A Computational Fluid Dynamics (CFD) Model for Gear Churning Predictions
This paper presents a computational fluid dynamics (CFD) model for predicting gear, or similar rotating component, oil churning losses. The modeling approach and parameters are optimized to ensure the accuracy, robustness, and computational efficiency of these predictions. These studies include a mesh sensitivity investigation, and a turbulence model selection. The focus is on multiple reference frame (MRF) modeling technique for its computational efficiency advantage. Model predictions are compared to experimental data  under different operating conditions, for a typical automatic transmission application. The model shows good agreement with the hardware both quantitatively and qualitatively, capturing the trends with speed and submersion level.