BazTech - Yadda

1

Optimization of Ferrite Stainless Steel Mechanical Properties Prediction with artificial Intelligence Algorithms

Honysz R.

Archives of Metallurgy and Materials

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2020

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Vol. 65, iss. 2

749-753

EN

The article presents a computational model build with the use of artificial neural networks optimized by genetic algorithm. This model was used to research and prediction of the impact of chemical elements and heat treatment conditions on the mechanical properties of ferrite stainless steel. Optimization has allowed the development of artificial neural networks, which showed a better or comparable prediction result in comparison to un-optimized networks has reduced the number of input variables and has accelerated the calculation speed. The introduced computational model can be applied in industry to reduce the manufacturing costs of materials. It can also simplify material selection when an engineer must properly choose the chemical elements and adequate plastic and/or heat treatment of stainless steels with required mechanical properties.

2

The Use of Fuzzy Systems for Forecasting the Hardenability of Steel

Sitek W., Irla A.

Archives of Metallurgy and Materials

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2016

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Vol. 61, iss. 2A

797--802

EN

The goal of the research carried out was to develop the fuzzy systems, allowing the determination of the Jominy hardenability curve based on the chemical composition of structural steels for quenching and tempering. Fuzzy system was created to calculate hardness of the steel, based on the alloying elements concentrations, and to forecast the hardenability curves. This was done based on information from the PN-EN 10083-3: 2008. Examples of hardenability curves calculated for exemplar steels were presented. Results of the research confirmed that fuzzy systems are a useful tool in evaluation the effect of alloying elements on the properties of materials compared to conventional methods. It has been demonstrated the practical usefulness of the developed models which allows forecasting the steels’ Jominy hardenability curve.

3

Neural networks model for prediction of the hardness of steels cooled from the austenitizing temperature

Trzaska J.

Archives of Materials Science and Engineering

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2016

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Vol. 82, nr 2

62--69

EN

Purpose: The paper presents the new neural networks model making it possible to estimate the hardness of continuously-cooled steel from the austenitizing temperature. Design/methodology/approach: The method proposed in the paper employs two applications of the neural networks of: classification and regression. Classification and consists in determining the value of dichotomous variables describing the occurrence of: ferrite, pearlite, bainite and martensite in the microstructure of a steel. The values of dichotomous variables have been used for calculating steel hardness. The other task is regression, which aims at calculating the steel hardness. Findings: The presented neural networks model can be used only in the range of concentrations of alloying elements shown in this paper. Practical implications: The model worked out makes it possible to calculate hardness for the steel with a known chemical composition. This model deliver important information for the rational selection of steel for those parts of the machines that are subjected to the heat treatment. The presented model make it possible the analysis of the interaction of the chemical composition on the hardness curves of the steel cooled from the austenitizing temperature. Originality/value: The paper presents the method for calculating hardness of the structural and engineering steels, depending on their chemical composition, austenitizing temperature and cooling rate.

4

The application of neural networks to analysis of the effects of chemical composition on hardenability of steel

Sitek W., Jabłoński A.

Journal of Achievements in Materials and Manufacturing Engineering

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2015

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Vol. 72, nr 1

32--38

EN

Purpose: The goal of the research carried out was evaluation of alloying elements effect on the development of artificial neural network models, allowing the determination of the Jominy hardenability curve based on the chemical composition of constructional and machine steels. Design/methodology/approach: MLP neural network was used to learn rule for modelling the steels properties. Then the neural network used for computer simulation synergistic effect of alloying elements on the hardenability of steel. Research limitations/implications: Results of the research confirmed that neural networks are a useful tool in evaluation the effect of alloying elements on the properties of materials compared to conventional methods. Additionally it confirms idea, that based on data from standards and catalogues is possible to develop the assumed model. Practical implications: It has been demonstrated complete the practical usefulness of the developed models in the selection of materials designed machine parts, which allows the direct relationship during the melting process real time control of the desired hardness of the steel hardenability curve. Originality/value: Based on the results of catalogues and standards with the used of neural networks developed and fully validated experimental model of the relationship between hardenability and chemical composition of the constructional and machine steels.

