heavy plastic deformation caused by the inserted rotating stir probe pin [2].

In FSW a rotating cylindrical, shouldered tool with a profiled probe penetrates into the material until the tool shoulder contacts with the upper surface of the plates, which are butted together as shown in figure 1.

Fig 1 Principle of FSW

The parts have to be clamped on to a backing bar in a manner that prevents the abutting joint faces from being forced apart. Frictional heat is generated between the wear resistant welding tool and the material of the work pieces. This heat causes the later to soften without reaching the melting point and allows traversing of the tool along the weld line. In FSW, tool rotation rate (rpm) in clockwise or counter clockwise direction and tool traverse speed (mm/min) along the joint are the most important parameters [3].


http://en.wikipedia.org/wiki/Aircraft

http://en.wikipedia.org/wiki/Wing

http://en.wikipedia.org/wiki/Fuselage

http://en.wikipedia.org/wiki/Homebuilt_aircraft


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II. LITRATURE REVIEW

The effect of FSW parameters on temperature was examined by Muhsin et al .[4]. They concluded that the maximum temperature is a function of tool rotation rate while the rate of heating was a function of traverse speed.

Munoz et al. [5] investigated the microstructure and mechanical properties of friction stir welded and TIG welded Al-Mg-Sc alloy and reported that the yield strength FSW welded joint is decreased 20 % compared to base metal.

Apart from this, there have been lot of efforts to understand the effect of process parameters on material flow behaviour, microstructure formation and mechanical properties of friction stir welded joints. Finding the most effective parameters on properties of friction stir welds as well as realizing their influence on the weld properties has been major topics for researchers [6–8].

Extensive literature of friction stir welding of Al alloys does indicate that there are few areas particularly on the relationship between welding parameters and change in the mechanical properties of weldment. This paper focuses on finding the optimal speed (rpm) and feed rate (mm/s) with respect to mechanical properties such as hardness number and tensile strength.

III. EXPERIMENTAL PROCEDURE

AA 6061 aluminum alloy chemical composition and mechanical properties are given in table 1 and 2 respectively.

TABLE 1 CHEMICAL COMPOSITION IN %WT

Name of the Al alloy

Mg Si Fe Cu Cr Mn Zn Ti Al

AA 6061 0.9 0.62 0.33 0.28 0.17 0.06 0.02 0.02 Balance

TABLE 2 MECHANICAL PROPERTIES

Name of the

Aluminum alloy

Yield strength in MPa

Ultimate strength in MPa

Elangation % Hardness in HV

AA 6061 110 207 16 75

All dimensions are in mm

Fig 2 Square Butt joint

The rolled plates of AA6061 aluminium alloy were machined to the required dimensions (300 mm X 150 mm). Square butt joint configuration as shown in fig 2 was prepared to fabricate FSW joints. A non-consumable, rotating tool made up of high carbon steel was used. Probe diameter is 6 mm, shoulder diameter is 18 mm and pin length is 5.5 mm. FSW was carried out on a FSW machine manufactured by RV machine tools, India. Machine specifications are given in table 3.

TABLE 3. MACHINE SPECIFICATIONS

Spindle ISO 40 Spindle speed 1000 to 3000 rpm (infinitely variable) Z axis thrust 3000 to 10000 kgf X axis thrust 1000 to 5000 kgf Spindle motor 11 kW/440 v, AC spindle servo motor Version CNC

The Aluminium plates are positioned in the fixtures, which

is prepared for fabricating FSW joints by using mechanical clamps so that the plates will not separate during welding.

In present work, different FSW butt welds were obtained by varying tool rotation speed and welding speed with in the range obtained by the previous works [9, 10] by keeping the axial force constant.

In this work FSW process was conducted with two variables: rotational speed (rpm) of the tool pin and traverse speed (mm/min) of the machine table. The rotational speed was chosen as: 720, 910, 1120 and 1400 rpm while the traverse speeds were 16, 20, and 31.5 mm/min.

IV. RESULT AND DISCUSSION

A. Macro and Microscopic Visual Examination The optical microstructures of the base metal and weld

centre are shown in fig 3 Macroscopic visual examination of all welded

specimens in transverse and longitudinal cross section showed defect-free sound weldments, produced under all applied experimental conditions. Uniform semicircular surface ripples in


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weld track were observed. These surface ripples, which have onion rings configuration, were caused by the final sweep of the trailing edge of the continuously rotating tool shoulder. A similar observation was made by many researchers [11-14].

Base metal FSW

Fig 3. Optical Micrographs of base metal and weldment

Combined influence of temperature and plastic deformation induced by the stirring action causes the recrystallized structure. In many FSW references on aluminum alloys, the initial elongated grains of the base materials are converted to a new equiaxed fine grain structure. This experiment confirms that behavior. The grain structure within the nugget is fine and equiaxed and the grain size is significantly smaller than that in the base materials due to the higher temperature and extensive plastic deformation by the stirring action of the tool pin. During FSW, the tool acts as a stirrer extruding the material along the welding direction. The varying rate of the dynamic recovery or recrystallization is strongly dependent on the temperature and the strain rate reached during deformation.

B. Hardness

Using Vicker’s hardness testing machine hardness across the welds cross-section was measured. Hardness values are taken from weld face, midway through the weld nugget and near to the root of the FSW joint. The average values were plotted against the distance from the welding centre (fig 4).

Fig 4. Hardness Vs distance from weldment at 1400 rpm

Comparing with base metal hardness decreases towards the

weld centre. This is due to the shear stress induced by the tool motion which lead to the generation of very fine grain structure as shown in fig 3. Dynamic recovery and recrystallization are the main softening mechanisms during FSW. When the average values of hardness in the welding centre were plotted against different tool rotation speed in fig 5, it was observed that when rotation speed increases more than 1200 rpm hardness in the weldment increases. This is because of the relatively high stacking fault energy which causes cross slip. This explanation was reached also by many researchers [15-19]. The result also reveals that 80-90% reduction in hardness comparing with base metal when traverse speed increases from 16 to 31.5 mm/min.

Fig 5. Hardness vs speed

0

20

40

60

80

-40

-30

-20

-10 0

10

20

30

40

Har

dn

ess

in H

V

Distance from Weldment in mm

WeldingSpeed 16mm/min

WeldingSpeed 31.5mm/min

0

20

40

60

80

720 910 1120 1400

Har

dn

ess

in H

V

Speed in rpm




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C. Tensile Properties

Fig 6.Ultimate strength vs Rotational speed

Fig 7.Yeild strength vs Rotational speed

Fig 8.Percentage Elongation vs Rotational speed

The transverse tensile properties such as yield stress, tensile strength and percentage of elongation of AA6061 aluminium alloy joints were evaluated. The measurements of ultimate tensile strength, yield stress and elongation for the welded specimen are shown in fig 6-8 respectively. The lowest ultimate

tensile stress (UTS) found for welds in Al6061-T6 was 66% of the base material strength, while the highest yield strength found was over 90% of the base material strength. When the welding speed reduces, the specimen elongation in the weldment is nearly equal to the base metal.

V. CONCLUSION

In this paper, an attempt was made to investigate the impact of process parameters of FSW in the mechanical properties of the joint. From this investigation, the following conclusions have been derived: (i) The weld root surface of all the weldments showed visually a well joined defect free sound flat surface. (ii) The increase in stir–probe rotation speed more than 1200 rpm enhanced the weld soundness which may be a result of softening process associated with dynamic recovery and recrystallization process at the weld. (iii) The formation of fine equiaxed grains and uniformly distributed, very fine strengthening precipitates in the weld region are the reasons for the superior tensile properties of FSW joints. (iv) The width of the stir zone may depend on the balance between the total heat input and the cooling in the plasticized material. The area of the weld nugget zone size slightly decreased as the welding speed increased. Comparing with other welding speeds, the lowest speed 16mm/min results better mechanical properties and increase in the area of the weld nugget.

REFERENCES

[1] Mohandoss T, Madhusudhanan reddy G (1996) Effect of frequency of pulsing in gas tungsten arc welding on the microstructure and mechanical properties of titanium alloy welds. J Matar Sci Lett 15:626-628.

[2] Larson, H,. Karlsson L “ A Welding Review”, Vol 54 No2

ESAB AB, Sweden, PP 6-10,2000. [3] H.J. Liu, H. Fuiji, M. Maeda, K, Nogi. 2003. Tensile

properties and fracture locations of friction-stir welded joints of 6061-T6 aluminium Alloy. Mater. Sci. Lett. P.22.

[4] Muhsin J.J., Moneer.H, Tolephih and Muhammed.A.M., Effect of Friction Stir Welding parameters (Rotation and Transverse) speed on the transient temperature distribution in FSW of AA 7020-T53. ARPN Journal of Engineering and Applied science Vol7, 2012.

[5] Munoz C, Ruckert G (2004) comparision of TIG welded and Friction stir welded Al-4.5 Mg-0.26 Sc alloy. J.Matar process Technol 152:97-105.

[6] Peel M, Steuwer A, Preuss M, Withers PJ. Microstructure, mechanical properties and residual stresses as a function of welding speed in AA5083 friction stir welds. Acta Mater 2003;51:4791–801.

0

50

100

150

720 910 1120 1400

Ult

imat

e S

tre

ngt

h in

M

Pa

Rotational Speed in rpm



0

50

100

150

720 910 1120 1400

Yie

ld S

tre

ss in

MP

a




13

14

15

16

17

720 910 1120 1400Pe

rce

nt

Elan

gati

on





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[7] Chen CM, Kovacevic R. Finite element modeling of friction stir welding– thermal and thermomechanical analysis. J Mach Tools Manuf 2003;43:1319–26.

[8] Schmidt H, Hattel J, Wert J. An analytical model for the heat generation in friction stir welding. Mater Sci Eng 2004;12:143–57.

[9] Elangovan K, Balasubramanian V (2008) influences of tool pin profile and tool shoulder diameter on the formation of friction stir processing zone in AA6061 aluminum alloy. Mater Des 29(2) :362- 373

[10] Elangovan K, Balasubramanian V, Valliappan M (2007) Influence of tool pin profile and axial force on the formation of friction stir processing zone in AA6061 aluminium alloy. Int J Adv Manuf Technol . DOI 10.1007/s00170-007-1100-2.

[11] Threadgill,P.L. Friction-Stir Welding-State of the Art, TWI, Report 678, England, 1999

[12] Lee, J.A. Carter, R.W., andDing, J.D.,”Friction Stir

Welding for Aluminum Metal MatrixComposites, NASA/TM-1999 Project No.98-09.

