Thermal comfort evaluation with a passive sensor manikin under radiant exposures in kitchen

Abstract

In residential kitchens, the high temperatures, humidity, and substantial radiant heat exposure from flame and stove are prevalent, therefore thermal comfort issues need to be considered seriously. Local air-conditioning (AC) can alleviate discomfort. However, current thermal comfort models lack consideration of the effects of local flame radiation exposure and local AC on human thermal responses. This study conducted experiments to investigate human thermal comfort under conditions with and without an AC system. Tests were performed using a passive sensor manikin to accurately describe the local boundary parameters around the occupant, with local air temperature, radiant flux, relative humidity, and air velocity measurements. The results showed that flame and gas stove generated radiant heat flux density at the right hand up to 235 W/m2. The chest and abdomen were also significantly affected, with radiant intensities exceeding 132 and 158 W/m2, respectively. A 16-segment human model was developed, adding the local radiant heat flux as an input parameter. A Python-based visualization tool, KTCET, was developed. KTCET integrates the thermal physiology model and thermal comfort model. The accuracy of KTCET was validated by comparing prediction results with experimental data. It demonstrated good agreement between the predictions and experimental values, indicating that KTCET effectively captured variation trends across different kitchen scenarios. KTCET was used to evaluate local AC airflow strategies and optimal operating parameters to improve kitchen thermal comfort. These insights can provide a scientific basis for the intelligent and customized design of residential kitchens.