AN EFFICIENT SOLUTION FOR AERODYNAMIC SHAPE OPTIMIZATION WITHIN THE MID-RANGE APPROXIMATION FRAMEWORK

Metamodels offer a good solution for optimization problems with expensive experiments or simulations. With a large number of design variables, it is not easy to establish a precise metamodel throughout the whole design space for complex nonlinear problems, especially for a high-fidelity CFD analysis. To address this issue, the paper has presented an efficient solution for high-fidelity large-scale aerodynamic shape optimization problems based on several developments in the mid-range approximation method within a trust-region optimization framework. The trust-region strategy has been improved to contain more optimization states with a flexible and controllable performance to suit different types of problems. A metamodel assembly technique and its gradient-enhanced version are developed to further relax the requirements of computational costs in the mid-range approximation method. Its performance is discussed through a detailed comparison of metamodel performance by using the Vanderplaats scalable beam problem. The single wing of the Common Research Model is offered to the proposed method to conduct the aerodynamic shape optimization. With all constraints satisfied, the optimized configuration has a 4.85% improvement in wing drag performance. The results show that the proposed method could achieve the design goal successfully within a reasonable computational cost.