5

Prediction optimization of mechanical properties of ferrite stainless steels after rolling treatment with use of genetic algorithms

Honysz R.

Journal of Achievements in Materials and Manufacturing Engineering

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2015

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Vol. 68, nr 1

17--24

EN

Purpose: The article discusses the use of artificial neural networks for research and prediction of the impact of chemical elements and heat treatment parameters on the mechanical properties of stainless steels optimized by genetic algorithm. Design/methodology/approach: To improve the quality of artificial neural network models and improve their performance the number of input variables of artificial neural networks has been optimized with use of genetic algorithms. Then a computational model build with optimised artificial neural networks were trained and verified. Findings: Optimization, except of tensile strength Rm case, has allowed the development of artificial neural networks, which either showed a better or comparable result from base networks, and also have a reduced number of input variables. As a result, in computational model constructed with use of these networks the noise information is reduced. Research limitations/implications: Data analysis was needed to verify if obtained data used for modelling are relevant to use them in artificial neural networks training processes. Practical implications: The use of artificial intelligence allows the multifaceted development of stainless steels engineering, even if only a small number of descriptors is available. Constructed and optimised computational model build with use of optimised artificial neural networks allows prediction of mechanical properties of rolled ferritic stainless steels after normalization. Originality/value: Introduced model can be obtain in industry to reduce manufacturing costs of materials. It can also simplify material selection, when engineer must properly choose the chemical elements and adequate plastic and/or heat treatment of stainless steels with required mechanical properties.

6

Influence of aging time and temperature on diffusion of alloyed copper

Konieczny J., Rdzawski Z., Bańbura P., Preficz B.

Journal of Achievements in Materials and Manufacturing Engineering

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2015

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Vol. 73, nr 1

27--35

EN

Purpose: The aim of this study is to determine the impact of aging time and temperature on the diffusion process of alloying elements inside alloyed copper CuCr0,7, CuFe2 and CuTi4. Design/methodology/approach: It was assumed the activation energy for diffusion of small interstitial atoms is smaller than for large substitute atoms. To determine the influence of aging time and temperature on diffusion of alloying elements in binary copper-based alloys CuCr0,7, CuFe2 and CuTi4 it has been necessary to develop a suitable mathematical model. It has been shown that with the increase of time t, the diffusion pathway L is increased, but the impact of time is not as large as the effect forced by altering temperature. In general, multiple increase of time is equivalent to increasing the temperature by a few degrees. Findings: The model should be used to estimate the average atom pathway of chromium, iron or titanium in copper matrix, caused by diffusion, and the diffusion path into the grain boundary without adsorption as a function of time and temperature aging Research limitations/implications: The model should be used to calculate the influence of temperature and time of aging on the atoms diffusion pathway of the alloying elements in the selected alloyed copper types. Practical implications: The results allow to calculate the average atom pathway L (with reasonable error level) for which the diffused atoms achieve the amount of free energy required to overcome the energetic barrier, on the basis of a combination of heat treatment parameters. Originality/value: This paper presents the impact of the aging temperature on diffusion in the alloyed copper CuCr0.7, CuFe2 and CuTi4.

7

Elastic modules identification by layered composite beams testing

Diveyev B., Konyk S.

Journal of Achievements in Materials and Manufacturing Engineering

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2015

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Vol. 72, nr 1

14--22

EN

Purpose: The study aims to predict elastic properties of composite laminated plates from the measured mechanical properties. Design/methodology/approach: Elastic constants of laminates and damping properties have been determined by using an identification procedure based on experiment design, and multi-level theoretical approach. Findings: The present paper is the first attempt at proposing a novel adaptive procedure to derive stiffness parameters from forced sandwich plate’s vibration experiments. Research limitations/implications: In the future the extension of the present approach to sandwich plates with different core materials will be performed in order to test various experimental conditions. Practical implications: Structures composed of laminated materials are among the most important structures used in modern engineering and especially in the aerospace industry. Such lightweight and highly reinforced structures are also being increasingly used in civil, mechanical and transportation engineering applications. Originality/value: The main advantage of the present method is that it does not rely on strong assumptions on the model of the plate. The key feature is that the raw models can be applied at different vibration conditions of the plate by a suitable analytical ore approximation method

8

Application of Artificial Neural Networks in Modeling of Manufactured Front Metallization Contact Resistance for Silicon Solar Cells

Musztyfaga-Staszuk M., Honysz R.

