Integration of computer-simulated persons with multi-node thermoregulation model that considers the effect of clothing for skin surface temperature distribution analysis

There is a growing demand for more advanced and diverse computer-simulated persons (CSPs) to accurately evaluate the indoor environmental quality and analyze the human body interactions with environmental factors. This study aimed to develop a CSP targeting the ANDI thermal manikin, which regulates skin temperature and thermal functions through a multi-node thermoregulation model, that is, the development of a digital twin for the ANDI thermal manikin. Additionally, to ensure the prediction reliability of the numerical thermoregulation model applied to the CSP using computational fluid dynamics (CFD) analysis, the CFD results were compared with those from the chamber experiment using an ANDI thermal manikin. We conducted integrated analyses of the CSP using the Fiala thermoregulation model to calculate the metabolic heat production, at transfer between different layers and sections, and skin surface temperature. The CFD analysis was performed using the CSP under the same environmental conditions as those used in the experiment. The CSP analysis results reproduced the experimental results obtained using the thermal manikin in the thermal comfort evaluation with acceptable accuracy, and the root mean square deviation of the predicted mean skin temperature was approximately 0.195. Furthermore, the importance of detailed clothing geometry was highlighted by confirming that the thickness of the ventilation layer between the skin and clothing has a significant effect on the thermal performance. The comprehensive prediction method for indoor environments based on the advanced CSP developed in this study can contribute to human-centered indoor environmental planning through parametric analyses under various environmental scenarios. •A digital twin of thermal manikin with thermoregulation model was developed.•The clothing model was created using a precision 3D scanner.•Thermal prediction of digital twin is validated by comparison with experiment data.•The average RMSD of the predicted mean skin temperatures was 0.195 °C.