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Search Results: 1 - 10 of 297315 matches for " J. Trzaska "
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Hybrid modelling methods in materials science - selected examples
W. Sitek,J. Trzaska
Journal of Achievements in Materials and Manufacturing Engineering , 2012,
Abstract: Purpose: The paper presents selected examples of application of computational tools, including artificial intelligence methods to solve examples of tasks in the area of materials science. (i) Selection method of steel grade with required hardenability; (ii) Modelling of CCT diagrams for engineering and constructional steels; (iii) Application of neural networks for selection of steel with the assumed hardness after cooling from the austenitising temperature; (iv) Designing of high-speed steels chemical compositionDesign/methodology/approach: In the paper been applied a hybrid approach that combined application of various mathematical tools including artificial neural networks, linear regression and genetic algorithms to solve selected tasks from the area of materials science.Findings: Computer modelling and simulation make improvement of engineering materials properties possible, as well as prediction of their properties, even before the materials are fabricated, with the significant reduction of expenditures and time necessary for their investigation and application. Methods used in hybrid systems are complementary and disadvantages of one method are compensated by the advantages of another method.Practical implications: Solutions presented in the work, based on using the adequate material models may feature an interesting alternative in designing of the new materials with the required properties. The practical aspect has to be noted, resulting form the developed models, which may successfully replace the above mentioned technological investigations, consisting in one time selection of the chemical composition and heat treatment parameters and experimental verification of the newly developed materials to check of its properties meet the requirements.Originality/value: The presented approach to new materials design assumes the maximum possible limitation of carrying out the indispensable experiments, to take advantage of the existing experimental knowledge resources in the form of databases and most effective computer science tools, including neural networks and evolutionary algorithms.
Numerical simulation of the alloying elements effect on steels’ properties
W. Sitek,J. Trzaska
Journal of Achievements in Materials and Manufacturing Engineering , 2011,
Abstract: Purpose: The goal of the research carried out was evaluation of alloying elements effect on high-speed steels hardness and fracture toughness and austenite transformations during continuous cooling of structural steels.Design/methodology/approach: Multi-layer feedforward neural networks with learning rule based on the error backpropagation algorithm were employed for modelling the steels properties. Then the neural networks worked out were employed for the computer simulation of the effect of particular alloying elements on the steels’ properties.Findings: Obtained results show that neural network are useful in evaluation of synergic effect of alloying elements on selected materials properties when classical investigations’ results do not provide evaluation of the effect of two or more alloying elements.Practical implications: Numerical simulation presented in the work, based on using the adequate material models may feature an alternative for classical investigations on effect of alloying elements on steels’ properties.Originality/value: The use of the neural networks as an tool for evaluation of the chemical composition effect on steels’ properties.
Modeling of Energy Processes in Wheel-Rail Contacts Operating under Influence of Periodic Discontinuous Forces  [PDF]
Zdzislaw Trzaska
Journal of Transportation Technologies (JTTs) , 2012, DOI: 10.4236/jtts.2012.22014
Abstract: In this paper we present new numerical simulation approaches for determining the energy processes under periodic conditions caused by time-discontinuous forces in the wheel-rail contacts. The main advantage of the presented method is the total elimination of frequency analysis, which in effect introduces important simplifications in the identification of the effects in the contact. The second important feature is the fact that the method is based on the analysis of appropriate loops on the energy phase plane leading to an easy estimation of the rail strength through the evaluation of the loop’s area. That model based simulation in the applied dynamics relies on advanced methods for model setup, robust and efficient numerical solution techniques and powerful simulation tools for practical applications. Fundamental properties of contact displacements of the rail surface have been considered on the basis of the newly established method. The contact zone between railway wheels and the rail surfaces made of bulk materials is perceived as strong enough to resist the normal (vertical) forces introduced by heavy loads and the dynamic response induced by track and wheel irregularities. The analysis is carried out for a wheel running on an elastic rail rested on sleepers arranged on completely rigid foundation. The equations of displacement motion are established through the application of the Lagrange equations approach. The established model of the wheel-rail contact dynamics has been applied to that same roll plane but with taking into account a nonlinear characteristic of the sleeper with respect to the ground. Attention then is focused completely on the modeling of the energy absorbed by the rail. The applied method employs the energy state variables as time functions leading to determine the susceptibility of a given contact on the strength induced by the rail roll.
