A database of clothing overall and local insulation and prediction models for estimating ensembles’ insulation

Abstract

Clothing has a significant impact on the heat transfer between the human body and the environment, and clothing insulation is an important input parameter for many thermal comfort models. With the development of studies on non-uniform environment and human's local thermal comfort, the clothing local insulation is required in the multi-node human thermoregulation models and significantly affects the accuracy of simulation results. However, there lacks data on clothing local insulation values in standards. In this study, the local insulation of 57 typical garments and 62 ensembles with different layers (1–6 layers) were measured using a thermal manikin. The results show that the ranges of overall insulation for tested garments and ensembles were 0.01–0.56 clo and 0.27–2.17 clo, respectively. The local insulation values differed greatly from the overall insulation values, and varied greatly between different body parts. Further, the linear regression was performed between the ensembles' local insulation at different body parts and the sum of the garments' local insulation. Based on the prediction equations of local insulation, a new method for estimating the overall insulation of ensembles was proposed. Compared with the tradition method using the linear regression equations of overall insulation, the new method reduced the mean relative error from 12.6%–9.1% to 3.4%. This study provided basic data and prediction equations of local insulation for future researches of clothing insulation and local thermal comfort.