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PREDICTION OF FRACTURE TOUGHNESS TRANSITION FROM TENSILE TEST DATA APPLYING NEURAL NETWORKS
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SYSNO ASEP 0484701 Document Type C - Proceedings Paper (int. conf.) R&D Document Type Conference Paper Title PREDICTION OF FRACTURE TOUGHNESS TRANSITION FROM TENSILE TEST DATA APPLYING NEURAL NETWORKS Author(s) Dlouhý, I. (CZ)
Hadraba, Hynek (UFM-A) RID, ORCID
Chlup, Zdeněk (UFM-A) RID, ORCID
Válka, Libor (UFM-A)
Žák, L. (CZ)Number of authors 5 Source Title PROCEEDING OF THE ASME PRESSURE VESSELS AND PIPING CONFERENCE, Codes and Standards, Vol. 1. - New York : American Society Mechanical Engineers, 2012 - ISBN 978-0-7918-4451-9 Pages s. 101-105 Number of pages 5 s. Publication form Print - P Action ASME 2011 - Pressure Vessels and Piping Conference Event date 17.07.2011 - 21.07.2011 VEvent location Baltimore Country MD - Moldova, republic of Event type WRD Language eng - English Country US - United States Keywords PRECRACKED CHARPY SPECIMENS ; IMPACT TOUGHNESS ; MO-V ; STEEL Subject RIV JL - Materials Fatigue, Friction Mechanics OECD category Audio engineering, reliability analysis R&D Projects GAP108/10/0466 GA ČR - Czech Science Foundation (CSF) CEZ AV0Z2041904 - UFM-A UT WOS 000320410100012 EID SCOPUS 84881455822 DOI 10.1115/PVP2011-57932 Annotation 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. Workplace Institute of Physics of Materials Contact Yvonna Šrámková, sramkova@ipm.cz, Tel.: 532 290 485 Year of Publishing 2018
Number of the records: 1