Open Access Open Access  Restricted Access Subscription Access

Evolving Digital Microstructures through Monte Carlo Simulation - A tool to Study Grain Growth in Polycrystalline Materials


Affiliations
1 Department of Mechanical Engineering, M. S. Ramaiah Institute of Technology, Bangalore, India
2 School of Aerospace Engineering, Georgia Institute of Technology, Atlanta 30332, United States
3 Valley Stream Drive 513, Newark, Delaware 19702, United States
4 Department of Mechanical Engineering, Atria Institute of Technology, Bangalore, India
 

Microstructures of polycrystalline materials carry valuable information which helps predict their mechanical behavior through study of their grain shapes and sizes.The average grain size, especially, has a profound effect on the strength of materials, as given by the Hall-Petch equation. The average grain size of polycrystals are known to vary according to degree of growth driven by curvature on the one hand, and on the other hand stunted by the presence of second phase particles. The study of growth and stagnation of grain size in polycrystals has been widely aided by the simulation approach of generating digital microstructures, which have been able to mimic the real microstructures closely. This study shows how the Monte Carlo simulation approach has been applied to generate realistic but generic microstructures, both in color and black&white, and, which follow the basic guide lines of formation of real microstructures.

Keywords

Grain Size Distribution, Metropolis Algorithm, Monte Carlo Simulation, Monte Carlo Steps.
User
Call for Papers
Notifications
JOURNAL COVERS
  

  • Martin JW, Doherty RD, Cantor B. Stability of microstructure in metallic systems, Cambridge Solid State Science Series. 2nd ed. Cambridge University Press; 1997.
  • Anderson MP, Srolovitz DJ, Grest GS, Sahni PS. Computer simulation of grain growth-I. Kinetics, Acta Metall. 1984; 32:783–92.
  • Anderson MP, Grest GS, Srolovitz DJ. Computer simulation of grain growth in three dimensions. Philosophical Magazine. 1989; B59(3):293–329.
  • Srolovitz DJ, Anderson MP, Grest GS, Sahni PS. Computer Simulation of grain growth-III. Influence of a particle dispersion. Acta Metall. 1984; 32:1429–38.
  • Zollner D, Streitenberger P. Three-dimensional normal grain growth: Monte Carlo Potts model simulation and analytical mean field theory. Scripta Mater. 2006; 54:1697–702.
  • Huang CM, Joanne CL, Patnaik BSV, Jayaganthan R. Monte Carlo simulation of grain growth in polycrystalline materials. App Surf Sc. 2006; 252:3997–4002.
  • Phaneesh KR, Bhat A, Mukherjee G, Kashyap KT. On grain growth kinetics in two-phase polycrystalline materials through Monte Carlo simulation. Bull Mater Sci. 2013 Aug; 36(4):709–13.
  • Smith CS. Grains, phases and interfaces, an interpretation of microstructures. Trans A.I.M.E. 1948; 175:15.
  • Feltham P. Grain growth in metals. Acta Metall. 1957; 5:97–105.
  • Ulam S, Richtmyer RD, Neumann JV. Statistical methods in neutron diffusion. Los Alamos Scientific Laboratory Report LAMS – 551. 1947.

Abstract Views: 199

PDF Views: 110




  • Evolving Digital Microstructures through Monte Carlo Simulation - A tool to Study Grain Growth in Polycrystalline Materials

Abstract Views: 199  |  PDF Views: 110

Authors

K. R. Phaneesh
Department of Mechanical Engineering, M. S. Ramaiah Institute of Technology, Bangalore, India
Anirudh Bhat
School of Aerospace Engineering, Georgia Institute of Technology, Atlanta 30332, United States
G. Mukherjee
Valley Stream Drive 513, Newark, Delaware 19702, United States
K. T. Kashyap
Department of Mechanical Engineering, Atria Institute of Technology, Bangalore, India

Abstract


Microstructures of polycrystalline materials carry valuable information which helps predict their mechanical behavior through study of their grain shapes and sizes.The average grain size, especially, has a profound effect on the strength of materials, as given by the Hall-Petch equation. The average grain size of polycrystals are known to vary according to degree of growth driven by curvature on the one hand, and on the other hand stunted by the presence of second phase particles. The study of growth and stagnation of grain size in polycrystals has been widely aided by the simulation approach of generating digital microstructures, which have been able to mimic the real microstructures closely. This study shows how the Monte Carlo simulation approach has been applied to generate realistic but generic microstructures, both in color and black&white, and, which follow the basic guide lines of formation of real microstructures.

Keywords


Grain Size Distribution, Metropolis Algorithm, Monte Carlo Simulation, Monte Carlo Steps.

References