EN
Tribological Behavior of Ultra-High Molecular Weight Polyethylene Polymer with Artificial Neural Network Modeling
Öz
This study presents the tribological properties, wear and friction, of ultra-high molecular weight polyethylene under conditions of dry sliding and Hank’s balanced salt solution lubrication. A pin-on-stainless steel disc apparatus was used for the friction and wear tests. Applied load conditions were 38, 50, 88, 100, 138, and 150N. Sliding speed conditions were 0.4, 0.5, 0.8, 1.0, 1.2 and 1.5 m/s. The results show that the coefficient of friction and the wear rate values decrease with the increase of applied load. The coefficient of friction and the wear rate values were highest under the dry sliding condition for the ranges of the sliding speed values and the applied loads tested in the study. In addition, the applicability of artificial neural networks (ANN) for predicting both the coefficients of friction and wear rate values of the material in different sliding conditions was studied. The neural network results were in agreement with the experimental results for the wear rates and coefficients of friction
Anahtar Kelimeler
Kaynakça
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Ayrıntılar
Birincil Dil
İngilizce
Konular
Makine Mühendisliği, Kompozit ve Hibrit Malzemeler
Bölüm
Araştırma Makalesi
Yayımlanma Tarihi
30 Kasım 2021
Gönderilme Tarihi
2 Temmuz 2021
Kabul Tarihi
22 Eylül 2021
Yayımlandığı Sayı
Yıl 2021 Cilt: 4 Sayı: 2
APA
Ermiş, K., & Ünal, H. (2021). Tribological Behavior of Ultra-High Molecular Weight Polyethylene Polymer with Artificial Neural Network Modeling. Kocaeli Journal of Science and Engineering, 4(2), 171-178. https://doi.org/10.34088/kojose.961118
AMA
1.Ermiş K, Ünal H. Tribological Behavior of Ultra-High Molecular Weight Polyethylene Polymer with Artificial Neural Network Modeling. KOJOSE. 2021;4(2):171-178. doi:10.34088/kojose.961118
Chicago
Ermiş, Kemal, ve Hüseyin Ünal. 2021. “Tribological Behavior of Ultra-High Molecular Weight Polyethylene Polymer with Artificial Neural Network Modeling”. Kocaeli Journal of Science and Engineering 4 (2): 171-78. https://doi.org/10.34088/kojose.961118.
EndNote
Ermiş K, Ünal H (01 Kasım 2021) Tribological Behavior of Ultra-High Molecular Weight Polyethylene Polymer with Artificial Neural Network Modeling. Kocaeli Journal of Science and Engineering 4 2 171–178.
IEEE
[1]K. Ermiş ve H. Ünal, “Tribological Behavior of Ultra-High Molecular Weight Polyethylene Polymer with Artificial Neural Network Modeling”, KOJOSE, c. 4, sy 2, ss. 171–178, Kas. 2021, doi: 10.34088/kojose.961118.
ISNAD
Ermiş, Kemal - Ünal, Hüseyin. “Tribological Behavior of Ultra-High Molecular Weight Polyethylene Polymer with Artificial Neural Network Modeling”. Kocaeli Journal of Science and Engineering 4/2 (01 Kasım 2021): 171-178. https://doi.org/10.34088/kojose.961118.
JAMA
1.Ermiş K, Ünal H. Tribological Behavior of Ultra-High Molecular Weight Polyethylene Polymer with Artificial Neural Network Modeling. KOJOSE. 2021;4:171–178.
MLA
Ermiş, Kemal, ve Hüseyin Ünal. “Tribological Behavior of Ultra-High Molecular Weight Polyethylene Polymer with Artificial Neural Network Modeling”. Kocaeli Journal of Science and Engineering, c. 4, sy 2, Kasım 2021, ss. 171-8, doi:10.34088/kojose.961118.
Vancouver
1.Kemal Ermiş, Hüseyin Ünal. Tribological Behavior of Ultra-High Molecular Weight Polyethylene Polymer with Artificial Neural Network Modeling. KOJOSE. 01 Kasım 2021;4(2):171-8. doi:10.34088/kojose.961118