A review of multi-scale and multi-physics simulations of metal additive manufacturing processes with focus on modelling strategies

Mohamad Bayat, Wen Dong, Jesper Thorborg, Albert C. To, Jesper H. Hattel*

*Corresponding author for this work

Research output: Contribution to journalJournal articleResearchpeer-review

Abstract

Numerical simulations have recently shown their potential as a robust, cheap and reliable tool for predicting the quality of components produced by metal additive manufacturing (MAM) processes. Despite the advantages of the MAM processes over conventional manufacturing methods, there is still a lack of thorough understanding on how different defects can form and originate during MAM processing. In that respect, advanced numerical techniques recently developed have the ability to predict the occurrence of such defects. These techniques have paved the way to efficiently obtain the optimal processing window for targeted mechanical properties to satisfy the end-use design requirements. The aim of this review paper is hence to present and classify numerical simulations of MAM, not solely based on their length-scale as often seen, but also based on the involved physics, as well as the modelling strategies at both the meso-scale and part-scale. The paper is arranged in the following way: First, literature describing purely conduction-based heat transfer simulations at meso-scale are presented. This is followed by a review of fluid-based simulations of increasing complexity based on the treatment of free surface of the melt pool at meso-scale. Finally, contributions based on different part-scale modeling approaches with a focus on thermo-mechanical behavior are reviewed.
Original languageEnglish
Article number102278
JournalAdditive Manufacturing
ISSN2214-8604
DOIs
Publication statusAccepted/In press - 2021

Keywords

  • MAM
  • Heat transfer
  • Fluid dynamics
  • Solid mechanics
  • Meso-scale
  • Part-scale

Fingerprint

Dive into the research topics of 'A review of multi-scale and multi-physics simulations of metal additive manufacturing processes with focus on modelling strategies'. Together they form a unique fingerprint.

Cite this