Crack growth-based life prediction for additively manufactured metallic materials considering surface roughness

Kaushik Kethamukkala, Changyu Meng, Jie Chen, Yongming Liu

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

Abstract

Additively Manufactured (AM) components are prone to fatigue damage due to defects accompanied by the manufacturing process, such as surface roughness, internal porosity, and anisotropy due to differences in build directions. This is especially true for as-built components with significant surface roughness, where the surface polishing and treatments are not possible due to resource or space limitations. This paper proposes a crack growth-based methodology for the fatigue life assessment of AM components subjected to uniaxial and multiaxial, constant and variable loading conditions. The work is based on a previously developed subcycle fatigue crack growth model. The developed FCG model is extended with the stress concentration factor due to surface roughness and an asymptotic stress intensity factor (SIF) interpolation method for notched specimens. The proposed model approximates the surface roughness as an equivalent notch having the same stress concentration as that posed by the irregularities on the surface. Fatigue life assessment is performed based on the concept of equivalent initial flaw size (EIFS) and FCG analysis. The proposed methodology is validated against in-house as well as experimental data from the available literature.

Original languageEnglish (US)
Article number107914
JournalInternational Journal of Fatigue
Volume176
DOIs
StatePublished - Nov 2023

Keywords

  • Additive manufacturing
  • Crack growth
  • Equivalent initial flaw size
  • Fatigue life prediction
  • Surface roughness

ASJC Scopus subject areas

  • Modeling and Simulation
  • General Materials Science
  • Mechanics of Materials
  • Mechanical Engineering
  • Industrial and Manufacturing Engineering

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