4.7 Article

Vortex-induced vibration of a circular cylinder with nonlinear stiffness: prediction using forced vibration data

期刊

NONLINEAR DYNAMICS
卷 108, 期 3, 页码 1867-1884

出版社

SPRINGER
DOI: 10.1007/s11071-022-07332-7

关键词

Vortex-induced vibration; Harmonically forced vibration; Nonlinear stiffness; Nonlinear energy sink

资金

  1. Key Lab of Sichuan Province [FMEDP202107]

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This study proposes a method to predict the VIV responses of a circular cylinder with nonlinear stiffness using harmonically forced vibration data, and validates its accuracy by comparing with free vibration CFD simulations. The results indicate that forced vibration data can qualitatively and to some extent quantitatively predict the VIV responses of the considered nonlinear systems.
Vortex-induced vibration (VIV) systems with stiffness nonlinearity have received increasing attention because the stiffness nonlinearity can broaden the effective flow velocity range for energy harvesting or achieve broadband VIV suppression. Reduced-order mathematical models are useful when it is necessary to analyze and optimize a VIV-based system with stiffness nonlinearity. However, the accuracy of existing reduced-order models in simulating the VIV of a structure with nonlinear stiffness remains unknown. This investigation proposes to predict the VIV of a circular cylinder with nonlinear stiffness using harmonically forced vibration data. The transverse force coefficients of a circular cylinder at a Reynolds number of Re = 150 are identified based on computational fluid dynamics (CFD) simulations with harmonically forced vibrations. The forced vibration data are utilized to predict the VIV responses of a circular cylinder with cubic nonlinear stiffness and a circular cylinder with a nonlinear energy sink (NES) attachment. The predictions based on forced vibration data are compared with free vibration CFD simulations to validate the accuracy of the proposed method. Numerical examples suggest that the forced vibration data can qualitatively and to some extent quantitatively predict the VIV responses of the considered nonlinear systems. Hence, the reduced-order model with forced vibration data can serve as an effective tool for analyzing and optimizing VIV systems with stiffness nonlinearities.

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