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作 者:陈璇[1] 张明亮 李万松 杨晨 杨金广 高丽敏[1] CHEN Xuan;ZHANG Mingliang;LI Wansong;YANG Chen;YANG Jinguang;GAO Limin(School of Power and Energy,Northwestern Polytechnical University,Xi’an 710072,China;CAS Aerostar Technology Co.,Ltd,Qingdao 266400,China;School of Energy and Power Engineering,Dalian University of Technology,Dalian 116024,China)
机构地区:[1]西北工业大学动力与能源学院,陕西西安710072 [2]中科航星科技股份有限公司,山东青岛266400 [3]大连理工大学能源与动力学院,辽宁大连116024
出 处:《推进技术》2025年第1期84-93,共10页Journal of Propulsion Technology
摘 要:为研究低雷诺数下轴流压气机叶型优化设计方法,本文验证了准三维求解器MISES对于低雷诺数流动的预测精度,对于V103叶型计算得到的转捩位置与实验值偏差小于5%,证实了其在低雷诺数流动中的可用性;基于多圆弧(MCA)叶型程序,利用增强精英保留遗传算法,搭建轴流压气机叶型准三维气动优化设计平台;以总压损失系数为优化目标,出口气流角为约束条件,对V103叶型进行了低雷诺数单点和高低雷诺数综合优化设计。结果表明:低雷诺数单点优化后,抑制了叶型层流分离泡现象,总压损失系数减小31.31%,性能显著改善;高低雷诺数综合优化后叶型在高雷诺数和低雷诺数下总压损失分别减小了3.05%和3.03%。本文研究结果证明了所发展工具的有效性和考虑雷诺数叶型优化的可行性。To investigate the optimal design method of axial flow compressor airfoils under low Reynolds number,the prediction accuracy of a quasi-3D solver MISES for low Reynolds number flow was first verified,and the predicted transition position for an airfoil(the V103 airfoil)is comparable to the experimental data with an error lower than 5%.Then based on a multiple circular arc(MCA)airfoil parameterization,the Strengthened Elitist Genetic Algorithm(SEGA)were used to build a quasi-3D aerodynamic optimization design platform for axial flow compressor airfoil.Taking the total pressure loss coefficient as the optimization objective function,and the outlet flow angle as constraint function,the V103 airfoil was comprehensively optimized for single-point under low Reynolds number and two-point at both high and low Reynolds numbers.The results show that,the laminar separation bubble is suppressed after single-point optimization under low Reynolds number,and the total pressure loss coefficient is reduced by 31.31%,and the performance is significantly improved,while the total pressure loss of the airfoil is reduced by 3.05%and 3.03%,respectively,under high and low Reynolds number after two-point optimization.The results of this paper prove the effectiveness of the research method and the feasibility of the airfoil optimization considering Reynolds number.
分 类 号:V231.3[航空宇航科学与技术—航空宇航推进理论与工程]
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