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Title: ExaAM: Metal additive manufacturing simulation at the fidelity of the microstructure

Abstract

Additive manufacturing (AM), or 3D printing, of metals is transforming the fabrication of components, in part by dramatically expanding the design space, allowing optimization of shape and topology. However, although the physical processes involved in AM are similar to those of welding, a field with decades of experimental, modeling, simulation, and characterization experience, qualification of AM parts remains a challenge. The availability of exascale computational systems, particularly when combined with data-driven approaches such as machine learning, enables topology and shape optimization as well as accelerated qualification by providing process-aware, locally accurate microstructure and mechanical property models. Here we describe the physics components comprising the Exascale Additive Manufacturing simulation environment and report progress using highly resolved melt pool simulations to inform part-scale finite element thermomechanics simulations, drive microstructure evolution, and determine constitutive mechanical property relationships based on those microstructures using polycrystal plasticity. We report on implementation of these components for exascale computing architectures, as well as the multi-stage simulation workflow that provides a unique high-fidelity model of process–structure–property relationships for AM parts. In addition, we discuss verification and validation through collaboration with efforts such as AM-Bench, a set of benchmark test problems under development by a team led by the Nationalmore » Institute of Standards and Technology.« less

Authors:
ORCiD logo [1];  [2];  [2];  [1];  [3]; ORCiD logo [2];  [1];  [1];  [2]; ORCiD logo [3];  [4];  [5];  [3];  [1];  [1];  [1];  [2];  [1];  [1];  [1]
+ Show Author Affiliations
  1. Oak Ridge National Laboratory (ORNL), Oak Ridge, TN, USA
  2. Lawrence Livermore National Laboratory (LLNL), Livermore, CA, USA
  3. Los Alamos National Laboratory (LANL), Los Alamos, NM, USA
  4. The Barnes Global Advisors, Stuart, FL, USA
  5. National Institute of Standards and Technology (NIST), Gaithersburg, MD, USA
Publication Date:
Research Org.:
Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States); Los Alamos National Laboratory (LANL), Los Alamos, NM (United States); Lawrence Livermore National Laboratory (LLNL), Livermore, CA (United States)
Sponsoring Org.:
USDOE Office of Science (SC); USDOE National Nuclear Security Administration (NNSA)
OSTI Identifier:
1839327
Alternate Identifier(s):
OSTI ID: 1883992; OSTI ID: 2290298
Report Number(s):
LA-UR-21-27894
Journal ID: ISSN 1094-3420
Grant/Contract Number:  
AC05-00OR22725; 89233218CNA000001; AC52-07NA27344
Resource Type:
Published Article
Journal Name:
International Journal of High Performance Computing Applications
Additional Journal Information:
Journal Name: International Journal of High Performance Computing Applications Journal Volume: 36 Journal Issue: 1; Journal ID: ISSN 1094-3420
Publisher:
SAGE Publications
Country of Publication:
United States
Language:
English
Subject:
97 MATHEMATICS AND COMPUTING; 3D printing; coupled physics; metal additive manufacturing; microstructure; multiscale materials

Citation Formats

Turner, John A., Belak, James, Barton, Nathan, Bement, Matthew, Carlson, Neil, Carson, Robert, DeWitt, Stephen, Fattebert, Jean-Luc, Hodge, Neil, Jibben, Zechariah, King, Wayne, Levine, Lyle, Newman, Christopher, Plotkowski, Alex, Radhakrishnan, Balasubramaniam, Reeve, Samuel Temple, Rolchigo, Matthew, Sabau, Adrian, Slattery, Stuart, and Stump, Benjamin. ExaAM: Metal additive manufacturing simulation at the fidelity of the microstructure. United States: N. p., 2022. Web. doi:10.1177/10943420211042558.
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Turner, John A., Belak, James, Barton, Nathan, Bement, Matthew, Carlson, Neil, Carson, Robert, DeWitt, Stephen, Fattebert, Jean-Luc, Hodge, Neil, Jibben, Zechariah, King, Wayne, Levine, Lyle, Newman, Christopher, Plotkowski, Alex, Radhakrishnan, Balasubramaniam, Reeve, Samuel Temple, Rolchigo, Matthew, Sabau, Adrian, Slattery, Stuart, & Stump, Benjamin. ExaAM: Metal additive manufacturing simulation at the fidelity of the microstructure. United States. https://doi.org/10.1177/10943420211042558
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Turner, John A., Belak, James, Barton, Nathan, Bement, Matthew, Carlson, Neil, Carson, Robert, DeWitt, Stephen, Fattebert, Jean-Luc, Hodge, Neil, Jibben, Zechariah, King, Wayne, Levine, Lyle, Newman, Christopher, Plotkowski, Alex, Radhakrishnan, Balasubramaniam, Reeve, Samuel Temple, Rolchigo, Matthew, Sabau, Adrian, Slattery, Stuart, and Stump, Benjamin. Mon . "ExaAM: Metal additive manufacturing simulation at the fidelity of the microstructure". United States. https://doi.org/10.1177/10943420211042558.
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@article{osti_1839327,
title = {ExaAM: Metal additive manufacturing simulation at the fidelity of the microstructure},
author = {Turner, John A. and Belak, James and Barton, Nathan and Bement, Matthew and Carlson, Neil and Carson, Robert and DeWitt, Stephen and Fattebert, Jean-Luc and Hodge, Neil and Jibben, Zechariah and King, Wayne and Levine, Lyle and Newman, Christopher and Plotkowski, Alex and Radhakrishnan, Balasubramaniam and Reeve, Samuel Temple and Rolchigo, Matthew and Sabau, Adrian and Slattery, Stuart and Stump, Benjamin},
abstractNote = {Additive manufacturing (AM), or 3D printing, of metals is transforming the fabrication of components, in part by dramatically expanding the design space, allowing optimization of shape and topology. However, although the physical processes involved in AM are similar to those of welding, a field with decades of experimental, modeling, simulation, and characterization experience, qualification of AM parts remains a challenge. The availability of exascale computational systems, particularly when combined with data-driven approaches such as machine learning, enables topology and shape optimization as well as accelerated qualification by providing process-aware, locally accurate microstructure and mechanical property models. Here we describe the physics components comprising the Exascale Additive Manufacturing simulation environment and report progress using highly resolved melt pool simulations to inform part-scale finite element thermomechanics simulations, drive microstructure evolution, and determine constitutive mechanical property relationships based on those microstructures using polycrystal plasticity. We report on implementation of these components for exascale computing architectures, as well as the multi-stage simulation workflow that provides a unique high-fidelity model of process–structure–property relationships for AM parts. In addition, we discuss verification and validation through collaboration with efforts such as AM-Bench, a set of benchmark test problems under development by a team led by the National Institute of Standards and Technology.},
doi = {10.1177/10943420211042558},
journal = {International Journal of High Performance Computing Applications},
number = 1,
volume = 36,
place = {United States},
year = {Mon Jan 10 00:00:00 EST 2022},
month = {Mon Jan 10 00:00:00 EST 2022}
}
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https://doi.org/10.1177/10943420211042558
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