Multi-Scale Modeling of Dynamic Recrystallization in Metals Undergoing Thermo-Mechanical Processing

This study focuses on devising a unified multi-scale numerical framework to predict the grain size evolution by dynamic recrystallization in metals and alloys for an array of severe plastic thermo-mechanical deformation conditions. The model is developed to predict the temporal and spatial grain size evolution of the material subjected to high strain rate and temperature dependent deformation. Dynamic recrystallization evolves by either a continuous grain refinement mechanism around room temperatures or by a discontinuous grain nucleation and growth mechanism at elevated temperatures. The multi-scale model bridges a dislocation density-based constitutive framework with microscale physics-based recrystallization laws to predict both the types of recrystallization phenomena simultaneously. The simulations are conducted within an integrated probabilistic cellular automata-finite element framework to capture the physics of the recrystallization mechanisms. High strain rate loading experiments in conjunction with microstructural characterization tests are conducted for pure copper to characterize the dynamic grain size evolution in the material and evaluated against the model predictions. Synchrotron X-rays are integrated with a modified Kolsky tension bar to conduct in situ temporal characterization of the grain refinement mechanism operating during the dynamic deformation of copper and evaluated against the developed model kinetics. Finally, the model is implemented to predict the grain size evolution developed during the friction stir spot welding of Al 6061-T6 for varying tool rotational speeds. The experiments show that the original microstructure is completely replaced by a recrystallized fine-grained microstructure with the final average grain size and morphology dependent on the process parameters. The model accurately predicts the process temperature rise with increasing tool rotational speeds, which results in a higher rate of grain coarsening during the dynamic recrystallization phenomenon

Dynamic recrystallization model during hot working by coupling phase-field method and finite element method

Multiscale model for hot–working, which can investigate the macroscopic mechanical behavior based on the microstructure evolution, has been developed by coupling the finite element (FE) method and phase–field (PF) method. Here, the microstructure evolutions in dynamic recrystallization are simulated by the multi–phase–field-dynamic recrystallization (MPF–DRX) model. The microscopic simulations are performed in every element used in the finite element simulations to calculate the macroscopic mechanical behaviors

Stochastic modeling of discontinuous dynamic recrystallization at finite strains in hcp metals

We present a model that aims to describe the effective, macroscale material response as well as the underlying mesoscale processes during discontinuous dynamic recrystallization under severe plastic deformation. Broadly, the model brings together two well-established but distinct approaches – first, a continuum crystal plasticity and twinning approach to describe complex deformation in the various grains, and second, a discrete Monte-Carlo-Potts approach to describe grain boundary migration and nucleation. The model is implemented within a finite-strain Fast Fourier Transform-based framework that allows for efficient simulations of recrystallization at high spatial resolution, while the grid-based Fourier treatment lends itself naturally to the Monte-Carlo approach. The model is applied to pure magnesium as a representative hexagonal closed packed metal, but is sufficiently general to admit extension to other material systems. Results demonstrate the evolution of the grain architecture in representative volume elements and the associated stress–strain history during the severe simple shear deformation typical of equal channel angular extrusion. We confirm that the recrystallization kinetics converge with increasing grid resolution and that the resulting model captures the experimentally observed transition from single- to multi-peak stress–strain behavior as a function of temperature and rate

Recrystallization simulation by use of cellular automata

This report is about cellular automaton models in materials science. It gives an introduction to the fundamentals of cellular automata and reviews applications particularly for predicting recrystallization phenomena. Cellular automata for recrystallization are typically discrete in time, physical space, and orientation space and often use quantities such as dislocation density and crystal orientation as state variables. They can be defined on a regular or non-regular 2D or 3D lattice considering the first, second, and third neighbor shell for the calculation of the local driving forces. The kinetic transformation rules are usually formulated to map a linearized symmetric rate equation for sharp grain boundary segment motion. While deterministic cellular automata directly perform cell switches by sweeping the corresponding set of neighbor cells in accord with the underlying rate equation, probabilistic cellular automata calculate the switching probability of each lattice point and make the actual decision about a switching event by evaluating the local switching probability using a Monte Carlo step. Switches are in a cellular automaton algorithm generally performed as a function of the previous state of a lattice point and the state of the neighboring lattice points. The transformation rules can be scaled in terms of time and space using for instance the ratio of the local and the maximum possible grain boundary mobility, the local crystallographic texture, the ratio of the local and the maximum occurring driving forces, or appropriate scaling measures derived from a real initial specimen. The cell state update in a cellular automaton is made in synchrony for all cells. The present report will particularly deal with the prediction of the kinetics, microstructure, and texture of recrystallization. Couplings between cellular automata and crystal plasticity finite element models will be also discussed

Some Critical Thoughts on Computational Materials Science

1. A Model is a Model is a Model is a Model The title of this report is of course meant to provoke. Why? Because there always exists a menace of confusing models with reality. Does anyone now refer to “first principles simulations”? This point is well taken. However, practically all of the current predictions in this domain are based on simulating electron dynamics using local density functional theory. These simulations, though providing a deep insight into materials ground states, are not exact but approximate solutions of the Schrödinger equation, which - not to forget - is a model itself [1]. Does someone now refer to “finite element simulations”? This point is also well taken. However, also in this case one has to admit that approximate solutions to large sets of non-linear differential equations formulated for a (non-existing) continuum under idealized boundary conditions is what it is: a model of nature but not reality. But us let calm down and render the discussion a bit more serious: current methods of ground state calculations are definitely among the cutting-edge disciplines in computational materials science and the community has learnt much from it during the last years. Similar aspects apply for some continuum-based finite element simulations. After all this report is meant to attract readers into this exciting field and not to repulse them. And for this reason I feel obliged to first make a point in underscoring that any interpretation of a research result obtained by computer simulation should be accompanied by scrutinizing the model ingredients and boundary conditions of that calculation in the same critical way as an experimentalist would check his experimental set-up

Dynamic recrystallization of Ti-based materials at crack surfaces at elevated temperatures –hybrid cellular automata simulation

In the study a Hybrid discrete-continuum Cellular Automata approach (HCA) based on coupling classical thermomechanics and logics of CA-switching to simulate new phase generation and grain growth is proposed. On the basis of the HCA the numerical experiments on thermal-activated recrystallization of pure titanium in the vicinity of crack edges were conducted. In doing so the 3D cellular automaton simulates the behavior of the V-notched specimen region that imitates the crack tip vicinity. Numerical experiments are aimed at calculating heat expansion in the material under study through taking into account thermal stresses accumulation and microrotation initiation. The latter gives rise to generation of new defects and increasing the local entropy