Classification of Thermal Comfort in Heterogeneous Space from a PMV Model Perspective
Sakurai, Kei
Xu, Feng
Sato, Yuki
Sakai, Yuka
Sabu, Shunsuke
Kanayama, Hiroaki
Satou, Daisuke
Kansha, Yasuki

How to Cite

Sakurai K., Xu F., Sato Y., Sakai Y., Sabu S., Kanayama H., Satou D., Kansha Y., 2023, Classification of Thermal Comfort in Heterogeneous Space from a PMV Model Perspective, Chemical Engineering Transactions, 103, 169-174.


Global warming is accelerating the need for air conditioner units in households, leading to an endless increase in the environmental burden. To mitigate this negative effect, the combined usage of sensors and air conditioner units is researched to assess the effectiveness in ensuring thermal comfort across a space. However, with comfortability being a complex index and the current sensors operating under the assumption of empty space, their application to real-life situations is left impractical. To bridge this gap in research, this paper examines the thermal environment of a heterogeneous space using the Predicted Mean Vote model. A mathematical sensitivity analysis was performed to identify the key parameters where air velocity showed the most significant influence, with the potential to fluctuate the PMV score by - 5 to - 40. Focusing on flow velocity, Particle Image Velocimetry was conducted using water as the medium, resulting in the space being divided into four zones. Through the ranking of each zone according to its influence on the PMV score, zones that are prone to fluctuations in thermal comfort are identified. Through the addition of sensors in these zones, the adjustment of the AC’s output can be facilitated to promote thermal comfo