Predicting Mesoscale Microstructural Evolution in Electron Beam Welding

Using the kinetic Monte Carlo simulator, Stochastic Parallel PARticle Kinetic Simulator, from Sandia National Laboratories, a user routine has been developed to simulate mesoscale predictions of a grain structure near a moving heat source. Here, we demonstrate the use of this user routine to produce voxelized, synthetic, three-dimensional microstructures for electron-beam welding by comparing them with experimentally produced microstructures. When simulation input parameters are matched to experimental process parameters, qualitative and quantitative agreement for both grain size and grain morphology are achieved. The method is capable of simulating both single- and multipass welds. The simulations provide an opportunity for not only accelerated design but also the integration of simulation and experiments in design such that simulations can receive parameter bounds from experiments and, in turn, provide predictions of a resultant microstructure.

[1]  L. Anand,et al.  Plasticity of initially textured hexagonal polycrystals at high homologous temperatures: application to titanium , 2002 .

[2]  W. Kurz,et al.  Fundamentals of Solidification , 1990 .

[3]  Elizabeth A. Holm,et al.  Three-dimensional simulation of grain growth in a thermal gradient with non-uniform grain boundary mobility , 2008 .

[4]  Michel Rappaz,et al.  Modeling of fundamental phenomena in welds , 1995 .

[5]  W. Kurz,et al.  Fundamentals of Solidification: Fourth Revised Edition , 1998 .

[6]  Christopher R. Weinberger,et al.  Direct numerical simulations in solid mechanics for understanding the macroscale effects of microscale material variability , 2015 .

[7]  M. Groeber,et al.  DREAM.3D: A Digital Representation Environment for the Analysis of Microstructure in 3D , 2014, Integrating Materials and Manufacturing Innovation.

[8]  Matthias Militzer,et al.  Phase field modeling of microstructure evolution in steels , 2011 .

[9]  B. Blanpain,et al.  An introduction to phase-field modeling of microstructure evolution , 2008 .

[10]  Veena Tikare,et al.  Numerical simulation of microstructural evolution during sintering at the mesoscale in a 3D powder compact , 2010 .

[11]  Todd Palmer,et al.  Heat transfer and fluid flow during keyhole mode laser welding of tantalum, Ti–6Al–4V, 304L stainless steel and vanadium , 2007 .

[12]  T. DebRoy,et al.  Three-dimensional monte carlo simulation of grain growth in the heat-affected zone of a 2.25Cr-1Mo steel weld , 2000 .

[13]  E. Holm,et al.  How Grain Growth Stops: A Mechanism for Grain-Growth Stagnation in Pure Materials , 2010, Science.

[14]  J. W. Elmer,et al.  Improving Process Control in Electron Beam Welding Using the Enhanced Modified Faraday Cup , 2008 .

[15]  P. S. Sahni,et al.  Computer simulation of grain growth—II. Grain size distribution, topology, and local dynamics , 1984 .

[16]  A. De,et al.  Spatial variation of melt pool geometry, peak temperature and solidification parameters during laser assisted additive manufacturing process , 2015 .

[17]  T. Bieler,et al.  Overview of constitutive laws, kinematics, homogenization and multiscale methods in crystal plasticity finite-element modeling: Theory, experiments, applications , 2010 .

[18]  Yunzhi Wang,et al.  Phase field modeling of defects and deformation , 2010 .

[19]  A. Rollett,et al.  Crystal Plasticity Finite Element Method Simulations for a Polycrystalline Ni Micro-Specimen Deformed in Tension , 2014, Metallurgical and Materials Transactions A.

[20]  Grain topology in Ti–6Al–4V welds—Monte Carlo simulation and experiments , 2004 .

[21]  Elizabeth A. Holm,et al.  The computer simulation of microstructural evolution , 2001 .

[22]  Jianguo Lin,et al.  A controlled Poisson Voronoi tessellation for grain and cohesive boundary generation applied to crystal plasticity analysis , 2012 .

[23]  G. Spanos,et al.  Three-dimensional analysis of grain topology and interface curvature in a β-titanium alloy , 2010 .

[24]  Somnath Ghosh,et al.  A framework for automated analysis and simulation of 3D polycrystalline microstructures. , 2008 .

[25]  T. DebRoy,et al.  Measurements and Monte Carlo simulation of grain growth in the heat-affected zone of Ti–6Al–4V welds , 2004 .

[26]  Johannes E. Schindelin,et al.  Fiji: an open-source platform for biological-image analysis , 2012, Nature Methods.

[27]  V. Tikare,et al.  A hybrid simulation methodology for modeling dynamic recrystallization in UO2 LWR nuclear fuels , 2012 .

[28]  T. DebRoy,et al.  Three dimensional Monte Carlo simulation of grain growth during GTA welding of titanium , 2000 .

[29]  P. S. Sahni,et al.  Kinetics of the Q-state Potts model in two dimensions , 1983 .

[30]  V. Tikare,et al.  Hybrid Potts-phase field model for coupled microstructural–compositional evolution , 2012 .

[31]  Steve Plimpton,et al.  Fast parallel algorithms for short-range molecular dynamics , 1993 .

[32]  Johannes E. Schindelin,et al.  The ImageJ ecosystem: An open platform for biomedical image analysis , 2015, Molecular reproduction and development.

[33]  Bulatov,et al.  Kinetics and Anisotropy of the Monte Carlo Model of Grain Growth , 2014 .

[34]  F. Abdeljawad,et al.  Stabilization of nanocrystalline alloys via grain boundary segregation: A diffuse interface model , 2015 .