Application of Variable-Fidelity Models to Aerodynamic Optimization
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摘要: 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．Abstract: 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 search 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.
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