{"title":"航空发动机进气口非稳态流变形的极值预测评估","authors":"Matteo Migliorini, P. Zachos, D. MacManus","doi":"10.1115/1.4064728","DOIUrl":null,"url":null,"abstract":"\n Unsteady flow distortion is of interest for the development air-breathing propulsion systems. These stochastic fluctuations can generate incompatibilities between intakes and aero-engines. Observing the extreme flow distortion events during experimental testing is not guaranteed and statistical models such as Extreme Value Theory (EVT) can be used to estimate the occurrence and magnitude of the fluctuations. However, the current industry standard does not provide guidance on how to apply these methods to obtain useful predictions. This work proposes a systematic process to assess the required number of observations for obtaining statistical convergence of the EVT predictions. This is achieved through shuffling of the data samples and relies on the availability of a sufficiently large initial dataset. This can be adopted by gas turbine engineers to evaluate the data recording requirements and to potentially reduce costs associated with experimental programs.","PeriodicalId":508252,"journal":{"name":"Journal of Engineering for Gas Turbines and Power","volume":"57 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-02-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Evaluation of Extreme Value Predictions for Unsteady Flow Distortion of Aero-Engine Intakes\",\"authors\":\"Matteo Migliorini, P. Zachos, D. MacManus\",\"doi\":\"10.1115/1.4064728\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"\\n Unsteady flow distortion is of interest for the development air-breathing propulsion systems. These stochastic fluctuations can generate incompatibilities between intakes and aero-engines. Observing the extreme flow distortion events during experimental testing is not guaranteed and statistical models such as Extreme Value Theory (EVT) can be used to estimate the occurrence and magnitude of the fluctuations. However, the current industry standard does not provide guidance on how to apply these methods to obtain useful predictions. This work proposes a systematic process to assess the required number of observations for obtaining statistical convergence of the EVT predictions. This is achieved through shuffling of the data samples and relies on the availability of a sufficiently large initial dataset. This can be adopted by gas turbine engineers to evaluate the data recording requirements and to potentially reduce costs associated with experimental programs.\",\"PeriodicalId\":508252,\"journal\":{\"name\":\"Journal of Engineering for Gas Turbines and Power\",\"volume\":\"57 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-02-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Engineering for Gas Turbines and Power\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1115/1.4064728\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Engineering for Gas Turbines and Power","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1115/1.4064728","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Evaluation of Extreme Value Predictions for Unsteady Flow Distortion of Aero-Engine Intakes
Unsteady flow distortion is of interest for the development air-breathing propulsion systems. These stochastic fluctuations can generate incompatibilities between intakes and aero-engines. Observing the extreme flow distortion events during experimental testing is not guaranteed and statistical models such as Extreme Value Theory (EVT) can be used to estimate the occurrence and magnitude of the fluctuations. However, the current industry standard does not provide guidance on how to apply these methods to obtain useful predictions. This work proposes a systematic process to assess the required number of observations for obtaining statistical convergence of the EVT predictions. This is achieved through shuffling of the data samples and relies on the availability of a sufficiently large initial dataset. This can be adopted by gas turbine engineers to evaluate the data recording requirements and to potentially reduce costs associated with experimental programs.