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不同模型组合的整体热感觉和舒适预测:冬季的冷、热阶跃环境。

Overall thermal sensation and comfort prediction with different model combinations: Cold and hot step-change environments in winter.

机构信息

School of Environmental and Municipal Engineering, Qingdao University of Technology, No. 777 Jialingjiang Road, Huangdao District, Qingdao, 266520, Shandong province, China.

School of Environmental and Municipal Engineering, Qingdao University of Technology, No. 777 Jialingjiang Road, Huangdao District, Qingdao, 266520, Shandong province, China.

出版信息

J Therm Biol. 2023 Apr;113:103458. doi: 10.1016/j.jtherbio.2022.103458. Epub 2023 Jan 13.

Abstract

Currently, numerous thermal comfort models have been proposed; however, research on the combination of different models is lacking. This study aims to predict the overall thermal sensation (OTS*) and thermal comfort (OTC*) with different model combinations under hot and cold step changes. Three cold- and hot-shock processes are designed in the climate chamber. Accordingly, the skin temperature, thermal sensation, and thermal comfort votes of 16 participants are collected. The impacts of winter hot and cold step changes on subjective votes and skin temperatures are evaluated. Further, the OTS* and OTC* values are calculated, and their accuracy under different model combinations is analyzed. The results reveal that thermal sensation changes in human body exhibit distinct asymmetry under the cold and hot step-changes, except for the cycle of "15-30-15 °C" (I15). The parts farther from the core area become more asymmetrical after the step changes. The single models exhibit the highest accuracy in different model combinations. The combined form of a single model is recommended for thermal sensation or comfort prediction.

摘要

目前已经提出了许多热舒适模型;然而,不同模型的组合研究还很缺乏。本研究旨在预测不同模型组合在热冲击和冷冲击下的整体热感觉(OTS*)和热舒适(OTC*)。在气候室中设计了三个冷冲击和热冲击过程。相应地,收集了 16 名参与者的皮肤温度、热感觉和热舒适投票。评估了冬季热冲击和冷冲击对主观投票和皮肤温度的影响。此外,计算了 OTS和 OTC值,并分析了不同模型组合下的准确性。结果表明,人体的热感觉变化在冷冲击和热冲击下表现出明显的不对称性,除了“15-30-15°C”(I15)的循环。在冲击后,离核心区域越远的部位变得越不对称。在不同的模型组合中,单一模型的准确性最高。推荐使用单一模型的组合形式来预测热感觉或舒适感。

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