Spiral groove journal bearings (SGJBs) are widely used in high-performance rotating machinery due to their excellent hydrodynamic performance and wear resistance. However, the strong nonlinear interactions among key geometric parameters made considerable challenges to performance optimization. This study introduces an integrated approach utilizing Response Surface Methodology (RSM) coupled with Finite Element Method (FEM) to systematically investigate the influences of groove width, length, depth, spiral angle, and groove numbers on bearing load-carrying capacity (LCC) and lubricant leakage. Analysis of variance (ANOVA) results identified significant interactions among parameters, with groove width, length, and depth strongly influence LCC, while groove length, depth, and number primarily govern leakage, with spiral angle having a comparatively minor effect. A multi-objective optimization framework was developed, achieving a 6% increase in LCC and a 37.17% reduction in leakage. The results provide valuable insights into the practical design to improve lubrication efficiency in high-performance engineering applications.
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