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Title: Simulation of metal additive manufacturing microstructures using kinetic Monte Carlo

Additive manufacturing (AM) is of tremendous interest given its ability to realize complex, non-traditional geometries in engineered structural materials. But, microstructures generated from AM processes can be equally, if not more, complex than their conventionally processed counterparts. While some microstructural features observed in AM may also occur in more traditional solidification processes, the introduction of spatially and temporally mobile heat sources can result in significant microstructural heterogeneity. While grain size and shape in metal AM structures are understood to be highly dependent on both local and global temperature profiles, the exact form of this relation is not well understood. We implement an idealized molten zone and temperature-dependent grain boundary mobility in a kinetic Monte Carlo model to predict three-dimensional grain structure in additively manufactured metals. In order to demonstrate the flexibility of the model, synthetic microstructures are generated under conditions mimicking relatively diverse experimental results present in the literature. Simulated microstructures are then qualitatively and quantitatively compared to their experimental complements and are shown to be in good agreement.
Authors:
 [1] ;  [2] ;  [3]
  1. Sandia National Lab. (SNL-NM), Albuquerque, NM (United States). Computational Materials and Data Science
  2. Sandia National Lab. (SNL-NM), Albuquerque, NM (United States). Materials Mechanics
  3. Sandia National Lab. (SNL-NM), Albuquerque, NM (United States). Multiscale Science
Publication Date:
Report Number(s):
SAND2017-4189J
Journal ID: ISSN 0927-0256; PII: S0927025617301751
Grant/Contract Number:
AC04-94AL85000
Type:
Published Article
Journal Name:
Computational Materials Science
Additional Journal Information:
Journal Volume: 135; Journal Issue: C; Journal ID: ISSN 0927-0256
Publisher:
Elsevier
Research Org:
Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
Sponsoring Org:
USDOE National Nuclear Security Administration (NNSA)
Country of Publication:
United States
Language:
English
Subject:
36 MATERIALS SCIENCE; 97 MATHEMATICS AND COMPUTING; kinetic Monte Carlo; microstructure; additive manufacturing
OSTI Identifier:
1393265
Alternate Identifier(s):
OSTI ID: 1356842