Design process of a solid rocket motor with the objective of meeting certain mission requirements can be specified as a search for a best set of design parameters within the overall design constraints. In order to ensure that the best possible design amongst all achievable designs is being achieved, optimization is required during the design process. In this thesis, an optimization tool for internal ballistic design of solid rocket motors was developed. A direct search method Complex algorithm is used in this study. The optimization algorithm changes the grain geometric parameters and nozzle throat diameter within the specified bounds, finally achieving the optimum results. Optimization tool developed in this study involves geometric modeling of the propellant grain, burnback analysis, a 0-dimensional ballistic performance prediction analysis of rocket motor and the mathematical optimization algorithm. The code developed is verified against pretested rocket motor performance.

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.

Within the scope of this thesis study, an optimization tool for the ballistic design of three-dimensional grains in solid propellant rocket motors is developed. The modeling of grain geometry and burnback analysis is performed analytically by using basic geometries like cylinder, cone, sphere, ellipsoid, prism and torus. For the internal ballistic analysis, a quasi-steady zero-dimensional flow solver is used. Genetic algorithms have been studied and implemented to the design process as an optimization algorithm. Lastly, the developed optimization tool is validated with the predesigned rocket motors.

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.

The performance prediction of solid propellant rocket motor depends on the calculation of internal aerodynamics of the motor through its operational life. In order to obtain the control volume, in which the solutions will be carried out, a process called &ldquo / grain burnback calculation&rdquo / is required. During the operation of the motor, as the interface between the solid and gas phases moves towards the solid propellant in a direction normal to the surface, the combustion products are generated and added into the control volume. This phenomenon requires handling of moving boundaries as the solution proceeds. In this thesis, Fast Marching Method is implemented to the problem of grain burnback. This method uses the upwinding nature of the propellant interface motion and solves the Eikonal type equations on a fixed three-dimensional tetrahedron mesh. The control volume is coupled to a one-dimensional and a three-dimensional Euler aerodynamic solver in order to obtain the performance of the engine. The speed by which the interface moves depends on the static pressure on the surface of the propellant and comes from the solver. Therefore an iterative method has been proposed between the interface capturing algorithms and the flow solver. Both of the calculation results, which are obtained from one-dimensional and three-dimensional solvers are compared with actual rocket firing data and validated.