Nanofluids for Performance Improvement of Heavy Machinery Journal Bearings: A Simulation Study

Abstract

Nanofluids have extensive applications in hydrodynamic journal bearings used in heavy industry machinery. Inorganic fullerene-like tungsten disulfide nanoparticles (IF-WS2 NPs) are the most common additive for lubrication purpose due to their excellent mechanical characteristics along with their effect on reducing friction and wear. In this work, a computational simulation approach with discrete phase modeling (DPM) of suspended nanoparticles was used to evaluate the application of the IF-WS2 nanofluid lubricant on load carrying capacity of high-load journal bearings where the normal loads are high, considering the bearing dimensions. For accurate simulation, nanofluid viscosity was calculated considering the aggregation effect of NPs by using scanning electron microscopy (SEM) imaging of the nanofluids. A benchmark study was first performed to assess the model accuracy. Hydrodynamic lubrication was simulated under different nanofluid weigh fractions. The simulated pressure distribution was then employed to determine the load capacity of the bearing. The results show an approximately 20% improvement of load carrying capacity at 5% weight fraction of WS2-oil nanofluid.