Cap. Yaara Karniel and Cap. Daniel Kariv, Maj. Michael Iovnovich

DOI Number: N/A

Conference number: IFASD-2019-016

The problem of flutter mechanism classification is important particularly for modern fighter aircrafts, for which the amount of aircraft configurations which require analysis is typically large. Common flutter mechanism classification and characterization techniques rely on characteristics which represent the structural motions at flutter conditions rather than a quantitative measure of the instability severity or its origins. Such classifications may be somewhat subjective, require tedious treatment by the analyst and may in some cases lead to wrong conclusions. The current study aims to enhance flutter mechanism characterization and classification processes by using an aeroelastic energy balance analysis which is formulated in structural coordinates. The method may be easily applicable to typical industrial flutter analysis data and enables to identify distributed aeroelastic energy patterns which are visualized on the configuration structural model. This analysis approach is shown to enable straightforward identification of the structural parts which are the dominant contributors to the unstable coupling and thereby to distinguish between physically dissimilar flutter cases. The application of aeroelastic energy-based parameters for flutter mechanism classification is presented in this study for a representative dataset including thousands of wing flutter cases of the F-16 aircraft with various stores. Using the suggested approach, six basic flutter mechanism groups are identified in the examined dataset. Over 98% of the examined flutter cases may be automatically classified to one of these mechanism groups, which demonstrates the potential of this approach.

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In Categories: 1. IFASD 2019, Computational Flutter
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