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Mathematical and Computational Applications is published by MDPI from Volume 21 Issue 1 (2016). Articles in this Issue were published by another publisher in Open Access under a CC-BY (or CC-BY-NC-ND) licence. Articles are hosted by MDPI on mdpi.com as a courtesy and upon agreement with the previous journal publisher.
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Math. Comput. Appl. 2004, 9(3), 399-408; https://doi.org/10.3390/mca9030399

Determination of Friction Coefficient at Journal Bearings by Experimental and by Means of Artificial Neural Networks Method

Celal Bayar University, Mechanical Engineering Department, 45140 Manisa, Turkey
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Published: 1 December 2004
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Abstract

Knowing friction coefficient is important for determination of wear loss conditions at journal bearings. Tribological events that influence wear and its variations affect experimental results. In this study, friction coefficient at CuSn10 Bronze radial bearings has been determined by a new approach as experimental and artificial neural networks method. In experiments, effects of bearings have been examined at dry and lubricated conditions and at different loads and velocities.
Keywords: Friction Coefficient; Journal Bearing; Artificial Neural Networks Friction Coefficient; Journal Bearing; Artificial Neural Networks
This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).
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Ünlü, B.S.; Durmuş, H.K.; Meriç, C.; Atik, E. Determination of Friction Coefficient at Journal Bearings by Experimental and by Means of Artificial Neural Networks Method. Math. Comput. Appl. 2004, 9, 399-408.

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