The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Computer prediction of human thermoregulatory and temperature responses to a wide range of environmental conditions
Open accessAbstract
Abstract A mathematical model for predicting human thermal and regulatory responses in cold, cool, neutral, warm, and hot environments has been developed and validated. The multi-segmental passive system, which models the dynamic heat transport within the body and the heat exchange between body parts and the environment, is discussed elsewhere. This paper is concerned with the development of the active system, which simulates the regulatory responses of shivering, sweating, and peripheral vasomotion of unacclimatised subjects. Following a comprehensive literature review, 26 independent experiments were selected that were designed to provoke each of these responses in different circumstances. Regression analysis revealed that skin and head core temperature affect regulatory responses in a non-linear fashion. A further signal, i.e. the rate of change of the mean skin temperature weighted by the skin temperature error signal, was identified as governing the dynamics of thermoregulatory processes in the cold. Verification and validation work was carried out using experimental data obtained from 90 exposures covering a range of steady and transient ambient temperatures between 5°C and 50°C and exercise intensities between 46 W/m2 and 600 W/m2. Good general agreement with measured data was obtained for regulatory responses, internal temperatures, and the mean and local skin temperatures of unacclimatised humans for the whole spectrum of climatic conditions and for different activity levels.
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Citations
Cites
Importance of skin temperature in the regulation of sweating.
Nadel, E. R., Bullard, R. W., & Stolwijk, J. A. (1971) · Journal of Applied Physiology · doi:10.1152/jappl.1971.31.1.80 · Cited by 545
Cited by
UTCI—Why another thermal index?
Jendritzky, G., de Dear, R., & Havenith, G. (2012) · International Journal of Biometeorology · doi:10.1007/s00484-011-0513-7 · Cited by 1,162
Blocken, B. (2015) · Building and Environment · doi:10.1016/j.buildenv.2015.02.015 · Cited by 1,163
Comparison of UTCI to selected thermal indices
Blazejczyk, K., Epstein, Y., Jendritzky, G., Staiger, H., & Tinz, B. (2012) · International Journal of Biometeorology · doi:10.1007/s00484-011-0453-2 · Cited by 1,129
UTCI-Fiala multi-node model of human heat transfer and temperature regulation
Fiala, D., Havenith, G., Bröde, P., Kampmann, B., & Jendritzky, G. (2012) · International Journal of Biometeorology · doi:10.1007/s00484-011-0424-7 · Cited by 994
Self-citationForty years of Fanger’s model of thermal comfort: comfort for all?
van Hoof, J. (2008) · Indoor Air · doi:10.1111/j.1600-0668.2007.00516.x · Cited by 733
Metadata
- Authors
- Fiala, D., Lomas, K. J., & Stohrer, M.
- Venue
- International Journal of Biometeorology
- Published
- 2001-09
- Volume
- 45
- Issue
- 3
- Pages
- 143-159
- ISSN
- 0020-7128 (ISSN-L)
- OpenAlex
- W2000396826
- Cited by
- 754
- References
- 1
- FWCI
- 1.47
- Type
- journal article
- Language
- en
- Open access
- green
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- Fiala, D., Lomas, K. J., & Stohrer, M. (2001). Computer prediction of human thermoregulatory and temperature responses to a wide range of environmental conditions. International Journal of Biometeorology. https://doi.org/10.1007/s004840100099
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.