Data-driven method to assess the influence of process parameters on the fatigue response of additively manufactured Ti6Al4V-Reference-Cited by-同舟云学术

Data-driven method to assess the influence of process parameters on the fatigue response of additively manufactured Ti6Al4V

Published:2023 Issue: Volume:47 Page:56-69
ISSN:2452-3216
Container-title:Procedia Structural Integrity
language:en
Short-container-title:Procedia Structural Integrity

Author:

Ciampaglia Alberto,Tridello Andrea,Berto Filippo,Paolino Davide

Publisher

Elsevier BV

Subject

General Engineering,Energy Engineering and Power Technology

Reference38 articles.

1. Effect of HIP post-processing at 850°C/200 MPa in the fatigue behavior of Ti-6Al-4V alloy fabricated by Selective Laser Melting;Alegre;International Journal of Fatigue,2022

2. Fatigue property prediction of additively manufactured Ti-6Al-4V using probabilistic physics-guided learning;Chen;Additive Manufacturing,2021

3. Data driven method for predicting the effect of process parameters on the fatigue response of additive manufactured AlSi10Mg parts;Ciampaglia;International Journal of Fatigue,2023

4. Influence of processing parameters of selective laser melting on high-cycle and very-high-cycle fatigue behaviour of Ti-6Al-4V;Du;Fatigue and Fracture of Engineering Materials and Structures,2021

5. Killer notches: The effect of as-built surface roughness on fatigue failure in AlSi10Mg produced by laser powder bed fusion;du Plessis;Additive Manufacturing,2020

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1. Recent advances in machine learning-assisted fatigue life prediction of additive manufactured metallic materials: A review;Journal of Materials Science & Technology;2024-11

2. Review of Recent Additive Manufacturing and Welding Research with Application of Physics-Informed Neural Networks;Journal of Welding and Joining;2024-08-31

3. Review on machine learning techniques for the assessment of the fatigue response of additively manufactured metal parts;Fatigue & Fracture of Engineering Materials & Structures;2024-06-03