[13] Colligan, K. 1999. Material flow behavior during friction stir welding of aluminum. Welding Journal 78(7): 229-s to 237-s.

[14] G.Elatharasan, V.S.Senthil kumar, An Experimental Analysis and optimization of process parameters of Friction Stir Welding of AA 6061 – T6 Aluminium alloy using RSM. ICONDM 2013, Vol 64, 2013.

[15] A study of process parameters of Friction Stir Welded AA6061 Aluminium alloy. ARPN Journal of Engineering and Applied science Vol6, 2011.

[16] Threadgill,P.L. Friction-Stir Welding-State of the Art, TWI, Report 678, England, 1999.

[17] Liu, L.E. Murr, C.S Niou, J.C. McClure, and F.R. Vega, Micro structural aspects of thefriction-stir welding of 6061-T6 aluminum, Scripta Mat, 1997, vol 33-3, pp 355-36

[18] Rhodes, C. G., Mahoney, M. W., and Bingel, W. H. 1997. Effects of friction stir welding on microstructure of 7075 aluminum. Scripta Materialia 36(1): 69–75.

[19] Qasim M Doos, Bashar, Abdul wahab Experimental study of Friction Stir Welding of 6061-T6 Aluminium pipe. International Journal of Mechanical Engineering and Robatics. Vol 1. 2012.


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Effect of Fiber Length on the Short-Term Flexural Creep Behavior of Polypropylene C.Subramanian*#1, Abdulrahman Khalfan Hassan Al Mamari #2, S.Senthilvelan#3

#1 Shinas College of Technology, Oman #2 Petroleum Development Oman, Oman

#3 Indian Institute of Technology Guwahati, India

[email protected] [email protected]

[email protected]

Abstract— Injection molded long fiber thermoplastic components are being used in recent days as a viable replacement for metals in many applications .Present work focus on the effect of fiber length on the short-term flexural creep performance of fiber reinforced thermoplastic polypropylene. Unreinforced polypropylene, 20 wt % short and 20 wt % long glass fiber reinforced polypropylene materials was injection-molded into flexural test specimens. Short-term flexural creep tests were performed for 2 h duration on molded specimen at various stress levels with the aid of in-house developed flexural creep fixture. Experimental creep performance of polypropylene composites for 2 h is utilized to predict the creep performance with the aid of four parameter HRZ model and compared with 24 h experimental creep data. Creep strain was found to be increased with respect to time for all the test materials and found to be sensitive with respect to the stress level. Test results also revealed that long fiber reinforced thermoplastic material possessed enhanced creep resistance over their counter parts and HRZ model is sufficient enough to predict creep performance of polypropylene composites over wide range of stress.

Keywords- Injection molding, flexural creep, thermoplastic, creep, strain

I. INTRODUCTION

Due to the mass production requirement in the automotive industries, discontinuous long fiber reinforced thermoplastics (LFRT) have shown significant role in replacing metals, short fiber reinforced thermoplastics, thermoset sheet molding and bulk molding composites [1]. The common problem associated with unreinforced thermoplastics is creep under moderate to severe stress at elevated temperature. Creep resistance of thermoplastic composites is significantly improved by increase in fiber loadings [2]. Dynamic mechanical analysis (DMA) was utilized to investigate the viscoelasticity of injection-molded nylon 6/6 material reinforced with short and long glass fibers by Sepe[3] and reported an increase in creep resistance for long glass fiber reinforced nylon composites. Challa and Progelhof [4] investigated the effect of temperature on the creep

characteristics of polycarbonate and developed a relationship based on Arrhenius theory to develop creep master curves. Pegoretti and Ricco [5] studied the propagation of crack under creep for varying temperature conditions for polypropylene composites and observed that speed with which the crack progresses was dependent on the test temperature. Krishnaswamy [6] performed extensive creep rupture testing on high density polyethylene pipes at various hoop stress levels and temperatures and observed the dependency of density and crystallinity towards failure. Houshyar [7] reported the improvement in creep properties with the addition of long polypropylene fibers in propylene-co-ethylene (PPE) matrix and visualized the improvement in interfacial properties. Trans-crystallization of the polypropylene matrix was observed in the PPE samples due to the thin layer of matrix on the reinforcement, which was attributed to good impregnation and wetting of the fibers. Greco et al. [8] investigated the flexural creep behavior for compression molded glass fiber reinforced polypropylene at various applied stress level. The effect of matrix crystallinity was highlighted for the improvement in creep properties for glass fiber reinforced polypropylene in their work. Acha et al. [9] studied the influence of interfacial adhesion in discontinuous jute fiber reinforced polypropylene. Relation between interfacial properties and creep deformation were investigated. Higher creep resistance was observed for polypropylene composites with good interfacial bonding which was confirmed by the observation of the composite fractured surfaces.

Findley and Khosla [10] conducted creep tests for unreinforced thermoplastics; polyethylene, polyvinyl chloride and polystyrene. Approximation was carried out for the linear viscoelastic region by power law and compared the creep performance by estimating the power law coefficient and power law exponent. Liou and Tseng [11] used Findley power law to estimate the creep compliance of carbon fiber nylon composites in hygrothermal condition. Power law model was modified by Hadid et al. [12] by incorporating the time and stress dependence during creep loading of polyamide





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specimens and estimated four parameters for describing the deformation occurring in the material and used stress–time superposition principle to predict long-term material creep behavior of injection molded fiber glass reinforced polyamide. Master curves were developed and a perfect superposition of the curves at various stress levels was visualized. Novak [13] used strain energy equivalence theory and developed a creep predictive model to predict the creep behavior of talc filled polypropylene. Banik et al. [14] reported the improvement in creep resistance due to unidirectional reinforcement for polypropylene-polypropylene composites. Burger and Findley power law model were used to predict the short term creep behavior and the underlying deformation mechanisms were also investigated. Liu et al. [15] used multi-Kelvin element theory and power law functions to predict creep compliance in polyethylene material and compared with the tensile creep experiments.

Even though a lot of works were carried out in the past pertaining to the experimental creep behavior of plastics and composites, estimation and prediction of creep data using mathematical and numerical modeling is limited. Hence in this work the influence of reinforced fiber length on the creep performance of thermoplastic composite at various stress levels at room temperature condition was carried out. The results obtained through flexural creep test were analyzed using Findley power law model and empirical model proposed by Hadid et al [12]. Short term experimental creep results were used to predict long term creep behavior of the molded specimen.

II. THEORECTICAL BACKGROUND

A. Findley’s Power Law Model

Mechanical behavior of polymeric material under constant stress was developed by Findley and Khosla [10]. The general form of the power law equation is given as

' nt= ε tε(t) (1)

where ε(t) is the time dependent strain, 'tε is power law

coefficient which is stress and temperature dependent coefficient, n is the power law exponent and t is the time after loading.Power law model is simple in approach and successfully predicted nonlinear viscoelastic creep behavior of thermoplastic composites over large range of stress[10-13]besides this model is also recommended by American Society of Civil Engineers (ASCE) for structural plastics design manual in the analysis of composite materials for long term structural behavior [16].

B. HRZ Model

Findley’s power law was unsuccessful in accounting for the stress effect on the mechanical behavior of polymeric material. The two power law parameters in the Findley-Khosla

model 'tε and n are significantly influenced by the applied

stress level. Hadid et al. [12] modified the Findley’s power

law to incorporate time and stress dependence in the model where the power law coefficient (ε'

t) and power law exponent (n) were plotted with respect to stress level (ζ). The best

fitting curve proposed the relation between 'tε and ζ as

( )ζ b'ε =at (2)

Similarly the best fitting curve proposed between n and ζ

value takes the form

( )n=c exp e.ζ (3)

Eqs. (2) and (3) are used in eq. (1) and strain at any particular time (t) can be calculated using the following HRZ equation

cexp(e.ζ)bε(t)= aζ t (4)

where a, b ,c ,e are the curve fitting parameters obtained from the regression analysis. Chevali et al. [17] used the four parameter HRZ model to fit the experimental data obtained from flexural creep investigation for nylon 6/6, polypropylene and high-density polyethylene based long fiber thermoplastic composites.

III. EXPERIMENTAL CREEP PERFORMANCE OF

POLYPROPYLENE COMPOSITES

A. Specimen Fabrication

In the current investigation, 20 wt % short glass fiber reinforced polypropylene (SFPP), 20 wt % long glass fiber reinforced polypropylene (LFPP) and unreinforced polypropylene (UFPP) obtained from Saint Gobain were used for injection molding the specimens. In general, lengths of the reinforced fibers in the short and long fiber reinforced pellets are 1 mm and 12.5 mm respectively [18]. Weight average fiber length of the reinforced fibers after injection molding for the chosen SFPP and LFPP materials are 0.440 mm and 1.251 mm respectively [19]. The base resin of LFPP and SFPP materials were having same molecular weight with a melt flow index of 40 g/10 min. According to the material supplier’s

data, silane type coupling agent has been used for the manufacturing of SFPP and LFPP materials. Since both the investigated materials used the same type and amount of coupling agent, material behavior discussions were limited only to the reinforced fiber length. Developed injection molding dies and molded specimens are shown in Figs 1a and 1b. Raw materials were initially preheated for two hours at 353 K and during molding, screw speed of 50 rpm and a low back pressure of 0.25 MPa were kept to retain the residual fiber length. Process parameters used for injection molding are listed in Table I. Due to the presence of reinforced fibers in LFPP and SFPP materials, temperature in the three zones were kept higher than unreinforced material.


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Fig 1a .Die for preparing specimens

Fig 1b. Injection molded specimens for flexural creep testing

TABLE 1 INJECTION MOLDING PARAMETERS FOR THE SPECIMENS

Screw diameter 35 mm L/D 20 Screw speed 50 rpm Barrel temperature Zone 1 Zone 2 Zone 3

255 ο C 250 ο C 240 ο C

Injection speed 50 mm/sec Mold temperature 40 ο C

IV. EXPERIMENTAL METHODOLOGY

A fixture is developed in house to evaluate the creep performance of molded specimen according to ASTM D2990 standard. The specimen is kept in between the supports as shown in Fig 2a and the load is applied at the centre of the test specimen with the means of steel rod attached with dead load. When the load is applied at the center the specimen is deflected and the deflection is recorded in the dial gauge as shown in Fig 2b. Test specimens were loaded with respect to various stress levels for 2 hrs. Constant load is maintained and test specimen deflection ( δ(t) ) is continuously measured and

recorded. Creep strain at instantaneous time ( )ε(t) is

computed using the relation (5) [20].

