Multi-objective optimization of air-oil two-phase flow for helicopter planetary gear bearings based on the Kriging surrogate model and NSGA-II algorithm

Due to the limited spatial constraints and complex motion of aerospace planetary gear reducers, under-race lubrication is employed for planetary gear bearings to ensure adequate lubrication performance with minimal oil flow. In this study, a specialized experimental setup was designed and developed to quantitatively evaluate the oil discharge at the bearing end face under under-race lubrication conditions. The results were compared with CFD simulations conducted under identical operating conditions, revealing discrepancies within an acceptable range. Subsequently, an in-depth investigation was conducted to examine the influence of various input parameters on the oil volume fraction and the churning loss. A surrogate model based on the Kriging method was constructed, and the NSGA-II algorithm was employed for multi-objective optimization of the lubrication design, leading to the identification of optimal input parameters.