Krzysztof Bzowski

Identification of Multi-inclusion Statistically Similar Representative Volume Element for Advanced High Strength Steels by Using Data Farming Approach☆

Abstract Statistically Similar Representative Volume Element (SSRVE) is used to simplify computational domain for microstructure representation of material in multiscale modelling. The procedure of SSRVE creation is based on optimization loop which allows to find the highest similarity between SSRVE and an original material microstructure. The objective function in this optimization is built upon computationally intensive numerical methods, including simulations of virtual material deformation, which is very time consuming. To avoid such long lasting calcu- lations we propose to use the data farming approach to identification of SSRVE for Advanced High Strength Steels (AHSS) characterized by multiphase microstructure. The optimization method is based on a nature inspired approach which facilitates distribution and parallelization. The concept of SSRVE creation as well as the software architecture of the proposed solution is described in the paper in details. It is followed by examples of the results obtained for the identification of SSRVE parameters for DP steels which are widely exploited in modern automotive industry. Possible directions for further development as well as possible industrial applications are described in the conclusions.

OpenCL implementation of cellular automata finite element (CAFE) method

The implementation of multiscale numerical simulations on heterogeneous hardware architectures is presented in the paper. The simulations are composed of coupled micro and macro scale approaches, which are implemented by using cellular automata and finite element method respectively. Details of both of these methods are described in the papers as well. The simulations were performed for the problem of material heat treatment (macro scale) with simultaneous application of grain growth calculation (micro scale). Comparison of quantitative results obtained by using separated and coupled computing methods are presented in form of speedup and efficiency coefficients.

Model-Based Approach To Study Hot Rolling Mills With Data Farming.

The paper describes a computer system for simulating metallurgical rolling processes that consist of multiple steps, each of which is performed by a different type of devices. Both devices and processed materials are described with models, which can be dynamically reconfigured between simulation runs to study different device and environment configurations. Such an approach is especially crucial in technology design based on multi-iterative optimization procedures, for which an objective function uses computationally intensive algorithms. Due to the approach proposed in this paper, in the first stage of optimization more general and coarse models can be applied characterized by lower predictive capabilities and higher computational efficiency. Afterwards, when the optimization procedure finds a solution close to the optimal one, very detailed models can be used to obtain high quality solutions in the last few steps of calculations. To achieve such an objective a hybrid computer system able to use High Performance Computing (HPC) infrastructures was designed and implemented. The details of proposed approach are described, which is followed by presentation of a data farming platform responsible for distribution of complex numerical simulations onto various computer clusters. Finally, a concrete use case of a hot rolling mill is presented and analyzed.

Application of Sensitivity Analysis to Grid-Based Procedure Dedicated to Creation of SSRVE

The methods of sensitivity analysis allow to reduce computational cost of multi-iterative optimization procedures by finding the most influential parameters of the particular model. The article presents details of implementation of the numerical library, which is dedicated to sensitivity analysis and can be used by middleware in e-infrastructures. Then, the application of implemented methods to parallel and distributed models is presented on the example of Statistically Similar Representative Volume Element SSRVE in the field of metal forming. The influence of parameters, used in the SSRVE methodology, on accuracy of obtained results and performance of calculations is analyzed. The results of sensitivity analysis are presented in the article as well.

Experimental Validation of the Carbon Diffusion Model for Transformation of Ferritic-Pearlitic Microstructure into Austenite during Continuous Annealing of Dual Phase Steels

Modeling of the transformation of the starting ferritic-pearlitic microstructure into austenite during heating in continuous annealing process was the objective of the work. Kinetics of this transformation was predicted by solving Avrami equation as well as carbon diffusion equation with a moving boundary. Mathematical and numerical models describing austenitic phase transformation were created for the 1D and 2D domains. Developed models were solved using the Finite Difference, as well as the Finite Element Method. Results of the numerical simulations include austenite volume fraction and carbon segregation profiles in the austenite. The former were compared with the experimental data obtained in laboratory simulations of the continuous annealing. Developed and validated model was applied to simulation of the austenitic transformation during annealing of DP steels.

