multi objective particle swarm optimization of tilting pad journal bearings operational parameters using thermo-elasto-hydrodynamic fsi-cfd model analysis

Due to the critical role of journal bearings in the performance and vibration of rotating systems across various industries (e.g., power plants, turbomachines, electric machines, and shipbuilding), accurate modeling of these bearings has long attracted significant attention from researchers and manufacturers. tilting pad journal bearings (tpjbs) are the most widely used type of journal bearings in nearly all applications. considering the complex geometry of tpjbs, thermo-elasto-hydrodynamic analysis and fluid-structure interaction (fsi) have been employed in this study. in this approach, the continuity, motion, and energy equations are solved in three dimensions, considering flow mixing conditions and the turbulent flow regime. this paper presents the first simulation model of a tpjb using 3d computational fluid dynamics, incorporating fluid heat transfer, fluid turbulence, and the deformation of the shaft and pads through two-way fsi, while also considering bearing parameter optimization using multi-objective particle swarm optimization (mopso) with a unique contribution of combination of cfd-fsi modeling with the optimization of key bearing performance parameters, such as the maximum oil temperature and the minimum oil film thickness. the results demonstrate good convergence, and the obtained performance parameters exhibit high accuracy