Počet záznamů: 1

Prediction of fracture toughness temperature dependence applying neural network

  1. 1.
    0366644 - UFM-A 2012 RIV RS eng J - Článek v odborném periodiku
    Dlouhý, Ivo - Hadraba, Hynek - Chlup, Zdeněk - Šmída, T.
    Prediction of fracture toughness temperature dependence applying neural network.
    Structural Integrity and Life. Roč. 11, č. 1 (2011), s. 9-14 ISSN 1451-3749
    Grant CEP: GA ČR(CZ) GAP108/10/0466
    Výzkumný záměr: CEZ:AV0Z20410507
    Klíčová slova: brittle to ductile transition * fracture toughness * artificial neural network * steels
    Kód oboru RIV: JL - Únava materiálu a lomová mechanika

    Reference temperature localizing the fracture toughness temperature diagram on temperature axis is predicted based on tensile test data. The regularization neural network is developed to solve the correlation of these properties. Three-point bend specimens were applied to determine fracture toughness. The fracture toughness transition dependence is quantified by means of master curve concept enabling to represent it by using one parameter, i.e. reference temperature. Tensile samples with circumferential notch are also examined. In total 29 data sets from low-alloy steels are applied for the analysis. A good correlation of predicted and experimentally determined values of reference temperature is found.
    Trvalý link: http://hdl.handle.net/11104/0201552