Nowadays, relevant data collected from hospital buildings remain insufficient because hospital buildings often have stricter environmental requirements resulting in more limited data access than other building types. Additionally, existing window-opening behavior models were mostly developed and validated using data measured from the experimental building itself. Hence, their accuracy is only assessed by the algorithm’s evaluation index, which limits the model’s applicability, given that it is not tested by the actual cases nor cross-verified with other buildings. Based on the aforementioned issues, this study analyzes the window-opening behavior of doctors and patients in spring in a maternity hospital in Beijing and develops behavioral models using logistic regression. The results show that the room often has opened windows in spring when the outdoor temperature exceeds 20 °C. Moreover, the ward windows’ use frequency is more than 10 times higher than those of doctors’ office. The window-opening behavior in wards is more susceptible to the influence of outdoor temperature, while in the doctors’ office, more attention is paid to indoor air quality. Finally, by embedding the logistic regression model of each room into the EnergyPlus software to simulate the CO2 concentration of the room, it was found that the model has better applicability than the fixed schedule model. However, by performing cross-validation with different building types, it was found that, due to the particularity of doctors’ offices, the models developed for other building types cannot accurately reproduce the window-opening behavior of doctors. Therefore, more data are still needed to better understand window usage in hospital buildings and support the future building performance simulations of hospital buildings.
Catalytic combustion can effectively and cleanly convert the chemical energy of fossil fuels into infrared radiation energy. However, there is little research on the use of this technology to cure powder coatings. Therefore, catalytic infrared heating equipment based on a Pt/Al2O3 noble metal catalyst was designed, constructed, and tested in this study. The optimal curing parameters for the catalytic infrared curing process for powder coatings were determined via experiments at 220 °C for 3 min and 230 °C for 2 min. As the curing temperature increased and the curing time increased, the mechanical properties of the coating were found to improve. However, the gloss of the coating was reduced and the color darkened. A one-dimensional heat transfer model was developed to investigate the heat transfer process for powder coatings. This study introduced an internal heat source for the first time, and the heat transfer process for polyester-based powder coatings with different substrate thicknesses was numerically simulated. The numerical simulations demonstrated that the efficiency of the heat transfer between the catalytic infrared gas supply and the coating surface was 0.4. When the substrate thickness was 1 mm, the coating was most rapidly cured at 230 °C. When the substrate thickness was ≥2 mm, the most rapid curing occurred at 220 °C.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.