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织构型水润滑推力轴承软弹流润滑分析及多目标协同优化
引用本文:王玉君,李强,张硕,许伟伟,唐心昊,王振波. 织构型水润滑推力轴承软弹流润滑分析及多目标协同优化[J]. 表面技术, 2021, 50(5): 141-151. DOI: 10.16490/j.cnki.issn.1001-3660.2021.05.015
作者姓名:王玉君  李强  张硕  许伟伟  唐心昊  王振波
作者单位:中国石油大学(华东) 新能源学院,山东 青岛 266580
基金项目:国家自然科学基金(51506225);山东省重点研发计划(2018GHY115018);中央高校基本科研业务费专项(18CX02129A);山东省自然科学基金面上项目(ZR2020ME174);中国石油大学(华东)研究生创新工程(YCX2019040)
摘    要:目的 提高以水作为润滑介质的织构型非金属推力轴承的润滑性能,为水润滑推力轴承的优化设计提供参考.方法 基于计算流体力学方法建立织构型水润滑推力轴承的流体动压润滑模型,采用双向流固耦合方法计算润滑流场与材料变形之间的相互作用.随后,以承载力最高和摩擦力最低为目标,采用响应曲面与非支配排序遗传算法相结合的多目标协同优化方法,对4种非金属材料的织构型推力轴承进行优化.结果 随着轴承材料弹性模量的降低,轴承内最高压力值逐渐降低,最大变形逐渐增加,且最优织构覆盖率值逐渐减小.当织构覆盖率为20%时,轴承材料对最优织构深度值无明显影响;当织构覆盖率增至40%及以上时,随着轴承材料弹性模量的降低,最优织构深度值逐渐增加.在同一轴承材料下,最优织构参数之间相互影响,随着织构覆盖率的增加,最优织构深度值逐渐增大.对于碳化硅陶瓷和尼龙等弹性模量较大的轴承材料,优化后,轴承内流体最高压力明显提升;对于超高分子量聚乙烯和赛龙等弹性模量较小的轴承材料,优化后,高压区面积明显增大.结论 轴承材料对轴承润滑性能及最优织构参数均有明显影响,且最优织构参数间相互影响.经过对织构型水润滑推力轴承的多目标协同优化,轴承润滑性能明显改善.

关 键 词:推力轴承  水润滑  表面织构  软弹流润滑  协同优化
收稿时间:2020-07-07
修稿时间:2020-08-04

Elastohydrodynamic Lubrication Analysis and Multi-objective Collaborative Optimization of Textured Water-lubricated Thrust Bearings
WANG Yu-jun,LI Qiang,ZHANG Shuo,XU Wei-wei,TANG Xin-hao,WANG Zhen-bo. Elastohydrodynamic Lubrication Analysis and Multi-objective Collaborative Optimization of Textured Water-lubricated Thrust Bearings[J]. Surface Technology, 2021, 50(5): 141-151. DOI: 10.16490/j.cnki.issn.1001-3660.2021.05.015
Authors:WANG Yu-jun  LI Qiang  ZHANG Shuo  XU Wei-wei  TANG Xin-hao  WANG Zhen-bo
Affiliation:College of New Energy, China University of Petroleum East China, Qingdao 266580, China
Abstract:The work aims to improve the lubrication performance of textured water-lubricated thrust bearings with non- metallic materials, and to provide reference for the optimal design of water-lubricated thrust bearings. Firstly, the hydrodynamic lubrication model of textured water-lubricated thrust bearing was established based on the Computational Fluid Dynamics (CFD). Subsequently, the interaction between the fluid and structural domain was calculated by the coupled Fluid-Structure Interaction (FSI) method. Finally, with the largest loading capacity and the lowest friction force as the objectives, a multi- objective collaborative optimization method combining the response surface methodology and Non-dominated Sorted Genetic Algorithm-II (NSGA-II) was used to optimize the textured thrust bearings with four different non-metallic materials. With the decrease of the elastic modulus of the bearing material, the maximum pressure value in the bearing decreased and the maximum deformation increased gradually. The optimal textured coverage rate gradually decreased with the decreasing elastic modulus of bearing material. When the textured coverage rate was 20%, the change of bearing material had no obvious effect on the optimal textured depth, but when the textured coverage rate increased to 40% or more, the optimal textured depth gradually increased with the decrease of elastic modulus of bearing material. The optimal textured depth and textured coverage rate had a strong interaction effect with each other under the same bearing material. With the increase of textured coverage rate, the optimal textured depth gradually increased. For the bearing materials with large elastic modulus such as SiC ceramic and nylon, the maximum pressure of fluid in the bearing was significantly increased after the optimization. For the bearing materials with small elastic modulus such as UHMWPE and thordon, the high pressure area was significantly increased after the optimization. In conclusion, the bearing material has significant effect on the lubrication performance, and the optimal textured parameters of the thrust bearing and the optimal textured parameters have a strong interaction effect on each other. Through the multi-objective collaborative optimization of the textured water-lubricated thrust bearing, the lubrication performance of the thrust bearing is significantly improved.
Keywords:thrust bearing   water lubrication   surface texture   elastohydrodynamic lubrication   collaborative optimization
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