Time-Domain Analysis of the Periodically Discontinuously Forced Fractional Oscillators  [PDF]
Zdzislaw Trzaska
Advances in Pure Mathematics (APM) , 2014, DOI: 10.4236/apm.2014.46036
Abstract:

A new method for the solution of non-sinusoidal periodic states in linear fractionally damped oscillators is presented. The oscillator is forced by a periodic discontinuous waveform and a viscous element is taken into account. The presented method avoids completely the Fourier series calculations of the input and output oscillator waveforms. In the proposed method, the steady-state response of fractionally damped oscillator is formulated directly in the time domain as a superposition of the zero-input and forced responses for each continuous piecewise segments of the forcing waveform, separately. The whole periodic response is reached by taking into account the continuity and periodicity conditions at instants of discontinuities of the excitation and then using the concatenation procedure for all segments. The method can be applied efficiently to discontinuous and continuous non-harmonic excitations equally well. Solutions are exact and there is no need to apply any of the widely up-to-date used frequency approaches. The Fourier series is completely cut out of the oscillator analysis.

Application of neural networks for selection of steel with the assumed hardness after cooling from the austenitising temperature
J. Trzaska,L.A. Dobrzański
Journal of Achievements in Materials and Manufacturing Engineering , 2006,
Abstract: Purpose: The aim of the study is to establish a system that supports the choice of steel grade for quenching and tempering at a required hardness curve as function of cooling rate from the austenitising temperature.Design/methodology/approach: It has been assumed that the steel will meet the criterion provided that the hardness curve, defined by the user, is included within the range of hardness change that is characteristic of a certain steel grade. In order to determine the steel hardness ranges it has been necessary to work out a suitable calculation model. Therefore, a neural network has been designed and verified numerically to calculate the steel hardness on the basis of chemical content for the predetermined cooling rate. To develop the relationship between the chemical composition, austenitising temperature, cooling rate and hardness of the steels for quenching and tempering the artificial neural network was used. The obtained results were used for determination of neural classifier. The classifiers based on the neural networks carries out the task of selection of the steel grade.Findings: Artificial neural networks can be applied for selection of steel with the assumed hardness after cooling from the austenitising temperature.Practical implications:The system presented can be applied to selection of steel grade intended for machine parts of predetermined hardness in the section of a hardened or normalized element.Originality/value: The research presented in this paper offers a new strategy useful in selection of steel grade.
Singular Hopf Bifurcations in DAE Models of Power Systems  [PDF]
Wieslaw Marszalek, Zdzislaw Trzaska
Energy and Power Engineering (EPE) , 2011, DOI: 10.4236/epe.2011.31001
Abstract: We investigate an important relationship that exists between the Hopf bifurcation in the singularly perturbed nonlinear power systems and the singularity induced bifurcations (SIBs) in the corresponding different- tial-algebraic equations (DAEs). In a generic case, the SIB phenomenon in a system of DAEs signals Hopf bifurcation in the singularly perturbed systems of ODEs. The analysis is based on the linear matrix pencil theory and polynomials with parameter dependent coefficients. A few numerical examples are included.
How to Measure in the Near Field and in the Far Field  [PDF]
Tomasz Dlugosz, Hubert Trzaska
Communications and Network (CN) , 2010, DOI: 10.4236/cn.2010.21010
Abstract: A background of the electromagnetic field (EMF) measurements is presented in the work. A special attention is given to the specificity of the measurements performed in the Near Field. Factors, that should be taken into consideration as during the measurements as well during their analysis, are discussed. Without their understanding and considering a comparison of the measurements’ results, meters’ calibration and EMF standards comparison between different centers is impossible.
