KOPAL, Ivan, Marta HARNIČÁROVÁ, Jan VALÍČEK, Jan KRMELA a Ondrej LUKAC. Radial Basis Function Neural Network-Based Modeling of the Dynamic Thermo-Mechanical Response and Damping Behavior of Thermoplastic Elastomer Systems. Polymer Science. BASEL, SWITZERLAND: MDPI, 2019, roč. 11, č. 6, s. nestránkováno, 20 s. ISSN 2073-4360. Dostupné z: https://dx.doi.org/10.3390/polym11061074. |
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@article{49521, author = {Kopal, Ivan and Harničárová, Marta and Valíček, Jan and Krmela, Jan and Lukac, Ondrej}, article_location = {BASEL, SWITZERLAND}, article_number = {6}, doi = {http://dx.doi.org/10.3390/polym11061074}, keywords = {"Author Keywords:artificial neural networks; radial basis functions; thermoplastic polyurethanes; visco-elastic properties; dynamic mechanical analysis ; KeyWords Plus:TRANSITION-TEMPERATURES; MECHANICAL-PROPERTIES; POLYURETHANE; PREDICTION; POLYMERS "}, language = {eng}, issn = {2073-4360}, journal = {Polymer Science}, title = {Radial Basis Function Neural Network-Based Modeling of the Dynamic Thermo-Mechanical Response and Damping Behavior of Thermoplastic Elastomer Systems}, url = {http://apps.webofknowledge.com/full_record.do?product=WOS&search_mode=GeneralSearch&qid=13&SID=F6xnU9HOLRR1jfSCtjp&page=1&doc=1}, volume = {11}, year = {2019} }
TY - JOUR ID - 49521 AU - Kopal, Ivan - Harničárová, Marta - Valíček, Jan - Krmela, Jan - Lukac, Ondrej PY - 2019 TI - Radial Basis Function Neural Network-Based Modeling of the Dynamic Thermo-Mechanical Response and Damping Behavior of Thermoplastic Elastomer Systems JF - Polymer Science VL - 11 IS - 6 SP - nestránkováno EP - nestránkováno PB - MDPI SN - 20734360 KW - "Author Keywords:artificial neural networks KW - radial basis functions KW - thermoplastic polyurethanes KW - visco-elastic properties KW - dynamic mechanical analysis KW - KeyWords Plus:TRANSITION-TEMPERATURES KW - MECHANICAL-PROPERTIES KW - POLYURETHANE KW - PREDICTION KW - POLYMERS " UR - http://apps.webofknowledge.com/full_record.do?product=WOS&search_mode=GeneralSearch&qid=13&SID=F6xnU9HOLRR1jfSCtjp&page=1&doc=1 L2 - http://apps.webofknowledge.com/full_record.do?product=WOS&search_mode=GeneralSearch&qid=13&SID=F6xnU9HOLRR1jfSCtjp&page=1&doc=1 N2 - 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. ER -
KOPAL, Ivan, Marta HARNIČÁROVÁ, Jan VALÍČEK, Jan KRMELA a Ondrej LUKAC. Radial Basis Function Neural Network-Based Modeling of the Dynamic Thermo-Mechanical Response and Damping Behavior of Thermoplastic Elastomer Systems. \textit{Polymer Science}. BASEL, SWITZERLAND: MDPI, 2019, roč.~11, č.~6, s.~nestránkováno, 20 s. ISSN~2073-4360. Dostupné z: https://dx.doi.org/10.3390/polym11061074.
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