Evaluates heat and moisture transfer in sweat-soaked clothing, suggesting improved thermal comfort assessment.
Clothing serves as a critical medium for heat and moisture transfer between the human body and the environment, with variations in its thermal properties significantly influencing thermal equilibrium. Although several clothing models have been developed to quantify heat and mass transfer between the human body and its surroundings, the effect of liquid perspiration on heat and moisture transfer is often overlooked, limiting the applicability of such models in assessing thermal comfort. This study comprehensively evaluates the dynamics of heat and moisture transfer within the air gap between the human body and clothing system. The parameter of clothing wettedness was introduced to identify distinct heat and moisture transfer pathways in sweat-soaked clothing. Field measurements revealed the relationship between clothing moisture content and wettedness, resulting in a generalized empirical equation for this parameter. An observation platform was established to monitor skin temperature and micro-environmental characteristics of clothing under various environmental conditions, allowing quantitative analysis of the influence of different environmental variables on clothing moisture absorption and desorption rates. Based on experimental data, a clothing model was developed and validated, demonstrating robust computational accuracy under dynamic environmental conditions. Finally, the model was integrated with the JOS-3 model to simulate trends in human thermo-physiological parameters under dynamic clothing thermal properties. Compared to the original model, the proposed model more accurately captures variations in physiological parameters during human sweating. Overall, the developed clothing model can effectively simulate reversible changes in thermal insulation and evaporative resistance during perspiration, providing a reliable basis for the precise evaluation of human thermal comfort across diverse thermal environments.
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Zhao et al. (2026) studied this question.
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