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![Figure 2. Schematic representation of the two-terminal inerter [13].](publication/369354100/figure/fig2/AS:11431281127776691@1679151815199/Schematic-representation-of-the-two-terminal-inerter-13_Q320.jpg)
Inspired by the mass amplification property of inerters, an inerter-based passive panel flutter control procedure is developed and proposed. Formulations of aeroelastic equations of motion are based on the use of a wide-beam (flat panel) element stiffness equation subjective to supersonic flow using piston theory. The onset of flutter is analyzed u...
Context in source publication
Context 1
... inertance of such a flywheel-based inerter depends primarily on the number of gears and the gear ratio used to drive the flywheels, rather than on the mass of the flywheels. A schematic representation of the inerter device is presented as a hatched box in Figure 2 [13]. Assuming that the physical mass of the inerter is negligible compared to the mass of the structure, the force F of an ideal linear inerter would be proportional to the relative acceleration of its terminals, as described in the following equation [13]. ...
Citations
Aeroelastic flutter is a dynamically complex phenomenon that has adverse and unstable effects on elastic structures. It is crucial to better predict the phenomenon of flutter within the scope of aircraft structures to improve upon the design of their wings. This review aims to establish fundamental guidelines for flutter analysis across subsonic, transonic, supersonic, and hypersonic flow regimes providing a thorough overview of established analytic, numerical, and reduced-order models as applicable to each flow regime. The review will shed light on the limitations and missing components within the previous literature on these flow regimes by highlighting the challenges involved in simulating flutter. Additionally, popular methods that employ the aforementioned analyses for optimizing wing structures under the effects of flutter, a subject currently garnering significant research attention, are also discussed. Our discussion offers new perspectives that encourages collaborative effort in the area of computational methods for flutter prediction and optimization.
