Development and evaluation of data transfer protocols in the fully coupled random cellular automata finite element model of dynamic recrystallization

Madej, Łukasz; Sitko, Mateusz; Legwand, Adam; Perzyński, K.; Michalik, Kazimierz

doi:10.1016/j.jocs.2018.03.007

Cited by 26 publications

(13 citation statements)

References 23 publications

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“…Simulation studies on microstructure evolution during recrystallization for a single-pass process have been performed by utilizing a CA model [ 9 , 10 , 11 ] and combining the CA method with the finite element method (FEM) [ 12 , 13 ] or the crystal plasticity finite element method (CPFEM) [ 14 , 15 , 16 ]. Those studies investigated the mesoscale grain structural evolution as well as the macro- or meso-scale mechanical response.…”

Section: Introductionmentioning

confidence: 99%

“…As a result of inherent experimental difficulties, these studies cannot fully elucidate the physical mechanisms contributing to grain refinement, because one needs to consider the temporal evolution of the multi-pass processes of recrystallization and the γ→α transformation, With the development of technologies in computer science, numerical simulation methods have popularized and become an important tool for understanding the mechanisms of microstructure formation during material processes due to their capabilities to present the visual, temporal evolution of microstructures. Among different numerical models, the cellular automata (CA) approach, combining both computational efficiency and simplicity [8], has been commonly applied to investigate various phenomena such as recrystallization [9][10][11][12][13][14][15][16][17][18][19][20][21][22], phase transformation [23][24][25][26][27][28][29][30][31], and grain coarsening [32,33].…”

Section: Introductionmentioning

confidence: 99%

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Multi-Scale Modeling of Microstructure Evolution during Multi-Pass Hot-Rolling and Cooling Process

Lin

Zou

et al. 2021

Materials

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In this work, a 6-pass hot-rolling process followed by air cooling is studied by means of a coupled multi-scale simulation approach. The finite element method (FEM) is utilized to obtain macroscale thermomechanical parameters including temperature and strain rate. The microstructure evolution during the recrystallization and austenite (γ) to ferrite (α) transformation is simulated by a mesoscale cellular automaton (CA) model. The solute drag effect is included in the CA model to take into account the influence of manganese on the γ/α interface migration. The driving force for α-phase nucleation and growth also involves the contribution of the deformation stored energy inherited from hot-rolling. The simulation renders a clear visualization of the evolving grain structure during a multi-pass hot-rolling process. The variations of the nonuniform, deformation-stored energy field and carbon concentration field are also reproduced. A detailed analysis demonstrates how the parameters, including strain rate, grain size, temperature, and inter-pass time, influence the different mechanisms of recrystallization. Grain refinement induced by recrystallization and the γα phase transformation is also quantified. The simulated final α-fraction and the average α-grain size agree reasonably well with the experimental microstructure.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Multi-Scale Modeling of Microstructure Evolution during Multi-Pass Hot-Rolling and Cooling Process

Lin

Zou

et al. 2021

Materials

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“…treatments, and then, the effective convection coefficient used in Eq. [8] was defined based on the recorded diagrams.…”

Section: Experimental Measurement Of Temperature Variationsmentioning

confidence: 99%

“…For instance, Zheng et al [7] simulated static recrystallization kinetics in carbon steels utilizing two-dimensional cellular automata modeling coupled with crystal plasticity formulation. Madej et al [8] developed a coupled cellular automata-finite element algorithm for predicting the rate of dynamic recrystallization during deformation. Lin et al [9] developed a probabilistic cellular automaton to simulate static recrystallization in Ni-based superalloys, and the rate of recrystallization and grain structure were predicted.…”

Section: Introductionmentioning

confidence: 99%

Microstructural Changes During Static Recrystallization of Austenitic Stainless Steel 304L: Cellular Automata Simulation

Alavi

Serajzadeh

2020

Metallogr. Microstruct. Anal.

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Static recrystallization and microstructural changes in austenitic stainless steel 304L were studied. The rolling experiments at 200 °C were carried out, and then, annealing treatment was made at temperatures ranging between 500 and 830 °C. A model was also developed to simulate the kinetics of non-isothermal recrystallization within the rolled steel. The distribution of plastic strains during rolling was predicted utilizing an elastic-plastic finite element formulation performed in ABAQUS/ Explicit, while the predicted results were used to generate the as-rolled microstructure and to estimate the stored energy. Finally, microstructural-thermal model based on cellular automata was developed to evaluate the rate of static recrystallization within the rolled steel. The comparison between experimental and simulations showed a good consistency. The predictions illustrated that inhomogeneous distribution of plastic strain was produced during multi-pass rolling leading to different rates of recrystallization in the center and the surface regions of the rolled plate. The onset temperature of recrystallization was found about 700 °C, and the activation energies for nucleation and growth for recrystallization were determined as 180 kJ/ mol and 240 kJ/mol, respectively. It was found that homogenous nucleation mechanism can be operative in recrystallization of multi-pass rolled steel, i.e., for reduction of 40% or higher.

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“…The microstructure morphology can be replicated based on the experimental data (e.g., computed tomography) or generated numerically. In the latter case, these kinds of models are called synthetic microstructure models [3][4][5][6]. Finally, microscale models are used to calculate the flow stress values for the macroscale model, and multiscale modelling framework is established [7,8].…”

Section: Introductionmentioning

confidence: 99%

Development of communication mechanism for the fully coupled multiscale model of 3D compression test

2020

Self Cite

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The implementation of a dedicated communication mechanism between micro-and macroscale models of the fully coupled multiscale numerical approach is the topic of the paper. The presented solution is based on the System V IPC message queue that is part of modern Linux-based operating systems. Developed and implemented approach is validated with a selected case study of a 3D compression test with the microscale model based on an implicit Johnson-Cook model, which is solved as a separate external process. The communication mechanism can be the basis of the efficient fully coupled FE 2 model.

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Development and evaluation of data transfer protocols in the fully coupled random cellular automata finite element model of dynamic recrystallization

Cited by 26 publications

References 23 publications

Multi-Scale Modeling of Microstructure Evolution during Multi-Pass Hot-Rolling and Cooling Process

Multi-Scale Modeling of Microstructure Evolution during Multi-Pass Hot-Rolling and Cooling Process

Microstructural Changes During Static Recrystallization of Austenitic Stainless Steel 304L: Cellular Automata Simulation

Development of communication mechanism for the fully coupled multiscale model of 3D compression test

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