2

6δ(t).dε(t) =

l (5)

where, δ (t) is the deflection at instantaneous time , d is the thickness and l the test specimen length. The corresponding stress is calculated using the relation

max3PlS =

22wd

(6)

Where Smax is the stress and P is the load, l is the length and w is the width and d is the thickness of the specimen .The length, width and thickness of the specimen is 70mm, 13 and 3mm respectively.

Fig 2(a-b). Assembled view of the flexural creep fixture

V. RESULTS AND DISCUSSIONS

A. Creep Behavior of Polypropylene Thermoplastic Composites

Creep performance evaluation was carried out at various loading levels ranging from 18.84 N/mm2 to 47.17 N/mm2 for all the materials. Fig 3 shows the 2h creep response of the chosen test specimens. A raise in creep strain was observed

Dial Gauge

Fixture

Steel Rod

Dead Weight

Specimen

Dial gauge Reading

Fixture


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with the time period for all the specimens. Subsequent to the preliminary rapid increase in creep strain, the rate of creep strain decreases. Three trails were conducted for calculating creep strain for all the molded materials and the deviation for LFPP, SFPP and UFPP were found to be 2.5 %, 3.2 % and 1.5 % respectively Improved creep resistance behavior of long fiber reinforced polypropylene is observed is due to the improved load transfer from the matrix to the reinforced fibers and the matrix constriction to deformation. Chevali et al. [17] also observed a similar behavior with the increase in loading of glass fiber reinforcement in the nylon composites.

Fig 3. Comparison of creep strain for three materials for a stress of

22.5N/mm2

Due to the increase in reinforced fiber length, stiffness retention is more pronounced in LFPP. Due to the substantial time requirement for the creep investigation, an empirical model is made use in the subsequent section to predict the creep strain for a specific period of time.

B. Empirical Model for Predicting Short Term Creep Behavior

The creep performance of molded specimens was experimentally investigated for 2h duration for the stress range varying from 18.84, 22.25, 38.27 and 47.17 N//mm2

and the test results are shown in Fig (4a-4c) .It is vivid from the results that for all the tested materials, creep strain increases with time and found to be increased with applied stress level. Power law function is fitted using eq. (1) for each

and every stress levels thereby power law coefficient ('tε ),

power law exponent (n) and correlation index (R2) are determined.

Fig 4a. Creep strain for UFPP

Fig 4b. Creep strain for SFPP

The correlation index, R2 indicates that power law function

provides a good approximation to the visco elastic behavior at every stress levels. It is vivid from Figs (4a-4c) that the power

law coefficient ( 'tε ) and power law exponent (n) are

dependent on the stress level and increases with the increase in stress level

Since the power law coefficient ( 'tε ) and power law exponent

(n) are sensitive to the stress level, a methodology adopted by Hadid et al.[12] was used to establish the dependence of

power law coefficient ( 'tε ) (Fig5a) and power law exponent

(n) (Fig 5b) on applied stress level. Fig 5a shows the best fitting curve using eq. (2) and depicts the influence of applied

stress (ζ) on power law coefficient ( 'tε ) for the test specimen .

The constant curve fitting parameters (a, b from eq. 2) are also shown in Fig 5a. In general the constant parameters a and b are dependent on glass transition temperature, degree of crystallinity, and fiber orientation in the composite[20] . These parameters represent the instantaneous strain normally


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visualized during the initial period of load application. Fig 5b shows the best fitting curve using eq. (3) and elucidates the influence of applied stress (ζ) on power law exponent (n) for the test specimen. The constant curve fitting parameters (c, e from eq. 3) are also shown in Fig 5b. The constant parameters c and e are dependent on the time period of testing and relaxation mechanisms involved for the composite. These parameters represent the viscous response visualized during the secondary creep process. Eq. (4) is used to predict creep performance of molded specimen and compared with the 24 h experimental data as shown in Fig 6 (a-c). It is found that HRZ model predicted well with the experimental creep performance of the chosen thermoplastic composite specimen.

Fig 4c. Creep strain for LFPP

Fig 5a. Variation of power law coefficients over stress

Fig 5b. Variation of power law exponents over stress

Fig 6a Experimental and predicted creep performance of UFPP for 55MPa

Fig 6b Experimental and predicted creep performance of SFPP for 40MPa


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Fig 6c Experimental and predicted creep performance of LFPP for 20MPa

VI. CONCLUSIONS

Discontinuous fiber reinforced polypropylene composites were injection molded and its short term flexural creep performance is investigated. Due to the extensive time requirement for the creep performance evaluation, HRZ model was used in this work. Creep performance of the molded specimens was experimentally evaluated for 2 h and short term creep performance (24 h) was predicted with the aid of HRZ model over wide range of stress. The predicted performance was compared with 24 h experimental results and found to be satisfactory. From the present investigation, HRZ model was found to be useful in predicting the short-term creep performance of viscoelastic engineering material. Experimental results confirmed that long fiber reinforced thermoplastics possessed enhanced creep retention characteristic. HRZ model parameters were also utilized to correlate investigated material characteristics.

REFERENCES

[1] J. Markarian, “Long fibre reinforcement drives automotive market forward”, Plastics, Additives and Compounding, Vol.7, pp.24-29, 2005.

[2] B.V. Gupta and J. Lahiri, “Non-linear viscoelastic behavior of polypropylene and glass reinforced polypropylene in creep,” Journal of Composite Materials, Vol.14, pp.288-296, 1980.

[3] Sepe, M.P. Use of advanced characterization techniques in evaluating the fitness-for-use of long-glass fiber thermoplastics: San Francisco, 1994, pp.2029-2032.

[4] S.R .Challa and R.C .Progelhof, “A study of creep and creep rupture of polycarbonate”, Polymer Engineering and Science, Vol.6, pp.546-554, 1995.

[5] A. Pegoretti and T.Ricco, “Creep crack growth in a short glass fibres reinforced polypropylene composite”, Journal of Material Science, Vol.19, pp.4637-4641, 2001.

[6] R.K. Krishnaswamy, “Analysis of ductile and brittle failures from creep rupture testing of high-density polyethylene (HDPE) pipes”, Polymer, Vol. 28, pp.11664 -11672, 2005.

[7] S.Houshyar , R.A.Shanks and A. Hodzic, “Tensile creep behavior of polypropylene fibre reinforced polypropylene composites”, Polymer Testing,Vol. 24,pp. 257-264,2005.

[8] A.Greco, Claudio Musardo and Alfonso Maffezzoli, “Flexural creep behaviour of PP matrix woven composite”, Composites Science and Technology, Vol.67, pp.1148-1158, 2007.

[9] B.A. Acha M.M.Reboredo, and N.E.Marcovich, “Creep and dynamic mechanical behavior of PP–jute composites: Effect of the interfacial adhesion”, Composites Part A: Applied Science and Manufacturing, Vol.33, pp.1507-1516, 2007.

[10] W.N. Findley and G. Khosla, “Application of the superposition principle and theories of mechanical equation of state, strain, and time hardening to creep of plastics under changing loads”, Journal of Applied Physics, Vol.26, pp.821–832,1955.

[11] W.J. Liou and C.I. Tseng, “Creep behavior of nylon-6 thermoplastic composites”, Polymer Composites, Vol.18, pp.492-499, 1997.

[12] M.Hadid, S.Rechak and A.Tati, “Long-term bending creep behavior prediction of injection molded composite using stress-time correspondence principle”, Materials Science and Engineering A, Vol.385, pp.54-58, 2004.

[13] G.E. Novak, “Creep fracture of long fiber reinforced nylon 66”, Polymer Composites, Vol.16, pp.38-51, 1995.

[14] K.Banik, J.Karger-Kocsis and T. Abraham, “Flexural creep of all-polypropylene composites: Model analysis”, Polymer Engineering Science, Vol.48, pp.941-948, 2008.

[15] H.Liu, M.A.Polak and A.Penlidis, “A practical approach to modeling time-dependent nonlinear creep behavior of polyethylene for structural applications”, Polymer Engineering Science, Vol.48, pp.159-167, 2008.

[16] American Society of Civil Engineers, Structural Plastic Design Manual, 1986.

[17] V.S.Chevali, D.R. Dean, and G.M. Janowski, “Flexural creep behavior of discontinuous thermoplastic composites: Non-linear viscoelastic modeling and time–temperature-stress superposition”, Composites: Part A, Vol. 40, pp. 870-877, 2009.

http://www.sciencedirect.com/science/journal/1464391X


http://www.springerlink.com/content/?Author=A.+Pegoretti

http://www.springerlink.com/content/?Author=T.+Ricco

http://www.sciencedirect.com/science/journal/00323861




[ISBN 978-81-925781-9-4], April 2014, pg. 80-86


[18] “Twintex Product Data Sheet”, Long fiber thermoplastic pellets, 2005, USA.

[19] C.Subramanian and S.Senthilvelan, “Development and preliminary performance evaluation of discontinuous fiber reinforced thermoplastic leaf

spring”, Journal of Materials: Design and Applications, Proc. of Ins. Mech. E Part L,Vol. 223(3), pp.131-142, 2009.

[20] “ASTM D-2990 Standard test methods for tensile, compressive, and flexural creep and creep-rupture of plastics”, ASTM International, Philadelphia.


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Exergy Analysis of Vapor Compression Refrigeration System Using R12 and R134a as Refrigerants

Mohan Chandrasekharan#1

# Department of Engineering, Mechanical Engineering Section, Al Musanna College of Technology, Muladdah, Post Box 191, Postal Code 314, Sultanate of Oman.

1 [email protected]

Abstract— This paper deals with a comparative analysis of the influence of refrigerant on the performance of a simple vapor compression refrigeration system. The study is based on the refrigerants R12 and R134a. A computational model based on energy and exergy analysis is presented for investigation of the effects of evaporating temperature and degree of sub-cooling on the coefficient of performance and exergitic efficiency of the refrigerator. A considerable part of the energy produced worldwide is consumed by refrigerators. So it is crucial to minimize the energy utilization of these devices. The exergy analysis has been widely used in the analysis of all engineering systems including refrigerators. It is a powerful tool for the design, optimization and performance evaluation of energy systems. It is well known fact that the CFC and HCFC refrigerants have been forbidden due to chlorine content and there high ozone depleting potential (ODP) and global warming potential (GWP). Hence HFC refrigerants are used now-a-days. Many research papers have been published on the subject of replacing CFC and HCFC refrigerants with other types of refrigerants. This paper presents a comparative analysis of two refrigerants working in a one stage vapor compression refrigeration system with sub-cooling and superheating. These refrigerants are: Dichlorodifluoromethane (R-12) and Tetrafluoroethane (R-134a). Keywords —Vapor compression refrigeration system, Exergy, COP, Exergetic efficiency, Degree of sub-cooling.

