Fracture and Structural Integrity e-ISSN 1971-8993 Open access
Fatigue and Fracture of metallic alloys Vol. 18, No. 68 (2024)

Predictive Modeling of Fracture Behavior in Ti6Al4V Alloys Manufactured by SLM Process

Author and affiliation details
  • Mohsen Sarparast Corresponding author Department of Mechanical, Industrial & Manufacturing Engineering, The University of Toledo, Toledo, OH, USA ORCID iD0000-0002-9159-8460 Mohsen.Sarparast@rockets.utoledo.edu
  • Majid Shafaie Department of Mechanical Engineering, Amirkabir University of Technology, Tehran, Iran. ORCID iD0000-0002-3140-5495
  • Mohammad Davoodi Department of Mechanical Engineering, K. N. Toosi University of Technology, Tehran, Iran
  • Ahmad Memaran Babakan Department of Mechanical Engineering, K. N. Toosi University of Technology, Tehran, Iran
  • Hongyan Zhang Department of Mechanical, Industrial & Manufacturing Engineering, The University of Toledo, Toledo, OH, USA
DOI
10.3221/IGF-ESIS.68.23
Pages
340-356
Published
Licence
CC BY 4.0
Published inVol. 18, No. 68 (2024)Go to the issue

Abstract

This study focuses on ductile fracture behavior prediction for Ti6Al4V alloys fabricated via Selective Laser Melting (SLM). A modified Gurson-Tvergaard-Needleman (GTN) model characterizes void growth and shear mechanisms under uniaxial stress. The research explores the impact of Artificial Neural Network (ANN) architecture, specifically hidden layers and neurons, on predicting fracture parameters. Results reveal that increasing hidden layers substantially enhances accuracy, particularly for fracture displacement. Notably, predicting maximum force requires fewer layers than fracture displacement. Using selected layers and neurons, the system consistently achieved R2-values exceeding 0.99 for both maximum force and fracture displacement. The study identifies the initial void volume fraction (f0) parameter as having the most significant influence on both properties.

Keywords

Article history

  1. ReceivedUntil the next stage: 70 days
  2. RevisedUntil the next stage: 1 day
  3. AcceptedUntil the next stage: 1 day
  4. Published

How to cite

APA

Sarparast, M., Shafaie, M., Davoodi, M., Memaran Babakan, A., & Zhang, H. (2024). Predictive Modeling of Fracture Behavior in Ti6Al4V Alloys Manufactured by SLM Process. Fracture and Structural Integrity, 18(68), 340–356. https://doi.org/10.3221/IGF-ESIS.68.23

IEEE

M. Sarparast, M. Shafaie, M. Davoodi, A. Memaran Babakan, and H. Zhang, “Predictive Modeling of Fracture Behavior in Ti6Al4V Alloys Manufactured by SLM Process,” Fracture and Structural Integrity, vol. 18, no. 68, pp. 340–356, 2024, doi: 10.3221/IGF-ESIS.68.23.

MLA

Sarparast, Mohsen, et al. “Predictive Modeling of Fracture Behavior in Ti6Al4V Alloys Manufactured by SLM Process.” Fracture and Structural Integrity, vol. 18, no. 68, 2024, pp. 340–356. https://doi.org/10.3221/IGF-ESIS.68.23.

Chicago

Sarparast, Mohsen, Majid Shafaie, Mohammad Davoodi, Ahmad Memaran Babakan, and Hongyan Zhang. 2024. “Predictive Modeling of Fracture Behavior in Ti6Al4V Alloys Manufactured by SLM Process.” Fracture and Structural Integrity 18 (68): 340–356. https://doi.org/10.3221/IGF-ESIS.68.23.

Harvard

Sarparast, M., Shafaie, M., Davoodi, M., Memaran Babakan, A. and Zhang, H. (2024) ‘Predictive Modeling of Fracture Behavior in Ti6Al4V Alloys Manufactured by SLM Process’, Fracture and Structural Integrity, 18(68), pp. 340–356. doi: 10.3221/IGF-ESIS.68.23.

Vancouver

Sarparast M, Shafaie M, Davoodi M, Memaran Babakan A, Zhang H. Predictive Modeling of Fracture Behavior in Ti6Al4V Alloys Manufactured by SLM Process. Fracture and Structural Integrity. 2024;18(68):340-356. doi:10.3221/IGF-ESIS.68.23

BibTeX

@article{sarparast2024, author = {Sarparast, Mohsen and Shafaie, Majid and Davoodi, Mohammad and Memaran Babakan, Ahmad and Zhang, Hongyan}, title = {Predictive Modeling of Fracture Behavior in Ti6Al4V Alloys Manufactured by SLM Process}, journal = {Fracture and Structural Integrity}, year = {2024}, volume = {18}, number = {68}, pages = {340--356}, doi = {10.3221/IGF-ESIS.68.23}, url = {https://doi.org/10.3221/IGF-ESIS.68.23}, issn = {1971-8993} }

RIS

TY - JOUR AU - Sarparast, Mohsen AU - Shafaie, Majid AU - Davoodi, Mohammad AU - Memaran Babakan, Ahmad AU - Zhang, Hongyan TI - Predictive Modeling of Fracture Behavior in Ti6Al4V Alloys Manufactured by SLM Process JO - Fracture and Structural Integrity T2 - Fracture and Structural Integrity PY - 2024 DA - 2024/03/10 VL - 18 IS - 68 SP - 340 EP - 356 DO - 10.3221/IGF-ESIS.68.23 UR - https://doi.org/10.3221/IGF-ESIS.68.23 SN - 1971-8993 ER -

Licence

Creative Commons Attribution 4.0 International

May be shared and adapted, provided appropriate credit is given. Copyright © 2024 Mohsen Sarparast, Majid Shafaie, Mohammad Davoodi, Ahmad Memaran Babakan, Hongyan Zhang.

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

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