{"title":"Multidisciplinary sensitivity analysis for turbine blade considering thickness uncertainties","authors":"Fan Yang, Chunyu Zhang, W. Gao, Lei Li","doi":"10.1515/tjeng-2022-0034","DOIUrl":null,"url":null,"abstract":"Abstract This work presents an approach for sensitivity analysis of turbine cooling blade with surface thickness uncertainties, combining mesh deformation method, neural network model and multidisciplinary analysis. Normally, for even tiny shape changes, conventional geometry-based method failed easily during the auto-processing analysis. Therefore, mesh deformation method was utilized to capture the tiny size changes in the multidisciplinary analysis for both the fluid and the structure meshes. The neural network model is constructed by design of experiments to reduce the computational cost. Sensitivity analysis of the multidisciplinary system of blade is performed by numerical difference algorithm with the neural network model. Results showed that the proposed method was effective and practical in engineering.","PeriodicalId":50284,"journal":{"name":"International Journal of Turbo & Jet-Engines","volume":" ","pages":""},"PeriodicalIF":0.7000,"publicationDate":"2022-12-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Turbo & Jet-Engines","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.1515/tjeng-2022-0034","RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"ENGINEERING, AEROSPACE","Score":null,"Total":0}
引用次数: 0
Abstract
Abstract This work presents an approach for sensitivity analysis of turbine cooling blade with surface thickness uncertainties, combining mesh deformation method, neural network model and multidisciplinary analysis. Normally, for even tiny shape changes, conventional geometry-based method failed easily during the auto-processing analysis. Therefore, mesh deformation method was utilized to capture the tiny size changes in the multidisciplinary analysis for both the fluid and the structure meshes. The neural network model is constructed by design of experiments to reduce the computational cost. Sensitivity analysis of the multidisciplinary system of blade is performed by numerical difference algorithm with the neural network model. Results showed that the proposed method was effective and practical in engineering.
期刊介绍：
The Main aim and scope of this Journal is to help improve each separate components R&D and superimpose separated results to get integrated systems by striving to reach the overall advanced design and benefits by integrating: (a) Physics, Aero, and Stealth Thermodynamics in simulations by flying unmanned or manned prototypes supported by integrated Computer Simulations based on: (b) Component R&D of: (i) Turbo and Jet-Engines, (ii) Airframe, (iii) Helmet-Aiming-Systems and Ammunition based on: (c) Anticipated New Programs Missions based on (d) IMPROVED RELIABILITY, DURABILITY, ECONOMICS, TACTICS, STRATEGIES and EDUCATION in both the civil and military domains of Turbo and Jet Engines.
The International Journal of Turbo & Jet Engines is devoted to cutting edge research in theory and design of propagation of jet aircraft. It serves as an international publication organ for new ideas, insights and results from industry and academic research on thermodynamics, combustion, behavior of related materials at high temperatures, turbine and engine design, thrust vectoring and flight control as well as energy and environmental issues.
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