{"title":"改善发动机性能的轴流压缩机叶片倾斜和扫掠三维优化","authors":"M. Heidarian, †. A.Madadi, M. Boroomand","doi":"10.47176/jafm.16.11.1857","DOIUrl":null,"url":null,"abstract":"Nowadays, optimization methods have been considered as a practical tool to improve the performance of turbo-machines. For this purpose, the numerical study of the aerodynamic flow of the NASA Rotor-67 axial compressor has been investigated, and the results of this three-dimensional simulation show good agreement with experimental data. Then, the blade stacking line is changed using lean and sweep for Rotor-67 to improve the compressor performance. The third-order polynomial is selected to generate the lean and sweep changes from the hub to the shroud. The compressor flow field is solved by a Reynolds averaged Navier-Stokes solver. The genetic algorithm, coupled with the artificial neural networks, is implemented to find the optimum values for blade lean and sweep. Considering the three objective functions of pressure ratio, mass flow rate, and isentropic efficiency, the optimized rotor is obtained using the optimization algorithm. Two geometries are obtained using the optimization algorithm. The results of the optimized compressor include improving the isentropic efficiency, pressure ratio, and mass flow equal to 0.57%, 0.93%, and 1.8%, respectively. After compressor optimization, the effect of the changes in the compressor performance parameters is studied on a single spool turbojet engine. The engine is modeled by analyzing the Brayton thermodynamic cycle of the assumed turbojet engine under design point operating conditions. Results show that for the best test case, the engine with the optimized rotor, the thrust, and SFC are improved by 1.86% and 0.21%, respectively.","PeriodicalId":49041,"journal":{"name":"Journal of Applied Fluid Mechanics","volume":" ","pages":""},"PeriodicalIF":1.1000,"publicationDate":"2023-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Three-Dimensional Optimization of Blade Lean and Sweep for an Axial Compressor to Improve the Engine Performance\",\"authors\":\"M. Heidarian, †. A.Madadi, M. Boroomand\",\"doi\":\"10.47176/jafm.16.11.1857\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Nowadays, optimization methods have been considered as a practical tool to improve the performance of turbo-machines. For this purpose, the numerical study of the aerodynamic flow of the NASA Rotor-67 axial compressor has been investigated, and the results of this three-dimensional simulation show good agreement with experimental data. Then, the blade stacking line is changed using lean and sweep for Rotor-67 to improve the compressor performance. The third-order polynomial is selected to generate the lean and sweep changes from the hub to the shroud. The compressor flow field is solved by a Reynolds averaged Navier-Stokes solver. The genetic algorithm, coupled with the artificial neural networks, is implemented to find the optimum values for blade lean and sweep. Considering the three objective functions of pressure ratio, mass flow rate, and isentropic efficiency, the optimized rotor is obtained using the optimization algorithm. Two geometries are obtained using the optimization algorithm. The results of the optimized compressor include improving the isentropic efficiency, pressure ratio, and mass flow equal to 0.57%, 0.93%, and 1.8%, respectively. After compressor optimization, the effect of the changes in the compressor performance parameters is studied on a single spool turbojet engine. The engine is modeled by analyzing the Brayton thermodynamic cycle of the assumed turbojet engine under design point operating conditions. Results show that for the best test case, the engine with the optimized rotor, the thrust, and SFC are improved by 1.86% and 0.21%, respectively.\",\"PeriodicalId\":49041,\"journal\":{\"name\":\"Journal of Applied Fluid Mechanics\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":1.1000,\"publicationDate\":\"2023-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Applied Fluid Mechanics\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://doi.org/10.47176/jafm.16.11.1857\",\"RegionNum\":4,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"MECHANICS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Applied Fluid Mechanics","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.47176/jafm.16.11.1857","RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"MECHANICS","Score":null,"Total":0}
Three-Dimensional Optimization of Blade Lean and Sweep for an Axial Compressor to Improve the Engine Performance
Nowadays, optimization methods have been considered as a practical tool to improve the performance of turbo-machines. For this purpose, the numerical study of the aerodynamic flow of the NASA Rotor-67 axial compressor has been investigated, and the results of this three-dimensional simulation show good agreement with experimental data. Then, the blade stacking line is changed using lean and sweep for Rotor-67 to improve the compressor performance. The third-order polynomial is selected to generate the lean and sweep changes from the hub to the shroud. The compressor flow field is solved by a Reynolds averaged Navier-Stokes solver. The genetic algorithm, coupled with the artificial neural networks, is implemented to find the optimum values for blade lean and sweep. Considering the three objective functions of pressure ratio, mass flow rate, and isentropic efficiency, the optimized rotor is obtained using the optimization algorithm. Two geometries are obtained using the optimization algorithm. The results of the optimized compressor include improving the isentropic efficiency, pressure ratio, and mass flow equal to 0.57%, 0.93%, and 1.8%, respectively. After compressor optimization, the effect of the changes in the compressor performance parameters is studied on a single spool turbojet engine. The engine is modeled by analyzing the Brayton thermodynamic cycle of the assumed turbojet engine under design point operating conditions. Results show that for the best test case, the engine with the optimized rotor, the thrust, and SFC are improved by 1.86% and 0.21%, respectively.
期刊介绍:
The Journal of Applied Fluid Mechanics (JAFM) is an international, peer-reviewed journal which covers a wide range of theoretical, numerical and experimental aspects in fluid mechanics. The emphasis is on the applications in different engineering fields rather than on pure mathematical or physical aspects in fluid mechanics. Although many high quality journals pertaining to different aspects of fluid mechanics presently exist, research in the field is rapidly escalating. The motivation for this new fluid mechanics journal is driven by the following points: (1) there is a need to have an e-journal accessible to all fluid mechanics researchers, (2) scientists from third- world countries need a venue that does not incur publication costs, (3) quality papers deserve rapid and fast publication through an efficient peer review process, and (4) an outlet is needed for rapid dissemination of fluid mechanics conferences held in Asian countries. Pertaining to this latter point, there presently exist some excellent conferences devoted to the promotion of fluid mechanics in the region such as the Asian Congress of Fluid Mechanics which began in 1980 and nominally takes place in one of the Asian countries every two years. We hope that the proposed journal provides and additional impetus for promoting applied fluids research and associated activities in this continent. The journal is under the umbrella of the Physics Society of Iran with the collaboration of Isfahan University of Technology (IUT) .