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Abstract— Design of hydraulic turbines involves several stages

of iterative calculations. Furthermore, the selection of the

turbine is unique to each site conditions. This makes the R&D of

the hydraulic turbines a complicated and time consuming work.

Recent advancements in computational tools and processors

have added advantages to the R&D process of hydraulic

turbines. These tools are able not only to compute solutions for

the complex design equations but also provide the user friendly

virtual environment for performance test and design

optimization.

A new program named as “Khoj” has been developed using

Matlab for design optimization of Francis runners. The

optimized design from the program can be further analyzed

using CFD, CAD and FSI tools, which estimate the effect of

design variables on performance of the turbine. For the project

on failure analysis of Khimti runner, the true size runner model

has been developed using SolidWorks. Stress and fatigue

analysis of the runner has been attempted using CosmosWorks.

Study of the general performance behavior of the Pelton runner

and identification of the possible causes of failure of the Khimti

runner at its operating conditions is under progress.

This paper presents the experiences of use of computational

tools for research and development of hydraulic turbines at

Kathmandu University. The research methodology followed and

the computational tools applied, with the recent results for

design optimization of Francis runner, effects of operating

conditions on sediment erosion and failure analysis of Pelton

runner of Khimti Hydropower will be elaborated in-depth.

Effectiveness and limitations of application of computational

tools for R&D of hydraulic turbines will also be discussed.

Index Terms— Computational tools, Design, Hydraulic

turbines, CFD, SolidWorks,

I. INTRODUCTION

EPAL has a huge potential of hydro power. Most of the

surface water in Nepal flows through four major river

basins, Saptakoshi, Narayani, Karnali and Mahakali, extended

Biraj Singh Thapa is a Graduate of Mechanical Engineering from

Kathmandu University. Currently, he is working as a Full time Researcher in Turbine Testing Lab, Kathmandu University. (bst@ku.edu.np).

Amod Panthee completed his Bacherlor‟s degree in Mechanical

Engineering from Kathmandu University. Currently, he is working as a Research Assistant on RenewableNepal Project at Turbine Testing Lab,

Kathmandu University. (*correspondence email: amodpanthi@ku.edu.np).

Hari Prasad Neopane, PhD. is Associate Professor at Department of Mechanical Engineering, School of Engineering, Kathmandu University. He

works as a program coordinator on EnPe-Master Program in Planning and

Operation of Energy Systems (MPPOES) at Department of Mechanical Engineering, Kathmandu University. (hari@ku.edu.np).

from east to the west. The total hydropower potential of Nepal

at Q40 is about 53,000 MW [1] as shown in TABLE I.

Despite, having the huge potential, Nepal is still lagging

behind in power generation with total harvested capacity of

650 MW.

Hydraulic turbines

are classified into

different categories

depending upon its

principle and range

of operation [2].

Therefore, the

selection of hydraulic

turbines varies

depending upon the

site criterions. The

installation of

hydropower plants despite having a huge potential becomes

more complex with change in design for a slight variation in

design inputs like Head (H) and Discharge (Q).

Moreover, Nepal is located on the lap of Himalayas. This

increases the sediment concentration in the rivers of Nepal

unlike other countries with igneous mountains. The river

characterized with high sediment concentration is one of the

problems in operation of hydraulic turbines erected at ROR

type or storage type projects [3]. The sediment eroded Francis

runner of Trishuli HEP is shown in Figure I.

The design of

hydraulic turbine

is complex since

it involves a long

iterative process

in design stage.

And it is

necessary to

predict the

behavior of

hydraulic turbines

at various

conditions on real

environment while designing. This makes the design of the

hydraulic turbine more time consuming. But, the use of

computational tools have added advantage in design of

hydraulic turbines and the prediction of behavior at various

Some Applications of Computational Tools for

R&D of Hydraulic Turbines

Biraj Singh Thapa, Amod Panthee*, Hari Prasad Neopane

N

TABLE I

TOTAL HYDROPOWER POTENTIAL

Major Basins Potential (at Q40)

Saptakoshi 17008.3

Narayani 17800.2

Karnali 15661.16

Mahakali 2261.83

Total 52731.83

Figure I: Sediment Eroded Francis Runner

of Trishuli HEP

RENTECH, Dec. 22, 2011 , RenewableNepal, KU, Nepal.

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operating conditions and complex iterative process can be

done in short period.

