Prediction Model of Human Thermal Sensation Under Low-Air-Pressure Environment

Abstract

Passengers in aircraft cabins experience a low-air-pressure environment in most time of the flying period. So the influence of low air pressure on passengers’ comfort needs further research. The most commonly used model to predict human comfort is predicted mean vote (PMV) model. But PMV is designed for standard atmospheric environment, not for low-pressure environment. Researchers have confirmed that under low-pressure environment, human body heat loss through convection will decrease while through evaporation will increase. Thus, PMV model is not suitable for prediction under low-pressure environment and needed to be revised. The main purpose of this study was to investigate human body heat loss under low-pressure environment through both theoretical derivation and experimental validation, thus the model to predict human thermal comfort under low-air-pressure environment could be promoted. The heat loss was divided into four parts: convection heat loss, skin evaporation heat loss, radiation heat loss, and respiration heat loss. From theoretical derivation, following conclusion could be obtained. Radiation heat loss is more related to temperature, and the influence of air pressure is not significant. The convection heat loss will decrease and skin evaporation heat loss will increase under low pressure environment. Heat loss through respiration increases under low-pressure environment. The total heat loss will increase under low-pressure environment. Experimental validation was conducted with six experiment conditions: 22 and 27 °C (1.0/0.9/0.8 atm). Thirty subjects were recruited, and thermal sensation was significantly lower under low-pressure environment than standard pressure environment. Linear regression was analyzed between the value of thermal sensation vote and human thermal storage rate. Instead of the value PMV model predicted which was significantly higher than thermal sensation vote, the new model developed was more effective in predicting human thermal comfort under low-pressure environment.