4.5 Article

Can the PHS model (ISO7933) predict reasonable thermophysiological responses while wearing protective clothing in hot environments?

Journal

PHYSIOLOGICAL MEASUREMENT
Volume 32, Issue 2, Pages 239-249

Publisher

IOP PUBLISHING LTD
DOI: 10.1088/0967-3334/32/2/007

Keywords

PHS model; heat stress; thermoregulatory modeling; protective clothing; hot environment

Funding

  1. VINNOVA (Swedish Governmental Agency for Innovation Systems) RD
  2. Taiga AB in Varberg, Sweden

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In this paper, the prediction accuracy of the PHS (predicted heat strain) model on human physiological responses while wearing protective clothing ensembles was examined. Six human subjects (aged 29 +/- 3 years) underwent three experimental trials in three different protective garments (clothing thermal insulation I-cl ranges from 0.63 to 2.01 clo) in two hot environments (40 degrees C, relative humidities: 30% and 45%). The observed and predicted mean skin temperature, core body temperature and sweat rate were presented and statistically compared. A significant difference was found in the metabolic rate between FIRE (firefighting clothing) and HV (high visibility clothing) or MIL (military clothing) (p < 0.001). Also, the development of heart rate demonstrated the significant effects of the exposure time and clothing ensembles. In addition, the predicted evaporation rate during HV, MIL and FIRE was much lower than the experimental values. Hence, the current PHS model is not applicable for protective clothing with intrinsic thermal insulations above 1.0 clo. The results showed that the PHS model generated unreliable predictions on body core temperature when human subjects wore thick protective clothing such as firefighting clothing (I-cl > 1.0 clo). The predicted mean skin temperatures in three clothing ensembles HV, MIL and FIRE were also outside the expected limits. Thus, there is a need for further extension for the clothing insulation validation range of the PHS model. It is recommended that the PHS model should be amended and validated by individual algorithms, physical or physiological parameters, and further subject studies.

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