posted on 2010-11-09, 10:28authored byRoger Haslam
Influential models, capable of predicting human responses to
hot and cold environments and potentially suitable for use
in practical applications, have been identified and
implemented in usable forms onto computers. Six models have
been evaluated: the Gagge and Nishi 2-node model of human
thermoregulation, the Stolwijk and Hardy 25-node model of
human thermoregulation, the Givoni and Goldman model of
rectal temperature response, the ISO/DIS 7933 analytical
determination and interpretation of thermal stress using
calculation of required sweat rate model, the Ringuest
25-node model of human thermoregulation, and the Wissler
225-node model of human thermoregulation. A preliminary
evaluation enabled the Ringuest and Wissler models to be
eliminated from further investigation. In the case of the
Ringuest model this was because of its poor predictions, and
for the Wissler model because of practical difficulties with
its implementation and use. The remaining models were
modified to quantify the insulative effects of clothing by
the method considered to be most appropriate, given the
current state of knowledge. The modified versions of the
models were evaluated by comparing their predictions with
human data published previously in the literature.
Experimental data were available for a wide range of
environmental conditions, with air temperatures ranging from
-10 to 50 °C, and with different levels of air movement,
humidity, work and clothing. Data for a total of 590
subject exposures were used. The experimental data were
grouped into environment categories to enable effects such
as the influence of wind or clothing, on the accuracy of the
models' predictions to be examined. This categorization
also enables advice to be given as to which model is likely
to provide the most accurate predictions for a particular
combination of environmental conditions. For the majority
of environment categories, for which evaluation data were
available, at least one of the models was able to predict to
an accuracy comparable with the degree of variation that
occurred within the data from the human subjects. It may be
concluded from the evaluation that it is possible to
accurately predict deep body and mean skin temperature
responses to cool, neutral, warm and hot environmental
conditions. The models' predictions of deep body
temperature in the cold are poor. Overall, the 25-node
model probably provided the most accurate predictions. The
2-node model was often accurate, but could be poor for
exercise conditions. The rectal temperature model usually
overestimated deep body temperature, except for very hot or
heavy exercise conditions, where its predictions were
reasonable. The ISO model's allowable exposure times were
often acceptable, but would not have protected subjects for
some exercise conditions.
A Doctoral Thesis. Submitted in partial fulfilment of the requirements for the award of Doctor of Philosophy of Loughborough University.
Please note that Appendix F has been removed from volume 2 due to copyright reasons.