This page has only limited features, please log in for full access.

Unclaimed
Ivan Kopal
Department of Numerical Methods and Computational Modeling, Faculty of Industrial Technologies in Púchov, Alexander Dubček University of Trenčín, Ivana Krasku 491/30, 020 01 Púchov, Slovakia

Basic Info

Basic Info is private.

Honors and Awards

The user has no records in this section


Career Timeline

The user has no records in this section.


Short Biography

The user biography is not available.
Following
Followers
Co Authors
The list of users this user is following is empty.
Following: 0 users

Feed

Journal article
Published: 16 May 2021 in Materials
Reads 0
Downloads 0

The formulation of the Hall–Petch relationship in the early 1950s has raised immense interest in studying the influence of the grain size of solid materials on their properties. Grain refinement can be achieved through extreme deformation. In the presented study, Equal-Channel Angular Pressing (ECAP) was successfully applied to produce an ultrafine-grained microstructure in a pure commercial Cu of 99.9 wt%. Samples were processed by ECAP at 21 °C for six passes via route A. A new equation of equilibrium that allows the exact determination of the number of extrusions and other technological parameters required to achieve the desired final grain size has been developed. The presented research also deals, in a relatively detailed and comparative way, with the use of ultrasound. In this context, a very close correlation between the process functions of extrusion and the speed of longitudinal ultrasonic waves was confirmed.

ACS Style

Marta Harničárová; Jan Valíček; Milena Kušnerová; Zuzana Palková; Ivan Kopal; Cristina Borzan; Milan Kadnár; Stanislav Paulovič. A New Method of Predicting the Structural and Mechanical Change of Materials during Extrusion by the Method of Multiple Plastic Deformations. Materials 2021, 14, 2594 .

AMA Style

Marta Harničárová, Jan Valíček, Milena Kušnerová, Zuzana Palková, Ivan Kopal, Cristina Borzan, Milan Kadnár, Stanislav Paulovič. A New Method of Predicting the Structural and Mechanical Change of Materials during Extrusion by the Method of Multiple Plastic Deformations. Materials. 2021; 14 (10):2594.

Chicago/Turabian Style

Marta Harničárová; Jan Valíček; Milena Kušnerová; Zuzana Palková; Ivan Kopal; Cristina Borzan; Milan Kadnár; Stanislav Paulovič. 2021. "A New Method of Predicting the Structural and Mechanical Change of Materials during Extrusion by the Method of Multiple Plastic Deformations." Materials 14, no. 10: 2594.

Journal article
Published: 11 November 2020 in Polymers
Reads 0
Downloads 0

Modelling the influence of high-energy ionising radiation on the properties of materials with polymeric matrix using advanced artificial intelligence tools plays an important role in the research and development of new materials for various industrial applications. It also applies to effective modification of existing materials based on polymer matrices to achieve the desired properties. In the presented work, the effects of high-energy electron beam radiation with various doses on the dynamic mechanical properties of melamine resin, phenol-formaldehyde resin, and nitrile rubber blend have been studied over a wide temperature range. A new stiffness-temperature model based on Weibull statistics of the secondary bonds breaking during the relaxation transitions has been developed to quantitatively describe changes in the storage modulus with temperature and applied radiation dose until the onset of the temperature of the additional, thermally-induced polymerisation reactions. A global search real-coded genetic algorithm has been successfully applied to optimise the parameters of the developed model by minimising the sum-squared error. An excellent agreement between the modelled and experimental data has been found.

ACS Style

Ivan Kopal; Juliána Vršková; Alžbeta Bakošová; Marta Harničárová; Ivan Labaj; Darina Ondrušová; Jan Valíček; Jan Krmela. Modelling the Stiffness-Temperature Dependence of Resin-Rubber Blends Cured by High-Energy Electron Beam Radiation Using Global Search Genetic Algorithm. Polymers 2020, 12, 2652 .

AMA Style

Ivan Kopal, Juliána Vršková, Alžbeta Bakošová, Marta Harničárová, Ivan Labaj, Darina Ondrušová, Jan Valíček, Jan Krmela. Modelling the Stiffness-Temperature Dependence of Resin-Rubber Blends Cured by High-Energy Electron Beam Radiation Using Global Search Genetic Algorithm. Polymers. 2020; 12 (11):2652.

