Classification for Hyperthermal Environments Based on a Comprehensive Score Index

Working in hyperthermal environments can lead to heat-related illnesses. Evaluating and predicting high-temperature environments can effectively reduce heat risks and hazards. However, there is still a lack of corresponding high-temperature environment assessment methods and indicators in existing research. Moreover, traditional evaluation indicators and prediction methods have shortcomings in objectivity, accuracy, and practicality. To fill these gaps, a climate chamber was constructed to simulate different environmental conditions, and human labor experiments with 98 subjects were conducted. The ambient temperatures were set to 34 °C, 36 °C, 38 °C, and 40 °C, and the relative humidity was set to 60%, 70%, 80%, and 90%, respectively. During the experiments, the subjects’ oral temperatures, heart rates, skin temperatures, and subjective perceptions were recorded. Based on the obtained parameters of the subjects, two principal components with an explained variance of 92.131% were extracted by principal component analysis, and with the determination of weightings, a comprehensive evaluation index (F) was established and the F-score was calculated. According to the F-score, 16 different hyperthermal environments were classified into three categories through hierarchical clustering analysis and discriminant analysis, with the corresponding F-score ranges of 28.14–39.76, 39.17–45.21, and 44.13–52.39. An analysis was conducted on the value of physiological and subjective indicators to test the nature of classification.

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Publication Details

Journal
Buildings
Published
2025-08-14
DOI
https://doi.org/10.3390/buildings15162886
Primary Topic
Energy and Environment Impacts
Type
article
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Classification for Hyperthermal Environments Based on a Comprehensive Score Index

Buildings
Energy and Environment Impacts
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Classification for Hyperthermal Environments Based on a Comprehensive Score Index

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Abstract

Working in hyperthermal environments can lead to heat-related illnesses. Evaluating and predicting high-temperature environments can effectively reduce heat risks and hazards. However, there is still a lack of corresponding high-temperature environment assessment methods and indicators in existing research. Moreover, traditional evaluation indicators and prediction methods have shortcomings in objectivity, accuracy, and practicality. To fill these gaps, a climate chamber was constructed to simulate different environmental conditions, and human labor experiments with 98 subjects were conducted. The ambient temperatures were set to 34 °C, 36 °C, 38 °C, and 40 °C, and the relative humidity was set to 60%, 70%, 80%, and 90%, respectively. During the experiments, the subjects’ oral temperatures, heart rates, skin temperatures, and subjective perceptions were recorded. Based on the obtained parameters of the subjects, two principal components with an explained variance of 92.131% were extracted by principal component analysis, and with the determination of weightings, a comprehensive evaluation index (F) was established and the F-score was calculated. According to the F-score, 16 different hyperthermal environments were classified into three categories through hierarchical clustering analysis and discriminant analysis, with the corresponding F-score ranges of 28.14–39.76, 39.17–45.21, and 44.13–52.39. An analysis was conducted on the value of physiological and subjective indicators to test the nature of classification.

BuildingsVol. 15(16)
China Academy of Building Research (CN)
Climate action
Openalex Percentile: Top 59%
Energy and Environment Impacts
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