A mesoscopic digital twin that bridges length and time scales for control of additively manufactured metal microstructures

Heo, Tae Wook; Khairallah, Saad; Shi, Rongpei; Berry, Joel; Perron, Aurelien; Calta, Nicholas P.; Martin, Aiden A.; Barton, Nathan; Roehling, John D.; Roehling, Tien Tran; Fattebert, Jean-Luc; Anderson, Andy; Nichols, Albert L.; Wopschall, Steven; King, Wayne E.; McKeown, Joseph T.; Matthews, Manyalibo J.

doi:10.1088/2515-7639/abeef8

Title: A mesoscopic digital twin that bridges length and time scales for control of additively manufactured metal microstructures

Journal Article · Mon Jun 14 00:00:00 UTC 2021 · JPhys Materials

DOI: https://doi.org/10.1088/2515-7639/abeef8 · OSTI ID:1813220

^[1]; Khairallah, Saad ^[1]; Shi, Rongpei ^[1]; Berry, Joel ^[1];

^[1]; Calta, Nicholas P. ^[1];

^[1]; Barton, Nathan ^[1]; Roehling, John D. ^[1]; Roehling, Tien Tran ^[1];

^[2]; Anderson, Andy ^[1]; Nichols, Albert L. ^[1]; Wopschall, Steven ^[1]; King, Wayne E. ^[3]; McKeown, Joseph T. ^[1]; Matthews, Manyalibo J. ^[1]

Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
The Barnes Global Advisors, Sewickley, PA (United States)

We present our recent development of an integrated mesoscale digital twin (DT) framework for relating processing conditions, microstructures, and mechanical responses of additively manufactured (AM) metals. In particular, focusing on the laser powder bed fusion technique, we describe how individual modeling and simulation capabilities are coupled to investigate and control AM microstructural features at multiple length and time scales. We review our prior case studies that demonstrate the integrated modeling schemes, in which high-fidelity melt pool dynamics simulations provide accurate local thermal profiles and histories to subsequent AM microstructure simulations. We also report our new mechanical response modeling results for predicted AM microstructures. In addition, we illustrate how our DT framework has been validated through modeling–experiment integration, as well as how it has been practically utilized to guide and analyze AM experiments. Finally, we share our perspectives on future directions of further development of the DT framework for more efficient, accurate predictions and wider ranges of applications.

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Research Organization:: Lawrence Livermore National Laboratory (LLNL), Livermore, CA (United States); Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)

Sponsoring Organization:: USDOE National Nuclear Security Administration (NNSA)

Grant/Contract Number:: AC05-00OR22725; AC52-07NA27344

OSTI ID:: 1813220

Report Number(s):: LLNL-JRNL--816984

Journal Information:: JPhys Materials, Journal Name: JPhys Materials Journal Issue: 3 Vol. 4; ISSN 2515-7639

Publisher:: IOP PublishingCopyright Statement

Country of Publication:: United States

Language:: English

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36 MATERIALS SCIENCE
additive manufacturing
digital twin
metals
microstructures
processing
properties

Title: A mesoscopic digital twin that bridges length and time scales for control of additively manufactured metal microstructures

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