Chicago/Turabian Style

Ivan Kopal; Juliána Vršková; Alžbeta Bakošová; Marta Harničárová; Ivan Labaj; Darina Ondrušová; Jan Valíček; Jan Krmela. 2020. "Modelling the Stiffness-Temperature Dependence of Resin-Rubber Blends Cured by High-Energy Electron Beam Radiation Using Global Search Genetic Algorithm." Polymers 12, no. 11: 2652.

Journal article
Published: 21 June 2019 in Polymers
Reads 0
Downloads 0

The presented work deals with the creation of a new radial basis function artificial neural network-based model of dynamic thermo-mechanical response and damping behavior of thermoplastic elastomers in the whole temperature interval of their entire lifetime and a wide frequency range of dynamic mechanical loading. The created model is based on experimental results of dynamic mechanical analysis of the widely used thermoplastic polyurethane, which is one of the typical representatives of thermoplastic elastomers. Verification and testing of the well-trained radial basis function neural network for temperature and frequency dependence of dynamic storage modulus, loss modulus, as well as loss tangent prediction showed excellent correspondence between experimental and modeled data, including all relaxation events observed in the polymeric material under study throughout the monitored temperature and frequency interval. The radial basis function artificial neural network has been confirmed to be an exceptionally high-performance artificial intelligence tool of soft computing for the effective predicting of short-term viscoelastic behavior of thermoplastic elastomer systems based on experimental results of dynamic mechanical analysis.

ACS Style

Ivan Kopal; Marta Harničárová; Jan Valíček; Jan Krmela; Ondrej Lukáč. Radial Basis Function Neural Network-Based Modeling of the Dynamic Thermo-Mechanical Response and Damping Behavior of Thermoplastic Elastomer Systems. Polymers 2019, 11, 1074 .

AMA Style

Ivan Kopal, Marta Harničárová, Jan Valíček, Jan Krmela, Ondrej Lukáč. Radial Basis Function Neural Network-Based Modeling of the Dynamic Thermo-Mechanical Response and Damping Behavior of Thermoplastic Elastomer Systems. Polymers. 2019; 11 (6):1074.

Chicago/Turabian Style

Ivan Kopal; Marta Harničárová; Jan Valíček; Jan Krmela; Ondrej Lukáč. 2019. "Radial Basis Function Neural Network-Based Modeling of the Dynamic Thermo-Mechanical Response and Damping Behavior of Thermoplastic Elastomer Systems." Polymers 11, no. 6: 1074.

Article
Published: 09 May 2019 in Materialwissenschaft und Werkstofftechnik
Reads 0
Downloads 0

The presented work deals with the application of artificial neural networks in the modelling of the thermal decomposition process of friction composite systems based on polymer matrices reinforced by yarns. The thermal decomposition of the automotive clutch friction composite system consisting of a polymer blend reinforced by yarns from organic, inorganic and metallic fibres impregnated with resin, as well as its individual components, was monitored by a method of non‐isothermal thermogravimetry over a wide temperature range. A supervised feed‐forward back‐propagation multi‐layer artificial neural network model, with temperature as the only input parameter, has been developed to predict the thermogravimetric curves of weight loss and time derivative of weight loss of studied friction composite system and its individual components acquired at a fixed constant heating rate under a pure dry nitrogen atmosphere at a constant flow rate. It has been proven that an optimized model with a 1‐25‐6 architecture of an artificial neural network trained by a Levenberg‐Marquardt algorithm is able to predict simultaneously all the analyzed experimental thermogravimetric curves with a high level of reliability and that it thus represents the highly effective artificial intelligence tool for the modelling of thermal stability also of relatively complicated friction composite systems.

ACS Style

I. Kopal; J. Vršková; D. Ondrušová; M. Harničárová; J. Valíček; Z. Koleničová. Modeling the thermal decomposition of friction composite systems based on yarn reinforced polymer matrices using artificial neural networks. Materialwissenschaft und Werkstofftechnik 2019, 50, 616 -628.

AMA Style

I. Kopal, J. Vršková, D. Ondrušová, M. Harničárová, J. Valíček, Z. Koleničová. Modeling the thermal decomposition of friction composite systems based on yarn reinforced polymer matrices using artificial neural networks. Materialwissenschaft und Werkstofftechnik. 2019; 50 (5):616-628.

