Skip to main navigation Skip to search Skip to main content

In-situ experimental and high-fidelity modeling tools to advance understanding of metal additive manufacturing

Lu Wang, Qilin Guo, Lianyi Chen*, Wentao Yan*

*Corresponding author for this work

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

Abstract

Metal additive manufacturing has seen extensive research and rapidly growing applications for its high precision, efficiency, flexibility, etc. However, the appealing advantages are still far from being fully exploited, and the bottleneck problems essentially originate from the incomplete understanding of the complex physical mechanisms spanning from the manufacturing processes, microstructure evolutions, to mechanical properties. Specifically, for powder-fusion-based additive manufacturing such as laser powder bed fusion, the manufacturing process involves powder dynamics, heat transfer, phase transitions (melting, solidification, evaporation, and condensation), fluid flow (gas, vapor, and molten metal liquid), and their interactions. These interactions induce not only various defects but also complex thermal-mechanical-compositional conditions. These transient conditions lead to highly non-equilibrium microstructure evolutions, and the resultant microstructures, together with those defects, can significantly alter the mechanical properties of the as-built parts, including strength, ductility and residual stress. We believe that the most efficient approach to advance the fundamental understanding is integrating in-situ experimentation and high-fidelity modeling. In this review, we summarize the state of the art of these two powerful tools: in-situ synchrotron experimentation and high-fidelity modeling, and provide an outlook for potential research directions. © 2023 Elsevier Ltd
Original languageEnglish
Article number104077
JournalInternational Journal of Machine Tools and Manufacture
Volume193
Online published3 Oct 2023
DOIs
Publication statusPublished - Dec 2023
Externally publishedYes

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 9 - Industry, Innovation, and Infrastructure
    SDG 9 Industry, Innovation, and Infrastructure

Research Keywords

  • Additive manufacturing
  • High-fidelity modeling
  • In-situ experimentation
  • Physical mechanisms
  • Process-structure–property

Fingerprint

Dive into the research topics of 'In-situ experimental and high-fidelity modeling tools to advance understanding of metal additive manufacturing'. Together they form a unique fingerprint.

Cite this