Evolving Close-to-Real Digital Microstructures in Polycrystalline Materials - A Monte Carlo Simulation Approach

K. R. Phaneesh, Anirudh Bhat, G. Mukherjee, K. T. Kashyap

Abstract

For more than three decades now simulation of recrystallization and grain growth phenomena in annealed metals have been studied through a variety of computer modeling techniques including that of Monte Carlo (MC) simulation. In this study, we have been able to show the efficiency of the MC technique by evolving simulated microstructures comparable very closely to real microstructures. The real microstructures were generated in about a 50% cold-worked alloy of Al-4% Cu (Duralumin) annealed to various degrees. The digital microstructures were evolved through a 2D simulation of a square lattice using Potts model Monte Carlo simulation technique based on the Metropolis algorithm. Through our work we have been able to show the close similarity between microstructures of real metals and microstructures digitally evolved through simulation, perhaps for the first time, thereby validating the MC technique as an efficient computer simulation tool for grain growth studies.

References

  1. S. (1984) Computer simulation of grain growth - I.
  2. Kinetics, Acta Metallurgica. 32. p.783-792. Burke, J. E. & Turnbull, D. (1952) Recrystallization and
  3. grain growth, Progress in Metal Physics. 3. p.220-292. Hillert, M. (1965) On the theory of normal and abnormal
  4. grain growth, Acta Metallurgica. 13 (3). p. 227-238. Humphreys, F. J. & Hatherly, M. (2005) Recrystallization
  5. and Related Annealing Phenomena. 2nd Ed. Elsevier,
  6. Miodownik, M. A. and Nestler, B. (2007)
  7. introduction to Microstructure Evolution. 1st Ed.
  8. T. (2013) Bulletin of Material Science. 36 (4). p. 709 -
  9. 37. p. 1375-1379. Saito, Y. (1997) The Monte Carlo simulation of
  10. & Engineering. A223. p. 114-124. Smith, C. S. (1952) Grain shapes and other metallurgical
  11. Cleveland, p. 65-108. Srolovitz, D. J., Anderson, M. P., Sahni P. S and Grest, G.
  12. S. (1984) Computer simulation of grain-growth: II.
  13. Acta Metallurgica. 32. p. 793-802. Ulam, S., Richtmyer, R. D. and Von Neumann, J. (1947)
  14. Scientific Laboratory Report. LAMS. p. 551. Wang, H., Liu, G. and Qin, X. (2009) Grain size
  15. distribution and topology in 3D simulation with large-
  16. Minerals, Metallurgy and Materials. 1. p. 37.
Download


Paper Citation


in Harvard Style

Phaneesh K., Bhat A., Mukherjee G. and Kashyap K. (2015). Evolving Close-to-Real Digital Microstructures in Polycrystalline Materials - A Monte Carlo Simulation Approach . In Proceedings of the 5th International Conference on Simulation and Modeling Methodologies, Technologies and Applications - Volume 1: SIMULTECH, ISBN 978-989-758-120-5, pages 118-124. DOI: 10.5220/0005531401180124


in Bibtex Style

@conference{simultech15,
author={K. R. Phaneesh and Anirudh Bhat and G. Mukherjee and K. T. Kashyap},
title={Evolving Close-to-Real Digital Microstructures in Polycrystalline Materials - A Monte Carlo Simulation Approach},
booktitle={Proceedings of the 5th International Conference on Simulation and Modeling Methodologies, Technologies and Applications - Volume 1: SIMULTECH,},
year={2015},
pages={118-124},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005531401180124},
isbn={978-989-758-120-5},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 5th International Conference on Simulation and Modeling Methodologies, Technologies and Applications - Volume 1: SIMULTECH,
TI - Evolving Close-to-Real Digital Microstructures in Polycrystalline Materials - A Monte Carlo Simulation Approach
SN - 978-989-758-120-5
AU - Phaneesh K.
AU - Bhat A.
AU - Mukherjee G.
AU - Kashyap K.
PY - 2015
SP - 118
EP - 124
DO - 10.5220/0005531401180124