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The optimum design of a solid propulsion system consists of optimization of various disciplines including structure, aerothermodynamics, heat transfer, and grain geometry. In this paper, an efficient model of every discipline has been developed, and a suitable framework is introduced for these hard-coupled disciplines. Hybrid optimization algorithm is used to find the global optimum point including genetic algorithm and sequential quadratic programing. To show the performance of the proposed algorithm, the required correction factor values have been carefully derived using comparison between more than 10 real solid propulsion systems and the proposed algorithm results. According to the results, the derived correction factors are close to 1, with scattering level better than 0.97. In addition, it is shown that the proposed algorithm (errors < 8%) is more accurate in comparison with the conventional approach (errors < 17%). Then, for a case study, multidisciplinary analysis has been done based on 3 general objectives including dry mass, total mass, and specific impulse. It means that the optimum specific impulse is not the maximum value and the optimum dry mass is not the minimum value. Finally, the proposed algorithm can be used to directly derive the optimum configuration for every mission requirement.

A New Approach to Multidisciplinary Design Optimization of Solid Propulsion System Including Heat Transfer and Ablative Cooling