Predicting ductile failure of aluminum components under general loading conditions: Computational implementation, model verification and experimental validation

N. Rom, J. Bortman, E. Priel

Research output: Contribution to journalArticlepeer-review

4 Scopus citations

Abstract

Predicting ductile failure in engineering structural components has been an active research topic for decades. Although the micro-mechanical phenomena that govern ductile failure are well understood, and many failure criteria proposed, a leading criterion has yet to be agreed upon. In the current study, four different ductile failure criteria were implemented in the finite element framework and used to study the ductile failure process of Al2024 and Al7075 specimens. The failure criteria included stress based, energy based and strain based formulations. Several different sets of experiments were first used to determine the different model parameters required to predict failure initiation. Then these same parameters were used to predict failure initiation for a different set of experiments with different geometries and under a complex stress and strain state. A critical analysis of the performance of the different ductile failure criteria was then conducted. It is shown that, while the stress based criteria fail to provide accurate predictions for the general loading case, the energy based and strain based criteria perform well and predict both the failure load and crack location.

Original languageEnglish
Article number112295
JournalInternational Journal of Solids and Structures
Volume275
DOIs
StatePublished - 15 Jul 2023

Keywords

  • Al2024
  • Al7075
  • CDM
  • Ductile failure
  • Finite elements

ASJC Scopus subject areas

  • Modeling and Simulation
  • General Materials Science
  • Condensed Matter Physics
  • Mechanics of Materials
  • Mechanical Engineering
  • Applied Mathematics

Fingerprint

Dive into the research topics of 'Predicting ductile failure of aluminum components under general loading conditions: Computational implementation, model verification and experimental validation'. Together they form a unique fingerprint.

Cite this