I. INTRODUCTION

Chlorofluorocarbons (CFCs) have been used widely over the last eight decades in refrigeration and air-conditioning due to their favorable characteristics such as low freezing point, non-flammability, non-toxicity and chemically stable behavior with other materials. Unfortunately, in recent years it has been recognized that the chlorine released from CFCs migrate to the stratosphere and destroys the earth’s ozone layer, causing

serious health problems [1, 2].

The Montreal Protocol signed by the international community in 1987 regulates the production and marketing of

ozone depleting substances. The CFCs were prohibited completely in 2010. Hydro-fluorocarbons (HFCs) are presently replacing CFCs as they do not contain any chlorine atoms and their ozone depletion potential (ODP) is zero.

Refrigerator pumps heat from a closed space to the atmosphere. Heat transfer between the system and the surroundings takes place at a finite temperature difference, which is a major source of irreversibility for the cycle. Irreversibility causes the system performance to degrade. The losses in the cycle need to be evaluated considering individual thermodynamic processes that make up the cycle. Energy analysis is still the most commonly used method in the analysis of thermal systems. The first law is concerned only with the conservation of energy, and it gives no information on how, where, and how much the system performance is degraded. Exergy analysis is a powerful tool in the design, optimization, and performance evaluation of energy systems [9].

The principles and methodologies of exergy analysis are well established [6-8]. An exergy analysis is usually aimed to determine the maximum performance of the system and identify the sites of exergy destruction. Analyzing the components of the system separately can perform exergy analysis of a complex system. Identifying the main sites of exergy destruction shows the direction for potential improvements.

There have been several studies on the performance of alternative environment-friendly refrigerants on the basis of energy and exergy analysis of refrigeration systems. Said and Ismail [8] assessed the theoretical performances of R123, R134a, R11 and R12 as coolants. It was established that for a specific amount of desired exergy, more compression work is required for R123 and R134a than R11 and R12. The differences are not very significant at high evaporation temperatures and hence R123 and R134a should not be excluded as alternative coolants. Also, in their study they



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obtained an optimum evaporation temperature for each condensation temperature, which yields the highest exergetic efficiency.

Aprea and Greco [9] compared the performance between R22 and R407C (a zeotropic blend) and suggested that R407C is a promising drop-in substitute for R22. Experimental tests were performed in a vapour compression plant with a reciprocating compressor to evaluate the compressor performance using R407C in comparison to R22. The plant overall exergetic performance was also evaluated and revealed that R22 performance is consistently better than that of its candidate substitute (R407C).

Aprea and Renno [9] studied experimentally, the performance of a commercial vapour compression refrigeration plant, generally adopted for preservation of foodstuff, using R22 and its candidate substitute (R417A) as working fluids. The working of the plant was regulated by on/off cycles of the compressor, operating at the nominal frequency of 50 Hz, imposed by the classical thermostatic control. The reported result indicated that the substitute refrigerant (R417A), which is a non-azeotropic mixture and non-ozone depleting, can serve as a long term replacement for R22; it can be used in new and existing direct expansion R22 systems using traditional R22 lubricants. Also in their analysis, the best exergetic performances of R22 in comparison with those of R417A were determined in terms of the coefficient of performance, exergetic efficiency and exergy destroyed in the plant components.

Khalid [10] studied the performance analysis of R22 and its substitute refrigerant mixtures R407C, R410A and R417A on the basis of first law. It was found that the COP of R417A is 12% higher than R22, but for R407C and R410A, COP is 5% lowered as compared to R22, and R417A can be used in existing system without any modification.

Various studies reviewed above focused mostly on the exergetic analysis of R22 and its alternative refrigerants. R12 is used solely in the majority of conventional household refrigerators, and there is currently little information on the exergetic performance of R12 alternatives.

Therefore, in this paper, exergetic performances of a domestic refrigeration system using R12 and its environment-friendly alternative refrigerant R134a are theoretically studied and compared.

II. SYSTEM DESCRIPTION

A one stage vapor compression refrigeration system is considered as numerical exemplification of the proposed study. The system is composed by a mechanical piston

compressor, a condenser, a throttling valve and an evaporator, as shown in Figure 1. The refrigerant enters the compressor at state 1, with a superheating degree ΔTSH with respect to the evaporation temperature TV. It follows the irreversible compression process 1-2, characterized by an increase in entropy from state 2s (adiabatic reversible compression) to state 2. The refrigerant leaves the compressor as superheated vapor at pressure PC and enters the condenser and sub-cooler, arriving in state 3 as sub-cooled liquid that is further throttled during the process 3-4. Its pressure is the vaporization pressure PV and the cycle is closed by a vaporization process 4-1 in the evaporator and super-heater.

Fig. 1: Single stage Vapor Compression Refrigeration System

III. MATHEMATICAL MODEL

The system is analyzed both from energetic and exergetic points of view.

A. Energetic Approach

This analysis is applied either to each device (seen as a control volume) or to the entire system (a control mass).

It is based on the First Law of Thermodynamics, whose mathematical expression for a control volume is:

∑ (

) ∑ (

)

where E represents system energy (J), t stands for time (s),

h is the specific enthalpy of refrigerant (J/kg), v2/2 is the specific kinetic energy (J/kg), gz is the specific potential

energy (J/kg), is the mass flow rate of refrigerant (kg/s),

and are the energetic exchanges of the control

(1)


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volume with its surroundings in form of heat flux and work rate (power).

The subscripts i and o stands for inlet and outlet states, respectively.

For steady state operation, equation (1) becomes:

∑ (

)

∑ (

)

(2)

In vapor compression refrigeration system, changes in kinetic and potential energies are negligible. So equation 2 becomes:

∑

∑

(3) which is applied to each device of the system:

(a) for the evaporator:

(4)

where represents the refrigeration load.

(b) for the condenser:

(5)

where is the rate of heat rejected at the condenser

(c) for the compressor:

(6)

where is the rate of work input to the compressor.

(d) for the throttling valve:

(7)

The energetic efficiency of the system is measured by the coefficient of performance:

(8)

B. Exergetic Approach

A reversible thermodynamic process can be reversed without leaving any trace on the surroundings. This is possible only if the net heat and net work exchange between the system and the surrounding is zero [9]. All real processes are irreversible. Some factors causing irreversibility in a refrigeration cycle include friction and heat transfer across a finite temperature difference in the evaporator, compressor, condenser, and refrigerant lines, sub-cooling to ensure pure liquid at capillary tube inlet, super heating to ensure pure vapour at compressor inlet, pressure drops, and heat gains in refrigerant lines [11]. Accurate analysis of the system is obtained by evaluating the exergy used in the system components. The p-h diagram of the vapor compression refrigeration cycle is presented in Figure 2. Exergy flow destroyed in each of the components is evaluated as follows [3, 9]:

The exergetic balance equation for a control volume is:

∑(

) (

) ∑

∑

(9)


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Fig. 2: Vapor compression refrigeration system on p-h diagram.

For steady state operation, equation 9 becomes:

∑(

) ∑

∑

(10)

Applying the exergetic balance equation to each component of the vapor compression refrigeration system,

(a) for the evaporator:

(

)

(11)

(b) for the compressor:

(12)

(c) for the condenser:

(13)

(d) for the throttling valve:

(14)

The throttling process is isenthalpic process. h3 = h4.

Therefore, equation 14 can be expressed as:

(15)

The total exergy destruction rate,

The overall system exergetic efficiency ( ) is the ratio of the exergy output ( ) to exergy input ( ) [3].

(

)

(17)

(18)

The only source of exergy input to the system is through the electrical power supplied to the compressor ( ), that is, = and Eq. (17) can be expressed as:

(

)

or

(

)

(19)


Figure 3 shows the variation of COP with varying evaporator temperature for R134a and R12. The graph shows that the COP increases with increase in evaporator temperature for both the refrigerants. At lower temperatures COP is slightly higher for R134a than R12. However, at higher evaporator temperatures, COP of R12 is higher than that of R134a.

Fig. 3: Variation of COP with evaporator temperature

Variation of exergetic efficiency with evaporator temperature is given in figure 4. Exergetic efficiencies of both the refrigerants decrease with increase in evaporator temperature. At lower evaporator temperatures, the exergetic efficiency of VCRS operating on R134a is higher than those


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operating on R12. But at higher evaporator temperatures R12 system has higher exergetic efficiency than R134a system.

Fig. 4: Variation of exergetic efficiency with evaporator temperature

The figure 5 shows the variation of COP with degree of sub-cooling. COP increases with increase in degree of sub-cooling for both the refrigerants. R134a is more sensitive to variation in degree of sub-cooling

Fig. 5: Variation of COP with degree of sub-cooling

The variation of exergetic efficiency with degree of sub-

cooling is shown in the figure 6 below. Exergetic efficiency increases with degree of sub-cooling for both the refrigerants. The variation is steeper for R134a than R12.

Fig. 6: Variation of exergetic efficiency with degree of sub-cooling

V. CONCLUSION

A comparative analysis of the refrigerant impact on the operation and performances of a one stage vapor compression refrigeration system was presented. The effects of evaporator temperature and sub-cooling were studied on the system operation and performances. Based on the exergy analysis, exergy destruction rates were estimated for each component of the system in a comparative manner for two refrigerants (R12, R134a).


[ISBN 978-81-925781-9-4], April 2014, pg. 87-92


REFERENCES

[1] Akash, B.A.; and Said, S.A. (2003). Assessment of LPG as a possible alternative to R12 in domestic refrigerators. Energy Conversion and Management, 44(3), 381-388.

[2] Sattar, M.A.; Saidur, R.; and Masjuki, H.H. (2007). Performance investigation of domestic refrigerator using pure hydrocarbons and blends of hydrocarbons as refrigerants. Proceedings of World Academy of Science, Engineering and Technology, ISSN 1307-6884, 23, 223-228.

