Solid Rocket Motor Design Optimization Using Genetic Algorithm

Abstract

A design optimization approach of a solid propellant rocket motor is considered. A genetic algorithm (GA) optimization method has been used. The optimized solid rocket motor (SRM) is intended to use as a booster of a flight vehicle, and delivering a specific payload following a predefined prescribed trajectory. Sensitivity analysis of the optimized solution has been conducted using Monte Carlo method to evaluate the effect of uncertainties in design parameters. The results show that the proposed optimization approach was able to find the convergence of the optimal solution with highly acceptable value for conceptual design phase.

Hybrid Optimization of Star Grain Performance Prediction Tool

“…Nisar [2] used a hybrid optimization technique (genetic algorithm and sequential quadratic programming) on 3D finocyl grain involving 18 parameters. Similarly, Villanueva [3] used GA on different grain geometries (end burning, tubular, star, etc.) which had up to 8 parameters.…”

A preliminary multidisciplinary design procedure for tactical missiles

“…In addition, meeting the thrust profile for a predefined missile mission was discussed in many studies [15][16][17][18] using analytical, numerical and CAD burn-back analysis techniques for 3D grain geometrical parameters. The sensitivity of motor performance to the variation of its design was examined 19 using Monte-Carlo method while the impact of uncertainties in design parameters was discussed 20 for dual-thrust motors. A significant increase in missile range can be achieved by increasing the grain volumetric loading by using star 21 or wagon-wheel 22 grain configuration.…”