Mateusz Sitko

Development of Dynamic Recrystallization Model Based on Cellular Automata Approach

Development of a numerical model for the dynamic recrystallization (DRX) on the basis of the Cellular Automata method and the Digital Material Representation (DMR) idea is the main goal of the present work. Basic assumptions (space definition, neighborhood type, state and internal variables) of the proposed model are presented and discussed. Particular attention is put on description of the developed transition rules used to replicate mechanisms leading to dynamic recrystallization. Finally, examples of obtained results of DRX morphology and kinetics are also presented within the paper.

Validation of Cellular Automata Model of Dynamic Recrystallization

Development and validation of the micro scale cellular automata (CA) model of dynamic recrystallization (DRX) were the main goals of the present paper. Major assumptions of the developed CA DRX model, which is based on the Digital Material Representation (DMR) concept, are described. Parameters like neighborhood type, state and internal variables of the proposed model and their influence on final results are presented and discussed. Particular attention was put on description of the developed transition rules used to replicate mechanisms leading to dynamic recrystallization. Finally, obtained results in the form of flow stress curves are compared with the experimental predictions.

Numerical Modelling of Fracture Based on Coupled Cellular Automata Finite Element Approach

Investigation of failure of Dual Phase steels on the basis of the developed concurrent cellular automata finite element model is the subject of the present paper. Physical background of phenomena responsible for failure in these steels is described first. Then details of the developed random cellular automata model are presented. Particular attention is put on proper definition of the transition rules describing initiation and propagation of fractures across the microstructure. Finally combined cellular automata finite element model is established. Examples of obtained results are also presented within the paper.

Optimised recrystallisation model using multiobjective evolutionary and genetic algorithms and k-optimality approach

The meta-models are constructed for static recrystallisation of dual phase steels using evolutionary neural nets (EvoNN). Four mutually conflicting objectives—(i) overall kinetics, (ii) grain size, (iii) the amount of strain and (iv) the precipitate volume fraction—are optimised simultaneously using an emerging k-optimal approach incorporated in the EvoNN, using a predator–prey genetic algorithm. The first objective involved minimisation of error with respect to experimental observation. The grain size and the amount of strain were minimised, whereas the precipitate volume fraction was maximised. The aim is to control the recrystallisation process in order to achieve desired material properties of dual phase steel during the final stages of heat treatment.

Parallelization of the Monte Carlo Static Recrystallization Model

Implementation of parallel version of the Monte Carlo MC static recrystallization algorithm for application in the PL-Grid Infrastructure is presented in this work. General assumptions of the algorithm are described first. This is followed by presentation of modifications that were introduced and are required for the parallel execution. Monte Carlo space division schemes between subsequent computing nodes are particularly addressed. Implementation details are also presented. Finally, influence of size and geometry of the MC space on calculations efficiency is discussed.

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

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.

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

Abstract Development and application of the hybrid fully coupled, random cellular automata finite element (RCAFE) approach to modelling dynamic recrystallization phenomenon, during a high temperature deformation is the overall goal of the paper. The finite element (FE) solver provides information on equivalent stress, equivalent strain, temperature fields as well as on geometry of deformed computational domain after each time step. These data are transferred to the developed random cellular automata (RCA) model, which is responsible for evaluation of corresponding microstructure morphology evolution and dislocation density changes under dynamic recrystallization (DRX) conditions. Finally, a set of data from the RCA part is send back to the FE solver and used as an input for the next time step. As a result, the fully coupled RCAFE model for simulation of a DRX progress is established. Crucial developments of the RCA model related to the space deformation and efficient neighbors selection are presented within the paper. However, particular attention is put on the development of efficient communication algorithms and methods for input/output data transfer between the FE and RCA modules. The communication protocols based on text files and sockets have different levels of complexity but both are based on the Abaqus VUMAT subroutine. Their capabilities and limitations are evaluated within the paper. Finally, an application of the proposed RCAFE method to simulation of a dynamic recrystallization progress at the level of single grains is presented and discussed to highlight capabilities of the model.

Physical and Numerical Simulation of Cold Rolling and Heating during Continuous Annealing of DP Steel Strips

Development of fast and efficient finite element model for rolling industrial grades of two DP steels was the subject of the present paper. Basis of the finite element framework, as well as material model development stages, are presented first. Model validation with experimental measurements is shown next. Finally, selected examples of multi scale modelling including microstructure level are presented to complement presented investigation and show possibilities of future developments.

Modelling of the cellular automata space deformation within the RCAFE framework

Development of the innovative approach to micro scale cellular automata (CA) space deformation during dynamic recrystallization process (DRX) is the main goal of the present paper. Major assumptions of the developed CA DRX model as well as novel space deformation algorithm, which is based on the random cellular automata concept and FE method, are described. Algorithms and methods to transfer input/output data between FE and CA are presented in detail. Visualization tool to analyze progress of deformation in the irregular CA space is also highlighted. Finally, initial results in the form of deformed and recrystallized microstructures are presented and discussed.

Modelling of the Microstructure Evolution Using Cellular Automata Framework and WorkFlow Approach

Development of an efficient and user friendly application (framework) for modelling microstructure evolution during thermo-mechanical processing using Cellular Automata (CA) method and WorkFlow approach is the subject of the present work. Description of the major assumptions and functionality of the developed framework is presented first. Then, major assumptions of the implemented cellular automata models dealing with simulation of phase transformation and static recrystallization are presented. Finally, the idea of the WorkFlow methodology is described and used to join the two CA microstructure evolution models into one complex solution. Examples of obtained results of microstructure behaviour during thermo-mechanical processing are also presented within the paper.