Papers by Daniel Bachniak
Rudy i Metale Nieżelazne, 2013
Computer methods in materials science, 2015
Statistically Similar Representative Volume Element (SSRVE) is a methodology applied for reductio... more Statistically Similar Representative Volume Element (SSRVE) is a methodology applied for reduction of complexity of material microstructure representation for dual phase materials like DP steels or composites. It is based on assumption that typical RVE can be further reduced into simplified form, which joined together periodically behaves the same as its larger equivalent. SSRVE is based on Non-Uniform Rational B-Splines representation and determined by using optimization procedure, where objective function includes comparison of mechanical properties, shape coefficients and statistical characteristics. The first of these elements requires application of Finite Element Method (FEM) allowing to simulate deformation of pattern RVE and current SSRVE within elastic or elastic-plastic range. This paper presents approach allowing to replace time consuming FEM with more efficient Isogeometric Analysis (IGA). The performance of new approach is analysed and compared to conventional FEM-based methodology. Special attention is put on possibilities of IGA implementation on heterogeneous hardware devices allowing to improve computational efficiency and decrease overall power consumption.
Applied mathematics, 2013
The main goal of the present research is to realize a sensitivity analysis of the developed compl... more The main goal of the present research is to realize a sensitivity analysis of the developed complex micro scale austenite (γ) to ferrite (α) phase transformation model. The proposed solution is implemented in the developed Cellular Automata Framework that facilitates implementation of various microstructure evolution models. Investigated model predicts phase transformation progress starting from the fully austenitic or two-phase regions. Theoretical background of the implemented austenite-ferrite phase transformation model is presented in the paper. The defined transition rules for initiation and subsequent growth as well as internal variables for each particular CA cell are also discussed. Examples of results obtained from the developed model, as well as model capabilities are shown. Finally sensitivity analysis using Morris OAT Design is also presented and discussed.
Journal of Metallic Materials, Aug 1, 2019
Archives of Metallurgy and Materials, Sep 1, 2015
Procedia Computer Science, 2017
Materials, 2020
The paper describes physical and numerical simulations of a manufacturing process composed of hot... more The paper describes physical and numerical simulations of a manufacturing process composed of hot forging and controlled cooling, which replace the conventional heat treatment technology. The objective was to investigate possibilities and limitations of the heat treatment with the use of the heat of forging. Three steels used to manufacture automotive parts were investigated. Experiments were composed of two sets of tests. The first were isothermal (TTT) and constant cooling rate (CCT) dilatometric tests, which supplied data for the identification of the numerical phase transformation model. The second was a physical simulation of the sequence forging-cooling on Gleeble 3800, which supplied data for the validation of the models. In the numerical part, a finite element (FE) thermal-mechanical code was combined with metallurgical models describing recrystallization and grain growth during forging and phase transformations during cooling. The FE model predicted distributions of the tem...
Metallurgical Research & Technology, 2021
The objectives of the paper were twofold. The first was exploring possibility of fast and reliabl... more The objectives of the paper were twofold. The first was exploring possibility of fast and reliable modelling of phase transformations during cooling of steels, accounting for the evolution of the carbon concentration in the austenite. Existing discrete models require long computing times and their application to optimization of industrial processes is limited. Therefore, a model based on the modified JMAK equation was proposed. Control of the carbon concentration in the austenite during ferritic and bainitic transformations allowed to predict incomplete austenite transformation and occurrence of the retained austenite. Moreover, prediction of the onset of pearlitic transformation after the bainitic was possible. The model was validated by comparison the predictions with the results of physical simulations. Numerical simulations for various industrial processes were performed. Problem of the difference in the incubation time between isothermal and constant cooling rate tests was raised.
