✍ Scribed by J. Trzaska; L.A. Dobrzański
No coin nor oath required. For personal study only.
The paper presents the methodology of modelling using the neural networks and regression method of the relationship between the chemical composition and austenitizing temperature, and the supercooled austenite transformation kinetics during the continuous cooling. The worked out model makes possible to calculate a CCT diagram for the steel with a known chemical composition and analysis of the influence of particular elements on the characteristic points and transformation curves of the supercooled austenite. In order to work out the methods the set of experimental data worked out on the basis of information available in the literature consisting of 300 CCT diagrams made for constructional and engineering steels was used. Model presented in the paper features a useful assistance in selection of the chemical composition of steel for machine elements subjected to heat treatment.
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