A GPU-Accelerated Fully Coupled Fluid-Solid-Thermal SPH Solver for Industrial Gearboxes: Application to Lubricant Flow and Heat Transfer in a Bevel-Helical Reducer
Yongchuan Yu, Dong Wu, Oskar J. Haidn, Xiangyu Hu

TL;DR
This paper introduces a GPU-accelerated fully coupled fluid-solid-thermal SPH framework for detailed analysis of gearboxes, revealing how operational parameters affect lubrication dynamics and heat transfer with significant computational speedup.
Contribution
The study develops a novel GPU-based fully coupled SPH solver enabling high-fidelity thermo-fluid simulations of gearboxes, demonstrating its effectiveness and providing new insights into thermal and fluid dynamics.
Findings
Churning losses increase nearly tenfold with speed.
Lubricant temperature rise decreases by 3-4 times as speed increases.
GPU acceleration achieves 7-9x speedup over CPU simulations.
Abstract
This study presents a GPU-accelerated, fully coupled fluid-solid-thermal Smoothed Particle Hydrodynamics (SPH) framework for high-fidelity analysis of splash-lubricated gearboxes. A series of thermo-fluid simulations of a bevel-helical gear reducer were conducted by varying shaft speed, oil immersion depth, and lubricant viscosity to evaluate their influence on splash dynamics, churning losses, and lubricant temperature rise. The results show that churning losses increase by nearly an order of magnitude as the speed rises from 150 to 600 rad/s, while the corresponding lubricant temperature rise becomes approximately three to four times smaller. Variations in immersion depth and viscosity adjust the heating rate only modestly-typically within 10-20%-with their influence reversing between low- and high-speed regimes. The GPU backend provides a 7-9 speedup over a high-performance desktop…
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Taxonomy
TopicsFluid Dynamics Simulations and Interactions · Gear and Bearing Dynamics Analysis · Fluid Dynamics and Heat Transfer
