Multidisciplinary Regional Jet Aircraft Design Optimization Using Advanced Variable Complexity Techniques

To improve design results while avoiding expensive computational cost, an advanced variable complexity modeling (AVCM) framework is studied and presented. AVCM is introduced by using Neural Network as a scaling method to low-fidelity model in the optimization loop in which trust region management strategy is implemented to ensure the matching of low-fidelity models to high-fidelity results. The logical and systematical approach for aircraft design synthesis program-ADSP is developed and validated by three regional jet aircrafts. Then, AVCM is integrated successfully under ADSP in multidisciplinary RJA design optimization to improve the accuracy of design method without any noticeable increase in design turnaround time Minimization of Take-off Gross Weight-TOGW is performed and the design result shows the feasibility and effectiveness of the present AVCM framework under MDO problem.