Ivan Kopal - Academia.edu (original) (raw)

Papers by Ivan Kopal

Nucleation and Atmospheric Aerosols, 2016

The International Journal of Advanced Manufacturing Technology

The presented publication is based on the interaction of the material core and its surface during... more The presented publication is based on the interaction of the material core and its surface during the machining process with a hydro abrasive flexible cutting tool (AWJ). In the AWJ technology, a cold cut is generated; therefore, there are no thermal stresses on the newly formed surface and, consequently, no significant internal and residual stresses. The cut is identifiable by directly measurable parameters: depth of cut, deviation of the cut path from the normal plane, and surface roughness. These geometric parameters are interdependent at each cut zone point and simultaneously dependent on a newly proposed, indirectly measurable material parameter, Kplmat. Although the deviation angle of the cutting path from the normal plane increases with increasing depth of cut, the ratio of the “material plasticity” Kplmat and the surface roughness Ra of the cutting surface remains equivalent to the ratio of the depth of cut and the deviation of the cutting path from the normal plane. Based o...

Materialwissenschaft und Werkstofftechnik

The current trend of greening production is increasingly bringing to the fore alternative types o... more The current trend of greening production is increasingly bringing to the fore alternative types of fillers, such as biofillers, which are obtained from renewable sources or waste [1, 2]. Unfortunately, biofillers cannot be used as majority fillers due to their incompatibility with elastomer matrices and high biodegradability susceptibility [3, 4]. Therefore, the way to their efficient industrial use leads through supplementary fillers to the commonly used inorganic fillers and the partial replacement of these fillers in the blend. The influence of Chitosan as the majority filler has been investigated and its combination with carbon black filler on the elastomeric matrix of natural rubber was investigated in the presented work. The results were compared with natural rubber blends filled exclusively with carbon black. Natural rubber blends with different content of Chitosan and carbon black and their various combinations were subjected to the determination of vulcanization parameters,...

ABSTACT This work provides non-contact optical technique to investigate the transverse vibration ... more ABSTACT This work provides non-contact optical technique to investigate the transverse vibration characteristics of laminate square plates in resonance. Most of the works on vibration analysis of plates published in the literature are analytical and numerical and very few experimental results are available. This work collects some information about possibilities, advantages, and disadvantages of ESPI applications by nondestructive testing of composite materials and briefly introduces a damping feature of composites. Theory of plate vibrations allows us to determine Poisson’s ratioν , Young's modulus E and shear modulus G from the measured resonant frequencies. We are able to analyze the damping behavior of various types of composite materials from measured shape modes. We also present ESPI like a very useful tool for determination of defects in composite components. ESPI can be used to perform nondestructive evaluation of glass-fiber reinforced plastic (GFRP) laminate plates con...

Machine Dynamics Problems, 2006

Rubber blends dynamic-mechanical characteristics has been investigated. The aim of this work is t... more Rubber blends dynamic-mechanical characteristics has been investigated. The aim of this work is to present DMA testing on Diamond Pyris DMA testing machine, characterisation of thermal dynamic mechanical properties of rubber blends. Dynamic mechanical analysis (DMA) is a powerful technique for the characterization of the viscoelastic properties of polymers. DMA measures the modulus (stiffness) and damping (energy dissipation) properties of materials as they are deformed under dynamic stress. These measurements provide quantitative information about the performance of materials. The technique can be used to evaluate a wide variety of materials such as thermoplastics, composites, thermosets, elastomers, films, fibers, coatings and adhesives. Polymeric materials exhibit viscoelastic behavior, which means that they simultaneously possess both solid-like as well as liquid –like characteristics. The degree to which the polymer exhibits more solidlike or liquid-like properties is dependent...

Machine Dynamics Problems, 2006

Machine Dynamics Problems, 2004

IOP Conference Series: Materials Science and Engineering, 2020

This paper is focused on the preparation of polymer blends with addition of alternative filler fr... more This paper is focused on the preparation of polymer blends with addition of alternative filler from glass industry in various granularity (>40 µm, 40–32 µm, 32–25 µm, 25–0 µm). The polymer matrix (PMX3) consists of melamine resin, phenolic resin and nitrile rubber. This polymer matrix composition is commonly applied in friction composite systems in automotive industry. The surface activity of various filler fractions was studied. The rheological properties, such as minimum torque, maximum torque, optimum vulcanization time and scorch time of prepared friction polymer matrix were tested, using the PRPA 2000 rheometer. Mooney viscosity of new prepared polymer matrix was studied with help of Mooney Viscosimetr 91.03 Gottert testing machine.

