Grey-Fuzzy Hybrid Optimization for Thermohydrodynamic Performance Prediction of Misaligned Rough Elliptic Bore Journal Bearing

Abstract

Rough elliptic bore misaligned journal bearing performance involves many geometric and operational parameters, which directly or indirectly affect the thermohydrodynamic performance output. Improper design and manufacturing of journal bearings lead to enhanced friction, reduced operational life, and poor serviceability. A rule of thumb is to understand the operational efficiency of the bearing through modelling and simulation and to implement the knowledge of bearing critical parameters in manufacturing and operation. Therefore, decision-making in bearing parameter selection is a crucial process, for which several optimization tools and techniques have been developed from time to time. Moreover, these techniques have their own merits and demerits. This paper proposes a grey-based fuzzy approach to optimize the thermohydrodynamic performance of journal bearings with roughness, bore non-circularity, and shaft misalignment. Based on the results, the optimal level of factors is ε1 (0.3)-β1 (0.5)-G3 (2)-y1 (0.1), while at this condition, the optimal solutions for responses, such as Wis, Wth, Fis, Fth, Qis, and Qth are 3.684, 2.84, 165.2, 178.3, 5.67, and 6.32, respectively.

Keywords

• elliptic bore journal bearing
• statistical properties
• grey-fuzzy algorithm
• misalignment