A Hybrid Optimization Approach for SRM FINOCYL Grain Design

This article presents a method to design and optimize 3D FINOCYL grain (FCG) configuration for solid rocket motors (SRMs). The design process of FCG configuration involves mathematical modeling of the geometry and parametric evaluation of various independent geometric variables that define the complex configuration. Virtually infinite combinations of these variables will satisfy the requirements of mass of propellant, thrust, and burning time in addition to satisfying basic needs for volumetric loading fraction and web fraction. In order to ensure the acquisition of the best possible design to be acquired, a sound approach of design and optimization is essentially demanded. To meet this need, a method is introduced to acquire the finest possible performance. A series of computations are carried out to formulate the grain geometry in terms of various combinations of key shapes inclusive of ellipsoid, cone, cylinder, sphere, torus, and inclined plane. A hybrid optimization (HO) technique is established by associating genetic algorithm (GA) for global solution convergence with sequential quadratic programming (SQP) for further local convergence of the solution, thus achieving the final optimal design. A comparison of the optimal design results derived from SQP, GA, and HO algorithms is presented. By using HO technique, the parameter of propellant mass is optimized to the minimum value with the required level of thrust staying within the constrained burning time, nozzle and propellant parameters, and a fixed length and outer diameter of grain.