• Wind and Structures
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• v.7 no.3
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• pp.173-186
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• 2004

Flutter derivatives provide the basis of predicting the critical wind speed in flutter and buffeting analysis of long-span cable-supported bridges. In this paper, one popular stochastic system identification technique, covariance-driven Stochastic Subspace Identification(SSI in short), is firstly presented for estimation of the flutter derivatives of bridge decks from their random responses in turbulent flow. Secondly, wind tunnel tests of a streamlined thin plate model and a ${\Pi}$ type blunt bridge section model are conducted in turbulent flow and the flutter derivatives are determined by SSI. The flutter derivatives of the thin plate model identified by SSI are very comparable to those identified by the unifying least-square method and Theodorson's theoretical values. As to the ${\Pi}$ type section model, the effect of turbulence on aerodynamic damping seems to be somewhat notable, therefore perhaps the wind tunnel tests for flutter derivative estimation of those models with similar blunt sections should be conducted in turbulent flow.

• Wind and Structures
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• v.22 no.3
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• pp.273-290
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• 2016

The flutter derivatives of bridge decks can be efficiently identified using the experimentally and/or numerically coupled forced vibration method. This paper addresses the issue of inherent requirement for adopting different frequencies of three modes in this method. The aerostatic force components and the inertia of force and moment are mathematically proved to exert no influence on identification results if the signal length (t) is integer (n=1,2,3...) times of the least common multiple (T) of three modal periods. It is one important contribution to flutter derivatives identification theory and engineering practice in this study. Therefore, it is unnecessary to worry about the determination accuracy of aerostatic force and inertia of force and moment. The influences of signal length, amplitude, and frequency ratio on flutter derivative are thoroughly investigated using a bridge example. If the signal length t is too short, the extraction results may be completely wrong, and particular attention should be paid to this issue. The signal length t=nT ($n{\geq}5$) is strongly recommended for improving parameter identification accuracy. The proposed viewpoints and conclusions are of great significance for better understanding the essences of flutter derivative identification through coupled forced vibration method.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2009.04a
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• pp.538-544
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• 2009

A vibration excitation system was designed and built of forced vibration experiments for using stepping motor and load cell. The identified flutter derivatives of the thin-plate acrylic model were very close to the analytical results of the idealized plate presented by Theodorsen. Five types of sectional models were tested in the wind tunnel using the proposed forced vibration method. To investigate the frequency, amplitude and angle of attack effects on flutter derivatives.

• Wind and Structures
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• v.9 no.2
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• pp.159-178
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• 2006

For the slender and flexible cable supported bridges, identification of all the flutter derivatives for the vertical, lateral and torsional motions is essential for its stability investigation. In all, eighteen flutter derivatives may have to be considered, the identification of which using a three degree-of-freedom elastic suspension system has been a challenging task. In this paper, a system identification technique, known as covariance-driven stochastic subspace identification (COV-SSI) technique, has been utilized to extract the flutter derivatives for a typical bridge deck. This method identifies the stochastic state-space model from the covariances of the output-only (stochastic) data. All the eighteen flutter derivatives have been simultaneously extracted from the output response data obtained from wind tunnel test on a 3-DOF elastically suspended bridge deck section-model. Simplicity in model suspension and measurements of only output responses are additional motivating factors for adopting COV-SSI technique. The identified discrete values of flutter derivatives have been approximated by rational functions.

• Wind and Structures
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• v.11 no.3
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• pp.209-220
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• 2008

Flutter derivatives provide the basis of predicting the critical wind speed in flutter and buffeting analysis of long-span cable-supported bridges. Many studies have been performed on the methods and applications of identification of flutter derivatives of bridge decks under wind action. In fact, strong wind, especially typhoon, is always accompanied by heavy rain. Then, what is the effect of rain on flutter derivatives and flutter critical wind speed of bridges? Unfortunately, there have been no studies on this subject. This paper makes an initial study on this problem. Covariance-driven Stochastic Subspace Identification (SSI in short) which is capable of estimating the flutter derivatives of bridge decks from their steady random responses is presented first. An experimental set-up is specially designed and manufactured to produce the conditions of rain and wind. Wind tunnel tests of a quasi-streamlined thin plate model are conducted under conditions of only wind action and simultaneous wind-rain action, respectively. The flutter derivatives are then extracted by the SSI method, and comparisons are made between the flutter derivatives under the two different conditions. The comparison results tentatively indicate that rain has non-trivial effects on flutter derivatives, especially on and $H_2$ and $A_2$thus the flutter critical wind speeds of bridges.

