The work presented in this thesis deals with the application of optimization tools to the design of solid rocket motor grains per internal ballistic requirements. Research concentrated on the development of an optimization strategy capable of efficiently and consistently optimizing virtually an unlimited range of radial burning solid rocket motor grain geometries. Optimization tools were applied to the design process of solid rocket motor grains through an optimization framework developed to interface optimization tools with the solid rocket motor design system. This was done within a programming architecture common to the grain design system, AML. This commonality in conjunction with the object-oriented dependency-tracking features of this programming architecture were used to reduce the computational time of the design optimization process. The optimization strategy developed for optimizing solid rocket motor grain geometries was called the internal ballistic optimization strategy. This strategy consists of a three stage optimization process; approximation, global optimization, and highfidelity optimization, and optimization methodologies employed include DOE, genetic algorithms, and the BFGS first-order gradient-based algorithm. This strategy was successfully applied to the design of three solid rocket motor grains of varying complexity. The contributions of this work was the development and application of an optimization strategy to the design process of solid rocket motor grains per internal ballistic requirements.

Solid propellant rocket motors are the most widely used propulsion systems for military applications that require high thrust to weight ratio for relatively short time intervals. Very wide range of magnitude and duration of the thrust can be obtained from solid propellant rocket motors by making some small changes at the design of the rocket motor. The most effective of these design criteria is the geometry of the solid propellant grain. So the most important step in designing the solid propellant rocket motor is determination of the geometry of the solid propellant grain. The performance prediction of the solid rocket motor can be achieved easily if the burnback steps of the rocket motor are known. In this study, grain burnback analysis for some 3-D grain geometries is investigated. The method used is solid modeling of the propellant grain for some predefined intervals of burnback. In this method, the initial grain geometry is modeled parametrically using commercial software. For every burn step, the parameters are adapted. So the new grain geometry for every burnback step is modeled. By analyzing these geometries, burn area change of the grain geometry is obtained. Using this data and internal ballistics parameters, the performance of the solid propellant rocket motor is achieved. To verify the outputs obtained from this study, rocket motor tests are performed. The results obtained from this study shows that, the procedure that was developed, can be successfully used for the preliminary design of a solid propellant rocket motor where a lot of different geometries are examined.

In this thesis, Initial Value Problem of Level-set Method is applied to solid propellant combustion to find the grain burnback. For the performance prediction of the rocket motor, 0-D, 1-D or 3-D flow models are used depending on the type of thre grain configuration.