Materialwissenschaft und Werkstofftechnik, 2017

In this work we study the influence of different types of plasticizers on the mechanical properti... more In this work we study the influence of different types of plasticizers on the mechanical properties of rubber blend mixtures before and after the ageing process. We have used Oleic acid as plasticizer. Reference samples were mixed with an oleic acid content of 1 part of the oleic acid to the 100 parts of rubber and 3 parts of the oleic acid to the 100 parts of rubber with weight percentages of the surfactant ETOXON 2, 4, 6, 8, 10, 20, 30 and basic mechanical properties such as tensile strength, Shore A hardness, ductility, moduli 100, 200, 300 have been measured. Measurements were performed 24 h after blend vulcanization and then 1 month after. We have studied the influence of plasticizers on the measured properties and the influence of ageing on the measured properties. All measured mechanical properties change with chemical composition except Shore A hardness.

International Journal of Thermophysics, 2016

The article deals with possible visualization of inhomogeneities in inorganic materials, such as ... more The article deals with possible visualization of inhomogeneities in inorganic materials, such as laminates, as well as organic materials, such as bones. This work also provides a study of the visualization of internal fixation (nail), introduced in a bone by the IR technique. In the theoretical part, we present thermal wave propagation and a theoretical approach to the possibility of visualization of the boundary between two different materials with different thermal conductivity. Further on, the experimental method is tested with success on discovering artificial defects in glass laminates. In the second part of the article, a successful method of the visualization of the internal fixator position in a bone under IR excitation is presented. Methods of processing the data measured with the use of an infrared camera are presented in detail.

Polymers

Modelling the flow properties of rubber blends makes it possible to predict their rheological beh... more Modelling the flow properties of rubber blends makes it possible to predict their rheological behaviour during the processing and production of rubber-based products. As the nonlinear nature of such complex processes complicates the creation of exact analytical models, it is appropriate to use artificial intelligence tools in this modelling. The present study was implemented to develop a highly efficient artificial neural network model, optimised using a novel training algorithm with fast parallel computing to predict the results of rheological tests of rubber blends performed under different conditions. A series of 120 real dynamic viscosity–time curves, acquired by a rubber process analyser for styrene–butadiene rubber blends with varying carbon black contents vulcanised at different temperatures, were analysed using a Generalised Regression Neural Network. The model was optimised by limiting the fitting error of the training dataset to a pre-specified value of less than 1%. All r...

in this paper is discussed a powerful method of an enhancement of subsurface defects detection in... more in this paper is discussed a powerful method of an enhancement of subsurface defects detection in automotive rubber made products via the pulsed phase thermography technique of the transient thermal data analysis. Hidden defects visibility improvement is attained by the artificial extension of an experimental thermal data set, acquired by a high sensitive infrared scanned detector camera, as well as by its upsampling before taking a one-dimensional discrete Fourier transform via a Goertzel algorithm. Tha data set extension in a periodic mode is originally done by using the two-dimensional discrete wavelet transform-based pattern. A lowpass linear finite impulse response digital filter, designed by using the least-square minimization method with the Kaiser window, is applied to prevent aliasing during the resampling procedure. It is demonstrated that the described approach to the transient experimental thermal data processing considerably amplifies defects detection posibilities of t...

Polymers

In this study, a new generalized regression neural network model for predicting the curing charac... more In this study, a new generalized regression neural network model for predicting the curing characteristics of rubber blends with different contents of carbon black filler cured at various temperatures is proposed for the first time The carbon black contents in the rubber blend and cure temperature were used as input parameters, while the minimum and maximum elastic torque, scorch time, and optimal cure time, obtained from the analysis of 11 rheological cure curves registered at 10 various temperatures, were considered as output parameters of the model. A special pre-processing procedure of the experimental input and target data and the training algorithm is described. Less than 55% of the experimental data were used to significantly reduce the total number of input and target data points needed for training the model. Satisfactory agreement between the predicted and experimental data, with a maximum error in the prediction not exceeding 5%, was found. It is concluded that the genera...

Vysoká škola báňská - Technická univerzita Ostrava, 2009

The paper deals with a curvature detection of a wheell;,arrow prototype. With the help of line la... more The paper deals with a curvature detection of a wheell;,arrow prototype. With the help of line laser profilometer the data in static regime were obtained. Measured data were processed by Matlab ®. The displacement in axiál x-direction was determined.