Archives of Metallurgy and Materials

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2015

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Vol. 60, iss. 3A

1673--1678

EN

This paper presents the application of artificial neural networks for prediction contact resistance of front metallization for silicon solar cells. The influence of the obtained front electrode features on electrical properties of solar cells was estimated. The front electrode of photovoltaic cells was deposited using screen printing (SP) method and next to manufactured by two methods: convectional (1. co-fired in an infrared belt furnace) and unconventional (2. Selective Laser Sintering). Resistance of front electrodes solar cells was investigated using Transmission Line Model (TLM). Artificial neural networks were obtained with the use of Statistica Neural Network by Statsoft. Created artificial neural networks makes possible the easy modelling of contact resistance of manufactured front metallization and allows the better selection of production parameters. The following technological recommendations for the screen printing connected with co-firing and selective laser sintering technology such as optimal paste composition, morphology of the silicon substrate, co-firing temperature and the power and scanning speed of the laser beam to manufacture the front electrode of silicon solar cells were experimentally selected in order to obtain uniformly melted structure well adhered to substrate, of a small front electrode substrate joint resistance value. The prediction possibility of contact resistance of manufactured front metallization is valuable for manufacturers and constructors. It allows preserving the customers’ quality requirements and bringing also measurable financial advantages.

PL

Artykuł przedstawia zastosowanie sztucznych sieci neuronowych do predykcji rezystancji przedniej metalizacji w krzemowych ogniwach słonecznych. Oceniono wpływ tak wytworzonej elektrody przedniej na własności elektryczne ogniw fotowoltaicznych. Przednią elektrodę ogniw fotowoltaicznych naniesiono metodą sitodruku SP (ang. Screen Printing) i następnie wytwarzano dwoma metodami: konwencjonalną (1. wypalanie w piecu taśmowym) i niekonwencjonalną (2. selektywne spiekanie laserowe). Do wyznaczenia rezystancji elektrod przednich zastosowano metodę linii transmisyjnych TLM (ang. Transmission Line Model). Sztuczne sieci neuronowe zostały opracowane z wykorzystaniem pakietu Statistica Neural Network firmy Statsoft. Opracowane sztuczne sieci neuronowe umożliwią modelowanie rezystancji wytworzonej przedniej metalizacji i ułatwią lepszy dobór parametrów produkcji. Następujące zalecenia technologiczne sitodruku połączonego z wypalaniem w piecu i selektywnym spiekaniem laserowym takie jak optymalny skład pasty, morfologię podłoża krzemowego, temperaturę wypalania oraz moc i prędkość skanowania wiązki laserowej, do wytworzenia przedniej elektrody krzemowych ogniw słonecznych dobrano eksperymentalnie celem uzyskania celem uzyskania jednolicie stopionej struktury dobrze przylegającej do podłoża, małej wartości rezystancji połączenia elektrody przedniej z podłożem. Możliwość estymacji rezystancji przedniej metalizacji jest wartościowa dla producentów i konstruktorów. Pozwala ona na dotrzymanie wymagań klienta i przynosi wymierne zyski.

9

Mechanical properties of antiwear Cr/CrN multi-module coatings

Ratajski J., Gilewicz A., Bartosik P., Szparaga Ł.

