Riassunto analitico
In the automotive industry, as well as in other fields, gearboxes play a crucial role in power transmission. The primary objectives of a gearbox, and more generally any power transmission system, are efficiency and reliability. Achieving these goals requires an optimized lubrication strategy, which reduces friction, minimizes wear, and enhances thermal management. While traditional experimental and analytical methods have been sufficient for lubrication optimization in the past, the increasing demands for higher power densities, elevated operating temperatures, and heavier loads require more advanced predictive tools.
Computational Fluid Dynamics has emerged as powerful approach for accurately evaluating and optimizing lubrication performance in modern gearbox designs. This thesis compares two distinct CFD methodologies for gearbox lubrication analysis: mesh-based and meshless methods, specifically Smoothed Particle Hydrodynamics (SPH). While the first discretizes the volume with a fixed computational grid, the latter discretizes domain with particles each of them containing information of the fluid.
The study compares the advantages and limitations of the two methods in modeling motion and predicting viscous losses for a gear free to rotate in a lubricant bath with the aim of assessing their accuracy.
|
