Numerical optimization of the groove texture bottom profile for thrust bearings

Wei Wang; Yongyong He; Jun Zhao; Yang Li; Jianbin Luo

doi:10.1016/j.triboint.2016.12.006

Numerical optimization of the groove texture bottom profile for thrust bearings

Wei Wang, Yongyong He^*, Jun Zhao, Yang Li, Jianbin Luo

^*Corresponding author for this work

Tsinghua University

Research output: Contribution to journal › Article › peer-review

64 Citations (Scopus)

Abstract

Most of the previous studies on the surface texture were based on pre-determined shapes and distributions, and the global-optimum shapes were uncertain. In this paper, a general parametric model of the groove bottom profile (inner structure, depth profile) of thrust bearings was developed and the GA-SQP hybrid method was adopted to obtain the global-optimum profile of the groove texture bottom. The optimization target was the maximization of the load carrying capacity (LCC) of the oil film. The results verified the superiority of the proposed GA-SQP hybrid method. The mechanism of the optimized bottom profile was investigated using the commercial software FLUENTR.

Original language	English
Pages (from-to)	69-77
Number of pages	9
Journal	Tribology International
Volume	109
DOIs	https://doi.org/10.1016/j.triboint.2016.12.006
Publication status	Published - 2017
Externally published	Yes

Keywords

GA-SQP hybrid algorithm
Hydrodynamic lubrication
Load carrying capacity
Surface texture

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10.1016/j.triboint.2016.12.006

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title = "Numerical optimization of the groove texture bottom profile for thrust bearings",

abstract = "Most of the previous studies on the surface texture were based on pre-determined shapes and distributions, and the global-optimum shapes were uncertain. In this paper, a general parametric model of the groove bottom profile (inner structure, depth profile) of thrust bearings was developed and the GA-SQP hybrid method was adopted to obtain the global-optimum profile of the groove texture bottom. The optimization target was the maximization of the load carrying capacity (LCC) of the oil film. The results verified the superiority of the proposed GA-SQP hybrid method. The mechanism of the optimized bottom profile was investigated using the commercial software FLUENTR.",

keywords = "GA-SQP hybrid algorithm, Hydrodynamic lubrication, Load carrying capacity, Surface texture",

author = "Wei Wang and Yongyong He and Jun Zhao and Yang Li and Jianbin Luo",

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year = "2017",

doi = "10.1016/j.triboint.2016.12.006",

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T1 - Numerical optimization of the groove texture bottom profile for thrust bearings

AU - Wang, Wei

AU - He, Yongyong

AU - Zhao, Jun

AU - Li, Yang

AU - Luo, Jianbin

PY - 2017

Y1 - 2017

N2 - Most of the previous studies on the surface texture were based on pre-determined shapes and distributions, and the global-optimum shapes were uncertain. In this paper, a general parametric model of the groove bottom profile (inner structure, depth profile) of thrust bearings was developed and the GA-SQP hybrid method was adopted to obtain the global-optimum profile of the groove texture bottom. The optimization target was the maximization of the load carrying capacity (LCC) of the oil film. The results verified the superiority of the proposed GA-SQP hybrid method. The mechanism of the optimized bottom profile was investigated using the commercial software FLUENTR.

AB - Most of the previous studies on the surface texture were based on pre-determined shapes and distributions, and the global-optimum shapes were uncertain. In this paper, a general parametric model of the groove bottom profile (inner structure, depth profile) of thrust bearings was developed and the GA-SQP hybrid method was adopted to obtain the global-optimum profile of the groove texture bottom. The optimization target was the maximization of the load carrying capacity (LCC) of the oil film. The results verified the superiority of the proposed GA-SQP hybrid method. The mechanism of the optimized bottom profile was investigated using the commercial software FLUENTR.

KW - GA-SQP hybrid algorithm

KW - Hydrodynamic lubrication

KW - Load carrying capacity

KW - Surface texture

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DO - 10.1016/j.triboint.2016.12.006

M3 - Article

AN - SCOPUS:85006699824

SN - 0301-679X

VL - 109

SP - 69

EP - 77

JO - Tribology International

JF - Tribology International

ER -

Numerical optimization of the groove texture bottom profile for thrust bearings

Abstract

Keywords

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