Computer methods in materials science, 2015
Statistically Similar Representative Volume Element (SSRVE) is a methodology applied for reductio... more Statistically Similar Representative Volume Element (SSRVE) is a methodology applied for reduction of complexity of material microstructure representation for dual phase materials like DP steels or composites. It is based on assumption that typical RVE can be further reduced into simplified form, which joined together periodically behaves the same as its larger equivalent. SSRVE is based on Non-Uniform Rational B-Splines representation and determined by using optimization procedure, where objective function includes comparison of mechanical properties, shape coefficients and statistical characteristics. The first of these elements requires application of Finite Element Method (FEM) allowing to simulate deformation of pattern RVE and current SSRVE within elastic or elastic-plastic range. This paper presents approach allowing to replace time consuming FEM with more efficient Isogeometric Analysis (IGA). The performance of new approach is analysed and compared to conventional FEM-based...
Journal of Materials Engineering and Performance, 2018
Accuracy of phase transformation models depends on the correctness of coefficients evaluation, ad... more Accuracy of phase transformation models depends on the correctness of coefficients evaluation, adequate to the investigated material. Dilatometric tests combined with the inverse analysis are used to perform identification. Since the problem is nonlinear, analytical approach is not possible and the inverse solution is transferred into the optimization task. It leads to difficulties typical for optimization of multivariable function such as local minima and lack of proof of the uniqueness. The problem of the effectiveness and uniqueness of the inverse algorithms used for identification of phase transformation models for steels was investigated for two models. The first was a modified JMAK (Johnson-Mehl-Avrami-Kolmogorov) equation. The second was an upgrade of the Leblond equation, in which second-order derivative of the volume fraction with respect to time was introduced. In classical identification, the result for one transformation depends on the coefficients for the remaining transformations and optimization has to be performed several times until the compatibility between transformations is reached. To avoid encountered problems, complex optimization simultaneously for all coefficients in the models was performed. This approach was based on nature-inspired optimization techniques. Models with identified coefficients for various steels were validated in simulations of industrial processes of laminar cooling and continuous annealing of strips.
Materials and Manufacturing Processes, 2017
Concurrency and Computation: Practice and Experience, 2016
SummarySensitivity analysis is widely used in numerical simulations applied in industry. The robu... more SummarySensitivity analysis is widely used in numerical simulations applied in industry. The robustness of such applications is crucial, which means they have to be fast and precise at the same time. However, the conventional approach to sensitivity analysis assumes realization of multiple execution of computationally intensive simulations to discover input/output dependencies. In this paper, we present a novel computational approach for performing large‐scale sensitivity analysis integrated with an extended platform for parameter studies – Scalarm – to make use of modern e‐infrastructures for distribution and parallelization purposes, profitable for complicated industrial problems. Copyright © 2016 John Wiley & Sons, Ltd.
Archives of Metallurgy and Materials, 2015
The coupled finite element multiscale simulations (FE
Lecture Notes in Computer Science, 2016
Sensitivity Analysis is widely used in numerical simulations applied in industry. The robustness ... more Sensitivity Analysis is widely used in numerical simulations applied in industry. The robustness of such applications is crucial, which means that they have to be fast and precise at the same. However, conventional approach to Sensitivity Analysis assumes realization of multiple execution of computationally intensive simulations to discover input/output dependencies. In this paper we present approach based on Scalarm platform, allowing to accelerate Sensitivity Analysis calculations by using modern e-infrastructures for distribution and parallelization purposes. The paper contains both description of the proposed solution and results obtained for a selected industrial case study.
Archives of Civil and Mechanical Engineering, 2016
Abstract Presented work is focused on modelling of the phase transformation during laminar coolin... more Abstract Presented work is focused on modelling of the phase transformation during laminar cooling after hot rolling of dual phase steel strips. Conventional FE model describing heat transfer was used in the macroscale. The model based on the solution of the diffusion equation with moving boundary was selected to predict properties of the steel based on phase transformations which occur in microscale. Preliminary observations indicated that results depend on various parameters of the model, such as: diffusion coefficient, boundary velocity factor and cooling rate. Therefore, sensitivity analysis of the model with respect to these parameters was performed in order to enhance the predictive capabilities of the model and to simplify further solution.
Procedia Computer Science, 2015
ISIJ International, 2015
Sensitivity analysis of the Finite Difference Cellular Automata model for Dual Phase steel phase ... more 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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Papers by Daniel Bachniak