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 human thermoregulation model has been adapted for predicting the thermal response of Typical Older Persons. The model known as the Older Persons Model predicts the core body temperature and regulatory responses of the older people in environmental exposures of cold, warm and hot. The model was developed by modifying an existing dynamic human thermoregulation model using anthropometric and thermo-physical properties of older people. The Model defines the body as two interrelating systems of the body structure (passive system) and the control system of the central nervous system (active system). The Older person's passive system of the model was developed by meticulously extracting relevant experimental data from selected published research works relating to anthropometric and thermo-physical properties of older people. The resultant body structure (passive system) is a multi-segmented representation of a Typical Older Person. The active system (central nervous system) was developed by the application of a novel optimization method based on the working principles of Genetic Algorithms. The use of Genetic Algorithm enables the complex characteristics of the central nervous system of the older persons to be well represented and evaluated based on available data. Active system control signal coefficients for sweating, shivering, vasodilation and vasoconstriction were explicitly derived based on experimental data sourced from literature. The Older Persons Model has been validated using independent experimental data and its results show good agreement with measured data. Furthermore, the Older Persons Model has been applied to several test cases extracted from published literature and its results show good agreement with published findings on the thermal behaviour of older persons. An interview study conducted as part of this research revealed that, professionals (built environment specialists) found the Older Persons Model useful in assisting to further understand the thermal response of the older persons. In conclusion, the adaptation of an existing human thermoregulation model has resulted in a new model, which allows improved prediction of heat and cold strain of the older person although there exist limitations.