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Journal of Mechanical, Civil and Industrial Engineering
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  This is an Open Access Journal Open Access journal
ISSN (Online) 2710-1436
Published by Al-Kindi Center for Research and Development Homepage  [14 journals]
  • Determination of GTN Model Parameters Based on Artificial Neutral Network
           for a Ductile Failure

    • Authors: YASSINE CHAHBOUB, SZAVAI Szabolcs
      Pages: 01 - 05
      Abstract: The Gurson – Tvergaard – Needleman (GTN) mechanical model is widely used to predict the failure of materials based on laboratory specimens, direct identification of Gurson – Tvergaard – Needleman parameters is not easy and time-consuming, and the most used method to determine them is the combination between the experimental results and those of the finite elements, the process consists of repeating the simulations several times until the simulation data matches the experimental data obtained at the specimen level.
      This article aims to find GTN parameters for the Compact Tension (CT) and Single Edge Tensile Test (SENT) specimen based on the Notch Specimen (NT) using the Artificial Neural Network (ANN) approach. . This work presents how the ANN could help us determine the parameters of GTN in a very short period of time. The results obtained show that ANN is an excellent tool for determining GTN parameters.
      PubDate: 2021-01-15
      DOI: 10.32996/jmcie.2021.2.1.1
      Issue No: Vol. 2, No. 1 (2021)
School of Mathematical and Computer Sciences
Heriot-Watt University
Edinburgh, EH14 4AS, UK
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