Two dimensional star grain optimization method using genetic algorithm

Abstract

This study describes the internal ballistic and the design optimization of two-dimensional star grain of rocket motors. The burnback analysis and geometric modeling of grain geometry are calculated using star grain geometry. In this study, the grain geometry was modeled parametrically using CAD software. The internal ballistic analysis by using MATLAB program, we used zero dimensional method for calculating the performance prediction. Genetic Algorithm optimization method has been used. Average thrust maximization, total impulse maximization and minimizing the neutrality of thrust time curve under design constraints is the objective functions. The uses of Genetic Algorithm optimization method clear the problem of suitable initial guess. This idea proves increase in capability of optimal solutions. According to different objective function it is capable to choose which is suitable according to the results.