DocumentCode :
3364313
Title :
Monte Carlo simulation of microstructure evolution during thermo-mechanical rolling of steel using grid computing technology
Author :
Hore, Sheuli ; Das, Sajal K. ; Banerjee, Sean ; Mukherjee, Sayan
Author_Institution :
Nat. Metall. Lab., Jamshedpur, India
fYear :
2013
fDate :
21-23 Feb. 2013
Firstpage :
1
Lastpage :
7
Abstract :
A Monte Carlo (MC) simulation methodology using high performance computing (HPC) has been proposed to characterize grain growth kinetics and recrystallisation phenomena during hot rolling of C-Mn and TRIP steels. The simulation framework comprises of mesoscale modelling of evolution of grain growth and microstructure incorporating the system energetics of grain boundary energy and stored energy which are essentially the driving force for the evolution process. An in-house MC computer code has been developed and implemented in the GARUDA grid. This facilitated achieving faster convergence of the MC algorithm for a given lattice structure. The simulated grain growth and microstructure evolution have been successfully validated with the published data. It is inferred that the MC simulation in conjunction with HPC grid capability can be a powerful tool to simulate material behaviour at mesoscopic scale during thermo-mechanical processing of materials.
Keywords :
Monte Carlo methods; carbon steel; digital simulation; grain boundaries; grain growth; grid computing; hot rolling; manganese; parallel processing; production engineering computing; recrystallisation; thermomechanical treatment; GARUDA grid; HPC grid capability; MC computer code; MC simulation methodology; Monte Carlo simulation methodology; TRIP steels; grain boundary energy; grain growth evolution mesoscale modelling; grid computing technology; growth kinetics; high performance computing; hot rolling; lattice structure; material behaviour simulation; material thermo-mechanical processing; microstructure evolution; recrystallisation phenomena; steel thermo-mechanical rolling; stored energy; Computational modeling; Grain size; Kinetic theory; Lattices; Microstructure; Predictive models; Steel; C-Mn steel; Grid computing; Monte Carlo simulation; Trip steel; average grain-size; grain growth evolution; recrystallisation kinetics;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Parallel Computing Technologies (PARCOMPTECH), 2013 National Conference on
Conference_Location :
Bangalore
Print_ISBN :
978-1-4799-1589-7
Type :
conf
DOI :
10.1109/ParCompTech.2013.6621406
Filename :
6621406
Link To Document :
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