Evaluation of Extreme Value Predictions for Unsteady Flow Distortion of Aero-Engine Intakes

Matteo Migliorini, P. Zachos, D. MacManus
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Abstract

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.
航空发动机进气口非稳态流变形的极值预测评估
非稳定流畸变是开发喷气推进系统的一个重要问题。这些随机波动会造成进气口和航空发动机之间的不兼容。在实验测试过程中无法保证观察到极端流动畸变事件,而统计模型(如极值理论 (EVT))可用于估计波动的发生和幅度。然而,目前的行业标准并未就如何应用这些方法获得有用的预测结果提供指导。这项工作提出了一个系统流程,用于评估获得 EVT 预测统计收敛性所需的观测值数量。这是通过对数据样本进行洗牌来实现的,并依赖于足够大的初始数据集。燃气轮机工程师可以采用这种方法来评估数据记录要求,并有可能降低与实验项目相关的成本。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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