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Utilization of linearization methods for measuring of thermal properties of materials

1 Department of Automation and Computer Science in Metallurgy, Faculty of Metallurgy and Materials Engineering, University of Ostrava, 17. Listopadu 15, Ostrava Poruba, 70833, Czech Republic
2 Center for Basic and Applied Research, Faculty of Informatics and Management, University of Hradec Kralove, Rokitanskeho 62, Hradec Kralove, 50003, Czech Republic
3 Faculty of Computing, Universiti Teknologi Malaysia and UTM-RDA Center of Excellence, UTM Johor Bahru, 81310 Johor, Malaysia

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The aim of the article is to describe the convective cooling of the measured samples and the subsequent processing of the measured to determine the material parameters of the solids in order to develop specialized software. In engineering practice, specifically in the field of materials research, it is necessary to measure the thermal properties of the materials under study. For a variety of materials, which may constitute the substitute for metals, such as steel, alloy, and others, including polymers and composites—especially for the newly developed materials, the table values of these parameters are not available. However, they are important to establish the thermal insulation properties of these materials, for further use in relevant industries. The time constant that determines the rate of cooling of the preheated sample is the basis for determining the additional thermal and technical parameters of the material. Based on the knowledge of the specific heat capacity, after specifying the range of the thermal diffusivity and thermal conductivity of the material, these parameters can be estimated. In order to estimate the coefficients, the non-linear parameter estimation methods can be used, which lead to the iterative calculations. A good candidate for these calculations is the MATLAB program, especially its CurveFitting toolbox. The price of Matlab SW, including CurveFitting Toolbox, is relatively high in terms of using the solution for this purpose. This resulted in the designing of new methods for CurveFitting described in this paper and implemented in the developed program named CurveFit.
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