Fracture and Structural Integrity e-ISSN 1971-8993 Open access
SI: Steels and Composites for Engineering Structures Vol. 15, No. 58 (2021)

Sensitivity analysis of the GTN damage parameters at different temperature for dynamic fracture propagation in X70 pipeline steel using neural network

Author and affiliation details
  • Abdelmoumin Ouladbrahim Corresponding author Department of Mechanical Engineering, University M’hamed Bougara Boumerdes, LEMI Laboratory, 35000 Boumerdes, Algeria. ORCID iD0000-0003-4729-298X moumindoc@gmail.com
  • Idir Belaidi Department of Mechanical Engineering, University M’hamed Bougara Boumerdes, LEMI Laboratory, 35000 Boumerdes, Algeria.
  • Samir Khatir Soete Laboratory, Faculty of Engineering and Architecture, Ghent University, Technologiepark Zwijnaarde 903, B-9052, Zwijnaarde, Belgium
  • Erica Magagnini DICEA, Structural Section, Polytechnic University of Marche, Italy
  • Roberto Capozucca DICEA, Structural Section, Polytechnic University of Marche, Italy
  • Magd Abdel Wahab Soete Laboratory, Faculty of Engineering and Architecture, Ghent University, Technologiepark Zwijnaarde 903, B-9052, Zwijnaarde, Belgium ORCID iD0000-0002-3610-865X
DOI
10.3221/IGF-ESIS.58.32
Pages
442-452
Published
Licence
CC BY 4.0
Published inVol. 15, No. 58 (2021)Go to the issue

Abstract

In this paper, the initial and maximum load was studied using the Finite Element Modeling (FEM) analysis during impact testing (CVN) of pipeline X70 steel. The Gurson-Tvergaard-Needleman (GTN) constitutive model has been used to simulate the growth of voids during deformation of pipeline steel at different temperatures. FEM simulations results used to study the sensitivity of the initial and maximum load with GTN parameters values proposed and the variation of temperatures.

Finally, the applied artificial neural network (ANN) is used to predict the initial and maximum load for a given set of damage parameters X70 steel at different temperatures, based on the results obtained, the neural network is able to provide a satisfactory approximation of the load initiation and load maximum in impact testing of X70 Steel.

           

Keywords

Article history

  1. ReceivedUntil the next stage: 19 days
  2. RevisedUntil the next stage: 1 day
  3. AcceptedUntil the next stage: 9 days
  4. Published

How to cite

APA

Ouladbrahim, A., Belaidi, I., Khatir, S., Magagnini, E., Capozucca, R., & Abdel Wahab, M. (2021). Sensitivity analysis of the GTN damage parameters at different temperature for dynamic fracture propagation in X70 pipeline steel using neural network. Fracture and Structural Integrity, 15(58), 442–452. https://doi.org/10.3221/IGF-ESIS.58.32

IEEE

A. Ouladbrahim, I. Belaidi, S. Khatir, E. Magagnini, R. Capozucca, and M. Abdel Wahab, “Sensitivity analysis of the GTN damage parameters at different temperature for dynamic fracture propagation in X70 pipeline steel using neural network,” Fracture and Structural Integrity, vol. 15, no. 58, pp. 442–452, 2021, doi: 10.3221/IGF-ESIS.58.32.

MLA

Ouladbrahim, Abdelmoumin, et al. “Sensitivity analysis of the GTN damage parameters at different temperature for dynamic fracture propagation in X70 pipeline steel using neural network.” Fracture and Structural Integrity, vol. 15, no. 58, 2021, pp. 442–452. https://doi.org/10.3221/IGF-ESIS.58.32.

Chicago

Ouladbrahim, Abdelmoumin, Idir Belaidi, Samir Khatir, Erica Magagnini, Roberto Capozucca, and Magd Abdel Wahab. 2021. “Sensitivity analysis of the GTN damage parameters at different temperature for dynamic fracture propagation in X70 pipeline steel using neural network.” Fracture and Structural Integrity 15 (58): 442–452. https://doi.org/10.3221/IGF-ESIS.58.32.

Harvard

Ouladbrahim, A., Belaidi, I., Khatir, S., Magagnini, E., Capozucca, R. and Abdel Wahab, M. (2021) ‘Sensitivity analysis of the GTN damage parameters at different temperature for dynamic fracture propagation in X70 pipeline steel using neural network’, Fracture and Structural Integrity, 15(58), pp. 442–452. doi: 10.3221/IGF-ESIS.58.32.

Vancouver

Ouladbrahim A, Belaidi I, Khatir S, Magagnini E, Capozucca R, Abdel Wahab M. Sensitivity analysis of the GTN damage parameters at different temperature for dynamic fracture propagation in X70 pipeline steel using neural network. Fracture and Structural Integrity. 2021;15(58):442-452. doi:10.3221/IGF-ESIS.58.32

BibTeX

@article{ouladbrahim2021, author = {Ouladbrahim, Abdelmoumin and Belaidi, Idir and Khatir, Samir and Magagnini, Erica and Capozucca, Roberto and Abdel Wahab, Magd}, title = {Sensitivity analysis of the GTN damage parameters at different temperature for dynamic fracture propagation in X70 pipeline steel using neural network}, journal = {Fracture and Structural Integrity}, year = {2021}, volume = {15}, number = {58}, pages = {442--452}, doi = {10.3221/IGF-ESIS.58.32}, url = {https://doi.org/10.3221/IGF-ESIS.58.32}, issn = {1971-8993} }

RIS

TY - JOUR AU - Ouladbrahim, Abdelmoumin AU - Belaidi, Idir AU - Khatir, Samir AU - Magagnini, Erica AU - Capozucca, Roberto AU - Abdel Wahab, Magd TI - Sensitivity analysis of the GTN damage parameters at different temperature for dynamic fracture propagation in X70 pipeline steel using neural network JO - Fracture and Structural Integrity T2 - Fracture and Structural Integrity PY - 2021 DA - 2021/09/25 VL - 15 IS - 58 SP - 442 EP - 452 DO - 10.3221/IGF-ESIS.58.32 UR - https://doi.org/10.3221/IGF-ESIS.58.32 SN - 1971-8993 ER -

Licence

Creative Commons Attribution 4.0 International

May be shared and adapted, provided appropriate credit is given. Copyright © 2021 Abdelmoumin Ouladbrahim, Idir Belaidi , Samir Khatir , Erica Magagnini, Roberto Capozucca , Magd Abdel Wahab.

Copyright 
Authors are allowed to retain both the copyright and the publishing rights of their articles without restrictions.  

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