Archives of Materials Science and Engineering

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2015

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Vol. 75, nr 1

35--45

EN

Purpose: The goal of this paper is to investigate the influence of thicknesses of Cr and CrN layers in Cr/CrN module of multi-module coatings, on their mechanical properties. Design/methodology/approach: The objects of research are systems composed of steel substrate and Cr/CrN multi-module coatings, deposited using PVD (Physical Vapour Deposition) method, via CAE (Cathodic Arc Evaporation) technique. Mechanical properties of the substrate/coating systems were determined using scratch test, Vickers indentation, while wear of the systems was investigated via ball on disk method. Internal strain and stress states in substrate/coating systems, arising during indentation, were calculated using FEM (Finite Element Method) computer model. Findings: For two different geometries of Cr/CrN multi-module coatings mechanical properties (hardness, fracture toughness, wear and adhesion forces) were examined. Additionally, in Rockwell indentation test, the states of first principal stress and effective plastic strain states were calculated. Research limitations/implications: The coatings were deposited using CAE, which results in occurrence of various defects (eg. droplets) inside coatings. This fact has its consequences, ie. perturbations in layers structure, resulting in stochastic, spatial changes of physico-chemical properties of the coatings. This defects may be reduced by special modifications of CAE (eg. active filters) techniques, but the overall mechanical properties of the coatings will not be highly improved. Practical implications: Investigations of the influence of architecture and geometry of multi-module Cr/CrN coatings on their mechanical properties is crucial, because of their wide range of industry applications. Originality/value: The main value of the paper is an experimental case study of mechanical properties of Cr/CrN multi-module coatings referenced to CrN/CrCN coatings. Moreover, using FEM model of the indentation, the differences between residual stresses and strains were discussed.

10

Optimization of chemical composition and heat treatment condition of structural steel

Honysz R., Dobrzański L. A.

Journal of Achievements in Materials and Manufacturing Engineering

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2014

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Vol. 64, nr 1

27--33

EN

Purpose: This paper presents the methodology and results of virtual research project involving the optimization of the chemical composition and heat treatment conditions of structural steels. Investigations were performed in virtual environment with use of materials science virtual laboratory. Design/methodology/approach: The first task was to search for such a range of chosen element concentration while keeping the concentration of other elements unchanged in order to satisfy all the conditions for steel mechanical properties defined by a virtual client. Second task of virtual research project consisted in searching for such ranges of temperature and time for hardening and tempering , to ensure that all the conditions for steel properties defined by a virtual client has been met without making changes in the chemical composition of steel. Findings: Virtual investigations results were verified in real investigative laboratory. Results of virtual examinations are presented as raw data and influence charts. Practical implications: The new material design methodology has practical application in the development of materials and modelling of steel descriptors in aim to improve the mechanical properties and specific applications in the production of steel. Presented examples of computer aid in structural steel production shows a potential application possibility of this methodology to support the production of any group of engineering materials. Originality/value: The prediction possibility of the material mechanical properties is valuable for manufacturers and constructors. It ensures the customers quality requirements and brings also measurable financial advantages.

11

Calculation of volume fractions of microstructural components in steels cooled from the austenitizing temperature

Trzaska J.

Journal of Achievements in Materials and Manufacturing Engineering

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2014

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Vol. 65, nr 1

38--44

EN

Purpose: The paper presents method in predicting the volume fractions of ferrite, pearlite, bainite and martensite of steel cooled continuously from the austenitizing temperature, basing on the chemical composition, austenitizing temperature and cooling rate. Design/methodology/approach: In the paper it has been applied a hybrid approach that combined application of various mathematical tools including logistic regression and multiple regression to solve selected tasks from the area of materials science. Findings: Computational methods are an alternative to experimental measurement in providing the material data required for heat treatment process simulation.Research limitations/implications: All equations are limited by range of mass concentrations of elements which is presented in Table 2. Practical implications: The worked out formulae may be used in computer systems of steels’ designing for the heat-treated machine parts. Originality/value: The paper presents the method for calculating the volume fractions of ferrite, pearlite, bainite and martensite of the structural steels, depending on their chemical composition, austenitizing temperature and cooling rate.

12

The influence of fill factor on the phononic crystal eigenfrequencies

Gruszka K., Nabiałek M., Szota M.