[3] Bolaji, B.O. (2005). CFC refrigerants and stratospheric ozone: past, present and future. In: Environmental sustainability and conservation in Nigeria, Okoko, E. and Adekunle, V.A.J. (Eds.); Book of Readings of Environment Conservation and Research Team, 37, 231-239.

[4] Moran, M.J. (1992). Availability analysis: a guide to efficient energy use. New Jersey: Prentice-Hall, Englewood Cliffs.

[5] Aprhornratana, S.; and Eames, I.W. (1995). Thermodynamic analysis of absorption refrigeration cycles using the second law of thermodynamics. International Journal of Refrigeration, 18(4), 244-252.

[6] Bejan, A. (1998). Advanced engineering thermodynamics. New York: John Wiley and Sons Inc.

[7] Dincer, I.; and Cengel, Y.A. (2001). Energy, entropy and exergy concepts and their roles in thermal engineering. Entropy, 3, 116-149.

[8] Said, S.A.M.; and Ismail, B. (1994). Exergetic assessment of the coolants HCFC123, HFC134a, CFC11, and CFC12. Energy, 19(11), 1181-1186.

[9] Aprea, C.; and Greco, A. (2002). An exergetic analysis of R22 substitution. Applied Thermal Engineering, 22(13), 1455-1469.

[10] Khalid, M.A. (2006). Comparison of performance analysis of R22 and its alternate. 11th HVACR Conference, Krachi, 56-67.

[11] Kilicaslan, C.; Songnetichaovalit, T.; and Lokathada, N. (2004). Experimental comparison of R22 with R417A performance in a vapour compression refrigeration system. Energy Conversion Management, 45, 1835-1847.


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Activity Concentrations of Natural Radionuclides in Soils of Rainforest Sites in Western Ghats

*P.K.Manigandan, and K.K.Natrajan

*Departemnt of Engineering, Al Musanna College of technology-Oman

*[email protected]

Abstract– Assessments of naturally occurring radionuclides in soil collected from a tropical rainforest forest of western Ghats, India were conducted. These radionuclides were distributed unevenly in the forest soil. For all soil samples, the terrestrial gamma dose rate and the corresponding outdoor annual effective dose equivalents were evaluated. The activity concentration of 232Th and average outdoor gamma dose rates were found to be higher than the global average which appears to affects Western Ghats environment in general, the radiological hazard indices were found to be within the International Commission on Radiological Protection recommended limits. Hence, obtained results for natural radionuclides in the forest soils were within the range specified by UNSCEAR (2000) report for virgin soils except 232Th.

Key words– Naturally occurring radionuclides, Western Ghats, Monazite, radiological hazard

I. INTRODUCTION

We have previously reported that activity concentration of thorium was high in the region of Western Ghats especially around the Nilgiri hill station due to the presence of monazite sand (Manigandan. 2009; Selvasekarapandian. 2000; Iyengar et al. 1990) [1-3]. The external radiation levels from monazite sands in India are higher than that of radiation level reported from Brazil. High content of thorium and traces of uranium are also reported from these areas. These thorium and uranium may be redistributed during igneous, sedimentary and metamorphic cycles of geological evolution, which might have resulted in small concentrations of deposits under favorable geological processes. Literature indicates that the deposit of monazite on the coastal areas of Kerala and Tamil Nadu were formed due to the weathering of rocks in Western Ghats. Monazite sands consist of phosphate minerals of elements such as cerium which occur as small brown crystals in the Kerala sands (these monazite sands are mined for both cerium and radioactive

thorium oxide). The sands originate in the granites and gneisses of the Western Ghats and are transported to the coast by more than 47 streams that indent the Kerala coastline (Valithan et al.1994) [4] and it is shown in the Figure 1.

The study of the radioactive components in soil is a fundamental link in understanding the behavior of radionuclides in the ecosystem and contributes to the total absorbed dose via ingestion, inhalation andexternal irradiation. Forest soils in comparison with agriculture soils are more suitable for radionuclide investigations, because they not are usually disturbed by cultivation over long period of time. Characteristics of forest soils may modify radionuclide transfer in the and their bioaccumulation in comparison with other ecosystems (Segovia et al. 2003)[5]. These are important factors that might result in additional population exposure due to external irradiation or intake of radioactivity by the people. This might have economic consequences due to possible recreational or industrial use of the forest or its products (Gaso et al. 1998: Vaca et al. 2001) [6-7]. Therefore, thorough knowledge about the level of exposure to natural radiation from natural gamma-emitting radionuclides is important to the authorities and policy makers for making the right decisions.

II. MATERIALS AND METHODS

A. Study Area

The soils analyzed were collected from elevations of between 2000 and 2400 m the Nilgiri Highlands, Tamil Nadu, South India, which are situated between 11° 00' and 11° 30' N and between 76° 00' and 77° 30' E. The Nilgiri massif is located at the junction between the Eastern and Western Ghats, and is bounded by abrupt slopes. The study area is shown in Fig. 1. The vegetation above 2000 m in the highlands is a mosaic of high-elevation evergreen forests, called „shola‟ locally, and

grasslands with different compositions of flora, including C4 grasses (Sukumar et al. 1995; Rajagopalan et al. 1997) [8-9].



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B. Sample Collection

The study area was divided into a 4-km grid and soil samples were collected from 15 sampling points in the natural, uncultivated, and grass-covered level areas within the grid, conforming to International Atomic Energy Agency recommendations (IAEA 1989)[10]. The 15 sampling points followed a zig-zag pattern. Five 20-cm-deep samples were collected at equal distances along a 1-m circle around the center of each sampling point. This sampling method was used to improve the representativeness of the samples. The position and elevation of each sampling point was determined using a global positioning system.

C. Sample Processing

The soil samples were transported to the laboratory and plant roots and other unwanted materials were removed. The samples were then dried in an oven at 105 °C for 12–24 h, ground, and passed through a 2-mm sieve. About 400 g of dry sample was weighed into a plastic container, which was capped and sealed. The container was sealed to ensure that none of the daughter products of uranium and thorium that were produced, particularly radon and thoron, could escape. The prepared samples were stored for 1 month before counting to ensure that equilibrium had been established between radium and its short-lived daughters. Detailed gamma-ray spectrometry analysis was performed on the soil samples.

D. Activity Determination

The samples were analyzed using a NaI(Tl) spectrometer coupled with TNIPCAII Ortec model 8K multi-channel analyzer . The 232Th-series, 238U-series, and 40K activities were estimated, as were the amounts of these radionuclides that would enter the air from the soil. A 3 inch × 3 inch NaI(Tl) detector was used, with adequate lead shielding, which reduced the background by a factor of 95. The energies of interest were found using an International Atomic Energy Agency standard source and the appropriate geometry. The system was calibrated in terms of both the energy response and the counting efficiency. Sample with a density of 1.3 g/cm3 was used for the calibration, which was the same as the mean density of the soil samples analyzed (1.24 g/cm3), the detector was very well shielded, and the counting time was 20,000s for each sample. The minimum detectable concentrations, defined as 3 × σ (the standard

deviation), were 7 Bq/kg for the 232Th-series, 8.4 Bq/kg for the 238U-series, and 13.2 Bq/kg for 40K.

The concentrations of the radionuclides of interest were determined using the counting spectrum for each sample. The peaks corresponding to 1.46 MeV (40K), 1.76 MeV (214Bi), and 2.614 MeV (208Tl) were considered when evaluating the 40K, 238U-series, and 232Th-series activities, respectively. The crystal detector resolution was 6% for 40K, 4.4% for the 232Th-series, and 5.5% for the 238U-series. The gamma-ray spectrum activities for each soil sample were analyzed using dedicated software, and references were chosen to achieve sufficient discrimination.

In addition to the gamma-ray spectrometric analysis, a low-level survey environmental radiation dosimeter (type ER 705; Nucleonic System PVT Ltd., Hyderabad, India) meter was used to measure the ambient radiation levels in the forest in the study area. The dosimeter had a halogen quenched Geiger–Müller detector (Ind. lnc., U.S.A ) powered by a rechargeable battery, and was designed to read the exposure rate at two levels, 0.1 μR/h and 1 μR/h. The dosimeter was calibrated using a standard

source before use.


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III. RESULTS AND DISCUSSION

The activity concentration of naturally occurring radionuclides in forest soil of Western Ghats is shown in Table 1. The mean activity concentration ranges for 238U in soil was 15.12 to 41.21Bq/ kg with an averages of 26.26 + 9.1Bq /kg. This shows that, similar activity concentration was found throughout the forestland with less variation. At the same time, samples that were collected from interior parts of the forest showed high concentration of thorium, since the samples collected from these areas were covered with bushes and trees of various species where soils were generally undisturbed much by weathering.

TABLE 1

THE ACTIVITY CONCENTRATION OF NATURALLY OCCURRING

RADIONUCLIDES AND RAEQ VALUES IN SOIL SAMPLES

* σ is Standard Deviation

On the other hand, the activity concentration of 232Th was much higher than 238U at all the locations. The activity of 232Th in soil ranged from 39.17 to 76.13Bq/kg with a mean of 53.61 + 10.4Bq/kg. The spectral measurement clearly exposed the spectral photo peaks at 238.3, 373.3, 510.7, 727.3, 911.2, 916, 1587 and 2614KeV which were due to the

daughter products of 232Th series viz, 212Pb, 228Ac, 208TI, 208Tl, 212Bi, 228Ac, 212Bi and 208Tl, respectively. Hence, this observation endorses presence of 232Th series in soil and also the deposits of monazite on the coastal areas of Kerala and Tamil Nadu were formed due to the weathering of rocks in Western Ghats.

The activity of 40K in soil ranged from 127.54 to 248.12Bq/ kg with a mean of 204.08 + 30.4Bq/ kg. The previous background radiation survey by Selvasekarapandian et al (2000)[2] showed that mean activity of 232Th-series, 238U-series and 40K are 4.4, 1.9 and 0.742 time was higher than the world average values reported by the UNSCEAR 2000 Report (Such as 238U, 232Th and 40K were 35Bq/kg, 30Bq/kg and 400Bq/kg respectively)[11] . The mean activity of 232Th observed in the present work is 1.5 times higher than the world average value whereas the mean activity of 238U and 40K was observed to be lower than the world average. These variations in the activity concentration may be explained by the difference in natural ecosystems and the terrestrial ecosystems. There are several important features, the main one being that, in terrestrial ecosystems, soils are periodically ploughed and fertilized, while in natural systems they exhibit a more or less clear subdivision in the upper, mainly organic horizon and the lower, mineral horizon. They differ in several important characteristics such as pH, moisture, nutrient status, biological activity etc. (Frissel et al. 1990) [12].