II. CHALLENGES IN R&D OF HYDRAULIC TURBINES

There are many challenges in research and development of

hydraulic turbines. The challenges are seen from the initial

design stage after the selection of suitable site for erection of

hydropower station. It is followed by the selection of most

efficient design from a list optimized design to work on real

environment. The challenges continue during operation and

post operation or maintenance stage of the hydraulic turbines.

A. Design of Francis Runner

The design of hydraulic turbines involves many

assumptions. Initial assumptions during design of Francis

turbine are infinite number of thin blades, streamlines are

symmetric about the rotational axis and no frictional losses

are present [4]. But it is difficult to achieve these conditions in

real working conditions. The other assumptions based on the

empirical relation to achieve the desired result with

assumptions stated above are given in TABLE II [4].

TABLE II

INITIAL DESIGN ASSUMPTIONS OF FRANCIS TURBINE

Outlet Peripheral Velocity (U2) Outlet Angle (β2)

35 m/s – 43 m/s 180 - 22

0

The first step in design of a hydraulic turbine is to assume a

streamline. The shape of the streamline is given by equation

(1). The shape of the streamline changes with change in

values of constants „a‟ and „b‟ assumed in the equation from a

circle to an ellipse [5].

(1) (2)

The remaining streamlines on a runner blade of the runner

is obtained using the continuity equation (2) and the

principles of geometry. The geometry of the streamlines is

shown in Figure II where the constants have their usual

meaning. All these assumptions and iterative processes make

the design process a challenging task.

Figure II: Distribution of points along the streamline

B. Operation of a Hydraulic Turbine

Hydraulic Turbines are operated at various conditions. It is

a usual trend to design a hydraulic turbine at Best Efficiency

Point (BEP). But, a hydraulic turbine is operated from part

load to full load depending upon the energy requirement. The

change in operation of hydraulic turbines at different

operating conditions reduces the efficiency and life of the

turbine. Apart from these, it also creates problem in operation

and maintenance of the turbine unit [6].

Depending upon the site of operation, there is a variation in

sediment concentration with different percentage composition

of quartz and mica in rivers of Nepal [3]. So, if we have a list

of optimized design for a specific site to be tested, it would be

a problem to test with a physical model in the lab. The test

becomes more costly and time consuming when tested on a

physical model.

Despite having a

sound hydraulic

design, a hydraulic

turbine fails during

operation. A typical

case of such failure

in Pelton runner of

Khimti HEP is

shown in Figure III.

The reasons for

failure of turbines

during operation may be manufacturing defects, modes of

operation which are steady state and transient state operation

and maintenance procedure applied in the hydraulic turbines.

During the operation of hydraulic turbines, the mode of

operation changes from steady state to transient state upon

variation in load. This produces vibrations and stress on

power

production unit

which might

cause a failure of

the hydraulic

turbines. When

the load is

transferred from

point A to point

B, shown in

Figure IV, the

stress developed in the runner varies which might cause the

untimely failure of the runner when operated on a cycle [7].

C. Maintenance of Hydraulic Turbine

The turbine components are passed through a series of heat

treatment procedure during maintenance. The residual stress

is induced when a large temperature difference has been

created at different sections within the runner components [8].

Also, the improper cooling of the hydraulic turbines forms

weld decay which is a combination of Carbon and Chromium

[9], the ingredients of material used in manufacturing

hydraulic turbines. This induces residual stress in turbine

component and the immediate site of failure [7].

Figure III: Root Crack in Pelton Runner

Figure IV: Pelton Bucket

A B

R1,1; Z1,1

R1,2; Z1,2

Ri+1,1; Zi+1,1

Ri-1,1; Zi-1,1 Ri,1; Zi,1

Ri,2; Zi,2

ri,1

bi,1

Z

R

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III. METHODOLOGY

The Francis runner blade has been developed using general

principles mentioned in Section II and literature [5] for

“Design Optimization of Francis Runner” and “Effects of

Operating Conditions on Sediment Erosion” using the Matlab

program “Khoj” and CAD software. These files are exported

to AnSys CFX for further analysis.

A. Design Optimization of Francis Runner

A range of optimization criterion has been set on outlet

diameter, number of pole pairs in generator, reduced

peripheral velocity at inlet, acceleration of flow through the

runner, height of the runner and blade angle distribution [10].

Several optimized design is then developed using the

optimization criterion. The comparison of the optimized

design is done with the reference design by setting the erosion

factor and erosion tendency as reference indicators.

