{"title":"Hybrid optimization of curvature continuous stacking line on the highly loaded diffuser cascade","authors":"Ke Yao, Xingyi Zhang, Xiaoqing Qiang","doi":"10.1007/s42401-023-00265-y","DOIUrl":null,"url":null,"abstract":"<div><p>The compressor is a critical component of aero-engines. In order to improve the performance, the compressor ratio of single-stage compressor is getting higher and higher, which will lead to high back pressure gradient and losses. To solve this problem, there are many techniques applied, such as cantilevered stator, tip clearance and slotted airfoils. However, traditional design methods are experience-dependent and time-consuming. This paper proposes a hybrid optimization method to optimize the stacking line of compressor cascade and reduce total pressure loss on both design and off-design conditions. The approach employs various surrogate models and a multi-infill strategy, outperforming traditional optimization methods using a single surrogate model and a single infilling strategy. The results show that compared to the original blade, the optimized blade has a 34.6<span>\\(\\%\\)</span> lower mass-averaged total pressure loss at the design point, while the static pressure ratio increases by 2.43<span>\\(\\%\\)</span>. This paper innovatively combines deep learning-based surrogate models, the hybrid optimization algorithm, and the curvature-based blade shaping method to optimize the blade shape, shorten the blade design time, and ultimately reduce the losses significantly.</p></div>","PeriodicalId":36309,"journal":{"name":"Aerospace Systems","volume":"7 3","pages":"585 - 597"},"PeriodicalIF":0.0000,"publicationDate":"2024-01-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Aerospace Systems","FirstCategoryId":"1085","ListUrlMain":"https://link.springer.com/article/10.1007/s42401-023-00265-y","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Earth and Planetary Sciences","Score":null,"Total":0}
引用次数: 0
Abstract
The compressor is a critical component of aero-engines. In order to improve the performance, the compressor ratio of single-stage compressor is getting higher and higher, which will lead to high back pressure gradient and losses. To solve this problem, there are many techniques applied, such as cantilevered stator, tip clearance and slotted airfoils. However, traditional design methods are experience-dependent and time-consuming. This paper proposes a hybrid optimization method to optimize the stacking line of compressor cascade and reduce total pressure loss on both design and off-design conditions. The approach employs various surrogate models and a multi-infill strategy, outperforming traditional optimization methods using a single surrogate model and a single infilling strategy. The results show that compared to the original blade, the optimized blade has a 34.6\(\%\) lower mass-averaged total pressure loss at the design point, while the static pressure ratio increases by 2.43\(\%\). This paper innovatively combines deep learning-based surrogate models, the hybrid optimization algorithm, and the curvature-based blade shaping method to optimize the blade shape, shorten the blade design time, and ultimately reduce the losses significantly.
期刊介绍:
Aerospace Systems provides an international, peer-reviewed forum which focuses on system-level research and development regarding aeronautics and astronautics. The journal emphasizes the unique role and increasing importance of informatics on aerospace. It fills a gap in current publishing coverage from outer space vehicles to atmospheric vehicles by highlighting interdisciplinary science, technology and engineering.
Potential topics include, but are not limited to:
Trans-space vehicle systems design and integration
Air vehicle systems
Space vehicle systems
Near-space vehicle systems
Aerospace robotics and unmanned system
Communication, navigation and surveillance
Aerodynamics and aircraft design
Dynamics and control
Aerospace propulsion
Avionics system
Opto-electronic system
Air traffic management
Earth observation
Deep space exploration
Bionic micro-aircraft/spacecraft
Intelligent sensing and Information fusion