Adaptive Multifidelity Constraints Method for Efficient Multidisciplinary Missile Design Framework

Abstract

The adaptive multifidelity constraints method is developed and proposed to ensure the convergence of significant constraints to high-fidelity results for increasing the reliability and robustness of an optimal configuration at the conceptual design stage without any noticeable turnaround time. The adaptive multifidelity constraints algorithm is demonstrated for two numerical examples, with savings of 58.6 and 64% in high-fidelity evaluations, to obtain the convergence of adaptive constraints to high-fidelity results. The implementation of the adaptive multifidelity constraints algorithm is integrated into the multidisciplinary air-to-ground missile design optimization framework. The lift, drag, and longitudinal control effectiveness coefficient constraints are considered as multifidelity constraints due to their importance in the sizing of air-to-ground missile control surfaces for diving and attacking missions. The optimal air-to-ground missile configuration using adaptive multifidelity constraints yields more reliable and robust results compared with the optimal air-to-ground missile configuration using the low-fidelity analysis only, whereas the adaptive constraints converge into the high-fidelity results.