A data-driven model on human thermophysiological and psychological responses under dynamic solar radiation
Yuchen Ji, Jusheng Song, Pengyuan Shen
2024
Building and Environment

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Summary
This study investigates human thermophysiological responses to dynamic solar radiation through field experiments and evaluates PET/UTCI indicators. A GA-optimized RNN model effectively predicts skin temperature and thermal sensation, revealing significant differences between dynamic and steady-state radiation impacts on comfort assessment.
Abstract
Excessive solar radiation can also cause thermophysiological and psychological discomfort in the human body. In real-world environments, solar radiation is highly variable. Moreover, the amount of solar radiation exposure that people receive due to their outdoor activities can have large fluctuation. The physiological and psychological responses of the human body under this dynamic solar radiation exposure are quite different from those under steady-state solar radiation exposure. Therefore, this paper studies the physiological and psychological responses of the human body under the condition of dynamic solar radiation through the method of field experimental research and explores the applicability of the existing indicators of PET and UTCI in the dynamic radiation environment. A novel recurrent neural network model was used to predict skin temperatures and thermal sensations, in which genetic algorithm was applied to tune hyper-parameters.
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LSTM diagram.
Publication Details
Journal
Building and Environment
Publication Year
2024
Authors
Yuchen Ji, Jusheng Song, Pengyuan Shen
Categories
Synergizing comfort and energy efficiency in the built environment