Název:
Prediction of Fracture Toughness Transition from Tensile Test Parameters Applying Artificial Neural Networks
Autoři:
Dlouhý, Ivo ; Hadraba, Hynek ; Chlup, Zdeněk ; Kozák, Vladislav ; Šmida, T. Typ dokumentu: Příspěvky z konference Konference/Akce: New Methods of Damage and Failure Analysis of Structural Parts, Ostrava (CZ), 2010-09-06 / 2010-09-10
Rok:
2010
Jazyk:
eng
Abstrakt: Reference 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.
Klíčová slova:
brittleness; fracture; thermal ageing Číslo projektu: CEZ:AV0Z20410507 (CEP), GAP108/10/0466 (CEP) Poskytovatel projektu: GA ČR Zdrojový dokument: New Methods of Damage and Failure Analysis of Structural Parts, ISBN 978-80-248-2265-5
Instituce: Ústav fyziky materiálů AV ČR
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Informace o dostupnosti dokumentu:
Dokument je dostupný v příslušném ústavu Akademie věd ČR. Původní záznam: http://hdl.handle.net/11104/0193545