The energy approach to electrochemical corrosion studies of nano-copper coatings
M. Trzaska,Z. Trzaska
Journal of Achievements in Materials and Manufacturing Engineering , 2011,
Abstract: Purpose: The paper presents research results on energy impacts and effects of corrosion of electrodeposited nano- and microcrystalline copper surface layers and involve activation energy and mass transfer effects.Design/methodology/approach: The activation energy and mass transfer effects indicate effectiveness of one-period energy approach in the control of the corrosion resistance of copper deposits. Properties of coatings are examined.Findings: Loops of one-period energy dissipated during the corrosion of electrodeposits were determined. Non-sinusoidal periodic excitations of the corrosion cell and integrations of response waveforms were taken into account. The corrosion energy is expressed by the area of the loop on the energy phase plane. The influences of supplying voltage on the topography, morphology and surface roughness of the electrodeposits were examined.Research limitations/implications: The approach is suitable for system operating under non-sinusoidal periodic conditions. The main feature lies in the elimination of the frequency analysis and gives significant simplifications of the corrosion rate measurements realized with a computer processing system or function generator and digital oscilloscope.Practical implications: The important implications consist in complete eliminations of Fourier series analysis and direct exhibitions of susceptibilities of the studied material to corrosion through evaluations of one-period energy loops. The approach involves more physically exact insights on non-sinusoidal influences of environments.Originality/value: The original value consists on introduction of the energy state variables and representing the absorbed energy during the corrosion tests by the area of one-period energy loops. The novelty lies on the identification of various crystalline structures susceptibility on corrosion destructions.
The calculation of CCT diagrams for engineering steels
J. Trzaska,A. Jagie??o,L.A. Dobrzański
Archives of Materials Science and Engineering , 2009,
Abstract: Purpose: of this paper is to present numerical methods for calculation of CCT diagrams for engineering steels.Design/methodology/approach: The presented numerical methods for calculating the anisothermic diagrams of supercooled austenite are based on physical, statistical or artificial intelligence methods. In many cases input data are chemical composition and austenitising temperature. The results of calculations consist of temperature of the beginning and the end of particular transformation, the volume fraction of structural components and hardness of steel after heat treatment.Findings: Numerical methods are an alternative to experimental measurement in providing the material data required for heat treatment process simulation.Research limitations/implications: All presented methods for calculation of CCT diagrams for engineering steels are limited by ranges of mass concentrations of elements.Practical implications: All presented methods may be used in computer steel selection systems for machines parts manufactured from engineering steels subjected to heat treatment.Originality/value: The presented methods can be used for selecting steel with required structure after heat treatment.
Computer programme for prediction steel parameters after heat treatment
J. Trzaska,L.A Dobrzanski,A. Jagie??o
Journal of Achievements in Materials and Manufacturing Engineering , 2007,
Abstract: Purpose: The purpose of this paper is presentation of the computer program for calculating the Continuous Cooling Transformation diagrams for constructional and engineering steels.Design/methodology/approach: The computer program uses the artificial neural networks for prediction steel properties after heat treatment. Input data are chemical composition and austenitizing temperature. Results of calculation consist of temperature of the beginning and the end of transformation in the cooling rate function, the volume fraction of structural components and hardness of steel cooled from austenitizing temperature with a fixed rate.Findings: The algorithm can be use in designing new chemical compositions of steels with assumed hardness after heat treatment.Research limitations/implications: The created method for designing chemical compositions is limited by ranges of mass concentrations of elements. The methodology demonstrated in the paper makes possibility to add new steels to the system.Practical implications: The method may be used in computer steel selection systems for machines parts manufactured from constructional or engineering steels subjected to heat treatment.Originality/value: The presented computer program can be used for selecting steel with required structure after heat treatment.
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