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Prediction of Fracture Toughness Transition from Tensile Test Parameters Applying Artificial Neural Networks

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    SYSNO ASEP0354571
    Document TypeK - Proceedings Paper (Czech conf.)
    R&D Document TypeConference Paper
    TitlePrediction of Fracture Toughness Transition from Tensile Test Parameters Applying Artificial Neural Networks
    Author(s) Dlouhý, Ivo (UFM-A) RID, ORCID
    Hadraba, Hynek (UFM-A) RID, ORCID
    Chlup, Zdeněk (UFM-A) RID, ORCID
    Kozák, Vladislav (UFM-A) RID, ORCID
    Šmida, T. (SK)
    Source TitleNew Methods of Damage and Failure Analysis of Structural Parts. - Ostrava : VŠB - TU Ostrava, 2010 / Strnadel B. - ISBN 978-80-248-2265-5
    S. 207-215
    Number of pages9 s.
    ActionNew Methods of Damage and Failure Analysis of Structural Parts
    Event date06.09.2010-10.09.2010
    VEvent locationOstrava
    CountryCZ - Czech Republic
    Event typeWRD
    Languageeng - English
    CountryCZ - Czech Republic
    Keywordsthermal ageing ; brittleness ; fracture
    Subject RIVJL - Materials Fatigue, Friction Mechanics
    R&D ProjectsGAP108/10/0466 GA ČR - Czech Science Foundation (CSF)
    CEZAV0Z20410507 - UFM-A (2005-2011)
    UT WOS000393446100026
    AnnotationReference temperature localizing the fracture toughness temperature diagram on temperature axis was predicted based on tensile test data. Regularization artificial neural network (ANN) was adjusted to solve the interrelation of these properties. For analyses, 29 data sets from low-alloy steels were applied. The fracture toughness transition dependence was quantified by means of master curve concept enabling to represent it using one parameter - reference temperature. Different strength and deformation characteristics from standard tensile specimens and notched specimens, instrumented ball indentation test etc. have been applied. A very promising correlation of predicted and experimentally determined values of reference temperature was found.
    WorkplaceInstitute of Physics of Materials
    ContactYvonna Šrámková, sramkova@ipm.cz, Tel.: 532 290 485
    Year of Publishing2011
Number of the records: 1  

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