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作 者:刘明昊 李芃[1] 臧建彬[1] LIU Minghao;LI Peng;ZANG Jianbin(School of Mechanical and Energy Engineering,Tongji University,Shanghai 201804,China)
机构地区:[1]同济大学机械与能源工程学院,上海201804
出 处:《制冷技术》2023年第3期51-57,共7页Chinese Journal of Refrigeration Technology
摘 要:为了有效预测佩戴医用外科口罩的人体在地铁乘坐全过程这一复杂环境下的皮肤温度这一生理参数,基于FIALA和STOLWIJK模型,考虑佩戴口罩对面部传热以及脑部血流量、代谢产热的影响,对口罩热阻加以分析,并修正了脑部血流量、代谢产热的参数值,用Fortran汇编语言建立了佩戴医用外科口罩人体的热反应模型。同时,针对过渡季节,测试了地铁乘坐全过程下的人体各部位皮肤温度和环境参数,用以分析验证模型。验证结果表明人体各部位测试结果和模拟值趋势吻合得很好,且皮肤温度最大差值均小于1℃,面部佩戴口罩预测精度为85.7%,躯干预测精度为86.8%,手臂预测精度为70.8%,腿部预测精度为66.8%,越靠近心脏端预测精度越高。In order to effectively predict the physiological parameter of skin temperature of a person wearing a medical surgical mask in the complex environment of the whole subway riding,based on FIALA and STOLWIJK models,considering that wearing a mask affects heat transfer on the face,blood flow and metabolic heat generation in the brain,the thermal resistance of the mask is analyzed,and the parameter values of brain blood flow and metabolic heat production are corrected,a thermal response model of the human body wearing a medical surgical mask was established using Fortran assembly language.At the same time,for the transition season,the skin temperature,and environmental parameters of various parts of the human body during the entire subway riding were tested to analyze.The validation results show that the test results of various parts of the human body agree well with the simulated value trend,and the maximum difference in skin temperature is less than 1℃.The prediction accuracy of facial wearing mask is 85.7%,torso prediction accuracy is 86.8%,arm prediction accuracy is 70.8%,and leg prediction accuracy is 66.8%,and the closer to the heart end,the higher the prediction accuracy.
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