期刊
APPLIED MATHEMATICAL MODELLING
卷 85, 期 -, 页码 19-45出版社
ELSEVIER SCIENCE INC
DOI: 10.1016/j.apm.2020.03.037
关键词
Mathematical model; Fluid-Solid-Thermal; Wear; Transient simulation
资金
- National Natural Science Foundation of China [51975064]
- General Projects of Basic Science and Frontier Technology Research of Chongqing [cstc2018jcyjAX0442]
- China Postdoctoral Science Foundation [2018M631059, 2019T120805]
- Major Research and Development Project of Innovation Program on the Common and Key Technologise of Key Industries [cstc2017zdcy-zdzxX0001]
In this study, the transient interactions between the sliding wear behaviour and fluid-solid-thermal (FST) characteristics of journal bearings are revealed using an established mathematical model. The calculated temperature distribution is validated by a comparison with experimental results from the literature. Furthermore, a wear test for lubricated journal bearings is conducted to verify the predicted wear rate. The time-varying wear and FST performances of the journal bearing, including the wear rate, wear depth, fluid pressure, contact pressure, and maximum temperature are calculated numerically. Through numerical simulations, the effects of the boundary friction coefficient and surface roughness on the wear and FST performances are evaluated. To demonstrate the importance of considering the three-dimensional (3D) thermal effect during the wear analysis of lubricated journal bearings, the numerical results predicted by the isothermal model and the thermal model are compared systematically within a wide range of operating conditions. The numerical results reveal that the worn surface profile slightly decreases the maximum temperature. Additionally, the worn region is primarily located at both edges of the bearing, and the time-varying worn surface profile may be beneficial for improving the hydrodynamic effect. Furthermore, the effect of the 3D thermal characteristics on the wear prediction of journal bearings cannot be ignored when the external load, boundary friction coefficient, surface roughness are relatively large. (C) 2020 Elsevier Inc. All rights reserved.
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