Convective heat loss from computational thermal manikin subject to outdoor wind environments

Urban residents are increasingly encouraged to go outside for recreational and relaxing purposes, which may improve personal health and reduce building energy consumption. Therefore, it is important to understand the heat transfer between human body and surrounding urban outdoor environments. This study aims to predict the convective heat loss from a human body subject to urban outdoor wind environments. Firstly, the effects of the wind velocity and turbulent conditions on the convective heat loss from human body are investigated through a computational thermal manikin model, which is validated against published experimental data. Subsequently, wind data from onsite measurements in the city of Sydney, Australia is used to predict human body's convective heat loss using numerically obtained empirical correlations. The present result shows that the convective heat loss of most body segments increases with increasing wind velocity and turbulent intensity and decreasing turbulence length scale. Empirical correlations for predicting the convective heat transfer coefficients as a function of the wind velocity, turbulent intensity and turbulence length scale are derived based on simple-geometry assumptions. It is found that, at a given wind velocity with the ranges of the turbulence conditions from the field measurements, the variations between the high and low values of the convective heat transfer coefficient can be up to 67%. The results of this study demonstrate the significance of capturing the turbulent wind conditions for accurately predicting heat loss for outdoor thermal comfort studies.

Automated summary

This study predicts the convective heat loss from a human body in urban outdoor wind environments by investigating the effects of wind velocity and turbulent conditions on the heat loss. The study shows that the convective heat loss of most body segments increases with increasing wind velocity and turbulent intensity, as well as decreasing turbulence length scale.