Multi Purpose Optimization for Design of Circular Hydrostatic Axial Bearings Using Genetic Algorithm

In this paper, a multi purpose function is presented for optimum design in circular hydrostatic axial bearings. One or more parameters that are directly or indirectly dependent on given data are optimized. Usually in the local optimization methods, it is not possible to optimize several parameters simultaneously. In this research, simultaneous optimization of the power loss and the oil temperature rise as effective parameters for increase in efficiency of bearing is considered. The genetic algorithm is used in simultaneous optimization of the power and the temperature values. The accuracy of the multi purpose optimization is evaluated by a practical sample and the obtained results of simultaneous combination of parameters effect are compared with distinct functions.