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Frontiers of Mechanical Engineering

, Volume 13, Issue 4, pp 482–492 | Cite as

Modeling process-structure-property relationships for additive manufacturing

  • Wentao Yan
  • Stephen Lin
  • Orion L. Kafka
  • Cheng Yu
  • Zeliang Liu
  • Yanping Lian
  • Sarah Wolff
  • Jian Cao
  • Gregory J. Wagner
  • Wing Kam Liu
Open Access
Review Article

Abstract

This paper presents our latest work on comprehensive modeling of process-structure-property relationships for additive manufacturing (AM) materials, including using data-mining techniques to close the cycle of design-predict-optimize. To illustrate the process-structure relationship, the multi-scale multi-physics process modeling starts from the micro-scale to establish a mechanistic heat source model, to the meso-scale models of individual powder particle evolution, and finally to the macro-scale model to simulate the fabrication process of a complex product. To link structure and properties, a high-efficiency mechanistic model, self-consistent clustering analyses, is developed to capture a variety of material response. The model incorporates factors such as voids, phase composition, inclusions, and grain structures, which are the differentiating features of AM metals. Furthermore, we propose data-mining as an effective solution for novel rapid design and optimization, which is motivated by the numerous influencing factors in the AM process. We believe this paper will provide a roadmap to advance AM fundamental understanding and guide the monitoring and advanced diagnostics of AM processing.

Keywords

additive manufacturing thermal fluid flow data mining material modeling 

Notes

Acknowledgements

W. Liu and W. Yan acknowledge the support by the National Institute of Standards and Technology (NIST) and Center for Hierarchical Materials Design (CHiMaD) (Grant Nos. 70NANB13Hl94 and 70NANB14H012). S. Lin and O. L. Kafka acknowledge the support of the National Science Foundation Graduate Research Fellowship (Grant No. DGE-1324585).

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Copyright information

© The Author(s) 2018

Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the appropriate credit is given to the original author(s) and the source, and a link is provided to the Creative Commons license, indicating if changes were made.

Authors and Affiliations

  • Wentao Yan
    • 1
  • Stephen Lin
    • 1
  • Orion L. Kafka
    • 1
  • Cheng Yu
    • 1
  • Zeliang Liu
    • 1
  • Yanping Lian
    • 1
  • Sarah Wolff
    • 1
  • Jian Cao
    • 1
  • Gregory J. Wagner
    • 1
  • Wing Kam Liu
    • 1
  1. 1.Department of Mechanical EngineeringNorthwestern UniversityEvanstonUSA

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