Thermal modelling of individual characteristics (Modellering van de individuele thermische reactie).
One of the major gaps in the prediction of heat stress response is the limited implementation of individual characteristics in prediction models. Without this individualization, the evaluation of the resultant average group response prediction necessitates the use of very conservative limit values f...
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| Format: | Default Report |
| Published: |
1997
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| Online Access: | https://hdl.handle.net/2134/25023 |
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| Summary: | One of the major gaps in the prediction of heat stress response is the limited implementation of individual characteristics in prediction models. Without this individualization, the evaluation of the resultant average group response prediction necessitates the use of very conservative limit values for body temperature increase. This is caused by the wide range of responses observed within a group. The present study aimed at the implementation of individual characteristics in a heat stress prediction model (THDYN), in order to investigate whether this would indeed result in a more precise prediction with less variance between predicted and observed responses. For this purpose, the relevant parameters related to anthropometric characteristics (body surface area A sub 0, body tissue conductance, body heat capacity), sweating and skin blood flow control (training and acclimation) were introduced in the model. The parameters were derived from literature. Next, data sets which were not used for the parameter estimation were used for a validation of the model changes. It was found that the individualized model indeed provided an improved prediction. The size of the improvement varied with the climate and the work type however. The best predictions for body heat storage were observed for fixed work loads in a warm humid and in a hot dry climate and for work loads relative to the individual maximum in a warm humid climate (Explained variance 27-53%). For relative work loads in a cool and in a hot dry climate the models predictive capacity for individuals was not significantly improved ( |
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