The secondary solar heat gain, defined as the heat flows from glazing to indoor environment through longwave radiation and convection, grows with the increasing of glazing absorption. With the rapid development and application of spectrally selective glazing, the secondary solar heat gain becomes the main way of glazing heat transfer and biggest proportion, and indicates it should not be simplified calculated conventionally. Therefore, a dynamic secondary solar heat gain model is developed with electrochromic glazing system in this study, taking into account with three key aspects, namely, optical model, heat transfer model, and outdoor radiation spectrum. Compared with the traditional K-Sc model, this new model is verified by on-site experimental measurements with dynamic outdoor spectrum and temperature. The verification results show that the root mean square errors of the interior and exterior glass surface temperature are 3.25 ℃ and 3.33 ℃, respectively, and the relative error is less than 10.37%. The root mean square error of the secondary heat gain is 13.15 W/m2, and the dynamic maximum relative error is only 13.2%. The simulated and measured results have a good agreement. In addition, the new model is further extended to reveal the variation characteristics of secondary solar heat gain under different application conditions (including orientations, locations, EC film thicknesses and weather conditions). In summary, based on the outdoor spectrum and window spectral characteristics, the new model can accurately calculate the increasing secondary solar heat gain in real time, caused by spectrally selective windows, and will provide a computational basis for the evaluation and development of spectrally selective glazing materials.
As regional drought conditions continue deteriorating around the world, residential water use has been brought into the built environment spotlight. Nevertheless, the understanding of water use behavior in residential buildings is still limited. This paper presents data analytics and results from monitoring data of daily water use (DWU) in 50 single-family homes in Texas, USA. The results show the typical frequency distribution curve of the DWU per household and indicate personal income, education level and energy use of appliances all have statistically significant effects on the DWU per capita. Analysis of the water-intensive use demonstrates the residents tend to use more water in post-vacation days. These results help generate awareness of water use behavior in homes. Ultimately, this research could support policy makers to establish a water use baseline and inform water conservation programs.