Abstract
This work presents a methodology to calibrate and verify the Herschel–Bulkley rheological model for lubricating greases in the context of Computational Fluid Dynamics (CFD). The approach combines Cone-on-Plate and Plate-on-Plate rheometry with numerical simulations to derive temperature-dependent model parameters and assess their predictive fidelity. Experimental measurements were conducted on an NLGI 1 grease for bearings application at 25 °C and 80 °C, covering a broad range of shear rates. Multiple regression strategies were tested, showing that the choice of error metric significantly affects model predictions, with logarithmic error minimization providing the most robust results across conditions. CFD validation was first carried out on the Cone-on-Plate configuration, yielding excellent agreement with both analytical Herschel–Bulkley predictions and experiments. The Plate-on-Plate setup introduced additional complexity due to shear rate gradients and higher edge effects. Comparisons demonstrated good agreement at elevated temperatures and small gaps, while larger discrepancies emerged at ambient temperature and wider gaps, with CFD generally overestimating torque. The findings highlight both the strengths and current limitations of the proposed approach for modeling grease-lubricated systems, and underscore the importance of temperature calibration protocols to enhance predictive accuracy in CFD analyses of grease-lubricated components such as rolling element bearings.