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Numerical optimization of surface texture for improved tribological performance of journal bearing at varying operating conditions

Ali Usman (Department of Mechanical Engineering, COMSATS University Islamabad, Wah Cantt, Pakistan)
Cheol Woo Park (Kyungpook National University, Daegu, The Republic of Korea)

Industrial Lubrication and Tribology

ISSN: 0036-8792

Article publication date: 11 September 2018

Issue publication date: 19 November 2018




Journal bearings are used in numerous rotary machines. The load carrying capacity and friction of a bearing have been major concerns in design. Recent developments in surface texturing have showed potential outcomes to improve the tribological characteristics of mating surfaces. This study aims to investigate surface textures, which are transverse to the sliding direction, for frictional response of the journal bearing.


A hydrodynamic lubrication model is considered to evaluate the effect of surface texturing on the performance of a journal bearing at varying operating conditions. The two-dimensional generalized Reynolds equation, coupled with mass-conserving Elrod cavitation algorithm, is solved to evaluate texture-induced variations in tribological performance parameters.


Results have showed remarkable improvements in frictional response. Moreover, micro-textures on the journal surface alter the cavitation response and film-reformation in the hydrodynamic conjunction of the plain bearing.


Operating condition-based comprehensive exhaustive optimization of texture geometry is performed to generate widespread conclusion.



The authors are grateful to Higher Education Commission of Pakistan for supporting this study by providing financial support. Authors are thankful to the Bio Experimental Fluid Engineering Laboratory (BEFEL) of Kyungpook National University, S. Korea, for providing technical assistance to perform this research. This study was also supported by a grant from the Priority Research Centers Program through the NRF as funded by the MEST (No. 2010-0020089) and a National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIP) (No.2017R1A2B2005515).


Usman, A. and Park, C.W. (2018), "Numerical optimization of surface texture for improved tribological performance of journal bearing at varying operating conditions", Industrial Lubrication and Tribology, Vol. 70 No. 9, pp. 1608-1618.



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