Modelling and experimental study of thermo-physiological responses of human exercising in cold environments

服装 气流 均方误差 皮肤温度 环境科学 通风(建筑) 空气层 空气温度 自然通风 水分 模拟 气象学 大气科学 机械 材料科学 数学 热力学 图层(电子) 计算机科学 工程类 物理 统计 复合材料 生物医学工程 历史 考古
作者
Feiyu Chen,Ming Fu,Yayun Li,Shifei Shen,Xian Guo
出处
期刊:Journal of Thermal Biology [Elsevier]
卷期号:109: 103316-103316 被引量:6
标识
DOI:10.1016/j.jtherbio.2022.103316
摘要

A numerical human thermo-physiological model is developed with the consideration of characteristics of exercising people in cold environments. The developed model is characterized by: 1) the concept of net exercise efficiency which is used to correct the calculation of metabolic heat production by excluding mechanical energy; 2) the effects of low temperature on basal metabolic rate and basal blood flow rate; 3) the integration with a multi-layer clothing model to calculate the heat and moisture transfer through the clothing system, which takes into account the air gaps between the clothing layers to reflect the ventilation and air penetration effect from the ambient wind. Human subject experiment is conducted in a climate chamber to validate the proposed model. The human subject experiment is also carried out in a cold environment (-5 °C) combined with different air velocity conditions (still air, 2 m/s), taking into account the activities of different intensities (standing statically, 2 km/h walking and 7 km/h running). Thermo-physiological parameters including the core temperature, 8-point local skin temperatures and the clothing layer temperatures, are measured during the experiment. Comparison between the predicted and experimental results gives the root mean squared error (RMSE) of core temperature and mean skin temperature of 0.06-0.10 °C and 0.17-0.27 °C, respectively. RMSE values for local skin and clothing layer temperatures are no higher than 1.5 °C and most within 0.8 °C. The model is also validated with published data under various ambient temperature and activity intensity conditions. The proposed model is shown to be capable of predict the thermo-physiological responses of people exposed and exercising in cold environments.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
更新
大幅提高文件上传限制,最高150M (2024-4-1)

科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
刚刚
慕青应助心灵美的山蝶采纳,获得10
刚刚
cxfeeling发布了新的文献求助10
刚刚
lll完成签到,获得积分10
刚刚
1秒前
JIANYOUFU完成签到,获得积分10
1秒前
lalala发布了新的文献求助10
1秒前
巫马炎彬完成签到,获得积分0
2秒前
2秒前
2秒前
星星之火完成签到,获得积分10
2秒前
彼方完成签到 ,获得积分10
2秒前
南亭发布了新的文献求助30
2秒前
2秒前
jjjoey发布了新的文献求助20
2秒前
干净的铅笔应助游尘采纳,获得10
2秒前
3秒前
顾风华完成签到,获得积分10
3秒前
4秒前
鱼在哪儿发布了新的文献求助30
4秒前
tuomasi发布了新的文献求助10
4秒前
hh完成签到 ,获得积分10
4秒前
4秒前
富婆完成签到 ,获得积分20
5秒前
星辰大海应助123采纳,获得10
5秒前
碧蓝小海豚应助刘佳灏采纳,获得10
5秒前
5秒前
胡方发布了新的文献求助10
5秒前
彭于晏应助繁荣的立果采纳,获得10
5秒前
ZPJK完成签到,获得积分10
5秒前
zzz完成签到,获得积分10
6秒前
wwwstt发布了新的文献求助10
6秒前
Akim应助果粒红豆豆采纳,获得10
6秒前
6秒前
7秒前
7秒前
7秒前
lll发布了新的文献求助10
7秒前
木木完成签到 ,获得积分10
7秒前
Feng发布了新的文献求助10
7秒前
高分求助中
Impact of Mitophagy-Related Genes on the Diagnosis and Development of Esophageal Squamous Cell Carcinoma via Single-Cell RNA-seq Analysis and Machine Learning Algorithms 1600
Exploring Mitochondrial Autophagy Dysregulation in Osteosarcoma: Its Implications for Prognosis and Targeted Therapy 1500
LNG地下式貯槽指針(JGA指-107) 1000
QMS18Ed2 | process management. 2nd ed 600
LNG as a marine fuel—Safety and Operational Guidelines - Bunkering 560
Clinical Interviewing, 7th ed 400
Functional Syntax Handbook: Analyzing English at the Level of Form 400
热门求助领域 (近24小时)
化学 医学 材料科学 生物 工程类 有机化学 生物化学 物理 内科学 纳米技术 计算机科学 化学工程 复合材料 基因 遗传学 物理化学 催化作用 免疫学 细胞生物学 电极
热门帖子
关注 科研通微信公众号,转发送积分 2941494
求助须知:如何正确求助?哪些是违规求助? 2600401
关于积分的说明 7001949
捐赠科研通 2241676
什么是DOI,文献DOI怎么找? 1189879
版权声明 590236
科研通“疑难数据库(出版商)”最低求助积分说明 582537