most citedA Probabilistic Framework for Predicting Spatiotemporal Intensity and Variability of Outdoor Thermal Comfort

10 citations

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physics.app-ph2025★ 10 cited

A Probabilistic Framework for Predicting Spatiotemporal Intensity and Variability of Outdoor Thermal Comfort

Shisheng Chen, Ruohan Xu, Nyuk Hien Wong +3

Thermal conditions in the urban canopy exhibit stochastic variability driven by varied radiative fluxes and turbulent wind fields, requiring probabilistic rather than deterministic…

physics.app-ph2025★ 4 cited

Quantifying Key Design Factors for Thermal Comfort in Underground Space Through Global Sensitivity Analysis and Machine Learning

Shisheng Chen, Nyuk Hien Wong, Chao Cen +6

This study identified the key design factors related to thermal comfort in naturally ventilated underground spaces under high temperature conditions (outdoor Tmax = 42.9 C) in Fuzh…