Chicago/Turabian Style

I. Kopal; J. Vršková; D. Ondrušová; M. Harničárová; J. Valíček; Z. Koleničová. 2019. "Modeling the thermal decomposition of friction composite systems based on yarn reinforced polymer matrices using artificial neural networks." Materialwissenschaft und Werkstofftechnik 50, no. 5: 616-628.

Journal article
Published: 28 November 2018 in Materials
Reads 0
Downloads 0

Irradiation by ionizing radiation is a specific type of controllable modification of the physical and chemical properties of a wide range of polymers, which is, in comparison to traditional chemical methods, rapid, non-polluting, simple, and relatively cheap. In the presented paper, the influence of high-energy ionizing radiation on the basic mechanical properties of the melamine resin, phenol-formaldehyde resin, and nitrile rubber blend has been studied for the first time. The mechanical properties of irradiated samples were compared to those of non-irradiated materials. It was found that radiation doses up to 150 kGy improved the mechanical properties of the tested materials in terms of a significant increase in stress at break, tensile strength, and tensile modulus at 40% strain, while decreasing the value of strain at break. At radiation doses above 150 kGy, the irradiated polymer blend is already degrading, and its tensile characteristics significantly deteriorate. An radiation dose of 150 kGy thus appears to be optimal from the viewpoint of achieving significant improvement, and the radiation treatment of the given polymeric blend by a beam of accelerated electrons is a very promising alternative to the traditional chemical mode of treatment which impacts the environment.

ACS Style

Ivan Kopal; Juliana Vršková; Ivan Labaj; Darina Ondrušová; Peter Hybler; Marta Harničárová; Jan Valíček; Milena Kušnerová. The Effect of High-Energy Ionizing Radiation on the Mechanical Properties of a Melamine Resin, Phenol-Formaldehyde Resin, and Nitrile Rubber Blend. Materials 2018, 11, 2405 .

AMA Style

Ivan Kopal, Juliana Vršková, Ivan Labaj, Darina Ondrušová, Peter Hybler, Marta Harničárová, Jan Valíček, Milena Kušnerová. The Effect of High-Energy Ionizing Radiation on the Mechanical Properties of a Melamine Resin, Phenol-Formaldehyde Resin, and Nitrile Rubber Blend. Materials. 2018; 11 (12):2405.

Chicago/Turabian Style

Ivan Kopal; Juliana Vršková; Ivan Labaj; Darina Ondrušová; Peter Hybler; Marta Harničárová; Jan Valíček; Milena Kušnerová. 2018. "The Effect of High-Energy Ionizing Radiation on the Mechanical Properties of a Melamine Resin, Phenol-Formaldehyde Resin, and Nitrile Rubber Blend." Materials 11, no. 12: 2405.

Conference paper
Published: 01 July 2018 in EDULEARN18 Proceedings
Reads 0
Downloads 0
ACS Style

Milena Kušnerová; Michal Řepka; Zuzana Palkova; Jan Valíček; Ivan Kopal; Marta Harničárová; Ivan Labaj. MEASUREMENT OF ELASTIC MODULUS IN TENSION USING DYNAMIXEL INTELLIGENT ACTUATOR. EDULEARN18 Proceedings 2018, 490 -497.

AMA Style

Milena Kušnerová, Michal Řepka, Zuzana Palkova, Jan Valíček, Ivan Kopal, Marta Harničárová, Ivan Labaj. MEASUREMENT OF ELASTIC MODULUS IN TENSION USING DYNAMIXEL INTELLIGENT ACTUATOR. EDULEARN18 Proceedings. 2018; ():490-497.

Chicago/Turabian Style

Milena Kušnerová; Michal Řepka; Zuzana Palkova; Jan Valíček; Ivan Kopal; Marta Harničárová; Ivan Labaj. 2018. "MEASUREMENT OF ELASTIC MODULUS IN TENSION USING DYNAMIXEL INTELLIGENT ACTUATOR." EDULEARN18 Proceedings , no. : 490-497.

