EVALUATION OF MATERIAL PROPERTIES OF STRUCTURAL STEELS USING ARTIFICIAL INTELIGENCE NEURAL NETWORK METHOD

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F25870807%3A_____%2F19%3AN0000017" target="_blank" >RIV/25870807:_____/19:N0000017 - isvavai.cz</a>
Result on the web
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DOI - Digital Object Identifier
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Result language
angličtina
Original language name
EVALUATION OF MATERIAL PROPERTIES OF STRUCTURAL STEELS USING ARTIFICIAL INTELIGENCE NEURAL NETWORK METHOD
Original language description
This work summarizes results and progress in new method development for identification of material properties of steel. This work deals with application of the small punch test for evaluation of material degradation of power station in the Czech Republic 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 the manufacturing of critical components (rotors, steampipes, 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. Paper contains results of experimental work carried out over past 7 years. After modification of actual neural network and increasing of the number of results interesting results of mechanical properties prediction have been obtained. Increasing data of points in common up to 300, leads to significantly lower deviation that varies about 3-5 %.
Czech name
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Czech description
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Project
<a href="/en/project/TE01020068" target="_blank" >TE01020068: Centre of research and experimental development of reliable energy production</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year
2019
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
Metal 2019 28th International Conference on Metallurgy and Materials Conference Proceedings
ISBN
978-80-87294-92-5
ISSN
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e-ISSN
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Number of pages
6
Pages from-to
703 - 708
Publisher name
Tanger Ltd.
Place of publication
Ostrava
Event location
Brno
Event date
May 22, 2019
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
999

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