Archives of Materials Science and Engineering

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2014

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Vol. 66, nr 2

74--80

EN

Purpose: The aim of this article is to determine the effect of basic cell fill factor change on the eigenfrequencies observed in two-dimensional phononic crystal. Design/methodology/approach: To perform simulation, the FDFD (finite difference frequency domain) algorithm was used. On this basis, the search for eigenfrequencies was carried out starting from lowest possible acoustic frequency range (~20 Hz) and limited to first nine search results found (up to nearly 2.2 kHz) for increasing fill factor while maintaining the shape of a rod inside cell. Findings: The fill factor has a significant influence on the eigenfrequencies of the studied system when the frequency is above 1 kHz. With the increase of this factor at relatively low frequencies (less than 1 kHz in this case) there were no major changes observed. Research limitations/implications: The results were found only for specific system consisting of materials with similar sound velocity. Therefore, more research should be carried out for other cases i.e. taking into account the different topology of primary cells and various materials with other propagation velocity of acoustic waves in these mediums. Practical implications: Simulation of two-dimensional phononic crystal systems allows for designing new specialized multi-component materials with various acoustic properties. These systems can be adapted in a variety of applications, including acoustic filters, slow-wave devices, acoustic autocollimators and many other. Originality/value: Basic research allow to improve the quality of knowledge on more advanced problems. For this reason, it is important to know in detail how simple systems work and to determine the basic properties of these systems.

13

Influence of rod diameter on acoustic band gaps in 2D phononic crystal

Gruszka K., Nabiałek M., Szota M.

Archives of Materials Science and Engineering

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2014

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Vol. 68, nr 1

24--30

EN

Purpose: The purpose of this paper is to investigate influence of changing the fill factor (or rod diameter) on acoustic properties of phononic crystal made of mercury rods inside of water matrix. Change in construction of primary cell without changing the shape of rod may cause shifts in bands leading to widening of forbidden band gaps, which is the basis of modern composite material designing process. Design/methodology/approach: Band structure is determined by using the finite element study known as finite difference frequency domain simulation method. This is achieved by virtual construction and simulation of primary cell of phononic crystal. Phononic crystals are special devices which by periodic arrangement of properties related to the sound can affect the transmission of acoustic waves thru their body. Findings: The fill factor/rod diameter has a significant influence on the acoustic band structure of studied phononic crystal which can be divided in two mainly effects: fission and compression of band structure. Research limitations/implications: In order to better understand basic properties of phononic crystals and to get full control over the band gaps a series of similar calculations should be done for broader range of frequencies covering both infrasound and ultrasound wavelength regions. Also structures of other cut shape of rod and different primary cell structure resulting in diverse phononic crystal structure should be investigated in the future. Practical implications: Phononic crystals are important devices in variety of applications ranging from noise control through acoustic computing, health applications and entertainment up to military applications. Therefore full knowledge about specific working conditions and elementary properties is necessary for complete control in targeted applications. Controlling the fill factor is one of the simplest methods to achieve specific band gap positions and widths. Originality/value: The novelty is in use of different phase materials with similar acoustic characteristics affecting the hole sonic properties of device manifested by their calculated band structure. The target group are scientists interested in practical applications of various acoustic materials.

14

Strain field analysis in nanoindentation test of gradient coatings

Szparaga Ł., Ratajski J., Bartosik B.

Archives of Materials Science and Engineering

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2013

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Vol. 64, nr 2

219--227

EN

Purpose: In the paper strain distributions within TiAlN/TiN gradient coatings in nanoindentation test were analysed. The main goal was to examine the influence of the type of a gradient layer on strain distributions in the area of the indenter/coating. Design/methodology/approach: For physical modelling purposes Cr, TiN and TiAlN layers were treated as a continuous medium. Basing on this simplification for the mathematical description of the strain states in the coating a classical theory of stiffness was used. Gradient layers were modelled using the conception of transition function which describe continuous physico-chemical material parameters changes in each layer in the multilayer coating. The computer analysis of the strain fields in the coating after deposition process was done vie FEM method. Findings: For a chosen types of gradient coatings the strain distributions in the coating under external loads (nanoindentation test) were calculated. Using created examples of transition functions, the influence of the shape of the function on strain isolines in the area of the indenter/coating was examined. Research limitations/implications: The main simplification which was done during creation of the mathematical model was an assumption that the coating and the substrate are continuous media. This assumption causes that some physical effects occurring during experimental nanoindentation test can not be properly described in a computer model. Also there are numerous mathematical models of contact, so obtained numerical results (strain distributions) strongly depend of the postulated contact model. Practical implications: For a practical implications of the obtained results one should include a mathematical description of the strain states in the nanoindentation test of gradient coatings. The stress and strain fields analysis is extremely important in respect of fracture analysis. It should be also emphasis, that proposed mathematical description of gradient layer using transition function conception is an easy way to represent physical and chemical properties of gradient coating in computer models. The advantage of such a description of gradient layers can be used for example in polyoptimization process of multilayer gradient coatings. Originality/value: The main value of the paper is the comparison study of strain distribution in nanoindentation test of three different gradient coatings represented be three types of transition functions: (a) step function, (b) linear function and (c) modified non symmetrical sigmoidal function.

