a year ago

Improvement and validation of the Tanabe model to simulate human thermal behaviors in hot environments at high altitudes

Exposure to hypobaric and hyperthermic environments can easily induce heat stress and affect operational efficiency. Thermal manikins represent advanced instruments for simulating human thermal behaviors in complex ambient conditions. However, currently, no thermal manikins are coupled with a human thermoregulatory model adapted for high-altitude environments. This study aimed to develop the traditional Tanabe model by incorporating air pressure into the calculation of the convective and evaporative heat transfer coefficients, therefore local skin temperature and thermal sensation at high altitudes could be predicted. To validate the model, these predicted variables were also measured in human thermal physiology experiments at the altitude of 0 m (101.3 kPa) and 4000 m (56.04 kPa) with an ambient temperature of 35 °C. The results demonstrated that local and weighted average skin temperatures were consistent between simulation and experimental results. The maximum deviation between experiments and simulation did not exceed 0.7 °C at segments except hand and foot, and 2.5 °C at each segment, at the altitude of 0 m and 4000 m respectively. The R2 values of Gaussian distribution and linear regression results concerning the experimental and simulation weighted average skin temperature and the PMV score at the altitudes of 0 m and 4000 m were 0.966, 0.975, 0.857, and 0.851. These findings suggest that differences in skin temperature and thermal sensation at different altitudes are influenced by variations in evaporation and dry heat exchanges. The improved Tanabe model in this study was validated and could be further utilized in investigating heat transfer processes and coefficients between the skin surface and the environment and developing control algorithms for thermal manikins.

Publisher URL: https://www.sciencedirect.com/science/article/pii/S1290072923003836

DOI: 14.20706.fb4829c5-e962-4cf2-9638-c7e8b1d8abc9.1688056733

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