摘要
为满足791翼型在多工况下具有较好水动力性能且能维持其稳定性的要求,在模糊集理论和鲁棒度的基础上分别建立多点优化和鲁棒优化数学模型,并依据样本空间和两者的优化目标分别建立代理模型。运用多目标遗传算法对代理模型寻优,并结合CFD数值计算和PIV实测结果对两种优化结果对比分析。结果表明:两种优化方法均能同时降低翼型在设计工况和非设计工况下的阻升比且能很好地改善尾流品质;多点优化能灵活调整不同工况下的权重因子,但其优化效果受所考虑工况数目的影响;相比于多点优化,鲁棒优化还能提升性能的稳定性,使其恶化的程度减弱,适用性更强。
Based on the fuzzy set theory and robustness, a multi-points numerical optimization method and a robustness optimization method were discussed in this paper to meet the requirements that the airfoil 791 should have better and stable hydrodynamic performance under multi-operation conditions. Agent models of these two kinds of optimization were established in accordance with their sample space and optimization objectives. Then multi-objective genetic algorithm was applied to search optimal solutions, which were compared and analyzed combining with CFD numerical calculation and PIV experiment. The results showed that these two optimization methods can simultaneously reduce the drag-lift ratio and improve the quality of airfoil wakes under design and off-design conditions. However, compared with multi-points optimization, which can flexibly adjust the weighting factors under different operating conditions, robust optimization can not only improve the stability of performance, but also reduce its deterioration degree. Thus, robust optimization is more applicable.
作者
赵斌娟
张成虎
付燕霞
刘琦
陈汇龙
ZHAO Bin-Juan ,ZHANG Cheng-Hu ,FU Yan-Xia, LIU Qi ,CHEN Hui-Long(School of Energy and Power Engineering, Jiangsu University; Zhenjiang 212013, Chin)
出处
《工程热物理学报》
EI
CAS
CSCD
北大核心
2018年第9期1958-1964,共7页
Journal of Engineering Thermophysics
基金
国家自然科学基金资助项目(No.51279067)
江苏省自然科学基金资助项目(No.BK20160539)
江苏省高校优势学科建设工程项目(No.PAPD)
关键词
791翼型
多点优化
鲁棒优化
模糊集理论
多目标遗传算法
791 airfoil
multi-points optimization
robust optimization
fuzzy set theory
multi-objective genetic algorithm
