Application of genetic algorithm in optimization of hydrodynamic bearings

Abstract

This paper presents comparison of the optimum performance characteristics of four different bearing configurations. An attempt has been made to find out the effect of four different bearing configurations of hydrodynamic journal bearing by changing groove locations. Various groove angles that have been considered are 10°, 20°, and 30°. The Reynolds equation is solved numerically in a finite difference grid satisfying the appropriate boundary conditions. Four optimum performance parameters considered viz non-dimensional load carrying capacity, flow coefficient, friction variable, and mass parameter. Optimum configuration of bearings ensures best flow, load and stability, and least friction of the bearings. Genetic algorithm (GA) for multi-objective function has been used for optimum performance parameter comparison of the bearings. Flow coefficient value is found higher for elliptical bearing, and optimum value of non-dimensional load carrying capacity mass parameter found to be the highest for four-lobe bearing.