15

On transition functions and nonlinearity measures in gradient coatings

Ratajski J., Szparaga Ł.

Journal of Achievements in Materials and Manufacturing Engineering

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2012

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Vol. 54, nr 1

83--92

EN

Purpose: In this paper the influence of the shape of transition functions between the single layers of multilayer coating on the final internal stresses states in the coating was investigated. Additionally the degree of nonlinearity and asymmetry of postulated gradient layers was calculated. Design/methodology/approach: Physical and mathematical models of the layers were created basing on classical theory of elasto-plastic materials. Computer model of the object (coating + substrate) describing internal strains and stresses states in layers, after deposition process, was created using FEM method. Findings: New concepts of nonlinearity and asymmetry measurability of transition function were introduced. Using predefined measures the dependence between internal stresses fields in postulated class of gradient layers and values of nonlinearity and asymmetry were obtained. Research limitations/implications: There are an infinite number of possible measures of heterogeneity and nonlinearity of the transition layers. Also there are infinitely many functions with the same measures of asymmetry and nonlinearity, but different mathematical forms, thus a functions of the same measures value form a kind of class of abstraction. So it is convenient to consider specific representatives of the given class and expand the obtained results to remaining representatives which is laborious and ambiguous task. Practical implications: Proposed measures of gradient layers will become a significant components of the PC software in future, which will upgrade the designing process of hard, wear resistant coatings architecture. Originality/value: A class of monotonic and asymmetric transition functions, describing continuous physico-chemical material’s parameters changes in each layer of K-layered coating was created. Also a new measures of nonlinearity and asymmetry of transition function were introduced.

16

Heat treatment influence on mechanical properties of structural steels for quenching and tempering

Dobrzański L. A., Honysz R.

Journal of Achievements in Materials and Manufacturing Engineering

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2012

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Vol. 55, nr 2

461--468

EN

Purpose: This paper introduces analysis results of heat treatment conditions influence on mechanical properties of alloy structural steels for quenching and tempering. Design/methodology/approach: Investigations were performed in virtual environment with use of materials science virtual laboratory. Virtual investigations results were verified in real investigative laboratory. Findings: Performed verification investigations presented in this paper on selected mechanical properties modelling examples of structural steels clearly show the correctness of the developed computational model of structural steel and confirm the possibility of its use in the industrial production, both to predict the properties, as well as to design new types of steel. Practical implications: Results of virtual examinations can be presented as raw data or influence charts Originality/value: The effectiveness of the virtual environment application for the prediction, simulation and modelling of the steel properties is presented.

17

Application of the artificial neural networks for prediction of hardness of alloyed copper

Konieczny J.

Journal of Achievements in Materials and Manufacturing Engineering

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2012

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Vol. 55, nr 2

529--535

EN

Purpose: The aim of the work is to employ the artificial neural networks for prediction of hardness of the alloyed copper like CuTi, CuFe, CuCr and CuNiSi. Design/methodology/approach: It has been assumed that the artificial neural networks can be used to assign the relationship between the chemical compositions of alloyed copper, temperature and time of solution heat treatment, degree of cold working deformation and temperature and time of ageing. In order to determine the relationship it has been necessary to work out a suitable calculation model. It has been proved that employment of genetic algorithm to selection of input neurons can be very useful tool to improve artificial neural network calculation results. The attempt to use the artificial neural networks for predicting the effect of the chemical composition and parameters of heat treatment and cold working deformation degree on the hardness succeeded, as the level of the obtained results was acceptable. Findings: Artificial neural networks, can be applied for predicting the effect of the chemical composition, parameters of heat treatment and cold working deformation degree on the hardness. Research limitations/implications: Worked out model should be used for prediction of hardness only in particular groups of alloyed copper, mostly because of the discontinuous character of input data. Practical implications: The results of research make it possible to calculate with a certain admissible error the hardness value basing on combinations of concentrations of the particular elements, heat treatment parameters and cold working deformation degree. Originality/value: In this paper it has been presented an original trial of prediction of the required hardness of the alloyed copper like CuTi, CuFe, CuCr and CuNiSi.

