Real-time measurement of building envelopes to improve U-value characterization
Abstract Approximately 40% of total US energy consumption in 2016 was attributed to commercial and residential buildings. In comparison with other building systems, energy is most heavily consumed by systems regulating thermal comfort. Thus, building energy consumption is strongly related to the thermal performance of building envelopes. Architects, engineers and owners have utilized energy modeling and simulations as a way to predict future energy consumption for new and existing buildings. Energy models are also used to evaluate the change in potential energy consumption when comparing multiple design options. Most building energy modeling software utilizes material properties databases for individual envelope components and calculates an assembly overall heat transfer coefficient, known as the U-value. For historic buildings the use of materials from existing databases may be inaccurate, since the actual assembly and materials may be unknown or may not have been previously tested. Low-cost non-destructive in-situ testing can be performed to determine actual U-values for existing building envelopes. Heat flux sensors, thermocouples and air temperature sensors can be used to measure real-time heat flow through building envelopes. These measurements can be used to calculate the transient U-value of the envelope assembly. Although most databases provide a static U-value for an assembly, the actual U-value of assemblies can vary over time in relation to indoor and outdoor temperatures. When measuring in-situ U-values, time averaging can be used to develop a baseline for energy modeling purposes. This paper presents research regarding the determination of in-situ U-values for two historic buildings using heat-flux sensors and time-averaging methods. The results of the study are compared with typical database U-values and show that there is a significant range and difference between the in-situ values and those that might be typically used in energy models. Energy simulations were performed for both the typical and in-situ cases to understand the difference and impact on predicted energy consumption.
Keywords: energy modeling, simulation, in-situ testing, heat flux, U-value