Defect and Diffusion Forum, 2020

Equal channel angular pressing (ECAP) is a widespread severe plastic deformation (SPD) method to ... more Equal channel angular pressing (ECAP) is a widespread severe plastic deformation (SPD) method to fabricate ultrafine-grained bulk materials. In the field of materials engineering, this method has already experienced rapid development over the past few decades. In this research, the authors sought to create a prediction of shortening and the material particle size after extrusion using ECAP. Behaviours of essential functions are analysed here on samples of pure copper Cu 99.9. It is the measurement and analytical processing of changes in the values of selected structural and mechanical parameters depending on the reduction of the structural granularity. Parameters such as deformation speed, deformation work and ECAP mechanical performance are also included in the results. The change in structure and mechanical parameters is also newly demonstrated by measuring the change in the velocity of the longitudinal ultrasound wave during the experimental passes. Based on the results obtained,...

In the present work, a new artificial neural network-based model for predicting the curing charac... more In the present work, a new artificial neural network-based model for predicting the curing characteristics of rubber blends with different contents of carbon black filler cured at various temperatures has been developed. The variations of 4 curing characteristics, most commonly used in the rubber industry, namely of the minimum and maximum elastic torque, scorch time and optimal cure time, with carbon black contents in the rubber blend and cure temperature, have been obtained on the basis of the analysis of 11 experimental isothermal rheological cure curves registered by an oscillating-disk rheometer at 10 cure temperatures. The computer implementation of the ANN model requires a special pre-processing of the raw experimental data, which is described in detail in the paper. The implementation of ANN model for predicting the curing characteristics of RBs with different contents of CB filler at various cure temperatures was done in the MATLAB® software package, Version 9.0.0.341360 R2016a 64-bit, equipped with a Neural Network Toolbox (Math Works, Natic, MA, USA), that provides a number of built-in tools for sufficiently powerful and user-friendly work with ANNs of a wide range of types and architectures. The GRNN was used to solve the given function approximation problem, in particular for its extremely high learning rate and rapid convergence to optimal regression levels even in the case of sparse data. The satisfactory agreement between the experimental and modelled values has been found for all four curing characteristics, with the maximum error in the prediction for modelled minimum and maximum elastic torque less than 3%, and for modelled scorch time and optimal cure time not exceeding 5% of their experimental values. It can be concluded that the generalized regression neural network is a very powerful tool for intelligent modelling the curing process of rubber blends even in the case of a small training dataset, and it can find a wide practical application in the area of the rubber industry.

Journal of Non-Crystalline Solids, 2022

Nucleation and Atmospheric Aerosols, 2016

The International Journal of Advanced Manufacturing Technology

The presented publication is based on the interaction of the material core and its surface during... more The presented publication is based on the interaction of the material core and its surface during the machining process with a hydro abrasive flexible cutting tool (AWJ). In the AWJ technology, a cold cut is generated; therefore, there are no thermal stresses on the newly formed surface and, consequently, no significant internal and residual stresses. The cut is identifiable by directly measurable parameters: depth of cut, deviation of the cut path from the normal plane, and surface roughness. These geometric parameters are interdependent at each cut zone point and simultaneously dependent on a newly proposed, indirectly measurable material parameter, Kplmat. Although the deviation angle of the cutting path from the normal plane increases with increasing depth of cut, the ratio of the “material plasticity” Kplmat and the surface roughness Ra of the cutting surface remains equivalent to the ratio of the depth of cut and the deviation of the cutting path from the normal plane. Based o...

Materialwissenschaft und Werkstofftechnik

The current trend of greening production is increasingly bringing to the fore alternative types o... more The current trend of greening production is increasingly bringing to the fore alternative types of fillers, such as biofillers, which are obtained from renewable sources or waste [1, 2]. Unfortunately, biofillers cannot be used as majority fillers due to their incompatibility with elastomer matrices and high biodegradability susceptibility [3, 4]. Therefore, the way to their efficient industrial use leads through supplementary fillers to the commonly used inorganic fillers and the partial replacement of these fillers in the blend. The influence of Chitosan as the majority filler has been investigated and its combination with carbon black filler on the elastomeric matrix of natural rubber was investigated in the presented work. The results were compared with natural rubber blends filled exclusively with carbon black. Natural rubber blends with different content of Chitosan and carbon black and their various combinations were subjected to the determination of vulcanization parameters,...

ABSTACT This work provides non-contact optical technique to investigate the transverse vibration ... more ABSTACT This work provides non-contact optical technique to investigate the transverse vibration characteristics of laminate square plates in resonance. Most of the works on vibration analysis of plates published in the literature are analytical and numerical and very few experimental results are available. This work collects some information about possibilities, advantages, and disadvantages of ESPI applications by nondestructive testing of composite materials and briefly introduces a damping feature of composites. Theory of plate vibrations allows us to determine Poisson’s ratioν , Young's modulus E and shear modulus G from the measured resonant frequencies. We are able to analyze the damping behavior of various types of composite materials from measured shape modes. We also present ESPI like a very useful tool for determination of defects in composite components. ESPI can be used to perform nondestructive evaluation of glass-fiber reinforced plastic (GFRP) laminate plates con...