Journal article
Published: 09 June 2018 in Polymers
Reads 0
Downloads 0

The precise experimental estimation of mechanical properties of rubber blends can be a very costly and time-consuming process. The present work explores the possibilities of increasing its efficiency by using artificial neural networks to study the mechanical behavior of these widely used materials. A multilayer feed-forward back-propagation artificial neural network model, with a strain and the carbon black content as input parameters and stress as an output parameter, has been developed to predict the uniaxial tensile response of vulcanized natural rubber blends with different contents of carbon black in the form of engineering stress-strain curves. A novel procedure has been created for the simulation of the optimized artificial neural network model with input datasets generated by a regression model of an experimental dependence of tensile strain-at-break on the carbon black content in the investigated blends. Errors of the prediction of experimental stress-strain curves, as well as of tensile strain-at-break, tensile stress-at-break and M100 tensile modulus were estimated for all simulated stress-strain curves. The present study demonstrated that the performance of a developed neural network model to predict the stress-strain curves of rubber blends with different contents of carbon black is also exceptionally high in the case of a network that had never learned the input data, which makes it a suitable tool for extensive use in practice.

ACS Style

Ivan Kopal; Ivan Labaj; Marta Harnicarova; Jan Valíček; Dušan Hrubý. Prediction of the Tensile Response of Carbon Black Filled Rubber Blends by Artificial Neural Network. Polymers 2018, 10, 644 .

AMA Style

Ivan Kopal, Ivan Labaj, Marta Harnicarova, Jan Valíček, Dušan Hrubý. Prediction of the Tensile Response of Carbon Black Filled Rubber Blends by Artificial Neural Network. Polymers. 2018; 10 (6):644.

Chicago/Turabian Style

Ivan Kopal; Ivan Labaj; Marta Harnicarova; Jan Valíček; Dušan Hrubý. 2018. "Prediction of the Tensile Response of Carbon Black Filled Rubber Blends by Artificial Neural Network." Polymers 10, no. 6: 644.

Article
Published: 30 May 2018 in Materialwissenschaft und Werkstofftechnik
Reads 0
Downloads 0

In the present study, the activation energy associated with the primary and the secondary relaxation transition events in thermoplastic polyurethane has been determined using the multi‐frequency dynamic mechanical analysis tests. The thermoplastic polyurethane under investigation was tested at temperatures between 145 K ‐ 526 K, at frequencies of 0.5 Hz, 1 Hz, 2 Hz, 5 Hz and 10 Hz and at a constant heating rate of 3 K⋅min–1. It was observed that the studied materials show three relaxation events – glass transition of soft segments, glass transition of hard segments as well as secondary transition associated with short range order translation and with reorientational motions within the polyurethane crystals. The activation energies for all three observed relaxation events were determined from dynamic mechanical properties measured at various frequencies using a linearized Arrhenius equation. The calculated activation energy is 379.73 kJ⋅mol‐1 for the glass transition of hard segments; for the secondary relaxation transition it is 65.53 kJ⋅mol‐1 and for the glass transition of soft segments it is 45.98 kJ⋅mol‐1.

ACS Style

I. Kopal; M. Harničárová; J. Valíček; P. Koštial; Z.K. Jančíková. Determination of activation energy of relaxation events in thermoplastic polyurethane by dynamic mechanical analysis. Materialwissenschaft und Werkstofftechnik 2018, 49, 627 -634.

AMA Style

I. Kopal, M. Harničárová, J. Valíček, P. Koštial, Z.K. Jančíková. Determination of activation energy of relaxation events in thermoplastic polyurethane by dynamic mechanical analysis. Materialwissenschaft und Werkstofftechnik. 2018; 49 (5):627-634.

Chicago/Turabian Style

I. Kopal; M. Harničárová; J. Valíček; P. Koštial; Z.K. Jančíková. 2018. "Determination of activation energy of relaxation events in thermoplastic polyurethane by dynamic mechanical analysis." Materialwissenschaft und Werkstofftechnik 49, no. 5: 627-634.

Journal article
Published: 01 January 2017 in Defect and Diffusion Forum
Reads 0
Downloads 0

Wood plastic composite (WPC) materials represent modern materials that are attracting interest worldwide. WPC are composite materials and they have properties of both components – plastic and wood. WPC materials are formed by combining two substances – discontinuous reinforcements (wood particles or cellulose microfibers) and a continuous binder (plastic matrix), in a certain proportion. The authors describe WPC machined surfaces after turning. On the basis of a set of experimental data collected by surface and mechanical tests obtained from the WPC materials, the mechanical deformation work was evaluated, the value of which presents specific information about the material as a specific material coefficient.

