In this blog, the Human Thermal Extension of TAITherm™ is used to explore a method of adapting the Berkeley Comfort Model (BCM) to predict the thermal sensation and comfort of East Asian populations. TAITherm™ is a state-of-the-art 3D thermal simulation software that, combined with the Human Thermal Extension, provides detailed transient analysis of the thermal response of the human body. It has been shown that East Asians, as the general population group, tend to prefer warmer environments. Still, there have not been any physiology-based comfort models specifically designed to model this difference. The BCM, utilized by the Human Thermal Extension, can predict local and overall thermal sensation and comfort based on the physiological state obtained from TAITherm’s high-resolution human thermal model. The BCM was adapted to model East Asian populations by modification of the temperature “setpoints” corresponding to the optimal thermal comfort state. Using the Human Thermal Extension of TAITherm™, the comfort of East Asian populations can be modeled with significantly improved accuracy, providing a reliable tool for future research and applications.
Methods
The BCM used in this study relies on physiological state information, i.e., transient core and skin temperatures, obtained from a high-resolution human thermal model as input [4]. As part of any study incorporating the BCM, up-front model “calibration” is needed to derive the local skin temperature “setpoints” corresponding to the optimal thermal comfort state that can be reached with the clothing insulation and activity level under consideration in the scenario of interest. Model calibration is typically accomplished by relying on the environment-based PMV model to identify ambient conditions that will produce a neutral sensation in steady-state. It follows that we should be able to enhance the model calibration process to allow the user to target a thermal state corresponding to any desired thermal preference (e.g., “cool” or “slightly warm”) rather than just its default, “neutral” setting. To test this hypothesis, model predictions with adjusted setpoints corresponding to warmer thermal preferences were compared to a series of human subject tests by Ozeki et al. involving a group of 8 Japanese males [5]. Two different sets of adjusted setpoints were considered, one set corresponding to a “slightly warm” (1.0) thermal preference and the other corresponding to a “warm” (2.0) thermal preference, according to the ASHRAE 7-point scale. The default, “neutral” (0.0), thermal preference was also run as a control. The human subject test prescribed that participants be seated in a “neutral” antechamber (24-25 °C) for 40 minutes, followed by a transition to a climate-controlled chamber set to varying levels of “cool” to “warm” ambient temperatures (20, 22.5, 27.5, and 30 °C) for 60 minutes, followed by a return to the “neutral room” for 40 minutes. Two levels of clothing insulation were considered in the study, 0.37 and 1.10 CLO. Mean skin temperature was derived from measured local skin temperatures, and overall thermal sensation and thermal comfort were reported at periodic intervals throughout the exposure on 7-point scales.
Results and discussion
The accuracy of each of the three variants of the model was assessed quantitatively by comparing the Root-Mean-Square-Deviation (RMSD) of the transient model predictions to the human subject test data. The study results, which are segregated by level of clothing insulation, are provided in Figure 1. The overall thermal sensation was best represented (i.e., had the lowest RMSD) when using the default setpoints corresponding to thermal neutrality. In contrast, overall thermal comfort was best expressed using setpoints corresponding to a “warm” thermal preference. This further supports that, despite East Asians preferring warmer thermal environments, there are little to no significant differences between East Asian and European thermal sensations [6].
The mean skin temperatures obtained within the warmer calibration environments, when compared to the default, “neutral” calibration, were approximately 0.5 °C higher for the “slightly warm” thermal preference and approximately one °C higher for the “warm” thermal preference. Independent of clothing insulation, these values were bound and consistent with the mean skin temperature delta (0.8 °C) observed in another study of Japanese individuals in an environment aligned with their thermal comfort preference [1].
Conclusion
By targeting a warmer thermal environment within the initial model calibration of the BCM through utilizing the Human Thermal Extension of TAITherm™, the thermal perception of East Asian populations was more accurately modeled. It was revealed that skin temperature setpoints corresponding to a “warm” calibration environment produced the best agreement of overall thermal comfort with the experimental data. However, the best agreement with overall thermal sensation was more accurately represented when the BCM was calibrated targeting thermal neutrality. This work can be expanded to more accurately predict the thermal comfort of more population groups with thermal perceptions different than Westerners/Europeans.
References
- Havenith G, Griggs K, Qiu Y, Doreman L, Kulasekaran V, Hodder S (2020) “Higher comfort temperature preferences for anthropometrically matched Chinese and Japanese versus white-western-middle-European individuals using a personal comfort/cooling system,” Building and Environment 183, 107162.
- Hepokoski M, Curran A, and Schwenn T, (2013) "A Comparison of Physiology-Based Metrics to Environment-Based Metrics for Evaluating Thermal Comfort," SAE Technical Paper 2013-01-0844.
- Hepokoski M, Curran A, Gullman S, and Jacobsson D, (2017) "Coupling a Passive Sensor Manikin with a Human Thermal Comfort Model to Predict Human Perception in Transient and Asymmetric Environments," SAE Int. J. Passeng. Cars - Mech. Syst. 10(1):135-140.
- Hepokoski M, Gibbs S and Curran A, (2016) “A new anatomical and thermophysiological description of a 50th percentile adult western male,” Digital Human Modeling Symposium, Montreal.
- Ozeki Y, Nakamura S, Ogata M, Miyajima H, Suzuki M, Tanabe S., “Predicting Local Thermal Sensation by Using Thermoregulation Model”, Transactions of AIJ. Journal of Environmental Engineering, Vol. 81 Issue 727, 2016.
- Lawes M, Havenith G, Hodder S, (2019) “The influence of ethnicity on thermal sensation responses in British and Chinese Individuals” Proceedings of the 18th International Conference on Environmental Ergonomics, Amsterdam, The Netherlands.
If you want to learn more about the Human Thermal Extension and TAITherm, please request a live demo of our software.
Visit our website at suppport.thermoanalytics.com for
- FAQs
- Webinars
- Tutorials
Get help from our technical support team:
