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DETERMINATION OF A COEFFICIENT OF THERMAL EXPANSION BY MACHINE LEARNING

1 MACHŮ Mario
Co-authors:
1 DROZDOVÁ Ľubomíra 1 SMETANA Bedřich 1 RŮŽIČKA Jan 1 ZLÁ Simona 1 SOROKINA Svetlana
Institution:
1 VSB - Technical University of Ostrava, Ostrava, Czech Republic, EU, mario.machu@vsb.cz
Conference:
29th International Conference on Metallurgy and Materials, Brno, Czech Republic, EU, May 20 - 22, 2020
Proceedings:
Proceedings 29th International Conference on Metallurgy and Materials
Pages:
57-61
ISBN:
978-80-87294-97-0
ISSN:
2694-9296
DOI:
https://doi.org/10.37904/metal.2020.3462
Published:
27th July 2020
Proceedings of the conference were published in Web of Science and Scopus.
Metrics:
1191 views / 1217 downloads
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Abstract

Objective of this work is to model the thermal expansion coefficients of selected steel grade and compare results with those measured by TMA method. Coefficient of thermal expansion is described as a function of steel composition (C, Mn, P, S, Si, Cr, Ni, Mo) and temperature.Experimental values are described and compared with model. Correlation analysis of these data sets is done. Presented model is based on using artificial neural network and represents a preliminary test of method capability to be used for such problems class – for predicting of thermophysical properties depending on composition and temperatre.

Keywords: Coefficient of thermal expansion, artificial neural network, material proporties, modelling

© This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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