Skin Heat Transfer and Thermal Sensation Coupling Model under Steady Stimulation
Thermal sensation prediction models can help to evaluate complex thermal environments and guide the environment conditioning strategy. However, most existing models are established basing on the thermal status of the entire human body or local body parts, failing to reflect thermal sensation generat...
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| Format: | Article |
| Language: | English |
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MDPI AG
2024-02-01
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| Series: | Buildings |
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| Online Access: | https://www.mdpi.com/2075-5309/14/2/547 |
| _version_ | 1827343918279163904 |
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| author | Yijia Zhou Hang Yu Maohui Luo Xiang Zhou |
| author_facet | Yijia Zhou Hang Yu Maohui Luo Xiang Zhou |
| author_sort | Yijia Zhou |
| collection | DOAJ |
| description | Thermal sensation prediction models can help to evaluate complex thermal environments and guide the environment conditioning strategy. However, most existing models are established basing on the thermal status of the entire human body or local body parts, failing to reflect thermal sensation generating mechanism or micro-scale (centimeter-scale) thermal sensation. This study put forward a new thermal sensation predicting approach by coupling the skin heat transfer and the thermoreceptor impulse signals. The micro-scale thermal sensitivity data under steady stimuli were applied to bridging the objective heat transfer model and the subjective sensation model. The model contains a one-dimensional skin heat transfer equation and three sensation-generating equations: the thermoreceptor impulse equation, the psychosensory intensity equation, and the thermal sensation equation. The dimension of the skin heat transfer equation was determined through a skin temperature diffusion experiment, and the coefficients of the static/dynamic impulse in the thermoreceptor impulse equation and the thermal sensation equation were obtained through polynomial fitting using thermal sensitivity data. The validated mean absolute percentage error (MAPE) was 0.08 and 0.1 under cooling and heating stimuli, respectively. This new model can predict thermal sensation on the centimeter scale and be applied under different boundary conditions. In the future, the new model can be further developed by testing dynamic stimuli and other boundary conditions so that it can be applied to more complex thermal exposures. |
| first_indexed | 2024-03-07T22:38:25Z |
| format | Article |
| id | doaj.art-2f49e59464a54d47bb9ee58dd706074c |
| institution | Directory Open Access Journal |
| issn | 2075-5309 |
| language | English |
| last_indexed | 2024-03-07T22:38:25Z |
| publishDate | 2024-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Buildings |
| spelling | doaj.art-2f49e59464a54d47bb9ee58dd706074c2024-02-23T15:10:33ZengMDPI AGBuildings2075-53092024-02-0114254710.3390/buildings14020547Skin Heat Transfer and Thermal Sensation Coupling Model under Steady StimulationYijia Zhou0Hang Yu1Maohui Luo2Xiang Zhou3School of Mechanical Engineering, Tongji University, Shanghai 201804, ChinaSchool of Mechanical Engineering, Tongji University, Shanghai 201804, ChinaSchool of Mechanical Engineering, Tongji University, Shanghai 201804, ChinaSchool of Mechanical Engineering, Tongji University, Shanghai 201804, ChinaThermal sensation prediction models can help to evaluate complex thermal environments and guide the environment conditioning strategy. However, most existing models are established basing on the thermal status of the entire human body or local body parts, failing to reflect thermal sensation generating mechanism or micro-scale (centimeter-scale) thermal sensation. This study put forward a new thermal sensation predicting approach by coupling the skin heat transfer and the thermoreceptor impulse signals. The micro-scale thermal sensitivity data under steady stimuli were applied to bridging the objective heat transfer model and the subjective sensation model. The model contains a one-dimensional skin heat transfer equation and three sensation-generating equations: the thermoreceptor impulse equation, the psychosensory intensity equation, and the thermal sensation equation. The dimension of the skin heat transfer equation was determined through a skin temperature diffusion experiment, and the coefficients of the static/dynamic impulse in the thermoreceptor impulse equation and the thermal sensation equation were obtained through polynomial fitting using thermal sensitivity data. The validated mean absolute percentage error (MAPE) was 0.08 and 0.1 under cooling and heating stimuli, respectively. This new model can predict thermal sensation on the centimeter scale and be applied under different boundary conditions. In the future, the new model can be further developed by testing dynamic stimuli and other boundary conditions so that it can be applied to more complex thermal exposures.https://www.mdpi.com/2075-5309/14/2/547thermal sensitivitythermal sensationskin heat transferthermoreceptor |
| spellingShingle | Yijia Zhou Hang Yu Maohui Luo Xiang Zhou Skin Heat Transfer and Thermal Sensation Coupling Model under Steady Stimulation Buildings thermal sensitivity thermal sensation skin heat transfer thermoreceptor |
| title | Skin Heat Transfer and Thermal Sensation Coupling Model under Steady Stimulation |
| title_full | Skin Heat Transfer and Thermal Sensation Coupling Model under Steady Stimulation |
| title_fullStr | Skin Heat Transfer and Thermal Sensation Coupling Model under Steady Stimulation |
| title_full_unstemmed | Skin Heat Transfer and Thermal Sensation Coupling Model under Steady Stimulation |
| title_short | Skin Heat Transfer and Thermal Sensation Coupling Model under Steady Stimulation |
| title_sort | skin heat transfer and thermal sensation coupling model under steady stimulation |
| topic | thermal sensitivity thermal sensation skin heat transfer thermoreceptor |
| url | https://www.mdpi.com/2075-5309/14/2/547 |
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