ACS Style

Marta Harničárová; Milena Kušnerová; Jan Valíček; Ivan Kopal; Vojtěch Václavík; Zuzana Mitaľová; Dušan Mitaľ. Analysis of Physical-Mechanical and Surface Properties of Wood Plastic Composite Materials to Determine the Energy Balance. Defect and Diffusion Forum 2017, 370, 78 -89.

AMA Style

Marta Harničárová, Milena Kušnerová, Jan Valíček, Ivan Kopal, Vojtěch Václavík, Zuzana Mitaľová, Dušan Mitaľ. Analysis of Physical-Mechanical and Surface Properties of Wood Plastic Composite Materials to Determine the Energy Balance. Defect and Diffusion Forum. 2017; 370 ():78-89.

Chicago/Turabian Style

Marta Harničárová; Milena Kušnerová; Jan Valíček; Ivan Kopal; Vojtěch Václavík; Zuzana Mitaľová; Dušan Mitaľ. 2017. "Analysis of Physical-Mechanical and Surface Properties of Wood Plastic Composite Materials to Determine the Energy Balance." Defect and Diffusion Forum 370, no. : 78-89.

Journal article
Published: 01 January 2017 in Defect and Diffusion Forum
Reads 0
Downloads 0

This paper aims to study the cooling of a solid body. An analytical analysis of a solid body cooling in different regimes is presented, such as a simple first order exponential model, a modified exponential model, a generalized exponential model and the so-called regular temperature regime. The analysis also includes the influence of the dynamically changing relaxation time and we also present the solution of the nonlinear heat equation.

ACS Style

Ivan Kopal; Pavel Koštial; Zora Jančíková; Jan Valíček; Marta Harničárová. An Analytical Framework for the Study of Solid Body Cooling. Defect and Diffusion Forum 2017, 370, 1 -18.

AMA Style

Ivan Kopal, Pavel Koštial, Zora Jančíková, Jan Valíček, Marta Harničárová. An Analytical Framework for the Study of Solid Body Cooling. Defect and Diffusion Forum. 2017; 370 ():1-18.

Chicago/Turabian Style

Ivan Kopal; Pavel Koštial; Zora Jančíková; Jan Valíček; Marta Harničárová. 2017. "An Analytical Framework for the Study of Solid Body Cooling." Defect and Diffusion Forum 370, no. : 1-18.

Journal article
Published: 01 January 2017 in Defect and Diffusion Forum
Reads 0
Downloads 0

This article presents the results of an experimental research dealing with the measurement of the thermal characteristics of concretes based on natural and artificial aggregates (steel slag). The samples of concrete composites were prepared on the basis of natural aggregate fractions 0/4, 4/8 and 8/16 mm and on the basis of steel slag fr. 4/8 mm. The volume ratio of the individual aggregate fractions in all experimental mixtures used for the production of concrete composites was 40:30:30 (fr. 0/4: 4/8: 8/16). The prepared samples of concrete composites based on natural aggregate and natural aggregate combined with steel slag were subjected to the tests of strength characteristics, water-tightness, thermal characteristics using a commercial device ISOMET 2104 (measurement of the coefficient of thermal conductivity λ, specific heat capacity c, and the coefficient of thermal diffusivity a), and heating in a prototype calorimetric computer-controlled chamber. The main attention was focused on the testing of the value changes of the coefficients of thermal conductivity λ depending on the changes of temperatures within the range of -5 °C to + 40 °C. The measurements of these thermal characteristics have very high informative value, especially because these material parameters are not tabulated for the newly designed building materials, and that is why they are not examined at extreme temperatures. This is a reason why they cannot be used as important data during the thermal calculations of a non-insulated concrete structure (e.g. using polystyrene and / or glass wool).

ACS Style

Milena Kušnerová; Ivan Kopal; Vojtěch Václavík; Tomáš Dvorský; Jan Valíček; Marta Harničárová; Vojtěch Šimíček; Lukáš Gola. Measuring the Thermal Characteristics of Concretes Exposed to Extreme Conditions. Defect and Diffusion Forum 2017, 370, 68 -77.

