Study on Application of Meshless rKPM to Lubrication Analysis of Journal Bearing
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摘要: 利用无网格重构核粒子法(rKPM)建立了动载荷径向滑动轴承润滑分析的计算模型,采用罚函数法施加Dirichlet本质边界条件,详细推导了基于无网格rKPM的动态reynolds方程的离散形式,并联立轴心轨迹运动方程,计算了油膜压力和非线性轴心轨迹。通过算例编程讨论了rKPM节点数及节点分布方式对油膜压力精度的影响,同时给出了罚因子的最佳取值范围为1.0×102~1.0×104,并进行了误差估计。结果表明:基于无网格rKPM的润滑计算模型无论节点规则分布还是随机分布,都能取得较高的精度,且计算精度随节点数增加而增大。Abstract: Sliding bearing is one of the most important friction pairs in engine lubrication system. In this paper, acalculation model for lubrication analysis of dynamically loaded journal bearing was established using meshlessreproducing Kernel Particle Method (rKPM). The penalty method was used to impose the Dirichlet essentialboundary condition, and the discrete formulation of dynamic reynolds equation based on rKPM was deduced indetail. Meanwhile, the oil film pressure and nonlinear journal orbit were computed by integrating the motionequation of the journal with the dynamic reynolds equation. Finally, the effect of node number and nodedistribution on the computational accuracy of oil film pressure was discussed through numerical example andprograms, and the best value range of penalty factor was 1. 0 × 102~1. 0 × 104, and the errors estimation wasperformed. The results indicate that the lubrication calculation model based on rKPM has a higher accuracy nomatter uniform or random node distribution, and the computational accuracy increases with the node number.
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Key words:
- calculations /
- error analysis /
- errors estimation /
- errors /
- estimation
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