Computer Simulation of Transformation during TRIP Steel Rod Drawing

Axis pins, shafts and other rod-like parts are some of the main components of units and machines. They are manufactured from steel rods ranging from 7 to 60 mm in diameter after single-pass drawing. Unalloyed carbon steel grades are generally used to produce these items. TRIP steels application is advantageous in terms of achieving new properties when manufacturing steel rods. The initial billet size, the need to take account a transformation in TRIP steel microstructure and a great number of analysed technological conditions make it challenging to apply new materials into rod drawing process. The research aim is to explore the stress-strain state during rod drawing of steel TRIP700. Modified multiscale computer simulation method has been applied. The simulation method takes into account transformation of retained austenite into martensite during plastic deformation. Decreasing of the computational resource intensity and calculation time has been achieved by application of concept of Statistically Similar Representative Volume Element (SSRVE). Comparative analysis of rod drawing micromodels with and without the TRIP-effect simulation has been performed. The analysis showed that a values of equivalent strains in the deformation zone of a TRIP-ignored micromodel was three-four times lower than in a TRIP-factored micromodel. The analysis of simulation results has revealed that, due to a wide contact area with adjacent grains and interaction between microstructure elements, more intensive martensitic transformation occurred within larger grains of retained austenite. The micromodel shown that position and orientation of grains in the deformed TRIP steel microstructure are some of the factors that predetermine transformation of retained austenite. On the basis of simulation results recommendations on preparation of rod drawing conditions have been developed. Developed technological conditions provides ability to obtain: high-plasticity characteristics and high potential strain-hardening capability during exploitation of a future part; maximum strengthening throughout the cross-section of the rod after drawing; high strain-hardening of the surface layer only. The using of SSRVE concept reduced a number of elements within the micromodel in 20 times, while it lowered the calculation time in 16 times.

Modelling of stamping of DP steel automotive part accounting for the effect of hard components in the microstructure

The paper presents simulations of the manufacturing of the automotive part, which has high influence on improvement of passengers safety. Two approaches to the Finite Element (FE) modelling of stamping of a part that provides extra stiffening of construction subassemblies in the back of a car were considered. The first is conventional simulation, which assumes that the material is a continuum with flow stress model and anisotropy coefficients determined from the tensile tests. In the second approach two-phase microstructure of the DP steel is accounted for in simulations. The FE2 method, which belongs to upscaling techniques, is used. Representative Volume Element (RVE), which is the basis of the upscaling approach and reflects the real microstructure, was obtained by the image analysis of the micrograph of the DP steel. However, since FE2 simulations with the real picture of the microstructure in the micro scale, are extremely time consuming, the idea of the Statistically Similar Representative Volume Element (SSRVE) was applied. SSRVE obtained for the DP steel, used for production of automotive part, is presented in the paper in the form of 3D inclusion. The macro scale model of the simulated part is described in details, as well as the results obtained for macro and micro-macro simulations.The paper presents simulations of the manufacturing of the automotive part, which has high influence on improvement of passengers safety. Two approaches to the Finite Element (FE) modelling of stamping of a part that provides extra stiffening of construction subassemblies in the back of a car were considered. The first is conventional simulation, which assumes that the material is a continuum with flow stress model and anisotropy coefficients determined from the tensile tests. In the second approach two-phase microstructure of the DP steel is accounted for in simulations. The FE2 method, which belongs to upscaling techniques, is used. Representative Volume Element (RVE), which is the basis of the upscaling approach and reflects the real microstructure, was obtained by the image analysis of the micrograph of the DP steel. However, since FE2 simulations with the real picture of the microstructure in the micro scale, are extremely time consuming, the idea of the Statistically Similar Representative Volume El...