The current approach in building design focuses almost solely on increasing energy efficiency by improving system-oriented controls and behavior. However, occupant behavior also affects energy efficiency. To provide a more realistic modeling result, occupant behavior needs to be included in energy modeling.  more

Agent-based modeling and multi-agent modeling are relatively new methods that have been successful in answering many biological, social and behavioral questions such as analysis of the spread of epidemics, workforce management, and modeling consumer behavior in recent years. They share overlapping roots with gaming theory and its concepts, and adopting this type of modeling into engineering systems decision-making can create solutions to our daily problems in ways that were not possible before. more

Micro-electro-mechanical systems (MEMS) were invented in the second half of the past century and since then their use has been growing rapidly. The automobile industry was an early adopter, using MEMS sensors for automobile navigation, tire pressure control, and airbag deployment. As we start transitioning from today’s buildings and systems to future smart buildings, design engineers will have a wide variety of MEMS applications to choose from. more

In my earlier columns, I tried to explain the concept of uncertainty analysis and also draw the attention of the industry to the advantages of performing probabilistic energy modeling. One of the most valuable complementary tools to uncertainty analysis is sensitivity analysis. Terje Aven in his book, Foundation of Risk Analysis,1 gives the following definition for sensitivity analysis: “A sensitivity analysis is a study of how sensitive the risk is with respect to changes in input parameter of risk model.” more

Building an energy-efficient building often begins with an energy (cost) comparison between a design building and an imaginary baseline building as defined in ASHRAE/IES Standard 90.1, Appendix G. Even though this method has contributed to higher performance of buildings and systems, I believe we can do better than that. more

In my November column, I discussed the necessity of performing a probabilistic energy modeling process instead of a deterministic one for an ASHRAE/IES Standard 90.1, Appendix G, design building. To be able to run a probabilistic energy model, the first step is to develop a tolerance margin library for all the construction material that would be used in constructing a building and for its associated equipment. more

Uncertainty analysis is the process of changing simulation model input parameters in a small margin of possible occurrences and observing how simulation output can be affected (output probability distribution). That is the basic difference between a deterministic simulation and a probabilistic (uncertain) simulation. Uncertainty analysis is a strong tool for modelers and those who use modeling results to make well-informed decisions. more