Human responses in heat – comparison of the Predicted Heat Strain and the Fiala multi-node model for a case of intermittent work.
(2017) In Journal of Thermal Biology 70. p.45-52- Abstract
- Two mathematical models of human thermal regulation include the rational Predicted Heat Strain (PHS) and the thermophysiological model by Fiala. The approaches of the models are different, however, they both aim at providing predictions of the thermophysiological responses to thermal environments of an average person. The aim of this study was to compare and analyze predictions of the two models against experimental data. The analysis also includes a gender comparison. The experimental data comprised of ten participants (5 males, 5 females, average anthropometric values were used as input) conducting an intermittent protocol of rotating tasks (cycling, stacking, stepping and arm crank) of moderate metabolic activities (134-291 W/m2) with... (More)
- Two mathematical models of human thermal regulation include the rational Predicted Heat Strain (PHS) and the thermophysiological model by Fiala. The approaches of the models are different, however, they both aim at providing predictions of the thermophysiological responses to thermal environments of an average person. The aim of this study was to compare and analyze predictions of the two models against experimental data. The analysis also includes a gender comparison. The experimental data comprised of ten participants (5 males, 5 females, average anthropometric values were used as input) conducting an intermittent protocol of rotating tasks (cycling, stacking, stepping and arm crank) of moderate metabolic activities (134-291 W/m2) with breaks in-between in a controlled environmental condition (34°C, 60% RH). The validation consisted of the predictions’ comparison against experimental data from 2.5 hours of data of rectal temperature and mean skin temperature based on contact thermometry from four body locations. The PHS model over-predicted rectal temperatures during the first activity for males and the cooling effectiveness of sweat in the recovery periods, for both males and females. As a result, the PHS simulation underestimated the thermal strain in this context. The Fiala model accurately predicted the rectal temperature throughout the exposure. The fluctuation of the experimental mean skin temperature was not reflected in any of the models. However, the PHS simulation model showed better agreement than the Fiala model. As both models predicted responses more accurately for males than females, we suggest that in future development of the models it is important to take this result into account. The paper further discusses possible sources of the observed discrepancies and concludes with some suggestions for modifications. (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/96b5092c-8b8f-4353-8aff-936055c1708e
- author
- Lundgren Kownacki, Karin LU ; Martinez, Natividad ; Johansson, Bo ; Psikuta, Agnes ; Annaheim, Simon and Kuklane, Kalev LU
- organization
- publishing date
- 2017-12
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- Heat stress; Exposure limit prediction; Thermal physiological model; Work capacity; Sex difference; Activity variation
- in
- Journal of Thermal Biology
- volume
- 70
- pages
- 45 - 52
- publisher
- Elsevier
- external identifiers
-
- scopus:85019993136
- pmid:29074025
- wos:000414878900007
- ISSN
- 0306-4565
- DOI
- 10.1016/j.jtherbio.2017.05.006
- language
- English
- LU publication?
- yes
- id
- 96b5092c-8b8f-4353-8aff-936055c1708e
- date added to LUP
- 2017-05-29 14:43:41
- date last changed
- 2022-03-16 22:41:38
@article{96b5092c-8b8f-4353-8aff-936055c1708e,
abstract = {{Two mathematical models of human thermal regulation include the rational Predicted Heat Strain (PHS) and the thermophysiological model by Fiala. The approaches of the models are different, however, they both aim at providing predictions of the thermophysiological responses to thermal environments of an average person. The aim of this study was to compare and analyze predictions of the two models against experimental data. The analysis also includes a gender comparison. The experimental data comprised of ten participants (5 males, 5 females, average anthropometric values were used as input) conducting an intermittent protocol of rotating tasks (cycling, stacking, stepping and arm crank) of moderate metabolic activities (134-291 W/m2) with breaks in-between in a controlled environmental condition (34°C, 60% RH). The validation consisted of the predictions’ comparison against experimental data from 2.5 hours of data of rectal temperature and mean skin temperature based on contact thermometry from four body locations. The PHS model over-predicted rectal temperatures during the first activity for males and the cooling effectiveness of sweat in the recovery periods, for both males and females. As a result, the PHS simulation underestimated the thermal strain in this context. The Fiala model accurately predicted the rectal temperature throughout the exposure. The fluctuation of the experimental mean skin temperature was not reflected in any of the models. However, the PHS simulation model showed better agreement than the Fiala model. As both models predicted responses more accurately for males than females, we suggest that in future development of the models it is important to take this result into account. The paper further discusses possible sources of the observed discrepancies and concludes with some suggestions for modifications.}},
author = {{Lundgren Kownacki, Karin and Martinez, Natividad and Johansson, Bo and Psikuta, Agnes and Annaheim, Simon and Kuklane, Kalev}},
issn = {{0306-4565}},
keywords = {{Heat stress; Exposure limit prediction; Thermal physiological model; Work capacity; Sex difference; Activity variation}},
language = {{eng}},
pages = {{45--52}},
publisher = {{Elsevier}},
series = {{Journal of Thermal Biology}},
title = {{Human responses in heat – comparison of the Predicted Heat Strain and the Fiala multi-node model for a case of intermittent work.}},
url = {{http://dx.doi.org/10.1016/j.jtherbio.2017.05.006}},
doi = {{10.1016/j.jtherbio.2017.05.006}},
volume = {{70}},
year = {{2017}},
}