Evaluation of four models for predicting thermal sensation in Chinese residential kitchen

Abstract

Thermal environment in residential kitchen in China is transient and non-uniform and with strong radiation asymmetry from gas stove. Due to the complexity of kitchen thermal environment, it is not sure if previous thermal comfort models can accurately predict the thermal comfort in residential kitchens. In order to evaluate if existing thermal comfort models can be applied for Chinese kitchens, this investigation conducted human subject tests for 20 cooks when preparing dishes in a kitchen. The study measured skin temperatures of the cooks and environmental parameters and used questionnaires to obtain their thermal sensation votes at the same time. The actual thermal sensation votes were compared with the predicted ones by four thermal comfort models: predicted mean vote (PMV) model, dynamic thermal sensation (DTS) model, the University of California at Berkeley (UCB) model, and the transient outdoor thermal comfort model from Lai et al. The results showed that all the models could predict the trend of the thermal sensations but with errors. The PMV model overpredicted the thermal sensations. The UCB and Lai's models showed a slower change in thermal sensation votes (TSV) after turning on the stove. The DTS model was more accurate than the others in predicting the mean thermal sensation, but with a large variation in predicting individual thermal sensation votes. A better thermal comfort model should be developed for Chinese residential kitchens.