Machine Dynamics Problems, 2006

Rubber blends dynamic-mechanical characteristics has been investigated. The aim of this work is t... more Rubber blends dynamic-mechanical characteristics has been investigated. The aim of this work is to present DMA testing on Diamond Pyris DMA testing machine, characterisation of thermal dynamic mechanical properties of rubber blends. Dynamic mechanical analysis (DMA) is a powerful technique for the characterization of the viscoelastic properties of polymers. DMA measures the modulus (stiffness) and damping (energy dissipation) properties of materials as they are deformed under dynamic stress. These measurements provide quantitative information about the performance of materials. The technique can be used to evaluate a wide variety of materials such as thermoplastics, composites, thermosets, elastomers, films, fibers, coatings and adhesives. Polymeric materials exhibit viscoelastic behavior, which means that they simultaneously possess both solid-like as well as liquid –like characteristics. The degree to which the polymer exhibits more solidlike or liquid-like properties is dependent...

Machine Dynamics Problems, 2006

Machine Dynamics Problems, 2004

IOP Conference Series: Materials Science and Engineering, 2020

This paper is focused on the preparation of polymer blends with addition of alternative filler fr... more This paper is focused on the preparation of polymer blends with addition of alternative filler from glass industry in various granularity (>40 µm, 40–32 µm, 32–25 µm, 25–0 µm). The polymer matrix (PMX3) consists of melamine resin, phenolic resin and nitrile rubber. This polymer matrix composition is commonly applied in friction composite systems in automotive industry. The surface activity of various filler fractions was studied. The rheological properties, such as minimum torque, maximum torque, optimum vulcanization time and scorch time of prepared friction polymer matrix were tested, using the PRPA 2000 rheometer. Mooney viscosity of new prepared polymer matrix was studied with help of Mooney Viscosimetr 91.03 Gottert testing machine.

Materialwissenschaft und Werkstofftechnik, 2017

In this work we study the influence of different types of plasticizers on the mechanical properti... more In this work we study the influence of different types of plasticizers on the mechanical properties of rubber blend mixtures before and after the ageing process. We have used Oleic acid as plasticizer. Reference samples were mixed with an oleic acid content of 1 part of the oleic acid to the 100 parts of rubber and 3 parts of the oleic acid to the 100 parts of rubber with weight percentages of the surfactant ETOXON 2, 4, 6, 8, 10, 20, 30 and basic mechanical properties such as tensile strength, Shore A hardness, ductility, moduli 100, 200, 300 have been measured. Measurements were performed 24 h after blend vulcanization and then 1 month after. We have studied the influence of plasticizers on the measured properties and the influence of ageing on the measured properties. All measured mechanical properties change with chemical composition except Shore A hardness.

International Journal of Thermophysics, 2016

The article deals with possible visualization of inhomogeneities in inorganic materials, such as ... more The article deals with possible visualization of inhomogeneities in inorganic materials, such as laminates, as well as organic materials, such as bones. This work also provides a study of the visualization of internal fixation (nail), introduced in a bone by the IR technique. In the theoretical part, we present thermal wave propagation and a theoretical approach to the possibility of visualization of the boundary between two different materials with different thermal conductivity. Further on, the experimental method is tested with success on discovering artificial defects in glass laminates. In the second part of the article, a successful method of the visualization of the internal fixator position in a bone under IR excitation is presented. Methods of processing the data measured with the use of an infrared camera are presented in detail.

Polymers

Modelling the flow properties of rubber blends makes it possible to predict their rheological beh... more Modelling the flow properties of rubber blends makes it possible to predict their rheological behaviour during the processing and production of rubber-based products. As the nonlinear nature of such complex processes complicates the creation of exact analytical models, it is appropriate to use artificial intelligence tools in this modelling. The present study was implemented to develop a highly efficient artificial neural network model, optimised using a novel training algorithm with fast parallel computing to predict the results of rheological tests of rubber blends performed under different conditions. A series of 120 real dynamic viscosity–time curves, acquired by a rubber process analyser for styrene–butadiene rubber blends with varying carbon black contents vulcanised at different temperatures, were analysed using a Generalised Regression Neural Network. The model was optimised by limiting the fitting error of the training dataset to a pre-specified value of less than 1%. All r...

