Prediction of fracture toughness transition from tensile test data using artificial neural networks
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26210%2F16%3APU119401" target="_blank" >RIV/00216305:26210/16:PU119401 - isvavai.cz</a>
Result on the web
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DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
Prediction of fracture toughness transition from tensile test data using artificial neural networks
Original language description
The aim of this paper is develop prediction procedure for the fracture toughness transition from tensile test data using artificial neural networks. In total 29 experimental data sets from low alloy steels are applied to validate the model of reference temperature prediction. The tensile tests have been done at general yield temperature of circumferential notched tensile tests (purely brittle fracture temperature) and at room temperature (purely ductile fracture temperature). To build the model, all parameters of tensile test and hardness values were used as input variables. The study indicates that the reference temperature characterizing the fracture toughness transition behaviour in low alloy steels with predominantly ferritic structure is predictable on the basis of selected characteristics of tensile test.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
JL - Fatigue and fracture mechanics
OECD FORD branch
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Result continuities
Project
<a href="/en/project/LO1202" target="_blank" >LO1202: NETME CENTRE PLUS</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2016
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
MULTI-SCALE DESIGN OF ADVANCED MATERIALS - CONFERENCE PROCEEDINGS
ISBN
978-80-214-5358-6
ISSN
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e-ISSN
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Number of pages
8
Pages from-to
79-86
Publisher name
Brno University of Technology
Place of publication
Brno
Event location
Mikulov
Event date
Jun 2, 2016
Type of event by nationality
CST - Celostátní akce
UT code for WoS article
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