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Choi, Joeun; Quagliato, Luca; Lee, Seungro; Shin, Junghoon; Kim, Naksoo
International journal of fatigue, April 2021, 2021-04-00, 20210401, Letnik: 145Journal Article
Display omitted •Multiaxial fatigue life research of the of tungsten-filled polychloroprene rubber.•Experiment utilizing notched specimens and limiting dome test experiments.•Semi-empirical fatigue model development considering anisotropy and triaxiality.•Additional fatigue life estimation considering machine learning-based models.•Reliable estimation of the fatigue life for both developed approaches. In this paper, multiaxial fatigue experiments on a hyperelastic rubber-like material made of polychloroprene rubber (CR) reinforced with tungsten nano-particles have been carried out on notched specimens and hourglass specimens, utilized for limiting dome height fatigue tests. Based on the uniaxial (Choi et al., 2020) and multiaxial fatigue experiments, a semi-empirical ε-N fatigue model is proposed, allows accounting for both material anisotropy and complex stress states, showing an average error of 20.7%. Furthermore, six machine learning models have been employed for the fatigue life prediction and shown that the Deep Neural Network is the most accurate, with an average error equal to 14.3%.
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Dostop do baze podatkov JCR je dovoljen samo uporabnikom iz Slovenije. Vaš trenutni IP-naslov ni na seznamu dovoljenih za dostop, zato je potrebna avtentikacija z ustreznim računom AAI.
Leto | Faktor vpliva | Izdaja | Kategorija | Razvrstitev | ||||
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JCR | SNIP | JCR | SNIP | JCR | SNIP | JCR | SNIP |
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Povezave do osebnih bibliografij avtorjev | Povezave do podatkov o raziskovalcih v sistemu SICRIS |
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Vir: Osebne bibliografije
in: SICRIS
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