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Title: A Monte Carlo model for 3D grain evolution during welding

Abstract

Welding is one of the most wide-spread processes used in metal joining. However, there are currently no open-source software implementations for the simulation of microstructural evolution during a weld pass. Here we describe a Potts Monte Carlo based model implemented in the SPPARKS kinetic Monte Carlo computational framework. The model simulates melting, solidification and solid-state microstructural evolution of material in the fusion and heat-affected zones of a weld. The model does not simulate thermal behavior, but rather utilizes user input parameters to specify weld pool and heat-affect zone properties. Weld pool shapes are specified by Bezier curves, which allow for the specification of a wide range of pool shapes. Pool shapes can range from narrow and deep to wide and shallow representing different fluid flow conditions within the pool. Surrounding temperature gradients are calculated with the aide of a closest point projection algorithm. Furthermore, the model also allows simulation of pulsed power welding through time-dependent variation of the weld pool size. Example simulation results and comparisons with laboratory weld observations demonstrate microstructural variation with weld speed, pool shape, and pulsed-power.

Authors:
ORCiD logo [1];  [1];  [1]
  1. Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
Publication Date:
Research Org.:
Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
Sponsoring Org.:
USDOE National Nuclear Security Administration (NNSA)
OSTI Identifier:
1374751
Report Number(s):
SAND-2017-8231J
Journal ID: ISSN 0965-0393; 655911
Grant/Contract Number:  
AC04-94AL85000
Resource Type:
Journal Article: Accepted Manuscript
Journal Name:
Modelling and Simulation in Materials Science and Engineering
Additional Journal Information:
Journal Volume: 25; Journal Issue: 6; Journal ID: ISSN 0965-0393
Publisher:
IOP Publishing
Country of Publication:
United States
Language:
English
Subject:
36 MATERIALS SCIENCE; 97 MATHEMATICS AND COMPUTING; welding; grain growth; Potts Monte Carlo; solidification

Citation Formats

Rodgers, Theron M., Mitchell, John A., and Tikare, Veena. A Monte Carlo model for 3D grain evolution during welding. United States: N. p., 2017. Web. doi:10.1088/1361-651x/aa7f20.
Rodgers, Theron M., Mitchell, John A., & Tikare, Veena. A Monte Carlo model for 3D grain evolution during welding. United States. doi:10.1088/1361-651x/aa7f20.
Rodgers, Theron M., Mitchell, John A., and Tikare, Veena. Fri . "A Monte Carlo model for 3D grain evolution during welding". United States. doi:10.1088/1361-651x/aa7f20. https://www.osti.gov/servlets/purl/1374751.
@article{osti_1374751,
title = {A Monte Carlo model for 3D grain evolution during welding},
author = {Rodgers, Theron M. and Mitchell, John A. and Tikare, Veena},
abstractNote = {Welding is one of the most wide-spread processes used in metal joining. However, there are currently no open-source software implementations for the simulation of microstructural evolution during a weld pass. Here we describe a Potts Monte Carlo based model implemented in the SPPARKS kinetic Monte Carlo computational framework. The model simulates melting, solidification and solid-state microstructural evolution of material in the fusion and heat-affected zones of a weld. The model does not simulate thermal behavior, but rather utilizes user input parameters to specify weld pool and heat-affect zone properties. Weld pool shapes are specified by Bezier curves, which allow for the specification of a wide range of pool shapes. Pool shapes can range from narrow and deep to wide and shallow representing different fluid flow conditions within the pool. Surrounding temperature gradients are calculated with the aide of a closest point projection algorithm. Furthermore, the model also allows simulation of pulsed power welding through time-dependent variation of the weld pool size. Example simulation results and comparisons with laboratory weld observations demonstrate microstructural variation with weld speed, pool shape, and pulsed-power.},
doi = {10.1088/1361-651x/aa7f20},
journal = {Modelling and Simulation in Materials Science and Engineering},
number = 6,
volume = 25,
place = {United States},
year = {Fri Aug 04 00:00:00 EDT 2017},
month = {Fri Aug 04 00:00:00 EDT 2017}
}

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