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A multiscale coupled Monte Carlo model to characterize microstructure evolution during hot rolling of Mo-TRIP steel
Authors:S Hore  SK Das  S Banerjee  S Mukherjee
Affiliation:1. CSIR-National Metallurgical Laboratory, Jamshedpur 831007, India;2. Department of Metallurgical and Materials Engineering, Jadavpur University, Kolkata 700032, India
Abstract:A multiscale modelling framework has been proposed to characterize microstructure evolution during hot strip rolling of transformation-induced plasticity (TRIP) steel. The modelling methodology encompasses a continuum dislocation density evolution model coupled with a lumped parameter heat transfer model which has been seamlessly integrated with a mesoscale Monte Carlo (MC) simulation technique. The dislocation density model computes the evolution of dislocation density and subsequently constitutive flow stress behaviour has been predicted and successfully validated with the published data. A lumped-parameter transient heat transfer model has been developed to calculate the average strip temperature in the time domain. The heat transfer model incorporates the effect of plastic work for different strain rates in the energy conservation formulation. A coupled initial value problem solver has been developed to integrate the system of stiff ordinary differential equations in the time domain to predict dislocation density and temperature profiles simultaneously. The temporal evolution of microstructure during hot rolling of TRIP steel is simulated by the MC method incorporating thermal and dislocation density data from the continuum models. Simulated microstructural maps, kinetics of recrystallization and grain size evolution have been generated in a 200 × 200 lattice system at different strain rates and temperatures. The simulation code has been implemented in a high-performance grid computing network. The predicted temporal evolution of grain size, recrystallized fractions and flow stress have been validated with the published literature and found to be in good agreement, confirming the predictive capability of the integrated model.
Keywords:Dynamic recrystallization  Microstructure  Dislocation density  Grain growth  Monte Carlo simulation
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