During any design phase, the associated process variations and uncertainties can cause the design to deviate from its expected performance. The purpose of this paper is to propose a robust design optimization (RDO) strategy for the 3D grain design of a dual thrust solid rocket motor (DTRM) under uncertainties in design parameters.
The methodology consists of design of 3D complex grain geometry and hybrid optimization approach through genetic algorithm, globally and simulated annealing, locally considering the uncertainties in design parameters. The robustness of optimized data is measured for a worst case parameter deviation using sensitivity analysis through stochastic Monte Carlo simulation considering variance of design parameters mean.
The important achievement that can be associated with this methodology is its ability also to evaluate and optimize the propulsion system performance in a complex scenario of intricate 3D geometry under uncertainty. The study shows the objective function to maximize the average thrust in dual levels could be achieved by the proposed optimization technique while satisfying constraints conditions. Also, this technique proved to be a great help in reducing the design space for optimization and increasing the computational quality.
This is the first paper to address the dual thrust solid rocket motor grain design under uncertainties using robust design and hybrid optimization approach.