While comparing radionuclides from different decay chains (232Th and 238U), it was observed that both the series are linearly related i.e. concentration of 232Th-series increases with increase of 238U-series, but Y- intercept is clearly different from zero. This fact reflects that the 232Th/238U activity ratio is not constant across the forest soil.

A graph is plotted between 232Th/238U activity ratios with the 238U concentration. The curves reflect the variation of activity ratio and expressed mathematically a hyperbolic function:

x = aCsb

Where X is the activity ratio, Cs is concentration of 238Uradionuclide in the soil and a and b parameters to determined. Using the above equation, the following function is obtained.

232Th/238U= 9.2 (238U)-0.456,

(With regression coefficients of –0.9)

This correlation reflects that the activity ratio remains constant only for high concentration of 238U in the soil. For

Location Activity Concentration

[Bq/kg] Radium

Equivalent (Raeq)

Observed Dose(ERD)

[nGy/h] 238U 232Th 40K S-1 33.42 61.32 224.56 138.40 115.72 S-2 41.21 70.28 233.71 159.71 118.23 S-3 44.11 76.13 248.12 172.08 123.81 S-4 37.91 64.61 221.5 147.36 100.82 S-5 19.99 46.5 127.54 96.31 90.45 S-6 27.9 51.86 218.06 118.85 82.95 S-7 18.57 46.96 201.14 101.21 89.77 S-8 24.38 48.67 148.89 105.44 93.18 S-9 18.56 44.14 211.19 97.94 90.91

S-10 30.12 58.46 214.56 130.24 98.9 S-11 15.12 39.17 198.79 86.44 93.98 S-12 21.03 45.89 205.37 102.47 96.59 S-13 19.99 47.76 202.77 103.90 86.36 S-14 21.42 48.91 195.39 106.41 94.32 S-15 20.19 53.55 209.67 112.91 78.41

Range 15.12

- 41.21

39.17- 76.13

127.54 -

248.12

86.44-172.08

78.41-123.81

Mean + σ *

26.26 + 9.1

53.61 + 10.4

204.08 + 30.4

118.66 + 25.3

96.96 + 12.9


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low activity concentration, contamination of radionuclides from 232Th decay chain seems to be undistinguished.

y = 9.2 x-0.456

0

0.5

1

1.5

2

2.5

3

0 20 40 60

Th

-232/

U-2

38

U-238 in Bq/kg

Fig-2

Fig 2. 232Th/238U activity ratio vs concentration of 238U in soil

A. Dose Calculation 1) Absorbed and observed dose rate: The mean activity

concentrations of 232Th and 40K are converted in to dose rate based on the conversion factor given by UNSCEAR (2000) [11] (Table 2).

D = nGy/h

………(1)

Where D is calculated the absorbed dose rate (nGy/h) CU ,

CTh and CK are the activity concentrations (Bq/kg) of 238U,232Th and 40K in soil samples respectively. The range of calculated absorbed dose rates is from 38.93 nGy/h to76.71 nGy/h with an average of 53.03 + 11.2nGy/h that similar the world average value of 51nGy/h reported in UNSCEAR (2000) [11].

The outdoor gamma dose rates were measured 1 m above the ground by a portable digital ERD at all the sampling sites. A total of five readings were recorded at each spot and the average was taken (Table 1). Other studies indicate an average outdoor gamma dose rate of 60 nGy/h in the world ranging from 10 to 200nGy/h (Taskin et al. 2009)[13] but

also similar to our determination within the experimental range.

The present study in Western Ghats shows that in the field, measured average gamma dose rate is 96.96 + 12.9nGy/h, which is slightly higher than the world average. The level of gamma radiation is directly associated with the activity concentrations of radionuclides in the soil and cosmic rays (Taskin et al. 2009) [13]. The excess dose measured in the field with the portable dosimeter (96.96±12.9 nGy/h) in comparison with the absorbed dose expected on the basis of radionuclide concentrations determined in soil samples (53.03±11.2 nGy/ h) is due to the significant contribution from the cosmic radiation in the present study area, located at 2400m above the sea level, where the contribution of cosmic ray is much higher than the normal one.

B. The Annual Effective Dose Equivalent (AEDE):

The absorbed dose to effective dose conversion coefficient (0.7 Sv/Gy) and an outdoor occupancy factor (0.2), which have been proposed by UNSCEAR (2000)[11], were used to estimate the annual effective dose rates, as shown in Eq. 2.

…….. (2)

The outdoor annual effective dose equivalents obtained for the samples are presented in Table 2 and it was found to be 65.03 + 13.8μSv which is within the world average value

of 70μsv (Orgun et al. 2007) [14].

C. Radiological Hazard Indices:

The Gamma ray radiation hazards caused by the specified radionuclides in samples were assessed by calculating the different indices. Even though total activity concentration of radionuclides is calculated, it does not provide the exact indication of total radiation hazards. Also, these hazard indices are used to select the right materials, because soil potentially contaminated is used for making earthen huts, bricks and pottery items.

The gamma–ray radiation hazards due to the specified radionuclides were assessed by two different indices (Radium-equivalent activity and external radiation hazard). A widely used hazard index (reflecting the external exposure) called the externalhazard index Hex is defined as follows:

…………….(5)


[ISBN 978-81-925781-9-4], April 2014, pg. 93-98


where CU, CTh and CK are mean activity concentrations of 238U, 232Th and 40K in Bq/kg respectively, Hazard indices of all sites samples were found to be less than unity (permissible level)(Orgun et al. 2007) [14].

TABLE 2

RADIOLOGICAL PARAMETERS FOR THE SOIL SAMPLES

* σ is SD (Standard Deviation)

D. Radium Equivalent (Raeq):

Exposure to radiation can be defined in terms of many parameters. It is well known that, Radium equivalent activity (Raeq) is also a widely used Radiation hazard index. The indices were defined as below (Beretka and Mathew 1985) [15]

…………….(4)

Where AU, ATh and AK are the activity concentration of 238U, 232Th and 40K (Bq/kg) in the soil samples respectively. Radium equivalent activity index (Raeq) represents a weighted sum of activities of the above-mentioned natural radionuclides and is based on the assumption that 259 Bq/kg of 232Th, 370 Bq/kg of 226Ra and 4810 Bq/kg of 40K produce the same gamma radiation dose rates. The use of materials whose radium equivalent activity concentration exceeds 370 Bq/kg is discouraged to avoid radiation hazards. The annual effective dose for Raeq of 370 Bq/kg corresponds to the dose limit of 1.0 mSv for the general population (Tahir et al. 2005) [16]. The calculated average radium equivalent activity value in the present study is 118.66 + 25.3Bq/kg which are lower than above said value of 370Bq/kg.

IV. CONCLUSION

The average values for 238U and 40K in all areas under investigation are within the world wide values reported by UNSCEAR (2000). The thorium concentration in the Western Ghats region is on the higher side of the world wide range which could be due to the existence of monazite sand in the area of study. The average outdoor gamma dose rate is higher than the world average, and thus Western Ghats region comes under above average background radiation in the world. In spite of all these, the other calculated radiological hazard indices are within the acceptable limits, (Safety Limit) and thus we can conclude that forest environment of Western Ghats has slightly high background radiation, but despite of this, it will not pose much radiological risks regarding harmful effects of ionizing radiation from the naturally occurring radionuclides in soil to the population. Also, the results of measurements will serve as base line data and, as a reference level for soil samples of Western Ghats.

ACKNOWLEDGEMENT

The authors are thankful to Dr. A. Natarajan, Head, HASL, IGCAR, Dr. A.R. Lakshmanan. HASL, IGCAR, Dr. A.R.Iyengar, Head, ESL, Kalpakkam for their constant encouragement throughout the period of work.

Location

D, Absorbed Dose (nGy/h)

External Hazard Index (Hext)

Outdoor Annual

effective dose

Equivalent

(μSv/y)

238U 232Th 40K Total

S-1 15.44 37.04 9.36 61.84 0.37 75.84

S-2 19.04 42.45 9.75 71.23 0.43 87.36

S-3 20.38 45.98 10.35 76.71 0.46 94.07

S-4 17.51 39.02 9.24 65.78 0.40 80.67

S-5 9.24 28.09 5.32 42.64 0.26 52.29

S-6 12.89 31.32 9.09 53.31 0.32 65.37

S-7 8.58 28.36 8.39 45.33 0.27 55.59

S-8 11.26 29.40 6.21 46.87 0.28 57.48

S-9 8.57 26.66 8.81 44.04 0.26 54.01

S-10 13.92 35.31 8.95 58.17 0.35 71.34

S-11 6.99 23.66 8.29 38.93 0.23 47.75

S-12 9.72 27.72 8.56 46.00 0.28 56.41

S-13 9.24 28.85 8.46 46.54 0.28 57.07

S-14 9.90 29.54 8.15 47.59 0.29 58.36

S-15 9.33 32.34 8.74 50.42 0.30 61.83

Range 6.99-20.38

23.66-45.98

5.32 -10.35

38.93-76.71 0.23 - 0.46

47.75 - 94.07

Mean+ σ 12.13 + 4.2

32.38 +6.3

8.51+1.27 53.02+11.2 0.31+0.07 65.03+13.

8


[ISBN 978-81-925781-9-4], April 2014, pg. 93-98


REFERENCE

[1] Manigandan P K (2009). “Activity concentration of radionuclides in plants in the environment of Western Ghats, India”. African Journal of Plant Science 3 (9): 205-209,

[2] Selvasekarapandian S, Manikandan N, Sivakumar R (2000). “Natural radiation distribution of soil at Kotagiritaluk of Nilgiris biosphere in India”. Eighth International Conference, October 16-20, Ibaraki, Japan.

[3] Iyengar M A R, Ganapathy S, Kannan V, Rajan MP, Rajaram S (1990). “Procedure Manual, Workshop on Environmental Radioactivity, Kiga, India”.

