EN
Tribological Behavior of Ultra-High Molecular Weight Polyethylene Polymer with Artificial Neural Network Modeling
Abstract
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
Keywords
References
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Details
Primary Language
English
Subjects
Mechanical Engineering, Composite and Hybrid Materials
Journal Section
Research Article
Publication Date
November 30, 2021
Submission Date
July 2, 2021
Acceptance Date
September 22, 2021
Published in Issue
Year 2021 Volume: 4 Number: 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, and 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 (November 1, 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 and H. Ünal, “Tribological Behavior of Ultra-High Molecular Weight Polyethylene Polymer with Artificial Neural Network Modeling”, KOJOSE, vol. 4, no. 2, pp. 171–178, Nov. 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 (November 1, 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, and Hüseyin Ünal. “Tribological Behavior of Ultra-High Molecular Weight Polyethylene Polymer With Artificial Neural Network Modeling”. Kocaeli Journal of Science and Engineering, vol. 4, no. 2, Nov. 2021, pp. 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. 2021 Nov. 1;4(2):171-8. doi:10.34088/kojose.961118