Performance of Adaptive Lubricants in a Hybrid Journal Bearing Operating Under Fully Saturated Conditions

Abstract

Adaptive lubricants involve binary mixture of synthetic oil and dissolved carbon dioxide (CO2). Unlike conventional lubricant oils, the lubricant viscosity not only varies with the temperature within the bearing but also can be directly adjusted through the CO2 concentration in the system. In this study, we consider the synthetic oil to be fully saturated by CO2 to investigate the maximum impacts of adaptive lubricants on the performance of a hybrid journal bearing. The adaptive lubricant analyzed for this study was the polyalkylene glycol (PAG) oil with low concentration of CO2 (<30%). A three-dimensional (3D) computational fluid dynamic (CFD) model of the bearing was developed and validated against the experimental data. The mixture composition and the resultant mixture viscosity were calculated as a function of pressure and temperature using empirical equations. The simulation results revealed that the viscosity distribution within the PAG/CO2-lubricated bearing is determined primarily by the pressure at the low operating speed. When the speed becomes higher, it is the temperature effect that dominates the viscosity distribution within the bearing. Moreover, the PAG/CO2-lubricated bearing can reduce up to 12.8% power loss than the PAG-lubricated bearing due to the low viscosity of PAG/CO2 mixture. More importantly, we have found that the PAG/CO2 can enhance the load capacity up to 19.6% when the bearing is operating at high-speed conditions.