in this paper is discussed a powerful method of an enhancement of subsurface defects detection in... more in this paper is discussed a powerful method of an enhancement of subsurface defects detection in automotive rubber made products via the pulsed phase thermography technique of the transient thermal data analysis. Hidden defects visibility improvement is attained by the artificial extension of an experimental thermal data set, acquired by a high sensitive infrared scanned detector camera, as well as by its upsampling before taking a one-dimensional discrete Fourier transform via a Goertzel algorithm. Tha data set extension in a periodic mode is originally done by using the two-dimensional discrete wavelet transform-based pattern. A lowpass linear finite impulse response digital filter, designed by using the least-square minimization method with the Kaiser window, is applied to prevent aliasing during the resampling procedure. It is demonstrated that the described approach to the transient experimental thermal data processing considerably amplifies defects detection posibilities of t...

Polymers

In this study, a new generalized regression neural network model for predicting the curing charac... more In this study, a new generalized regression neural network model for predicting the curing characteristics of rubber blends with different contents of carbon black filler cured at various temperatures is proposed for the first time The carbon black contents in the rubber blend and cure temperature were used as input parameters, while the minimum and maximum elastic torque, scorch time, and optimal cure time, obtained from the analysis of 11 rheological cure curves registered at 10 various temperatures, were considered as output parameters of the model. A special pre-processing procedure of the experimental input and target data and the training algorithm is described. Less than 55% of the experimental data were used to significantly reduce the total number of input and target data points needed for training the model. Satisfactory agreement between the predicted and experimental data, with a maximum error in the prediction not exceeding 5%, was found. It is concluded that the genera...

Vysoká škola báňská - Technická univerzita Ostrava, 2009

The paper deals with a curvature detection of a wheell;,arrow prototype. With the help of line la... more The paper deals with a curvature detection of a wheell;,arrow prototype. With the help of line laser profilometer the data in static regime were obtained. Measured data were processed by Matlab ®. The displacement in axiál x-direction was determined.

Defect and Diffusion Forum, 2020

Equal channel angular pressing (ECAP) is a widespread severe plastic deformation (SPD) method to ... more Equal channel angular pressing (ECAP) is a widespread severe plastic deformation (SPD) method to fabricate ultrafine-grained bulk materials. In the field of materials engineering, this method has already experienced rapid development over the past few decades. In this research, the authors sought to create a prediction of shortening and the material particle size after extrusion using ECAP. Behaviours of essential functions are analysed here on samples of pure copper Cu 99.9. It is the measurement and analytical processing of changes in the values of selected structural and mechanical parameters depending on the reduction of the structural granularity. Parameters such as deformation speed, deformation work and ECAP mechanical performance are also included in the results. The change in structure and mechanical parameters is also newly demonstrated by measuring the change in the velocity of the longitudinal ultrasound wave during the experimental passes. Based on the results obtained,...

In the present work, a new artificial neural network-based model for predicting the curing charac... more In the present work, a new artificial neural network-based model for predicting the curing characteristics of rubber blends with different contents of carbon black filler cured at various temperatures has been developed. The variations of 4 curing characteristics, most commonly used in the rubber industry, namely of the minimum and maximum elastic torque, scorch time and optimal cure time, with carbon black contents in the rubber blend and cure temperature, have been obtained on the basis of the analysis of 11 experimental isothermal rheological cure curves registered by an oscillating-disk rheometer at 10 cure temperatures. The computer implementation of the ANN model requires a special pre-processing of the raw experimental data, which is described in detail in the paper. The implementation of ANN model for predicting the curing characteristics of RBs with different contents of CB filler at various cure temperatures was done in the MATLAB® software package, Version 9.0.0.341360 R2016a 64-bit, equipped with a Neural Network Toolbox (Math Works, Natic, MA, USA), that provides a number of built-in tools for sufficiently powerful and user-friendly work with ANNs of a wide range of types and architectures. The GRNN was used to solve the given function approximation problem, in particular for its extremely high learning rate and rapid convergence to optimal regression levels even in the case of sparse data. The satisfactory agreement between the experimental and modelled values has been found for all four curing characteristics, with the maximum error in the prediction for modelled minimum and maximum elastic torque less than 3%, and for modelled scorch time and optimal cure time not exceeding 5% of their experimental values. It can be concluded that the generalized regression neural network is a very powerful tool for intelligent modelling the curing process of rubber blends even in the case of a small training dataset, and it can find a wide practical application in the area of the rubber industry.

Journal of Non-Crystalline Solids, 2022