The Effects of the Dynamic Thermophysical Properties of Clothing and the Walking Speed Input Parameter on the Heat Strain of a Human Body Predicted by the PHS Model

Abstract

The prediction accuracy of the Predicted Heat Strain (PHS) model is affected by the correction approaches of static thermophysical properties of clothing considering the pumping effects of wind and body movement. In this study, a comparison of different correction algorithms for three types of clothing and their influence on the heat strain predicted by the PHS model was carried out with experimental data obtained from the literature. Results show that the dynamic insulation values calculated by ISO 9920 corrections are larger than those obtained by ISO 7933 when the static insulation values are higher than 0.4 clo, but when the static values are lower than 0.4 clo, it varies contrarily. The dynamic evaporative resistance values calculated with ISO 9920 equations are larger than those with ISO 7933. The prediction accuracy of the PHS model with ISO 9920 corrections and the addition of the walking speed input parameter can be improved for normal clothing (NC) in a hot environment and high clothing insulation. For specialized, insulating, cold weather clothing (SC), ISO 7933 corrections with an added walking speed input parameter to the PHS model have a good prediction precision.

The predicted heat strain model considering wet and dynamic thermal insulation for thermal protective clothing: Modification and validation analysis

“…10,11 A few studies have explored applying the PHS model in high thermal insulation clothing ensembles (I cl > 1.5 clo) in high-temperature environments. The results showed that the human body's core temperature wearing firefighters' protective clothing was overestimated by about 1.5 C in exposure to a temperature of 40 C. 12 To this end, the applicability of the correction methods of clothing dynamic thermal insulation in different clothing types has been explored, [13][14][15] including ISO 7933, ISO 9920, and the Lu model. 16 However, the predictive deviation in high insulation clothing ensembles still exceeds the acceptable range (0.2 C).…”