MANIPULATING THE METROPOLIS ALGORITHM TO YIELD GRAIN GROWTH KINETICS OF REAL METALS – A MONTE CARLO SIMULATION ATTEMPT

1 PHANEESH Kalale. R
Co-authors:
2 RAJENDRA. P 3 PRADEEP KUMAR K. V 4 ANIRUDH Bhat.
Institutions:
1 Ramaiah Institute of Technology, Faculty of Mechanical, Bangalore, India, krphaneesh@gmail.com
2 Ramaiah Institute of Technology, Faculty of Mechanical, Bangalore, India, p.rajendra06@gmail.com
3 Ramaiah Institute of Technology, Faculty of Mechanical, Bangalore, India, pradeepkv.5987@gmail.com
4 Georgia Institute of Technology, Faculty of Mechanical, Atlanta, USA, anirudhbhat86@gmail.com
Conference:
27th International Conference on Metallurgy and Materials, Hotel Voronez I, Brno, Czech Republic, EU, May 23rd - 25th 2018
Proceedings:
Proceedings 27th International Conference on Metallurgy and Materials
Pages:
87-92
ISBN:
978-80-87294-84-0
ISSN:
2694-9296
Published:
24th October 2018
Proceedings of the conference were published in Web of Science and Scopus.
Metrics:
31 views / 19 downloads
Abstract

A modification to the Metropolis algorithm, which drives Monte Carlo (MC) simulation of grain growth, is suggested here. Though MC simulation allows for study of effects of variables on growth kinetics and growth inhibition in ways not possible by experimentation, the method has been largely limited to the understanding of these phenomena with a generic metal in mind rather than a specific one. During MC simulation, variables such as time, temperature and grain size have only their simulation equivalents considered and are assumed the same for all materials. The present work manipulates the Metropolis algorithm in such a way that it mimics growth kinetics of known metals, as observed through experimentation. We propose Kalale-Bhat-Mukherjee-Kashyap (KBMK) factors, which help yield precise grain growth exponents. This, along with other results relating length and time scales between real and simulated microstructures, can pave the way for an effective Material-Specific MC simulation of grain growth in future.

Keywords: Metropolis Algorithm; Hamiltonian; Grain growth exponent; MCS; KBMK factors
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