Thermal sensation: a mathematical model based on neurophysiology

Authors

  • B. R. M. Kingma,

    1. Department of Human Biology, NUTRIM School for Nutrition, Toxicology and Metabolism of Maastricht University Medical Center+, Maastricht, The Netherlands
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  • L. Schellen,

    1. Department of Architecture, Building and Planning, Unit Building Physics and Systems, Eindhoven University of Technology, Eindhoven, The Netherlands
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  • A. J. H. Frijns,

    1. Department of Mechanical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands
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  • W. D. van Marken Lichtenbelt

    1. Department of Human Biology, NUTRIM School for Nutrition, Toxicology and Metabolism of Maastricht University Medical Center+, Maastricht, The Netherlands
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B. Kingma
Department of Human Biology
Maastricht University
Universiteitssingel 50, PO Box 616, NL-6200 MD Maastricht, The Netherlands
Tel.: +31 (0)43 388 42 60
Fax: +31 (0)43 367 09 76
e-mail: b.kingma@maastrichtuniversity.nl

Abstract

Abstract

Thermal sensation has a large influence on thermal comfort, which is an important parameter for building performance. Understanding of thermal sensation may benefit from incorporating the physiology of thermal reception. The main issue is that humans do not sense temperature directly; the information is coded into neural discharge rates. This manuscript describes the development of a mathematical model of thermal sensation based on the neurophysiology of thermal reception. Experimental data from two independent studies were used to develop and validate the model. In both studies, skin and core temperature were measured. Thermal sensation votes were asked on the seven-point ASHRAE thermal sensation scale. For the development dataset, young adult males (= 12, 0.04Clo) were exposed to transient conditions; Tair 30-20-35-30°C. For validation, young adult males (= 8, 1.0Clo) were exposed to transient conditions; Tair: 17-25-17°C. The neurophysiological model significantly predicted thermal sensation for the development dataset (r2 = 0.89, < 0.001). Only information from warm-sensitive skin and core thermoreceptors was required. Validation revealed that the model predicted thermal sensation within acceptable range (root mean squared residual = 0.38). The neurophysiological model captured the dynamics of thermal sensation. Therefore, the neurophysiological model of thermal sensation can be of great value in the design of high-performance buildings.

Practical Implications

The presented method, based on neurophysiology, can be highly beneficial for predicting thermal sensation under complex environments with respect to transient environments.

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