Multidisciplinary optimization for configuration of a reentry capsule considering uncertainty

The robust multi-disciplinary, multi-objective shape optimization of re-entry capsule with aero-thermodynamic, trajectory, stability and the geometry considerations are presented in this paper. In this research, the results of maximizing the volumetric efficiency of the capsules while minimizing the ballistic coefficient and the longitudinal stability derivative with considering uncertainties are discussed in presence of some constraints on geometry, heating load, and load factor. To reduce the time and cost of robust optimization, the Adaptive Monte Carlo Simulation technique is used which decreases the number of required evaluations within the robust optimization process. Utilizing the constrained multi-objective genetic algorithm will result in a collection of robust optimal solutions. The results show that the performance of obtained robust optimal configurations is in a way that the considered constraints aren’t violated with 99.8% of confidence level even in the presence of uncertainties.