Multi-Disciplinary Design Optimization of a Space Re-entry Bio-Capsule Configuration

In this paper, the multi-disciplinary design optimization of a re-entry bio-capsule configuration is performed. In this process, all design disciplines related to the configuration and structural objectives, such as minimizing the structure's deformation, maximizing the structure's first natural frequency, and maximizing the buckling load multiplier of the structure, are considered. Therefore, the design disciplines selected include geometry, aerodynamics, trajectory, heating, and structure. In this regard, considering the design space defined by the allowable limits of the geometric variables of the bio-capsule, surrogate models are extracted using the combinatorial Kriging-Response Surface Method (RSM). After modeling the design disciplines and preparing the surrogate models, the optimal design point is identified using the Genetic Algorithm (GA). To solve this problem, the multi-objective All-At-Once (AAO) framework is used. The optimization approaches of the problem include mass minimization, CDA parameter maximization, volumetric efficiency maximization, ballistic coefficient minimization, static longitudinal stability maximization, structural deformation minimization, internal volume maximization, first natural frequency maximization, and buckling load multiplier maximization. The results showed that using the combinatorial surrogate model method significantly improves the accuracy of the surrogate models in the optimization process (accuracy reaches more than 90%). Finally, the different configurations obtained by the present method were compared with the flight test results of the native bio-capsule configuration, which showed a favorable match in all flight path parameters of the capsules.