Multi scale cellular automata and finite element based model for cold deformation and annealing of a ferritic–pearlitic microstructure

Madej, Łukasz; Sieradzki, L.; Sitko, Mateusz; Perzyński, K.; Radwański, Krzysztof; Kuziak, R.

doi:10.1016/j.commatsci.2013.04.020

Cited by 57 publications

(25 citation statements)

References 22 publications

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“…To capture differences in grain flows due to various crystallographic orientations in the reality, a diversification of the flow curves for each grain is introduced using the Gaussian distribution. Thus, each grain is described by slightly different flow stress values [12]. Differences in crystallographic aspects of deformation are not considered in the present model as conventional finite element model is applied.…”

Section: Finite Element Model Based On Digital Materials Representatiomentioning

confidence: 99%

Cellular Automata Finite Element Approach for Modelling Microstructure Evolution under Thermo-Mechanical Processing Conditions

Gołąb¹,

Sitko²,

Szyndler³

et al. 2014

Lecture Notes in Computer Science

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Abstract. The concurrent cellular automata finite element (CAFE) approach for modelling microstructure evolution under thermo-mechanical processing conditions is the subject of the present work. Particular attention is put on modelling two phenomena, static recrystallization after deformation and phase transformation during heating. Details of the developed models are presented within the paper. Both models are implemented based on the CA Framework, which is also described in the work. Finally cellular automata approaches are combined with the finite element model based on the digital material representation idea. The numerical modelling of complex multistage hot deformation process was selected as a case study to show capabilities of the developed cellular automata finite element model.

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Section: Finite Element Model Based On Digital Materials Representatiomentioning

confidence: 99%

Cellular Automata Finite Element Approach for Modelling Microstructure Evolution under Thermo-Mechanical Processing Conditions

Gołąb¹,

Sitko²,

Szyndler³

et al. 2014

Lecture Notes in Computer Science

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show abstract

“…The CA method was widely used in various fields of research, and in metal forming, it was successively applied to simulate strain localization [132], dynamic recrystallization [84], cold deformation and annealing [129], and other phenomena.…”

Section: Multi-scale Multi-physics and Multi-resolution Modelsmentioning

confidence: 99%

Metal forming beyond shaping: Predicting and setting product properties

et al. 2015

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“…The input microstructure for CA model was obtained from earlier ferrite recrystallization model described in. 21) This microstructure consists of deformed pearlite and equiaxed recrystallized ferrite grains. Several state variables and internal variables are included in the CA model to comprehend the process of both carbon diffusion and interface mobility.…”

Section: Description Of Phase Transformation Model During Heatingmentioning

confidence: 99%

Sensitivity Analysis of the Finite Difference 2-D Cellular Automata Model for Phase Transformation during Heating

et al. 2015

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Sensitivity analysis of the Finite Difference Cellular Automata model for Dual Phase steel phase transformation during heating was performed in the present work. The main goal of the work was to determine the process parameters that are most important throughout transformation and should be particularly considered during the identification of model parameters: deformation, coefficients related with grains nucleation, activation energy, pre-exponential factor, and curvature parameters. The Morris OAT is a screening method capable of recognising the important factors of model and global sensitivity analysis was computed using this method. Different responses of the model outcomes were obtained by changing subsequent model input parameters. Results from Morris OAT design showed that deformation and activation energy have the most significant impact on the kinetics of phase transformation whereas average grain size strongly depends on all of the model parameters. Next, local sensitivity analysis was considered to check the behavior of each parameter locally. Finally both global and local sensitivities were compared and it was found that local sensitivity analysis in the case of such complex models can lead to inaccurate results.

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Multi scale cellular automata and finite element based model for cold deformation and annealing of a ferritic–pearlitic microstructure

Cited by 57 publications

References 22 publications

Cellular Automata Finite Element Approach for Modelling Microstructure Evolution under Thermo-Mechanical Processing Conditions

Cellular Automata Finite Element Approach for Modelling Microstructure Evolution under Thermo-Mechanical Processing Conditions

Metal forming beyond shaping: Predicting and setting product properties

Sensitivity Analysis of the Finite Difference 2-D Cellular Automata Model for Phase Transformation during Heating

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