Madej, Łukasz
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inżynieria materiałowa
informatyka techniczna i telekomunikacja
informatyka techniczna i telekomunikacja
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Item type:Article, Access status: Open Access , Full-field approaches for austenite-ferrite phase transformation simulations(Wydawnictwa AGH, 2025) Wermiński, Mariusz; Sitko, Mateusz; Madej, ŁukaszUnderstanding the local evolution of phase transformations in steels, particularly the γ (austenite) → α (ferrite) transformation, is crucial for controlling the microstructure and properties of steel components. Over recent decades, significant progress has been made in the numerical modeling of this complex phenomenon. This development has been driven by both scientific curiosity and industrial needs, especially in processes such as hot rolling, forging, thermal treatment, etc. The developed models have evolved from simple solutions based on local equilibrium to more complex approaches that consider local heterogeneities. Modern computational approaches, such as Phase-Field (PF), Level-Set (LS), Cellular Automata (CA), Monte Carlo (MC) or Vertex based simulations, allow for the precise reproduction of microstructural evolution considering local instabilities. They also enable the analysis of phase boundary motion in an explicit manner. These techniques also allow for direct integration with thermodynamic data and mechanical models, thereby better capturing the physical mechanisms of phase transformations, such as chemical composition, diffusion resistance, or the influence of deformation. An overview of the state of the art in this area is presented within the paper. The model’s concepts, assumptions, fundamental equations, advantages, limitations, and potential practical applications are summarized. Special attention is given to modeling the γ → α transformation by the Cellular Automata method. The importance of incorporating phenomena such as diffusion, nucleation, and growth is emphasized. The need for consistency between experimental results and simulations is also highlighted.Item type:Article, Access status: Open Access , The role of neighborhood density in the random cellular automata model of grain growth(Wydawnictwa AGH, 2021) Czarnecki, Michał; Sitko, Mateusz; Madej, ŁukaszThe paper focuses on adapting the random cellular automata (RCA) method concept for the unconstrained grain growth simulation providing digital microstructure morphologies for subsequent multi-scale simulations. First, algorithms for the generation of initial RCA cells alignment are developed, and then the influence of cells density in the computational domain on grain growth is discussed. Three different approaches are proposed based on the regular, hexagonal, and random cells' alignment in the former case. The importance of cellular automata (CA) cell neighborhood definition on grain growth model predictions is also highlighted. As a research outcome, random cellular automata model parameters that can replicate grain growth without artifacts are presented. It is identified that the acceptable microstructure morphology of the solid material is obtained when a mean number of RCA cells in the investigated neighborhood is higher than ten.Item type:Article, Access status: Open Access , A repeatability study of artificial neural network predictions in flow stress model development for a magnesium alloy(Wydawnictwa AGH, 2021) Siewior, Hubert; Madej, ŁukaszThis work is devoted to an evaluation of the capabilities of artificial neural networks (ANN) in terms of developing a flow stress model for magnesium ZE20. The learning procedure is based on experimental flow-stress data following inverse analysis. Two types of artificial neural networks are investigated: a simple feedforward version and a recursive one. Issues related to the quality of input data and the size of the training dataset are presented and discussed. The work confirms the general ability of feedforward neural networks in flow stress data predictions. It also highlights that slightly better quality predictions are obtained using recursive neural networks.Item type:Article, Access status: Open Access , The role of die definition in the numerical simulations of two-points incremental forming processes(Wydawnictwa AGH, 2023) Perzyński, Konrad; Pawlikowski, Kacper; Madej, ŁukaszThe main objective of this work is to investigate the influence of the definition of dies type in the finite element simulation of the two-points incremental forming processes (TPIF). Particular attention is on determining the effect of assigning elastic properties for the 3D printed dies or considering fully rigid on the final results. During the research, three different shapes of dies were analyzed. Simulation results in the form of sheet thickness distributions and measured forces are presented for comparison purposes.Item type:Article, Access status: Open Access , A case study on tundish fluid flow with electromagnetic stirring(Wydawnictwa AGH, 2024) Zielińska, Monika; Yang, Hongliang; Madej, Łukasz; Malinowski, ŁukaszTundish is a crucial component just before casting and plays a pivotal role in enhancing the cleanliness and overall homogeneity of the final steel composition. The paper deals with the development of an advanced Computational Fluid Dynamics (CFD) model, specifically focusing on the molten steel flow within the tundish to numerically support its further improvements. A noteworthy addition to the model is the consideration of an electromagnetic stirring device. This device significantly influences steel cleanliness and composition, thereby affecting the final properties of the formed metallic parts in subsequent processing stages. The current investigation presents a comprehensive analysis of flow patterns and stirring energy distributions in relation to active and dead zones within the tundish. Through the developed coupled electromagnetic/fluid dynamic model, the paper demonstrates the feasibility of optimizing mixing processes to control the properties of the final product.Item type:Article, Access status: Open Access , Development of an object identification algorithm for the forging industry based on standard vision systems(Wydawnictwa AGH, 2024) Litwa, Adrian; Madej, ŁukaszThe work aims to develop an algorithm for identifying objects in a forging plant under production conditions. Particular emphasis is placed