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Many commercial buildings today do not perform the way they were simulated. One potential reason for this discrepancy is that designers using building energy simulation programs do not fully understand the analysis methods that the programs are based on and may therefore have unreasonable expectations about the actual system performance or energy use. Therefore, the purpose of this study is to trace the origins of the most widely used building energy simulation programs and the analysis methods of thermal envelope loads used in the software to analyze high-performance commercial buildings in the United States. Such an analysis is important to better understand the capabilities of building energy simulation programs so they can be used more accurately to simulate the performance of an intended design. In this study, a new comprehensive genealogy chart was developed to support the explanations for the origins of the analysis methods of thermal envelope loads used in whole-building energy simulation programs. Two other works (Oh and Haberl 2015a, 2015b) explained the origins of the analysis methods of solar photovoltaic, solar thermal, passive solar, and daylighting simulation programs.

Thermal comfort, indoor air quality (IAQ), and energy use are closely related, even though these have different aspects with respect to building performance. We analyzed thermal comfort and IAQ using real-time multiple environmental data, which include indoor air temperature, relative humidity, carbon dioxide (CO2), and particulate matter (e.g., PM10 and PM2.5), as well as electricity use from an energy recovery ventilation (ERV) system for a childcare center. Thermal comfort frequency and time-series analyses were conducted in detail to thoroughly observe real-time thermal comfort and IAQ conditions with and without ERV operation, and to identify energy savings opportunities during occupied and unoccupied hours. The results show that the highest CO2 and PM10 concentrations were reduced by 51.4% and 29.5%, respectively, during the occupied hours when the ERV system was operating. However, it was also identified that comfort frequencies occurred during unoccupied hours and discomfort frequencies during occupied hours. By analyzing and communicating the three different types of real-time monitoring data, it is concluded that the ERV system should be controlled by considering not only IAQ (e.g., CO2 and PM2.5) but also thermal comfort and energy use to enhance indoor environmental quality and save energy based on real-time multiple monitoring data.

This paper presents improved methods to detect cracks and thermal leakage in building envelopes using unmanned aerial vehicles (UAV) (i.e., drones) with video camcorders and/or infrared cameras. Three widely used contour detectors of Sobel, Laplacian, and Canny algorithms were compared to find a better solution with low computational overhead. Furthermore, a scheme using frame-based location identification was developed to effectively utilize the existing approach by finding the current location of the drone-assisted image frame. The results showed a simplified drone-assisted scheme along with automation, higher accuracy, and better speed while using lower battery energy. Furthermore, this paper found that the cost-effective drone with the attached equipment generated accurate results without using an expensive drone. The new scheme of this paper will contribute to automated anomaly detection, energy auditing, and commissioning for sustainably built environments.