Search results for: Jan Kusiak

Items from 1 to 11 out of 11 results

article

Thermal-mechanical finite element simulation of flat bar rolling coupled with a stochastic model of microstructure evolution

Danuta Szeliga, Natalia Czyżewska, Jan Kusiak, Roman Kuziak, more

Computer Methods in Materials Science > 2022 > Vol. 22, No. 3 > 127--138

It is generally recognized that the kinetics of phase transformations during the cooling of steel products depends to a large extent on the state of the austenite after rolling. Austenite deformation (when recrystallization is not complete) and grain size have a strong influence on the nucleation and growth of low-temperature phases. Thus, the general objective of the present work was the formulation...

article

Problem of Identification of Phase Transformation Models Used in Simulations of Steels Processing

Łukasz Rauch, Daniel Bachniak, Roman Kuziak, Jan Kusiak, more

Journal of Materials Engineering and Performance > 2018 > 27 > 11 > 5725-5735

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...

article

Multi-criteria optimization strategies for tree-structured production chains

Piotr Jarosz, Jan Kusiak, Stanisław Małecki, Paweł Morkisz, more

International Journal of Material Forming > 2019 > 12 > 2 > 185-196

The aim of this paper is presentation of some optimization strategies applicable in the optimization of multi-stage and multi-thread chain structures (linear and tree-structured acyclic graphs) with multiple intermediate goal functions. The inspirations for this type of analysis are production chains often seen in industrial plants. Production in these plants consists of sequences of multiple units...

chapter

Filtering of Thermomagnetic Data Curve Using Artificial Neural Network and Wavelet Analysis

Łukasz Rauch, Jolanta Talar, Tomáš Žák, Jan Kusiak

Lecture Notes in Computer Science > Artificial Intelligence and Soft Computing - ICAISC 2004 > Mechanical Applications > 1093-1098

New methods of filtering of experimental data curves, based on the artificial neural networks and the wavelet analysis are presented in the paper. The thermomagnetic data curves were filtered using these methods. The obtained results were validated using the modified algorithm of the cubic spline approximation.

chapter

Optimization of Parameters of Feed-Back Pulse Coupled Neural Network Applied to the Segmentation of Material Microstructure Images

Łukasz Rauch, Łukasz Sztangret, Jan Kusiak

Lecture Notes in Computer Science > Artifical Intelligence and Soft Computing > Neural Networks and Their Applications > 80-87

The paper presents application of bio-inspired optimization procedures to the problem of image segmentation of material microstructures. The method used for image processing was Feed-Back Pulse Coupled Neural Network (FBPCNN), which is very flexible in the case of highly diversified images, offering interesting results of segmentation. However, six input parameters of FBPCNN have to be adjusted dependently...

chapter

Identification of Material Models of Nanocoatings System Using the Metamodeling Approach

Magdalena Kopernik, Andrzej Stanisławczyk, Jan Kusiak, Maciej Pietrzyk

IFIP — The International Federation for Information Processing > System Modeling and Optimization > Regular Papers > 319-330

Hard systems of nanocoatings deposited using PVD (physical vapor deposition) are used in the artificial heart prosthesis. Correct determination of nanomaterial parameters is crucial for accuracy of simulation. The objective of this work is identification of material parameters of nanocoatings in hard system using the inverse analysis based on the artificial neural network metamodeling. The inverse...

article

Metamodeling and Optimization of a Blister Copper Two-Stage Production Process

Piotr Jarosz, Jan Kusiak, Stanisław Małecki, Paweł Morkisz, more

JOM > 2016 > 68 > 6 > 1535-1540

It is often difficult to estimate parameters for a two-stage production process of blister copper (containing 99.4 wt.% of Cu metal) as well as those for most industrial processes with high accuracy, which leads to problems related to process modeling and control. The first objective of this study was to model flash smelting and converting of Cu matte stages using three different techniques: artificial...

article

Conventional and Multiscale Modeling of Microstructure Evolution During Laminar Cooling of DP Steel Strips

Maciej Pietrzyk, Jan Kusiak, Roman Kuziak, Łukasz Madej, more

Metallurgical and Materials Transactions A > 2014 > 45 > 13 > 5835-5851

Physical and numerical simulations of the hot rolling and laminar cooling of DP steel strips are presented in the paper. The objectives of the paper were twofold. Physical simulations of hot plastic deformation were used to identify and validate numerical models. Validated models were applied to simulate the manufacturing of DP steel strips. Conventional flow stress model and microstructure evolution...

article

Open AGH – otwarte zasoby edukacyjne w praktyce

Karolina Grodecka, Jan Marković, Jan Kusiak

e-mentor > 2012 > 3 (45) > 57-63

The article describes opportunities and obstacles related to the application of Open Educational Resources (OERs) in Poland. It is based on the authors’ experience with creating and managing Open AGH, the OER repository for AGH – University of Science and Technology in Krakow. Among others the article discusses a survey on OERs, which was conducted in October 2010 among AGH teachers. Diagnosis of...

article

Modelling of microstructure and mechanical properties of steel using the artificial neural network

Jan Kusiak, Roman Kuziak

Journal of Materials Processing Tech. > 2002 > 127 > 1 > 115-121

The paper presents some results of the research connected with the development of new approach based on the artificial intelligence of predicting the volume fraction and mean size of the phase constituents occurring in a steel after thermomechanical processing and cooling. The independent variables in the model are austenite grain size and cooling rate over the temperature range of the occurrence...

article

Preface

Ian Pillinger, Peter Hartley, Jan Kusiak, Janusz Majta

Journal of Materials Processing Tech. > 2002 > 125-126 > Complete > vii

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