AMA Style

Milena Kušnerová, Ivan Kopal, Vojtěch Václavík, Tomáš Dvorský, Jan Valíček, Marta Harničárová, Vojtěch Šimíček, Lukáš Gola. Measuring the Thermal Characteristics of Concretes Exposed to Extreme Conditions. Defect and Diffusion Forum. 2017; 370 ():68-77.

Chicago/Turabian Style

Milena Kušnerová; Ivan Kopal; Vojtěch Václavík; Tomáš Dvorský; Jan Valíček; Marta Harničárová; Vojtěch Šimíček; Lukáš Gola. 2017. "Measuring the Thermal Characteristics of Concretes Exposed to Extreme Conditions." Defect and Diffusion Forum 370, no. : 68-77.

Journal article
Published: 30 April 2016 in International Journal of Materials Research
Reads 0
Downloads 0

In this paper, a stiffness–temperature model based on Weibull statistics was applied to quantitatively describe changes in the storage modulus of thermoplastic polyurethane over a wide range of temperature. The variation of the storage modulus with temperature was obtained from dynamic mechanical analysis tests across transition temperatures. Both the physical and statistical parameters of the applied model were estimated in the process of parametric fitting of the model to the storage modulus versus a temperature curve by using a trust region algorithm for a robust nonlinear least squares method. Good agreement between the modeled and experimental data has been found over the entire investigated temperature range, including all observed relaxation transitions.

ACS Style

Ivan Kopal; Dana Bakošová; Pavel Koštial; Zora Jančíková; Jan Valíček; Marta Harničárová. Weibull distribution application on temperature dependence of polyurethane storage modulus. International Journal of Materials Research 2016, 107, 472 -476.

AMA Style

Ivan Kopal, Dana Bakošová, Pavel Koštial, Zora Jančíková, Jan Valíček, Marta Harničárová. Weibull distribution application on temperature dependence of polyurethane storage modulus. International Journal of Materials Research. 2016; 107 (5):472-476.

Chicago/Turabian Style

Ivan Kopal; Dana Bakošová; Pavel Koštial; Zora Jančíková; Jan Valíček; Marta Harničárová. 2016. "Weibull distribution application on temperature dependence of polyurethane storage modulus." International Journal of Materials Research 107, no. 5: 472-476.

Journal article
Published: 01 January 2016 in Procedia Engineering
Reads 0
Downloads 0

Nowadays, the optical methods for deformation measurement are gaining more and more applications from the aspect of solution of problems relating to elasticity and strength. The advantage of such methods is based on the measurement of non-destructive way without assembly of measuring elements regarding to the critical areas of structures. One of these contactless measuring methods is Electronic Speckle Pattern Interferometry ESPI that is based on the discovery of so-called speckle patterns. Electronic Speckle Pattern Interferometry is an optical full-field measurement method for determination of deformations of object surfaces with sensitivity below fractions of the wavelength of light. A back scattered object beam of an object surface and a reference beam, originating from the same laser light source, are superimposed on a video camera and interfere to a speckle pattern. Speckle pattern is based on the record before and after deformation of the object yield to a non-unique fringe pattern. Using a phase shifting method, this non-uniqueness can be solved and the fringe pattern can be evaluated using a computer algorithm. In this study, experimental investigation of vibration behaviour of square rubber blends plates by electronic speckle pattern interferometry (ESPI) is employed. Resonant frequencies and corresponding mode shape are obtained experimentally using the introduced method. Frequencies of resonant vibrational modes depend on elastic properties of material, especially on Young modulus E, Poisson ratio μ and density of material ρ. This fact gives us, in principle, the possibility to estimate the elastic constant of materials from the vibrational measurement. The numerical calculations by the finite element method (Cosmos) are performed and the results are compared to the experimental measurements.

ACS Style

Dana Bakošová; Ivan Kopal. Study of Rubber Blends by Electronic Speckle Pattern Interferometry. Procedia Engineering 2016, 136, 233 -238.

AMA Style

Dana Bakošová, Ivan Kopal. Study of Rubber Blends by Electronic Speckle Pattern Interferometry. Procedia Engineering. 2016; 136 ():233-238.

Chicago/Turabian Style

Dana Bakošová; Ivan Kopal. 2016. "Study of Rubber Blends by Electronic Speckle Pattern Interferometry." Procedia Engineering 136, no. : 233-238.