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.
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.
出处
《应用数学和力学》
EI
CSCD
北大核心
2006年第8期947-953,共7页
Applied Mathematics and Mechanics
基金
国家自然科学基金资助项目(10502043)
关键词
气动优化
变可信度
近似模型管理结构
aerodynamic optimization
variable- fidelity
approximation management framework