| description abstract | Supercritical CO2 (SCO2) power cycles offer significant advantages in terms of thermal efficiency, cost-effectiveness, and environmental benefits. However, the successful implementation of these cycles depends on the design and analysis of bearings that can operate at high speeds and temperatures. Despite their importance, critical aspects like supporting bearings have received limited attention. This study addresses these gaps by developing sophisticated 3D computational fluid dynamics (CFD) models to accurately predict static characteristics like load capacity and leakage rate of SCO2-lubricated hybrid bearings. These bearings use SCO2 as the lubricating fluid due to the difficulty in maintaining separation between oil and the process fluid in oil-based bearings operating at extreme temperatures and pressures. An optimization tool, response surface optimization along with a 3D CFD model has been utilized to determine the bearing equilibrium point. After validation of the CFD model against available experimental measurements, a parametric study has been conducted to evaluate the effects of various geometric and operating parameters on bearing performance. The hybrid bearing geometry has been optimized based on the findings of the parametric study. The optimized bearing designs achieved a significant boost in load capacity while substantially reducing the leakage rate. This study introduces a new design/optimization process for SCO2-lubricated bearings using a 3D CFD model. The results indicate a strong correlation between load capacity, leakage rate, and variables such as orifice diameter, supply pressure, recess height, and recess length. These insights provide valuable guidance for practical SCO2-lubricated hybrid bearing design and optimization. | |
