Proceedings of the 2016 International Conference on Artificial Intelligence and Engineering Applications

Research on lubrication performance of micro-textured journal bearing based on fluent

Authors
Lili Wang, Shaohui Guo, Guoxiao Yin
Corresponding Author
Lili Wang
Available Online November 2016.
DOI
https://doi.org/10.2991/aiea-16.2016.42How to use a DOI?
Keywords
Micro-texture; journal bearing; bearing capacity; friction coefficient.
Abstract

The micro-textured surface technology has obvious effect on improving the lubrication performance of the journal bearing. In this paper, a 3D micro-textured journal bearing model is established by fluent and compared with non-textured smooth journal bearing. The effect of circumferential total texture and partial texture of different positions in bearing area on bearing lubrication performance is analyzed. Results show that circumferential total texture and partial texture can effectively improve the bearing capacity of bearing and reduce the friction coefficient, and there is a reasonable and effective range for the quantity, position and density of micro texture.

Copyright
© 2016, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 2016 International Conference on Artificial Intelligence and Engineering Applications
Series
Advances in Computer Science Research
Publication Date
November 2016
ISBN
978-94-6252-270-1
ISSN
2352-538X
DOI
https://doi.org/10.2991/aiea-16.2016.42How to use a DOI?
Copyright
© 2016, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Lili Wang
AU  - Shaohui Guo
AU  - Guoxiao Yin
PY  - 2016/11
DA  - 2016/11
TI  - Research on lubrication performance of micro-textured journal bearing based on fluent
BT  - Proceedings of the 2016 International Conference on Artificial Intelligence and Engineering Applications
PB  - Atlantis Press
SP  - 223
EP  - 227
SN  - 2352-538X
UR  - https://doi.org/10.2991/aiea-16.2016.42
DO  - https://doi.org/10.2991/aiea-16.2016.42
ID  - Wang2016/11
ER  -