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Field Test Best Practices: A Resource for Practical Residential Building Science

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Experiment Design

Design the experiment so that the preliminary model can be verified and/or fine-tuned for improved accuracy over a wide range of environmental conditions. Clearly define the control volume that is being used to calculate air, moisture, and energy balances. Often, a cleverly-designed experiment can take a relatively short time (no more than a week) to conduct, yet still yield the desired verification of the model. Some phenomena are, by their nature, very slow-moving, (e.g., deep-ground temperatures), and experiments that involve these types of measurements may last many months or even years.

Research Questions

Formulating good research questions is a critical first step in planning an effective field test program (e.g., the list of required sensors and their placement around the house cannot be determined without the appropriate research questions). When drafting research questions, begin with the big picture. What are you trying to accomplish in the project at hand? The research question should flow from a clear project objective. Next, clearly define the areas that need to be addressed and determine why they need to be addressed. This process should include both research questions and hypothesized outcomes.

Role of Building Simulation in Field Testing

Use a building energy simulation program to refine initial estimates of project benefits. The researcher should make his/her best effort to accurately simulate the behavior of the ECM or phenomenon being investigated. This may involve reviewing the source code to understand how the physics is currently modeled and what the relevant underlying assumptions are. A literature search should help guide the development of a reasonable mathematical model based on available information.

Assessment of Current State of Knowledge to Determine Best Technical Approach

Research the existing literature to find what is already understood about the issue and identify the type of datasets required to further that understanding. Are the relevant questions best addressed through field testing? Are there faster, easier, or less expensive ways to answer the questions? Based on the current knowledge, what are the remaining gaps? What are the estimated benefits of resolving these gaps? What are the options for addressing the gaps identified above? Which approaches have the most chance of success?

Short-Term Experiments

Short term experiments provide valuable information that can be obtained only when the home is unoccupied and hence the internal conditions can be controlled. They are appropriate for brief, high-value tests such as measuring building UA and tracer-gas measurements of air-tightness and distribution. One limitation of short-term testing is that datasets cannot be obtained for a wide range of weather conditions and occupant behaviors.

Long Term Monitoring

If seasonal variations and occupant effects are key concerns, long-term monitoring is more appropriate than short term monitoring. Typically these homes are occupied (except in special circumstances such as lab houses, where occupancy effects are eliminated or simulated) and therefore allow investigations of house performance under realistic operating conditions, which include human interactions, range of weather conditions, and equipment degradation over time. An inherent complication with occupied long-term monitoring is that occupant behavior cannot be controlled; however, it must be noted that the performance of the building with real occupants is ultimately the relevant metric.