A computational fluid dynamics-based conjugate heat transfer coupling between airflow and human thermoregulation

Accurate modeling of the human body is essential in indoor computational fluid dynamics (CFD) studies, as it strongly influences airflow and heat transfer patterns. This study presents a coupled CFD–human thermoregulation model (HTM) framework based on conjugate heat transfer in OpenFOAM, integrating Fiala's multi-segment HTM directly into the CFD solver. Validation against experimental data shows that the framework predicts segmental skin temperatures with good accuracy. The method is further applied to a Boeing 737 cabin, where it captures airflow, temperature distributions, and thermal comfort indices. Compared with the conventional approach that assumes a fixed and uniform skin temperature, the coupled framework reveals local predicted mean vote (PMV) deviations of up to 0.4, highlighting the importance of dynamic human response in non-uniform environments. Overall, the framework provides a practical tool for reliable thermal comfort prediction and supports the design of heating, ventilation, and air conditioning systems in complex indoor settings.