基于遗传算法并考虑质量守恒空化边界的最优织构形状

王希龙; 马晨波; 张玉言; 贝光耀; 孙见君

引用本文:	王希龙,马晨波,张玉言,贝光耀,孙见君.基于遗传算法并考虑质量守恒空化边界的最优织构形状[J].中国表面工程,2023,36(2):125~137
	WANG Xilong,MA Chenbo,ZHANG Yuyan,BEI Guangyao,SUN Jianjun.Optimal Texture Shape Based on Genetic Algorithm and Considering Mass Conservation Cavitation Boundary[J].China Surface Engineering,2023,36(2):125~137

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基于遗传算法并考虑质量守恒空化边界的最优织构形状
王希龙, 马晨波, 张玉言, 贝光耀, 孙见君
南京林业大学机械电子工程学院南京 210037

摘要:

织构形状对摩擦副的润滑性能具有重要的影响，然而最优织构形状随工况参数的变化规律仍缺乏系统性研究。基于满足质量守恒的 JFO(Jakobsson-Floberg-Olsson)空化边界条件，通过求解雷诺方程，结合遗传算法并以油膜承载力最大为目标，建立并简化最优织构形状优化模型，对比分析不同工况下最佳微孔与最优织构的承载力情况，探讨最优织构形状的相关几何参数随摩擦副端面间距、滑动速度与空化压力等参数的变化规律。结果表明：不同工况条件下最优形状织构的承载性能均优于最佳微孔织构，尤其当摩擦副端面间距小、滑动速度大时，性能提升更为显著；简化的最优织构形状几何模型共计 3 设计变量，即液体流入侧两点 X_a、X_g横坐标 X₁、X₂ 及织构深度 hg；随摩擦副端面间距增大，X₁先减小后基本不变，X₂逐渐减小，对应的最优织构深度与面积比增大，量纲一织构深度基本不变；随滑动速度增大，X₁先缓慢增大后基本不变，X₂ 逐渐增大，对应的最优织构深度增大，面积比减小；随空化压力增大，X₁先缓慢增大后缓慢减小，X₂逐渐增大，对应的最优织构深度增大，面积比减小。研究最优织构形状参数、深度及面积比随工况参数的变化规律，可为织构形状的摩擦学设计提供理论指导。

关键词: 表面织构遗传算法 JFO 空化边界条件最优形状

DOI：10.11933/j.issn.1007?9289.20220406001

分类号:TH117

基金项目:国家重点研发计划(2018YFB2000800)、江苏省重点研发计划(BE2021062)和国家自然科学基金(51805269)资助项目

Optimal Texture Shape Based on Genetic Algorithm and Considering Mass Conservation Cavitation Boundary

WANG Xilong, MA Chenbo, ZHANG Yuyan, BEI Guangyao, SUN Jianjun

School of Mechanical and Electronic Engineering, Nanjing Forestry University, Nanjing 210037 , China

Abstract:

Texture shape has a significant influence on the lubrication performance of friction pairs. However, there is still a lack of systematic research on the variation in the optimal texture shape with the operating parameters. Therefore, based on the Jakobsson-Floberg-Olsson (JFO) cavitation boundary condition satisfying mass conservation, by solving the Reynolds equation, combining the genetic algorithm, and considering the maximum oil film load-carrying capacity as the goal, the optimization model of the optimal texture shape is simplified. Additionally, the load-carrying capacities of the optimal micropore and optimal texture under different working conditions are compared and analyzed. Moreover, the variation law of the geometric parameters of the optimal texture shape with the friction pair end-face distance, sliding speed, cavitation pressure, and other parameters are discussed. The results show that under the working condition of the low sliding speed of friction pairs and low cavitation pressure, the load-carrying capacities calculated via the Reynolds, Half-Sommerfeld, and JFO cavitation boundary conditions have insignificant differences. For simple calculations under this working condition, the Reynolds or Half-Sommerfeld cavitation boundary conditions can replace the JFO cavitation boundary conditions. However, under the working conditions of high sliding speed and high cavitation pressure, the JFO cavitation boundary conditions, considering mass conservation, should be used instead of the Half-Sommerfeld or Reynolds conditions. The most commonly used microporous texture was optimized to obtain the best microporous texture under different working conditions. Then, the load-carrying capacity of the optimal texture was compared with that of the optimal microporous texture. Under different working conditions, the load-carrying capacity of the optimal shaped texture was better than that of the optimal microporous texture, especially when the end-face spacing of the friction pair was small, the sliding speed was high, and the performance improvement was more significant. The fifteen variable design models were used to optimize the texture, and the optimal texture shape under different friction pair end-face spacings, sliding speeds, and cavitation pressures were obtained. An analysis of the optimal texture shape shows that the optimal texture is axisymmetric under different working conditions. Therefore, the original fourteen variables used to describe the texture shape can be calculated symmetrically and reduced to eight. When texture depth hg was added, there were nine design variables in total. Further calculations showed that the shape of the liquid outflow side of the optimal texture does not change with the working conditions, and only the liquid inflow side changes. Thus, the texture optimization model can be further simplified. There are three design variables in the simplified geometric model of the optimal texture shape: two points X_a, X_gabscissa X₁, X₂, and texture depth hg on the liquid inflow side. To verify the feasibility of the simplified model under different working conditions, the load-carrying capacities of the optimal texture obtained using the models with the three, nine, and fifteen design variables were compared. The results revealed that the load-carrying capacity of the optimal texture obtained using the models with various design variables showed insignificant change with a maximum less than 2%, proving the feasibility of the simplified model with the three design variables. With an increase in the distance between the end faces of the friction pairs, X₁ first decreased and then remained unchanged, X₂ gradually decreased, the corresponding optimal texture depth and area ratio increased, and the dimensionless texture depth remained unchanged. With the increase in sliding speed, X₁ first increased slowly and then remained unchanged, X₂ gradually increased, the corresponding optimal texture depth increased, and the area ratio decreased. With an increase in cavitation pressure, X₁ first increased slowly and then decreased slowly, X₂ gradually increased, the corresponding optimal texture depth increased, and the area ratio decreased. The results provide theoretical guidance for the tribological design of optimal texture shapes.

Key words: surface texture genetic algorithm JFO cavitation boundary conditions optimal shape