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Tribology Transactions Volume 57, 2014 - Issue 2
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Original Articles

Exploration on a Fast EHL Computing Technology for Analyzing Journal Bearings with Engineered Surface Textures

Chia-Wen Chan Department of Mechanical Engineering, Chang Gung University, Tao-Yuan, 333, Taiwan; Department of Mechanical Engineering, Northwestern University Evanston, Illinois, 60208
,
Yan-Feng Han Department of Mechanical Engineering, Northwestern University Evanston, Illinois, 60208; State Key Laboratory of Mechanical Transmission, Chongqing University, Chongqing, 40044, China
,
Zhanjiang Wang State Key Laboratory of Mechanical Transmission, Chongqing University, Chongqing, 40044, China
,
Jiaxu Wang State Key Laboratory of Mechanical Transmission, Chongqing University, Chongqing, 40044, China
,
Fanghui Shi Tribology and Thermofluids CAE Group, General Motors, Michigan, 48340
,
Nenzi Wang Department of Mechanical Engineering, Chang Gung University, Tao-Yuan, 333, Taiwan
&
Q. Jane Wang Department of Mechanical Engineering, Northwestern University Evanston, Illinois, 60208; State Key Laboratory of Mechanical Transmission, Chongqing University, Chongqing, 40044, China
 show all
Pages 206-215 | Received 02 Sep 2013, Accepted 05 Nov 2013, Published online: 10 Mar 2014
 
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Abstract

Solving elastohydrodynamic lubrication (EHL) problems is a complex and time-consuming process due to the interactive solutions of the Reynolds equation and contact elasticity. Analyzing journal bearing EHL problems is even more difficult due to the scale difference in the structural and surface features, which may span four orders of magnitude. This article presents a fast EHL computing technology utilizing a parallel numerical iterative method (the red–black successive overrelaxation method) and multithreaded computing scheme conducted by OpenMP directives. The fast computational approaches allow the construction of high-density EHL meshes for effective descriptions of important texture features of journal bearing surfaces.

Acknowledgments

Review led by Liming Chang

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