变可信度模型在气动优化中的应用

Application of Variable-Fidelity Models to Aerodynamic Optimization

在气动外形优化中,采用近似模型管理结构(AMF)方法,对变可信度模型进行组织和管理.这样能够充分利用低可信度模型,将主要计算量集中在低可信度模型的优化迭代过程中.同时,采用高可信度模型监控优化过程,使最终的优化解收敛到高可信度模型上.最后,设计了零阶变可信度气动特性优化管理结构与搜索算法,对某飞翼型无人机的翼型进行了气动优化.优化外形的气动性能与初始外形比有所提高.实际结果表明所提出的方法具有良好的可行性和适用性.

For aerodynamic shape optimization, the approximation management framework （AMF） method was used to organize and manage the variable-fidelity models. The method can take full advantage of the low-fidelity, cheaper models to concentrate the main workload on the low-fidelity models in optimization iterative procedure. Furthermore, it can take high-fidelity, more expensive models to monitor the procedure to make the method globally convergent to a solution of high-fidelity problem. Finally, zero order variable-fidelity aerodynamic optimization management framework and algorithm were demonstrated on an airfoil optimization of UAV with a flying wing. Compared with the original shape, the aerodynamic performance of the optimal shape is improved. The results show the method has good feasibility and applicability.