18

Informative technologies in the material products designing

Dobrzański L., Honysz R.

Archives of Materials Science and Engineering

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2012

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Vol. 55, nr 1

37-44

EN

Purpose: The purpose of materials products designing is to optimize their functional properties in terms of technological, economic and ecological aspects. Design/methodology/approach: Materials science is an example of a field, in which informative technologies used to understand and anticipate the construction of materials and their properties has a significant success. Findings: Innovation and development of new informative technologies and the widespread use of modern materials will be essential for promoting economic development in the near future by application of entirely new, interdisciplinary field of science: computational materials science. Practical implications: The use of informative technologies allows exploring in a short time and at low expense, many solutions for the design of the mechanical properties of materials and their simulation beyond the standardized range. Originality/value: The most important benefit of material designing is the ability of suitable selection of material (or its manufacturing) for various applications with use of informative technologies.

19

Fractal and multifractal characteristics of the PVD and CVD coatings deposited onto compound tool ceramics

Kwaśny W., Mikuła J.

Archives of Materials Science and Engineering

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2012

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Vol. 56, nr 1

37-44

EN

Purpose: The goal of this work is the fractal and multifractal characteristics of the TiN and TiN+multiTiAlSiN+TiN coatings obtained in the PVD process, and of the TiN+Al2O3 coating obtained in the CVD process on the Al2O3+TiC oxide tool ceramics substrate. Design/methodology/approach: The investigations were carried out of the multi-edge inserts from the Al2O3+TiC oxide tool ceramics uncoated and coated with the TiN and TiN+multiTiAlSiN+TiN coatings deposited in the cathode arc evaporation CAE PVD process, as well as with the TiN+Al2O3 coating obtained in the CVD process. Determining the fractal dimension and the multifractal analysis of the examined coatings were made basing on measurements obtained from the AFM microscope, using the projective covering method. Findings: Investigations carried out confirm that the fractal dimension and parameters describing the multifractal spectrum shape may be used for characterizing and comparing surfaces of coatings obtained in the PVD and CVD processes and of the substrate material from the Al2O3+TiC. Research limitations/implications: Investigation or relationship between parameters describing the multifractal spectrum and physical properties of the examined materials calls for further analyses. Originality/value: Investigations carried out confirm that the fractal dimension and parameters describing the multifractal spectrum shape may be used for characterizing and comparing surfaces of coatings obtained in the PVD and CVD processes.

20

Virtual examinations of alloying elements influence on alloy structural steels mechanical properties

Dobrzański L. A., Honysz R.

Journal of Achievements in Materials and Manufacturing Engineering

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2011

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Vol. 49, nr 2

251--258

EN

Purpose: The paper introduces analysis results of selected alloying elements influence on mechanical properties of alloy structural steels for quenching and tempering. Design/methodology/approach: Investigations were performed in virtual environment with use of materials science virtual laboratory. Virtual investigations results were verified in real investigative laboratory. Findings: Materials researches performed with use of material science virtual laboratory in range of determining the mechanical properties are consistent with the results obtained during the real research in real laboratory. Practical implications: Development of virtual tools, which are simulating the investigative equipment and simulating the research methodology, can serve as a basis for combining aspects of laboratory research, simulation, measurement, and education. Application of these tools will allow the transfer of research and teaching procedures from real laboratory to virtual environment. This will increase the number of experiments conducted in virtual environment and thus, it will increase the efficiency of such researches. Originality/value: Modelling of structural steels mechanical properties is valuable for steel designers and manufacturers, because it is associated with financial benefits, when expensive and time-consuming researches are reduced to necessary minimum.