The purpose of this paper is to develop artificial neural networks (ANNs) allowing us to simulate the local thermal insulation of clothing protecting against cold on a basis of the characteristics of materials and design solutions used.
For this purpose, laboratory tests of thermal insulation of clothing protecting against cold as well as thermal resistance of textile systems used in the clothing were performed. These tests were conducted with a use of thermal manikin and so-called skin model, respectively. On a basis of results gathered, 12 ANNs were developed that correspond to each thermal manikin’s segment besides hands and feet which are not covered by protective clothing.
In order to obtain high level of simulations, optimization measures for the developed ANNs were introduced. Finally, conducted validation indicated a very high correlation (above 0.95) between theoretical and experimental results, as well as a low error of the simulations (max 8 percent).
The literature reports addressing the problem of modeling thermal insulation of clothing focus mainly on the impact of the degree of fit and the velocity of air movement on thermal insulation properties, whereas reports dedicated to modeling the impact of the construction of clothing protecting against cold as well as of diverse material systems used within one design of clothing on its thermal insulation are scarce.
The paper has been based on the results of Phase III of the National Program “Safety and working conditions improvement,” funded in the years 2014-2016 in the area of research and development works by the Ministry of Science and Higher Education/The National Centre for Research and Development.
The program coordinator: Central Institute for Labour Protection – National Research Institute.
Dabrowska, A.K. (2018), "Artificial neural networks for prediction of local thermal insulation of clothing protecting against cold", International Journal of Clothing Science and Technology, Vol. 30 No. 1, pp. 82-100. https://doi.org/10.1108/IJCST-08-2016-0098
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