NEURAL NETWORK UTILIZATION FOR EVALUATION OF THE STEEL MATERIAL PROPERTIES

1 Kander Ladislav
Co-authors:
2 Špička Jan 1 Čížek Petr
Institutions:
1 Material and Metallurgical Research Ltd., Ostrava, Czech Republic, EU, ladislav.kander@mmvyzkum.cz
2 Research and Testing Insitute Plzeň, Plzeň, Czech Republic, spicka@vzuplzen.cz
Conference:
27th International Conference on Metallurgy and Materials, Hotel Voronez I, Brno, Czech Republic, EU, May 23rd - 25th 2018
Proceedings:
Proceedings 27th International Conference on Metallurgy and Materials
Pages:
718-723
ISBN:
978-80-87294-84-0
ISSN:
2694-9296
Published:
24th October 2018
Proceedings of the conference were published in Web of Science and Scopus.
Metrics:
12 views / 5 downloads
Abstract

The aim of this work is to develop and test a new method for identification of material properties of the steel. This work deals with application of the small punch test for evaluation of material degradation of power station in the ČEZ company (main Czech energetic company) within the project TE01020068 “Centre of research and experimental development of reliable energy production, work package 8: Research and development of new testing methods for evaluation of material properties”. The main effort is here an improvement of empirical correlation of selected steel materials used in power industry for manufacturing of the critical components (rotors, steam-pipes, etc.). The effort here is on the utilization of the finite element method (FEM) and the neural network (NN) for evaluation of mechanical properties (Young modulus of elasticity, yield stress, tensile strength) of the selected material, based on SPT results only.

Keywords: Keywords:, Small Punch Test, Neural Network, Power Plant Steel, Mechanical properties
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