Erosion Tendency (3) is quantification of tendency of a

specific design of the runner to be eroded in similar sediment

conditions. Erosion Factor (4) is the ratio of erosion tendency

of each new design with respect to reference design.

m3/s

3 (3)

- (4)

The erosion factor for the reference design is set 1 and

compared to the results obtained for optimized design.

B. Effects of Operating Conditions on Sediment Erosion

The factors responsible for sediment erosion are particle

mass, particle velocity, grain shape and size, concentration of

particles and angle of attack at which the collision occurs

between the particle and the surface of the runner blade. The

empirical erosion model, Tabakoff erosion model (5), is used

in analysis which incorporates the factors responsible for

erosion to determine the erosion rate [6].

(5)

Where,

, Vp is the

particle impact velocity, is the impact angle in radians

between the particle path and the wall, is the angle of

maximum erosion. , are the model

constants and depend upon the particle and wall material

combination.

The blade profile is meshed with hexahedral element using

Turbo-Grid. The analysis is done on two modes of operation,

i.e. at best efficiency point with guide vane opening of 160

and at full load point with guide vane opening of 220. The

sediment particles chosen for analysis are of spherical and

non-spherical types. The boundary condition is set as uniform

injection of sand particles of uniform diameter for both modes

of operation [6].

C. Failure Analysis of Pelton Runner

The 3D model of

the Pelton Runner,

shown in Figure V,

has been developed

using the

orthographic

projection of runner

sections provided by

Himal Power Limited

using SolidWorks.

The other model

runner was developed

for stress and fatigue

analysis of the Pelton

runner because of software limitation. The information on

analysis conditions is tabulated in TABLE III.

TABLE III

ANALYSIS CONDITIONS ON COSMOSWORKS

Load

Force 85630 N normal to the reference plane

Distribution Uniform Distribution and Sequential Loading

Restraint

Description On 1 Face (at center)

Study Property

Mesh Type Solid Mesh

Jacobian Check 4 Points

No. of Elements 55709

IV. RESULTS

A. Design Optimization of Francis Runner

The optimized design developed within the defined range of

operation is shown in Figure VII. The optimized design is then

compared with the reference design, shown in Figure VI, of

Jhimruk HEP in Nepal. The result of comparison between the

reference and optimized design is shown in TABLE IV.

Figure VI(a): Streamlines on

Reference Design

Figure VI(b): Sediment Erosion

on Reference Design

Figure VII(a): Streamline on

Optimized Design

Figure VII(b): Sediment

Erosion on Optimized Design

Figure V: 3D Model of Pelton Runner

of Khimti HEP

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TABLE IV

COMPARISON OF EROSION FACTOR

Reference Design Optimized Design

Erosion Factor 1.0 0.481

The design optimization result also showed that the

sediment erosion is reduced significantly with increase in the

runner height [10]. Erosion is also dependent upon the blade

angle distribution. It was found that the erosion rate is

reduced for the optimized design with blade shape 1

compared with the reference design of blade shape 3 [10]

shown in Figure VIII.

B. Effects of Operating Conditions on Sediment Erosion

The effects of operating conditions on sediment erosion

have been analyzed on Francis blade of Cahua Power Plant of

Peru. The result showed that the erosion rate density is higher

at full load operation point than operation at best efficiency

point for both spherical and non-spherical sediments [6],

shown in Figure IX and Figure X.

Figure IX: Erosion due to Spherical Sediment

(a) at BEP (b) at Full Load

Figure X: Erosion due to Non-Spherical Sediment

(a) at BEP (b) at Full Load

This is due to the increase in flow turbulence and higher

relative flow velocities at runner outlet. The increase in

erosion rate is due to the presence of higher rotational motion

which caused more separation of flow. The result suggests

that the operating conditions of hydraulic turbines have

significant effect on erosion of the turbine components.

The analysis was repeated varying the concentration of

sediments at two modes of operation. The results from the

analysis is shown in Figure XI. It can be observed that with an

increase in sediment concentration, the erosion rate density is

increased for both modes of operation. It can be concluded

from the result that the erosion rate in the runner blade is

always higher when operated at full load than at best

efficiency point [6].

Figure XI: Variation of Relative Erosion Rate Density with

mode of Operation

C. Fault Analysis of Pelton Runner at Khimti HEP

The model runner was analyzed using CosmosWorks add-

in in SolidWorks for stress and fatigue analysis. Figure XII

shows the Factor of Safety (FOS) plot of the model runner.

