Original title: PREDICTION OF FRACTURE TOUGHNESS TRANSITION FROM TENSILE TEST DATA APPLYING NEURAL NETWORKS
Authors: Dlouhý, I. ; Hadraba, Hynek ; Chlup, Zdeněk ; Válka, Libor ; Žák, L.
Document type: Papers
Conference/Event: ASME 2011 - Pressure Vessels and Piping Conference, Baltimore (MD), 20110717
Year: 2012
Language: eng
Abstract: 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.
Keywords: IMPACT TOUGHNESS; MO-V; PRECRACKED CHARPY SPECIMENS; STEEL
Project no.: GAP108/10/0466 (CEP), CEZ:AV0Z2041904 (CEP)
Funding provider: GA ČR
Host item entry: PROCEEDING OF THE ASME PRESSURE VESSELS AND PIPING CONFERENCE, ISBN 978-0-7918-4451-9

Institution: Institute of Physics of Materials AS ČR (web)
Document availability information: Fulltext is available at the institute of the Academy of Sciences.
Original record: http://hdl.handle.net/11104/0279850

Permalink: http://www.nusl.cz/ntk/nusl-373429


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