Zobrazeno 1 - 10
of 56
pro vyhledávání: '"Ivan Kopal"'
Publikováno v:
ACS Omega, Vol 9, Iss 23, Pp 24685-24694 (2024)
Externí odkaz:
https://doaj.org/article/e616cef1d76f4d24bf733b012708a8a6
Autor:
Ivan Kopal, Marie Švecová, Vojtěch Jeřábek, David Palounek, Tereza Čapková, Alena Michalcová, Ladislav Lapčák, Pavel Matějka, Marcela Dendisová
Publikováno v:
ACS Omega, Vol 9, Iss 5, Pp 6005-6017 (2024)
Externí odkaz:
https://doaj.org/article/18165c2d8b8f466a8312f261daf2827a
Publikováno v:
Polymers, Vol 15, Iss 17, p 3636 (2023)
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
Externí odkaz:
https://doaj.org/article/67e4aeb0fd4b4322905ae7194e021e07
Autor:
Marta Harničárová, Jan Valíček, Milena Kušnerová, Ivan Kopal, Miloslav Lupták, Rastislav Mikuš, Zdeněk Pavelek, Martin Fabián, Vladimír Šepelák
Publikováno v:
Materials, Vol 15, Iss 6, p 2020 (2022)
SPD (several plastic deformations) methods make it possible to obtain an ultrafine-grained structure (UFG) in larger volumes of material and thus improve its mechanical properties. The presented work focuses on the structural and mechanical changes o
Externí odkaz:
https://doaj.org/article/9ef54787d1ab4b4a87f996ea9f75743a
Autor:
Ivan Kopal, Ivan Labaj, Juliána Vršková, Marta Harničárová, Jan Valíček, Darina Ondrušová, Jan Krmela, Zuzana Palková
Publikováno v:
Polymers, Vol 14, Iss 4, p 653 (2022)
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 c
Externí odkaz:
https://doaj.org/article/e52468425e6c4483bf7e5608eb026f83
Autor:
Marta Harničárová, Jan Valíček, Milena Kušnerová, Zuzana Palková, Ivan Kopal, Cristina Borzan, Milan Kadnár, Stanislav Paulovič
Publikováno v:
Materials, Vol 14, Iss 10, p 2594 (2021)
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 p
Externí odkaz:
https://doaj.org/article/6da0f9a4286e48f5bfd04dd7128fb7e9
Autor:
Ivan Kopal, Juliána Vršková, Alžbeta Bakošová, Marta Harničárová, Ivan Labaj, Darina Ondrušová, Jan Valíček, Jan Krmela
Publikováno v:
Polymers, Vol 12, Iss 11, p 2652 (2020)
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 industria
Externí odkaz:
https://doaj.org/article/1ce9efd3686b47578210797ec513a634
Publikováno v:
Polymers, Vol 11, Iss 6, p 1074 (2019)
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 l
Externí odkaz:
https://doaj.org/article/0678f978319446489f9a1ae4a640b9a3
Autor:
Ivan Kopal, Juliana Vršková, Ivan Labaj, Darina Ondrušová, Peter Hybler, Marta Harničárová, Jan Valíček, Milena Kušnerová
Publikováno v:
Materials, Vol 11, Iss 12, p 2405 (2018)
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 relative
Externí odkaz:
https://doaj.org/article/d29f78856dcb4bc3adaeeb8fd3da3790
Prediction of the Tensile Response of Carbon Black Filled Rubber Blends by Artificial Neural Network
Publikováno v:
Polymers, Vol 10, Iss 6, p 644 (2018)
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 m
Externí odkaz:
https://doaj.org/article/ec61eff006f9427fb4f6031b31ddb711