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Title: Laser powder bed fusion additive manufacturing of metals; physics, computational, and materials challenges

Abstract

The production of metal parts via laser powder bed fusion additive manufacturing is growing exponentially. However, the transition of this technology from production of prototypes to production of critical parts is hindered by a lack of confidence in the quality of the part. Confidence can be established via a fundamental understanding of the physics of the process. It is generally accepted that this understanding will be increasingly achieved through modeling and simulation. However, there are significant physics, computational, and materials challenges stemming from the broad range of length and time scales and temperature ranges associated with the process. In this paper, we review the current state of the art and describe the challenges that need to be met to achieve the desired fundamental understanding of the physics of the process.

Authors:
; ; ;  [1];  [2];  [3]
  1. Engineering Directorate, Lawrence Livermore National Laboratory, Livermore, California 94550 (United States)
  2. Computation Directorate, Lawrence Livermore National Laboratory, Livermore, California 94550 (United States)
  3. NIF and Photon Sciences Directorate, Lawrence Livermore National Laboratory, Livermore, California 94550 (United States)
Publication Date:
OSTI Identifier:
22482277
Resource Type:
Journal Article
Journal Name:
Applied Physics Reviews
Additional Journal Information:
Journal Volume: 2; Journal Issue: 4; Other Information: (c) 2015 AIP Publishing LLC; Country of input: International Atomic Energy Agency (IAEA); Journal ID: ISSN 1931-9401
Country of Publication:
United States
Language:
English
Subject:
71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSICS; ADDITIVES; LASERS; MANUFACTURING; MATERIALS; METALS; POWDERS; SIMULATION

Citation Formats

King, W. E., E-mail: weking@llnl.gov, Anderson, A. T., Ferencz, R. M., Hodge, N. E., Khairallah, S. A., Kamath, C., and Rubenchik, A. M. Laser powder bed fusion additive manufacturing of metals; physics, computational, and materials challenges. United States: N. p., 2015. Web. doi:10.1063/1.4937809.
King, W. E., E-mail: weking@llnl.gov, Anderson, A. T., Ferencz, R. M., Hodge, N. E., Khairallah, S. A., Kamath, C., & Rubenchik, A. M. Laser powder bed fusion additive manufacturing of metals; physics, computational, and materials challenges. United States. doi:10.1063/1.4937809.
King, W. E., E-mail: weking@llnl.gov, Anderson, A. T., Ferencz, R. M., Hodge, N. E., Khairallah, S. A., Kamath, C., and Rubenchik, A. M. Tue . "Laser powder bed fusion additive manufacturing of metals; physics, computational, and materials challenges". United States. doi:10.1063/1.4937809.
@article{osti_22482277,
title = {Laser powder bed fusion additive manufacturing of metals; physics, computational, and materials challenges},
author = {King, W. E., E-mail: weking@llnl.gov and Anderson, A. T. and Ferencz, R. M. and Hodge, N. E. and Khairallah, S. A. and Kamath, C. and Rubenchik, A. M.},
abstractNote = {The production of metal parts via laser powder bed fusion additive manufacturing is growing exponentially. However, the transition of this technology from production of prototypes to production of critical parts is hindered by a lack of confidence in the quality of the part. Confidence can be established via a fundamental understanding of the physics of the process. It is generally accepted that this understanding will be increasingly achieved through modeling and simulation. However, there are significant physics, computational, and materials challenges stemming from the broad range of length and time scales and temperature ranges associated with the process. In this paper, we review the current state of the art and describe the challenges that need to be met to achieve the desired fundamental understanding of the physics of the process.},
doi = {10.1063/1.4937809},
journal = {Applied Physics Reviews},
issn = {1931-9401},
number = 4,
volume = 2,
place = {United States},
year = {2015},
month = {12}
}

Works referencing / citing this record:

Process-Structure Linkages Using a Data Science Approach: Application to Simulated Additive Manufacturing Data
journal, March 2017

  • Popova, Evdokia; Rodgers, Theron M.; Gong, Xinyi
  • Integrating Materials and Manufacturing Innovation, Vol. 6, Issue 1
  • DOI: 10.1007/s40192-017-0088-1