Multi Objective Particle Swarm Optimization of Tilting Pad Journal Bearings Operational Parameters Using Thermo-Elasto-Hydrodynamic FSI-CFD Model Analysis

سال انتشار: 1403
نوع سند: مقاله کنفرانسی
زبان: انگلیسی
مشاهده: 25

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شناسه ملی سند علمی:

CFD21_074

تاریخ نمایه سازی: 19 اردیبهشت 1404

چکیده مقاله:

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 ۳D 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.

کلیدواژه ها:

Multi objective particle swarm optimization ، Structure-fluid interaction ، ۳D computational fluid dynamics ، Tilting pad journal bearings ، Thermo-elasto-hydrodynamic ، turbulent flow

نویسندگان

Seyedeh Zahra Mikaeeli

PhD student, K.N. TOOSI University of Technology

Zahra Taherkhani

Technology Development Analyst, Research & Technology Dept. MAPNA Group

Cyrus Aghanajafi

Professor, K.N. TOOSI University of Technology

Hossein Akrami

Applied Research Analyst, Research & Technology Dept. MAPNA Group

Mohsen PirMohammadi

R&D Manager, Research & Technology Dept. MAPNA Group