Advanced Tools for Building Simulation: Energy and Airflow 2.17 Advanced Tools for Building Simulation

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  • csd Center for Sustainable Development

    Advanced Tools for Building Simulation:

    Energy and Airflow Greg Arcangeli

    Editor

    Werner Lang Aurora McClain

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    II-Strategies Analysis

  • 2.17 Advanced Tools for Building Simulation

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    Introduction

    A number of architecture schools have integrated aspects of sustainability into their curricula, and many design studios require students to incorporate sustainable strategies in their projects. However, even programs at the forefront of this movement have not provided their students with a means to empiri- cally measure and evaluate the behaviors of passive and active building environmental systems. In the studio setting, and in the pro- fessional office for that matter, the most logical means for such testing is building simulation software. Simulations performed during the de- sign process allow for meaningful comparison of the effects of different building orientations, material choices, glazing systems, shading strategies and HVAC systems on a building’s energy consumption.

    This educational lacuna is understandable, since accurate building simulation requires a certain depth of specific technical knowledge normally reserved for engineering or computer science departments. To accurately model building performance, one must understand the physical principals of heat transfer and thermodynamics, be able to intelligently specify HVAC systems, and know how to properly configure and interpret a simulation in software that often has a fairly opaque inter- face. However, without such a tool, it becomes

    practically impossible to quantitatively test a range of design solutions.

    This paper will provide an introduction to the practice of advanced building simulation. It will begin with a discussion of the motivations for building modeling before moving on to the theory and practice of advanced energy simu- lation. The final section will touch on the more complex topic of airflow modeling, and high- light the state-of-the art in building modeling: coupled energy and airflow simulations. Even for the user of simpler, more accessible model- ing packages that fall outside the category of “advanced,” much of the information in this article is pertinent, and may even improve the usefulness of future simulations.

    Motivations for building modeling

    Building simulation software can facilitate and improve the design of an energy efficient building. Buildings account for roughly 40% of US energy consumption, and by extension, are major emitters of CO2. This is one clear motivation for designing an energy efficient building. Another, which speaks directly to most clients, is simply to reduce a building’s operating costs in the face of rising energy prices. Any building design that aims to im- prove energy performance will benefit from energy and/or airflow simulations. Typically, the numerical model is used to find

    Advanced Tools for Build- ing Simulation: Energy and Airflow

    Greg Arcangeli

    Based on a presentation by Atila Novoselac

    Figure 1: Airflow analysis of a porous double-curved brick assembly

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    II-Strategies Analysis

    There are many serious efforts underway to quantify the effects of poor IAQ. For example, the federally-funded Indoor Air Quality (IAQ) Scientific Findings Resource Bank at Law- rence Berkeley National Laboratory measures economic effects of IAQ and occupant health (see Figure 2).

    In the case of both energy analysis and issues of IAQ, simulation software can model building performance to a degree that is accurate- enough to estimate up-front capital costs and operating costs. These simulation tools are a crucial component in the complex task of quantifying benefits, such as better employee health and CO2 reduction that result from a better designed building that may present higher initial costs to the client.

    Modeling energy performance

    Capabilities of energy modeling software Simply put, energy modeling tools examine two aspects of building efficiency. First, they measure the efficiency of the building enve- lope, including skin, structure, and lighting. Second, it tests the efficiency of various solu- tions for the HVAC system. The relationship between envelope efficiency and HVAC ef- ficiency determines the total energy consump- tion of the building for a given comfort level. Since the benefits of an efficient envelope can be negated by a cheap and inefficient HVAC system, or vice-versa, finding an appropriate match is a critical part of building simulation. All advanced energy modeling programs are built on a similar foundation. Since they all

    an optimal balance between up-front capital investment in a building and the payback pe- riod of an energy efficient design due to lower operating expenses. This calculation requires an energy simulation for a given building and HVAC configuration, combined with a life-cycle analysis.

    It often turns out that the midpoint between first costs and the payback period is still more than most clients are willing to pay. To make the proposition more convincing, the life-cycle analysis side of the equation needs to be set up to factor in the importance of CO2 emis- sion reduction and the productivity benefits of increased comfort for the occupants. Work on quantifying these “hidden” costs is well underway in academic and governmental departments.

    Building simulation software can also help to ensure that the building environment and indoor air quality (IAQ) will be comfortable and healthy for occupants. We spend on average 86% of our time indoors, and buildings are the primary location of our exposure to toxins.1 Intuitively we understand that indoor air quality is important, but unlike energy or water con- servation, which are fairly predictable and can be directly measured, the relationship of health and productivity to indoor air quality is not as precisely understood and is far more difficult to accurately predict. In addition, the costs associated with poor IAQ are hard to measure and generally are “hidden” in sick days, lower productivity, unemployment insurance, and medical costs.2

    simulate how energy moves through the set of rooms or building described in the model, they utilize the same basic equations for the different modes of heat transfer: conductivity, convection, long- and short-wave radiation, and also mass transfer. Energy modeling software solves the complex equations that describe these phenomena, but of course this computational prowess does not guarantee an accuracy of solutions. A good building simula- tion program still requires a knowledgeable user to properly set up the conditions for the software to analyze.

    Setting up a model

    The basic steps for setting up any energy simulation model are:

    1. Define the simulation domain:

    The model domain could be a single room, one floor of a building, or an entire building. It is up to the person running the simulation to choose the area that makes the most sense for the model. Smaller domains allow for a level of modeling detail (including furniture, partitions, etc.) that might overwhelm comput- ing resources if simulated at the scale of a building. A whole-building simulation might be useful for testing a building skin strategy.

    2. Identify the most important phenomena and define the most important elements:

    This includes identifying the sources that are likely to play a significant role in the heat trans-

    Source of Productivity Gain

    Reduced sick building syndrome

    Reduced allergies and asthma

    Reduced respiratory disease

    Better thermal environment and lighting

    Annual Health Benefits

    20% to 50% reduction in symptoms experienced frequently by 15 million workers

    8% to 25% decrease in symptoms in 53 million people with allergies and 16 million people with asthma

    16 to 37 million avoided illnesses

    not applicable

    Annual Savings

    $10 to $30 billion

    ~ $300 per office worker

    $1 to $4 billion

    $20 to $80 per person (with allergies)

    $6 to $14 billion

    $23 to $54 per person

    $20 to $160 billion

    Figure: 2 Potential Annual Healthcare Savings and Productivity Gains from Improved Indoor Environments

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    3. Discretize elements and define connections

    In this step, the important phenomena and elements are sorted into unique entities, or calculation nodes, and the energy exchanges between them are identified. In order to prop- erly navigate this part of the simulation set-up, users must have a precise understanding of the space they are modeling, and the physical phenomena likely to be present within.

    fers within the domain. It is also necessary to identify significant energy flows between the domain and exterior adjacencies, which could be neighboring rooms or outdoor environment.

    Phenomena and elements within the domain typically include people, computers, light fixtures, or any other object in the space that emits and/or absorbs energy. This step requires judgements about which nodes are significant to the model. For example, furniture might not be included if it is expected to mini- mally affect the simulation results, because it would increase modeling time, and drain com- puting resources during the simulation. Also, one must account for the effects of the HVAC system, which is designed to keep the indoor environment at a predeter