[4] M.S Valithan C.C Kartha, C.C. Nair K Shivakumar and T.T Eapan (1994) geochemical basis of tropical endomyocardial fibrosis. Current Science. 67(2): 99-104

[5] Segovia N, Gaso MI, Alvarado E, Pena P, Morton O, Armienta MA, Reyes AV (2003). “Environmental radioactivity studies in the soil of a coniferous forest”. Radiat Meas 36:525–528

[6] Gaso MI, Segovia N, Herrera T, Perez-Silva E, Cervantes ML, Quintero E, Palacios J, Acosta E (1998). “Radiocesium accumulation in edible wild mushrooms from coniferous forests around the Nuclear Centre of Mexico”. Sci Total Environ 223:119–129

[7] Vaca F, Manjon G, Garcia-Leon M (2001). “The presence of some artificial and natural radionuclides in a Eucalyptus forest in the South of Spain”. J Environ Radioactivity 56:309–325

[8] Sukumar R, Suresh HS and Ramesh R (1995). “Climate change and its impact on tropical montane ecosystems in southern India”. Curr. Sci., 22 : 533-536.

[9] Rajagopalan G, Sukumar R, Ramesh R and Pant RK (1997). “Late Quaternary vegetational and climatic changes from tropical peats in southern India - An extended record up to 40,000 years B.P”. Curr. Sci., 73: 60-63.

[10] IAEA (1989), “Measurement of Radionuclides in Food and Environment, IAEA Technical Report Series No: 295”, IAEA, Vienna .

[11] UNSCEAR (2000). “Sources and biological effects of ionizing radiation”. Report to general assembly with scientific annexes. United Nations, New York

[12] Frissel M J, Noordijk KH and van Bergejik K E (1990). “The impact of extreme environmental condition, as occurring in natural ecosystem‟s on the

soil to plant transfer of radionuclides”. Elsevier, London and New York: 40-47

[13] Taskin H, Karavus M, Topuzoglu A, Hindiroglu S and Karahan G, (2009). “Radionuclide concentrations in soil and lifetime cancer risk due to the gamma radioactivity in Kirklareli, Turkey”. Journal of Environmental Radioactivity., 100: 49-53.

[14] Orgun Y, Altinsoy N, Sahin SY, Gungor Y, Gultekin AH, Karaham G and Karaak Z, (2007). “Natural and anthropogenic radionuclides in rocks and beach sands from Ezineregion (canakkale), Western Anatolia, Turkey”. Applied Radiation and Isotopes, 65: 739-747.

[15] Beretka J, Mathew P J (1985). “Natural radioactivity of Australian building materials, industrial wastes and by- products”. Health Phys. 48: 87-95.

[16] Tahir S N A, Ismail K, Zadi J H (2005). “Measurement of activity concentrations of naturally occurring radionuclides in soils samples from Punjab province of Pakistan and assessment of radiation hazards”. Radiation Protection Dosimetry. 113 (4): 421–427


[ISBN 978-81-925781-9-4], April 2014, pg. 99-104


Optimization of Hybrid Renewable Energy System for a Remote Village in Bataan, Philippines

Eugene V. Vega*1, Nelson S. Andres**

* Engineering DepartmentAl Mussana College of Technology Sultanate of Oman ** College of Engineering and Architecture Bataan Peninsula State University Balanga City, Philippines

[email protected]

Abstract— Over 1.3 billion people around the world do not have access to electricity. In these places, two immediate options are common: to use fossil fueled electricity generators or to extend the grid to reach the remote communities. However, these practices are prohibitive due to high cost of fuel and maintenance, lack of infrastructure, low demand density and capital scarcity. The utilization of stand-alone hybrid renewable energy systems (HRES) is an attractive option to provide electricity to remote villages. This study aims to assess the technical and financial feasibility of a hybrid renewable energy system to supply the basic electricity needs of Sitio Bangkal, Abucay, Bataan Philippines using HOMER, an optimization software for microgrid applications. The energy sources considered are solar energy, wind power and diesel generator. HOMER simulates the ability of the HRES to supply the electricity demand under different configurations and returns the most financially viable option based on least net present cost (NPC). Also, the sensitivity of the net present cost and levelized cost of energy is investigated under a range of fuel prices and demand growth.

Keywords— Hybrid energy system, renewable energy, wind power, solar energy

I. INTRODUCTION

Over 1.3 billion people around the world do not have access to electricity [1]. In these places, one immediate option is to use fossil fueled electricity generators. This option is considered prohibitive due to high cost of fuel and maintenance and transport of fuel to the remote location. Another alternative is to extend the grid and distribution network to supply the electricity needs of the community. This approach is technically and financially ineffective due to a combination of capital deficiency, ineffective energy service, unreliable grid service, extended building times and infrastructure challenges to connect remote areas. Adequately financed and operated microgrids based on renewable and appropriate resources can overcome many of the challenges faced by traditional lighting or electrification strategies [2].

A hybrid renewable energy system (HRES) is an energy system that integrates renewable energy sources such as wind, solar and biomass with fossil fuel based generators to

produce electrical energy. They generally operate independently with large grids and are used to energize remote area, such as small island communities or far-flung areas where grid extension is not feasible.

Hybrid systems offer better performance, flexibility of planning and environmental benefits compared to the diesel generator based stand-alone system. Remote areas provide a big challenge to electric power utilities. Hybrid power systems provide an excellent solution to this problem as one can use the natural sources available in the area e.g. the wind and/or solar energy and thereby combine multiple sources of energy to generate electricity.

Stand-alone rural microgrids provide benefits to communities by changing the low-quality energy sources with higher-quality energy fuels and technologies. Some benefits include improved health, safety, productivity and education. Per capita electricity consumption is highly correlated with improved quality of life of rural communities. For developing countries, a slight increase in electricity consumption increases the quality of life significantly [2].

One such rural community which can benefit from a stand-alone HRES microgrid is Sitio Bangkal located in the agricultural municipality of Abucay, Bataan in the Philippines. Sitio Bangkal is an upland village of 560 residents where the major livelihood is upland farming and livestock production. This remote village is 510 m above sea-level surrounded by mountainous terrain and facing the Manila Bay where above average wind speeds are prevalent in the area and almost year-round of sunshine is available. Many far flung areas in the community are not yet electrified. Few households have stand-alone diesel generator sets for their own use. The area is less viable for grid extension, due to their remoteness and low density of demand which makes the connection to the local grid an expensive solution.

Therefore, the establishment of stand-alone off-grid and renewable energy source is being considered to supply the electricity demands of this community.


[ISBN 978-81-925781-9-4], April 2014, pg. 99-104


This paper aims to assess the technical and financial feasibility of a hybrid renewable energy system to supply the basic electricity needs of the community.

II. HOMER

HOMER is a model developed by the U.S. National Renewable Energy Laboratory (NREL) to assist in the design of hybrid micropower systems. It is a tool used in the comparison of power generation technologies across a wide range of applications. HOMER models a micropower system’s physical behavior and its life-cycle cost, thus allowing the comparison of many different design alternatives based on their technical and economic qualities [3].

HOMER implements three primary functions: simulation, optimization, and sensitivity analysis. In the simulation process, HOMER simulates the operation of a system by making energy balance calculations for each hour of the year to determine its technical feasibility. A configuration is considered technically feasible if it can meet the electricity demand for each hour of the year under the constraints specified. For each of the technically viable configuration, HOMER also calculates the corresponding life-cycle cost. The system life cycle cost accounts for costs such as capital, replacement, operation and maintenance, fuel, and interest throughout the project life time.

In the optimization process, HOMER simulates all possible system configurations as specified in the search space. The search space is a set of choices of energy source, and the capacity or number of each component in the system. HOMER then lists the configuration that satisfies the technical limitations with the least net present cost, (NPC).

In the sensitivity analysis process, HOMER accomplishes multiple optimization processes under a specified range of input assumptions to determine the effects of uncertainty or variation in the model input variables. Optimization determines the optimal value of the variables over which the system designer has control such as the mix of components that make up the system and the size or quantity of each. Sensitivity analysis helps assess the effects of uncertainty or changes in the variables over which the designer has no control.

III. SIMULATION

A. Load Profile

The load profile for Sitio Bangkal was estimated from electrical load survey of the area and electrification plan sourced from the local government. The load demand profile was inferred from loads for street lighting and electrification of the sitio hall, a health clinic, a pre-school

and a cooperative store. The daily load demand profile is shown in Figure 1. On average, the electricity demand is 45.1 kW-h per day and the peak load for a day is estimated at 4.8 kW. The corresponding load factor is 0.389.

Fig 1. Estimated daily load profile for Sitio Bangkal

B. Renewable Energy Resource

The renewable energy sources considered are wind power and solar energy integrated with a diesel fueled generator.

Wind resource study from time-series wind speed data from January to December 2009 in 30-minute time steps is used. On the average, 200 W/m2 of wind power can be harnessed in Sitio Bangkal which is considered a moderate wind resource potential [4].

The wind speed distribution in HOMER is modeled as a Weibull probability density function which is widely used in wind energy engineering. It can be characterized given the monthly average wind speeds and the corresponding Weibull shape factor [5]. The average monthly wind speeds ranging from 3 to 8 m/s and a Weibull shape factor of 1.46 [4] is used as input in HOMER. The anemometer height was assumed to be at 10 m and the surface roughness coefficient was taken as 0.5 for forests and woodlands. The monthly wind resource is shown in Figure 2.

Figure 2. Monthly wind resource

The solar resource data in HOMER is typically input as global solar radiation on the horizontal surface which


[ISBN 978-81-925781-9-4], April 2014, pg. 99-104


includes both direct normal and diffuse radiation. Based on the latitude and longitude of the location, 14.7° N and 120.5° E in this case, solar radiation data was taken from NREL's Climatological Solar Radiation (CSR) database which directly feed into HOMER. The average daily radiation and the corresponding clearness index are shown in Figure 3.

Figure 3. Monthly solar radiation resource

C. System Components

The system hardware components are composed of a diesel fueled generator, PV arrays, wind turbine, battery bank, and converter. A schematic diagram of the system hadware components and the flow of energy in the system is shown in Figure 4.

1) Diesel Generator: A diesel fueled generator set is considered to supply power at night or during periods of low wind speed. The capital cost for the generator is 600 US$/kW and replacement cost of 600 US$/kW and cost of operation and maintenance at 0.25 US$/hr. The lifetime operating hours is taken as 15000 hours.

2) PV Array: A fixed-slope PV array is considered with a capital cost of 3000 US$/kW with no salvage value and operation and maintenance cost of 28$/ year [6]. A derating factor of 0.8 is employed to account for reduced output due to dirt, wiring losses, shading, aging, and the like. The model also uses a temperature correction factor to correct for the effect of ambient temperature on PV output. The lifetime of the PV array is assumed to be 20 years.

