Abstract

Space propulsion systems play an increasingly important role in planning of space missions. The traditional method for design of space propulsion systems includes numerous design loops, which does not guarantee to reach the best optimal solution. Multidisciplinary Design Optimization (MDO) is an approach for the design of complex systems that considers a design environment with multiple disciplines. The aims of this study are to implement and compare Multidisciplinary Feasible and Collaborative Optimization architectures for the multi-Objective optimization of a bi-propellant space propulsion system design. Several disciplines such as thrust chamber, cooling, and structure were exploited in a proper combination. The main optimization objectives in the MDO frameworks were to minimize the total wet mass and maximize the total impulse by considering several constraints. Furthermore, Genetic Algorithm and Sequential Quadratic Programming are employed as the system-level and local-level optimizers. The presented design methodology provides an interesting decision making approach to select the best system parameters of space propulsion systems under conflicting goals.

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