Predicting Dynamic Thermal Sensation (Dts) in Outdoor Settings

Abstract

Past outdoor thermal comfort research has mainly focused on steady-state exposure mainly because outdoor environments are highly dynamic. This study investigated dynamic thermal sensations through a series of field studies conducted in Sydney, Australia with 65 participants exposed to three different outdoor scenarios including both rapid changes in ambient environments and different activity levels. Two predictive approaches for thermal sensation were evaluated including using a) steady-state thermal indices PET, SET*, and UTCI, and b) dynamic thermal sensation (DTS) models from Fiala and Lai. Predicted thermal sensation results indicate that steady-state thermal indices can explain most of the variance in thermal sensation under outdoor environments if subjects’ activity levels are low. We further compare and improve DTS models by considering additional physiological variables and updated the coefficients derived from our field studies. Heat flux and the change rate of heat flux demonstrated strong ability to capture the thermal sensation change during high level activities and rapidly changing environments, respectively.  Compared to the traditional methods by mapping thermal indices onto the thermal sensation scale. The outcome of this research provides a method to capture more nuanced dynamic variability in thermal sensations as urban residents go about their lives in urban settings.

Keywords: Dynamic thermal sensation (DTS), Outdoor thermal indices, Gagge's two-node model, Outdoor thermal comfort