3) Wind Turbine: A generic wind turbine-generator is used to harness wind power. The capital and replacement cost for the turbine is assumed to be 2000 US$/kW and operation and maintenance cost of 40$/ year [7]. The turbine hub height is taken as 25 meters and life time is 15 years.

4) Battery Bank: To store excess electricity during periods of low demand, battery banks are included in the system. The battery selected is Surrette 4KS25P having nominal voltage of 4 volts and capacity of 7.6 kW-hr with lifetime of 4 years. The capital and cost of replacement is

1500 $/kW and cost of operation and maintenance is 60$/ year [8].

5) Converter: A converter is required for systems in which DC components serve AC loads and vice versa. A converter can be an inverter or a rectifier. An inverter is used to convert DC output from the wind turbine, PV array or battery when serving the AC primary load. On the other hand, a converter is used to change AC output from the generator to DC when charging the batteries. The capital cost for the converter is taken as 900$/kW and cost of replacement as 800$. It is assumed to have a lifetime of 15 years and inverter and rectifier efficiencies are assumed to be 90% and 85% respectively.

Figure 4. Components diagram and energy flow of the system

IV. OPTIMIZATION

From the simulation results of technically feasible configurations, HOMER will display the list of configurations sorted based on least net present cost (NPC).

The net present cost (or life-cycle cost) of the system is the sum of the present value of all the costs of installing, replacement and operation and maintenance of each component within the project lifetime. HOMER calculates the NPC by discounting to the present the annual cash flows of each component according to:

CRF

CC ann

NPC


[ISBN 978-81-925781-9-4], April 2014, pg. 99-104


(1) where Cann is the annualized cost of each component. The

annualized cost of a component is the cost that, if it were to occur equally in every year of the project lifetime, would give the same net present cost as the actual cash flow sequence associated with that component. CRF is the capital recovery factor given by:

(2)

where i is the real interest rate and N is the project life

time in years. In this model, i was taken as 3.7% [9] and N as 20 years.

TABLE 1

Least Npc Configurations According To Categories

Component Configuration

1 2 3 4 5

PV Array (kW)

10 16

Wind Turbine (kW)

4

10

Diesel Generator

(kW) 2 2 4 4 6

Battery 12 12 12 6

Inverter (kW) 6 6 4 2

Rectifier (kW) 6 6 4 2

Net Present Cost (US$)

$109,096 $124,472 $149,343 $196,620 $338,374

LCOE (US$/kW-hr)

$0.475 $0.542 $0.650 $0.856 $1.473

V. RESULTS

A. Configuration with Least Net Present Cost

For all technically feasible configurations, HOMER will calculate the net present cost and list them in the order of least life cycle cost. More conveniently, HOMER sorts the results according to categories.

The simulation results show that solar and wind power alone cannot meet the load demand of the system, thus for all other technically feasible configuration, a diesel generator is necessary to supply this shortage. This is partly due to the intermittent availability of renewable energy such as during low wind speed conditions for wind turbines or unavailability of solar resource at night.

Table 1 shows the technically feasible configurations as determined by HOMER listed according to categories with the least net present cost. The most optimal configuration

based on NPC is configuration 1. This configuration employs a 10 kW PV array, a 4 kW wind turbine, a 2 kW diesel generator, 12 batteries and a 6 kW converter. The net present cost is $109, 096 and the levelized cost of energy (LCOE) is $0.475/kW-hr. In comparison with a diesel-only system (configuration 5), which has 6 kW generators to serve the primary load, the NPC is $338, 374 and LCOE is 1.473$/kw-hr. Thus, in terms of light cycle cost, the HRES is a cheaper alternative than a diesel-only system.

The components cost summary for this optimized HRES configuration is shown in Figure 5. A large fraction of the net present cost is attributed to the PV array and battery bank.

Figure 5. Cash flow summary for each system component

Figure 6. NPC comparison of optimal HRES and diesel-only system

A cost comparison of the NPC of the optimal hybrid

renewable energy system with diesel-only system by cost type shows that capital requirement for HRES is substantially lower than diesel-only system. However, the operation and maintenance cost and fuel cost of the diesel-only system is significantly greater than that of the HRES.

The estimated annual electricity production of the optimal stand-alone system is 22767 kWh/year. Figure 7 shows the distribution of electricity production of this system by source. Only 9% of the total electricity produced is from diesel fuel. The renewable energy fraction, or the fraction of the energy delivered to the load that originated from renewable power sources is 88%. The monthly average electricity production is shown in Figure 8.

1)1(

)1(

N

N

i

iiCRF


[ISBN 978-81-925781-9-4], April 2014, pg. 99-104


Figure 7. Annual electricity production by source

Figure 8. Monthly electricity production by source

B. Break-even grid extension distance

The break-even grid extension distance is the distance from the grid where the net present cost of grid extension is equal to the net present cost of the optimal stand-alone system.

The NPC of grid extension is the sum of the annualized cost of the buying electricity from the grid over the project life time and the net present cost of extending the grid per kilometer. The annualized cost of buying electricity is the grid electricity price times the annual demand and annualized using the capital recovery factor (Equation 2). The net present cost per km is the sum of the capital and O&M cost per kilometer divided by the capital recovery factor (Equation 2).

The cost of grid electricity is 0.266 US$/kW-hr which is based on current price. The capital cost per km is taken as 12000 US$/km and O&M cost as 1500 US$/km [10].

Model results in Fig. 9 shows that a grid extension distance of 1.46 km breaks even the cost for the optimal stand-alone stand-alone system as compared with grid extension. This means that a distance of more than 1.46 km renders the stand-alone system as more economically feasible than grid extension. Sitio Bangkal is estimated to be 11 km away from the nearest available grid tap. This shows that grid extension is a more costly option as compared with any of the off-grid stand-alone system.

C. Sensitivity Analysis

The diesel price is considered as one of the major contributing factor in the increased cost of maintaining a

diesel generator set. A sensitivity analysis of the diesel price with levelized cost of electricity is modeled in HOMER. This will determine to what extent the diesel price will affect the NPC and the LCOE. The range of price of diesel taken for sensitivity analysis is between 0.8-1.2 US$ per liter. Similarly, sensitivity of the NPC and LCOE with respect to the primary electricity demand growth is investigated. The of primary demand values taken are for 10%, 20% and 30% increase.

From Fig. 10, it can surmised that at the lower diesel price range of 0.8 to 0.9 US$ and a mild increase in load up to 50 kW-hr/d, the LCOE is more sensitive. However at higher demand of more than 50 kW-hr/d, the LCOE becomes less sensitive to diesel price and demand.

Figure 9. Monthly electricity production by source

Table 2 SENSITIVITY WITH INCREASE IN LOAD DEMAND

Component/Cost Primary load demand

45 kW-h/d 59 kW-h/d PV Array (kW) 10 14

Wind Turbine (kW) 4 6

Diesel Generator 9kW) 2 4

Battery 12 14

Inverter (kW) 6 6

Rectifier (kW) 6 6

Net Present Cost (US$) $109,096 $140,916

LCOE (US$/kW-hr) $0.475 $0.472

The total NPC of the system is less sensitive to the

variation in fuel price due to the high renewable energy fraction of the system. Only 9% of the annual electricity production is from diesel generator.

The effect on NPC of the diesel price and demand increase is shown in Fig. 10. The NPC increases with increase in primary load due to the need to upgrade and install additional components to meet the load demand. A comparison of these costs based on the current load demand of 45 kW-h/day and end-of project life load demand of 58.6


[ISBN 978-81-925781-9-4], April 2014, pg. 99-104


kw-hr/day when diesel priced is fixed at 1 US$/liter is shown in Table 2. It can be noted that although the NPC is increased significantly, the renewable energy fraction and thus, LCOE practically stays the same.

Figure 10. Sensitivity of LOE with diesel price

Figure 10. Sensitivity of NPC with diesel price

VI. CONCLUSION

An optimization study was conducted to assess the technical and financial feasibility of a hybrid renewable energy system to supply the electricity demand of the remote village of Sitio Bangkal in the Philippines.

HOMER was used to determine the optimal configuration for an HRES consisiting of PV array, wind turbine, diesel generator, battery banks and converters. A comparison of the net present cost of the HRES with diesel-only system and the option for grid extension is done. Also, sensitivity analysis of the net present cost and levelized cost of energy over a range of diesel price and load growth is made.

The results show that the optimal configuration consists of 10kW PV array, 4 kW turbine, 2 kW diesel generator, 12 batteries and 6 kW converter. The estimated NPC is $ 109,096 and the levelized cost of energy is $0.475/kW-hr. Over the project life time, this is considered a more financially viable option compared with a diesel-only system.

In comparison with the alternative of grid extension, the model results show that the optimal HRES is considered more feasible as it is cheaper to build and maintain HRES than to extend the grid considering the distance of Sitio Bangkal from the grid.

Sensitivity analysis shows that the LCOE and NPC of the system is not significantly sensitive to diesel price due to a high renewable energy fraction of the system. An increase of demand load however, requires a larger infrastructure and components capacity and thus raises the NPC.

REFERENCES

[1] World Energy Outlook 2013. Paris: OECD/IEA, 2013.

[2] D. Schnitzer, D. Shinde Lounsbury et al. “Microgrids for rural electrification,”UN Foundation (2014).

[3] T. Lambert, P. Gilman, and P. Lilienthal. "Micropower system modeling with HOMER." Integration of alternative sources of energy 1 (2006).

[4] E. Vega and N. Andres “ Wind power assessment using

Weibull distribution model,” in PROC 31st APAMS,

2011.

[5] Clean Energy Project Analysis: RETScreen Engineering & Cases Textbook: Wind Energy Project Analysis Chapter. Varennes, Que.: Minister of Natural Resources Canada, 2004. Print.

[6] D. Feldman, G. Barbose, R. Margolis, et al. “Photovoltaic (PV) Pricing Trends: Historical, Recent, and Near-Term Projections”

[7] "Renewable Power Generation Costs in 2012: An Overview - IRENA." Yumpu.com. N.p., n.d. Web. 12 Apr. 2014.

[8] (2014) The Rolls Battery website. [Online]. Available: http:// http://www.rollsbattery.com/

[9] " World Development Indicators | The World Bank. N.p., n.d. Web. 12 Apr. 2014

http://www.rollsbattery.com/

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