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Evaluation of System Identification Methods for Free Vibration Flutter Derivatives of Long-Span Bridges

Authors :
Muhammad Saqlain Awan
Ali Javed
Muhammad Faheem Ud Din Afzal
Luis Federico Navarro Vilchez
Armin Mehrabi
Source :
Applied Sciences, Vol 13, Iss 8, p 4672 (2023)
Publication Year :
2023
Publisher :
MDPI AG, 2023.

Abstract

The significance of long-span bridges being susceptible to wind-induced vibrations and the need for evaluating their aerodynamic performance is the focus of this study. The main emphasis is on experimental methods for assessing the bridges’ aerodynamic stability, using sectional model tests with the free vibration technique. The dynamic properties of the model are determined from the measured response, using various system identification methods, including the modified Ibrahim time domain (MITD) and iterative least squares (ILS) for two-degree-of-freedom systems and the logarithmic decrement method (LDM) and the Hilbert transform method (HTM) for single-degree-of-freedom (SDOF) systems. A new dynamic testing setup was designed to facilitate single-degree-of-freedom (heave and pitch) and coupled two-degree-of-freedom (2DOF) motion in a wind tunnel section model. The vertical and torsional stiffnesses of the model were adjusted with elastic springs. A Great Belt Bridge section model was selected for testing due to its streamlined aerodynamic shape. The direct and crossflow derivatives were extracted from the measured response using the system identification methods mentioned. Additionally, analytical studies and numerical computational fluid dynamics simulations were conducted to validate the experimental results. The study found that HTM is most effective in SDOF due to its ability to extract both damping and frequency from the nonlinear response, whereas the MITD method is faster in converging system parameters in 2DOF system tests. The experimental and numerical results are comparable to the flat plate, which confirms the streamlined behavior of the Great Belt section from an aerodynamic perspective.

Details

Language :
English
ISSN :
20763417
Volume :
13
Issue :
8
Database :
Directory of Open Access Journals
Journal :
Applied Sciences
Publication Type :
Academic Journal
Accession number :
edsdoj.6a0730974bc4e18afcefe7ad3d0d959
Document Type :
article
Full Text :
https://doi.org/10.3390/app13084672