|
|
Multicriterial Tool for Analysis and Predict Human Thermal Stress
Řehák Kopečková, Barbora ; Soukup,, Radek (referee) ; Kolářová,, Jana (referee) ; Jícha, Miroslav (advisor)
The thesis is concerned with the development of a multi-criteria tool capable of determining, for given input conditions, the most appropriate model for predicting the thermal state of a person in a protective suit, based on developed objective decision scheme. Four heat stress indices or physiological models were selected for the development of this tool: PHS (Predicted Heat Strain), IPHS (Individual Predicted Heat Strain), Gagg's 2-node model and the FMTK model. The algorithms of PHS, IPHS and Gagge were implemented in Matlab. Subsequently, all 4 models were validated against the experimental results. Based on the results of the validations, the applicability of these models for predicting human heat stress was verified. For some models, the applicability conditions were possible to extend. The accuracy of rectal temperature prediction was the main criteria. Furthermore, based on the results of the validation studies, metrics were selected to build an objective decision system. This was used to select the most appropriate model for the given environmental conditions. In the cooperation with SÚJCHBO, the data for model validation were delivered: 140 tests were carried out for 4 protective suits (FOP, Tyhem, Tiger, OPCH) and 4 ambient temperatures (-10, 5, 25 and 35 °C). 12 test persons were involved, 6 male test persons aged 29-53 years, 170-187 cm tall and weighing 69-92 kg, and 6 female test persons aged 28-49 years, 158-176 cm tall and weighing 56-71 kg. In total, 1987 simulations have been carried out using selected models, for different initial values of rectum and skin temperature, and for different estimates of metabolic activity. A look-up table was created to find the most appropriate model for the given conditions according to the inputs to the multicriteria tool via a decision scheme, based on the evaluation of the results of the simulations against the experiments in terms of the MAE (Mean Absolute Error) and the difference between the predicted and measured rectal temperature at the end of the test. Finally, the resulting multicriteria tool was created in Excel, including a graphical interface for entering values.
|
guest ::