The result shows that the root area of the runner geometry is

critical site for occurrence of failure [7]. The result justifies

the occurrence of crack in the root of pelton bucket shown in

Figure III.

Figure XII: FOS Analysis on a Model Runner

V. CONCLUSION

The use of computational tools in R&D of hydraulic

turbines helps in complex solving the complex mathematical

equations reducing both cost and time. The advantage on

Figure VIII: Blade Angle Distribution

Full Load

BEP

RENTECH, Dec. 22, 2011 , RenewableNepal, KU, Nepal.

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reduction of cost and time can be justified by the use of the

real environment conditions for virtual testing in lab

repeatedly for different test conditions, which might increase

in cost and time if the problem has to be solved using the real

physical model. In design of hydraulic turbines, it plays an

important role offering flexibility while choosing different

variables that accounts different design result. The effects

due to change of each variable on design can be easily

understood which helps in producing an efficient design. It

also helps in finding the possible causes of failure of

hydraulic turbines during initial design stage.

The use of computational tools can be sometimes

disadvantageous. The assumptions should be carefully taken

to represent the real operating conditions. The results obtained

are dependent upon the accuracy of the input data and

assumptions. Therefore, it is necessary to verify the design

outputs obtained from the computational tool using a physical

model test at lab. Despite significant reduction in erosion

factor of optimized design, Figure VII (a), streamlines in the

optimized design are not uniform as in the reference design,

Figure VI (a). This might cause reduction in efficiency of the

significant design which should be verified with a physical

model test at lab.

The fault analysis of Pelton runner of Khimti HEP is at its

initial research stage. Further works can be done on stress and

fatigue analysis of the real model of runner. The effects due to

the heat treatment procedure on the runner can be analyzed

using appropriate assumptions with the aid of computational

tools. The effect due to different modes of operation on the

turbine component is another prospective area where

computational tools can be used.

REFERENCES

[1] Jha, R. (2007), Total Run-of-River type Hydropower

Potential in Nepal, Hydro Nepal.

[2] Thapa, B. (2004), Sand Erosion in Hydraulic Machinery,

PhD Thesis, Norwegian University of Science and

Technology (NTNU).

[3] Neopane, H. P. (2010), Sediment Erosion in Hydro

Turbines, PhD thesis, Norwegian University of Science

and Technology (NTNU).

[4] Brekke, H. (2001), Hydraulic Turbines: Design, Erection

and Operation, Norwegian University of Science and

Technology (NTNU).

[5] Francke, H. H., et al. (2009), High Pressure Hydraulic

Machinery, Water Power Laboratory, Norwegian

University of Science and Technology (NTNU).

[6] Neopane, H. P. (2011), Relationships between Operating

Conditions of Turbines and Sediment Erosion,

Proceedings in the International Conference of Hydro

2011.

[7] Panthee, A. (2011), Fault Analysis of Pelton Runner of

Khimti Hydropower, Industrial Training Report, Turbine

Testing Lab, Kathmandu University.

[8] Kubota, T., & Tanaka, O. (2010). Fuji Electric Co., Ltd.

Retrieved July 24, 2011, from Fuji Electric:

http://www.fujielectric.com/company/tech_archives/pdf/3

0-04/FER-30-04-151-1984.pdf

[9] Steel Casting Handbook, Supplement 7 Welding of High

Alloy Casting (2004), Steel Founders Society of America.

[10] Thapa, B. S., Eltvik, M., Gjøsæter, K., Dahlhaug, O. G.

(2012), Design Optimization of Francis Runners for

Sediment Handling, Proc. in Int. Conf. on Water

Resources and Renewable Energy Development in Asia,

Thailand.

BIOGRAPHIES

Biraj Singh Thapa is a graduate of Mechanical Engineering from

Kathmandu University. Currently, he is working as a Full time Researcher in RenewableNepal Project at Turbine Testing Lab, School of Engineering,

Kathmandu University.

Amod Panthee completed his Bachelor Degree in Mechanical Engineering

from Kathmandu University. Currently, he is working as a Research Assistant in RenewableNepal project at Turbine Testing Lab, School of Engineering,

Kathmandu University.

Hari Prasad Neopane completed his PhD from NTNU. He is Associate

Professor at Department of Mechanical Engineering, School of Engineering,

Kathmandu University. He works as a program coordinator on EnPe-Master Program in Planning and Operation of Energy Systems (MPPOES) at

Department of Mechanical Engineering, Kathmandu University.

RENTECH, Dec. 22, 2011 , RenewableNepal, KU, Nepal.