on the accurate detection and tracking of forgings that are transferred along the forging line and, if possible, detection will also cover employees controlling and supporting the operation of forging machines, all of this with the use of standard vision systems. An algorithm prepared in such way will allow the performance of effective detections that will support activities related to the control of the movement of forging elements, the analysis of safety in workplaces, and the monitoring of compliance with Occupational Health and Safety Regulations by employees, as well as also allowing for the introduction of additional optimization algorithms that will further enrich the presented model, which may prove to be a long-term goal that will form the basis for subsequent work. Three algorithmic solutions with different levels of complexity were considered during the research. The first two are based on artificial neural network solutions, while the last one utilizes classical image processing algorithms. The datasets for training and validation in the former cases were generated based on the recordings taken from standard cameras located in the forging plant. Data were acquired from three cameras, two of which were used to create training and validation sets, and a third one was used to verify how the developed algorithms would work in a variable environment that was previously unknown to the models. The impact of model parameters on the results is presented at this stage of the research. It has been proven that machine learning-based solutions cope very well with object detection problems and achieve high accuracies after a precise selection of hyperparameters. Algorithms show the performance of detections with excellent accuracy of 92.5% for YOLOv5 and 94.3% for Mask R-CNN. However, a competitive solution using only image transformations without machine learning showed satisfactory results that can also be obtained with simpler approaches.Item type:Doctoral Dissertation, Access status: Open Access , Development of the multi-scale analysis model to simulate strain localization occurring during material processing(Data obrony: 2007) Madej, Łukasz
Wydział Inżynierii Metali i Informatyki PrzemysłowejA detailed description of possibilities given by the developed Cellular Automata - Finite Element (CAFE) multi scale model for prediction of the initiation and propagation of micro shear bands and shear bands in metallic materials subjected to plastic deformation is presented in the work. Particular emphasis in defining the criterion for initiation of micro shear and shear bands, as well as in defining the transition rules for the cellular automata, is put on accounting for the physical aspects of these phenomena occurring in two different scales in the material. The proposed approach led to the creation of the real multi scale model of strain localization phenomena. This model predicts material behavior in various thermo-mechanical processes. Selected examples of applications of the developed model to simulations of metal forming processes, which involve strain localization, are presented in the work. An approach based on the Smoothed Particle Hydrodynamic, which allows to overcome difficulties with remeshing in the traditional CAFE method, is a subject of this work as well. In the developed model remeshing becomes possible and difficulties limiting application of the CAFE method to simple deformation processes are solved. Obtained results of numerical simulations are compared with the experimental results of cold rolling process to show good predicative capabilities of the developed model.Item type:Article, Access status: Open Access , Two-dimensional hp-adaptive algorithm for continuous approximations of material data using space projection(Wydawnictwa AGH, 2013) Gurgul, Piotr; Sieniek, Marcin; Paszyński, Maciej; Madej, Łukasz; Collier, NathanIn this paper we utilize the concept of the $L^2$ and $H^1$ projections used to adaptively generate a continuous approximation of an input material data in the finie element (FE) base.This approximation, along with a corresponding FE mesh, can be used as material data for FE solvers. We begin with abrief theoretical background, followed by description of the hp -adaptive algorithm adopted here to improve gradually quality of the projections. We investigate also a few distinct sample problems, apply the aforementioned algorithms and conclude with numerical results evaluation.Item type:Article, Access status: Open Access , Development of a constitutive material model of Mo-Mn-Fe-Co-Ni high entropy alloy through a structured two-phase inverse analysis(Wydawnictwa AGH, 2025) Orbea Larrañaga, Aitor; Mendiguren Olaeta, Joseba; Cichocki, Kamil; Madej, ŁukaszHigh entropy alloys, characterized by their near-equimolar compositions of five or more elements, exhibit unique properties including high strength, thermal stability, and corrosion resistance, making them ideal candidates for demanding applications. Unfortunately, experimental research on their behavior under processing and in-use conditions is expensive and time-consuming. Therefore, the use of computer-aided technology design is required. However, reliable constitutive material models for these alloys are rarely available in the literature. Thus, this research aims to develop a constitutive material model of a Mo-Mn-Fe-Co-Ni high entropy alloy through a structured two-phase inverse analysis. First, a preliminary inverse analysis was conducted to recalculate load-displacement data measured during uniaxial compression tests at varied temperatures and strain rates to the required flow stress data. This first phase helps mitigate the impact of testing artifacts – such as friction and localized heating – that can introduce inhomogeneities in the material and affects the hardening behavior. Then, a full inverse analysis was performed to precisely calibrate the constitutive model parameters, ensuring an accurate representation of the alloy’s flow stress behavior under the tested conditions. This second phase optimizes the model to reflect the material’s inherent properties rather than external test-induced effects, thus improving the robustness and reliability of the flow stress data across a range of loading scenarios. As a result, a reliable form of the constitutive model, along with the identified parameters, was obtained and can be used during computer-aided technology design.