Influence of gender, age and BMI on human physiological response and thermal sensation for transient indoor environments with displacement ventilation

置换通风 瞬态(计算机编程) 热感觉 通风(建筑) 热舒适性 流离失所(心理学) 感觉 瞬态响应 热的 环境科学 机械 材料科学 工程类 心理学 计算机科学 物理 机械工程 气象学 电气工程 认知心理学 操作系统 心理治疗师
作者
Kai Rewitz,Dirk Müller
出处
期刊:Building and Environment [Elsevier BV]
卷期号:219: 109045-109045 被引量:16
标识
DOI:10.1016/j.buildenv.2022.109045
摘要

Thermophysiological comfort models allow the prediction of subjective thermal sensation for transient and inhomogeneous boundary conditions for a defined validation range. However, their validation ranges are relatively limited due to only low availability of high quality experimental measurement data. The present work aims to provide a high-resolution and well-documented data set to develop and validate scalable modeling approaches. Therefore, a 300 min test study with a total of 48 subjects is conducted in the climate test bench “Aachen Comfort Cube” (ACCu). We varied the mean temperature from 18 °C to 28 °C and back to 18 °C. We use the experiments to analyze differences with regard to the physiological parameters of gender, age and body-mass-index (BMI). For this purpose, core body and skin temperatures at 25 positions are recorded and related to local and global subjective evaluations. The results show different statistical differences in skin temperature and thermal sensation depending on the subgroup parameters and boundary conditions. These findings are mostly in agreement with general findings of existing literature. However, a significant difference in local skin temperature does not consequently lead to differences for local thermal sensation. Additionally, for nearly equal local skin temperatures significant difference in local thermal sensation can be found. BMI respectively body fat percentage seems so be the most influencing parameter on physiological responses due to lower thermal conductivity of fat tissue layer. These results highlight the need for separate scaling of physiological and psychological submodels regarding individualization approaches. The available data allow such an approach. • Gender, age and BMI are influencing physiological and psychological responses. • Body mass composition represented in simplified form by BMI has biggest impact. • Test data allow individualization approaches of thermophysiological comfort models. • Separate calibration of physiological and psychological submodels needed.
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