Abstract:

：The relationship between texture depth and texture area ratio with the additional load-carrying capacity of oil film considered at different oil film thickness is simulated by using the computational fluid dynamics method (CFD) based on N-S equation. Meantime, the influence of surface tension on the load-carrying capacity of oil film is investigated; the additional load-carrying capacity of oil film from surface texture and the own load-carrying capacity of oil film from surface tension are fitted by using the nonlinear mapping function of neural network. The texture depth and the texture area ratio are optimized with optimization algorithm of particle swarm and tested with experiments. The results show that the texture depth is related to the oil film thickness for round dimple texture when the additional load-carrying capacity of oil film got the maximum. The ratio between them is around 1.0 and the optimal area ratio is 45%. With the influence of surface tension is considered, when the total load-carrying capacity for oil film get the maximum, the optimal texture depth and area ratio are 2.5-7.5 μm and 45%, respectively. The comparison of those results show if take the surface tension into consideration or not will not affect the determination of optimal area ratio, but affect the determination of the optimal texture depth. According to the optimal results of texture depth and area ratio, the lower friction coefficient can be obtained by choosing geometric parameters of surface texture at different load-carrying capacity. And through the experiments, good agreement between simulation results and test data is achieved.

Key words: computational fluid dynamics(CFD), friction coefficient, load-carrying capacity, neural network, surface tension, surface texture