• Wind and Structures
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• v.35 no.5
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• pp.323-336
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• 2022

This study investigates the applicability of the direct identification of flutter derivatives in the time domain using Rational Function Approximation (RFA), where the extraction procedure requires either a combination of at least two wind speeds or one wind speed. In the frequency domain, flutter derivatives are identified at every wind speed. The ease of identifying flutter derivatives in the time domain creates a paradox because flutter derivative patterns sometimes change in higher-order polynomials. The first step involves a numerical study of RFA extractions for different deck shapes from existing bridges to verify the accurate wind speed combination for the extraction. The second step involves validating numerical simulation results through a wind tunnel experiment using the forced vibration method in one degree of freedom. The findings of the RFA extraction are compared to those obtained using the analytical solution. The numerical study and the wind tunnel experiment results are in good agreement. The results show that the evolution pattern of flutter derivatives determines the accuracy of the direct identification of RFA.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.19 no.6
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• pp.575-582
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• 2009

This study presents the vibration excitation system to extract the aerodynamic stability derivatives which is generally called as flutter derivatives in civil engineering. The system consists of the excitation part to give a forced harmonic motion to the model and the sensing part to measure the aerodynamic forces as well as inertia forces acting on a bridge model. A data processing algorithm for extracting the flutter derivatives from the measured forces is also presented. From the wind tunnel tests, verification of present system was done by comparing the measured and analytical results for rectangular shaped model. The effects of excitation frequencies and amplitudes on flutter derivatives are discussed. Five kinds of actual bridge model were presented from the wind tunnel.

• Wind and Structures
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• v.14 no.5
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• pp.413-434
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• 2011

Without output covariance estimation, one reference-based Stochastic Subspace Technique (SST) for extracting modal parameters and flutter derivatives of bridge deck is developed and programmed. Compared with the covariance-driven SST and the oscillation signals incurred by oncoming or signature turbulence that adopted by previous investigators, the newly-presented identification scheme is less time-consuming in computation and a more desired accuracy should be contributed to high-quality free oscillated signals excited by specific initial displacement. The reliability and identification precision of this technique are confirmed by a numerical example. For the 3-DOF sectional models of Sutong Bridge deck (streamlined) and Suramadu Bridge deck (bluff) in wind tunnel tests, with different wind velocities, the lateral bending, vertical bending, torsional frequencies and damping ratios as well as 18 flutter derivatives are extracted by using SST. The flutter derivatives of two kinds of typical decks are compared with the pseudo-steady theoretical values, and the performance of $H_1{^*}$, $H_3{^*}$, $A_1{^*}$, $A_3{^*}$ is very stable and well-matched with each other, respectively. The lateral direct flutter derivatives $P_5{^*}$, $P_6{^*}$ are comparatively more accurate than other relevant lateral components. Experimental procedure seems to be more critical than identification technique for refining the estimation precision.

• Wind and Structures
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• v.14 no.3
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• pp.221-238
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• 2011

The estimated response of large-scale engineering structures to severe wind loads is prone to modelling uncertainties that can only ultimately be assessed by full-scale testing. To this end ambient vibration data from full-scale monitoring of the historic Clifton Suspension Bridge has been analysed using a combination of a frequency domain system identification method and a more elaborate stochastic identification technique. There is evidence of incipient coupling action between the first vertical and torsional modes in strong winds, providing unique full-scale data and making this an interesting case study. Flutter derivative estimation, which has rarely previously been attempted on full-scale data, was performed to provide deeper insight into the bridge aerodynamic behaviour, identifying trends towards flutter at higher wind speeds. It is shown that, as for other early suspension bridges with bluff cross-sections, single-degree-of-freedom flutter could potentially occur at wind speeds somewhat below requirements for modern designs. The analysis also demonstrates the viability of system identification techniques for extracting valuable results from full-scale data.

• Wind and Structures
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• v.6 no.3
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• pp.179-196
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• 2003

A long suspension bridge is often located within a unique wind environment, and strong winds at the site seldom attack the bridge at a right angle to its long axis. This paper thus investigates the buffeting response of long suspension bridges to skew winds. The conventional buffeting analysis in the frequency domain is first improved to take into account skew winds based on the quasi-steady theory and the oblique strip theory in conjunction with the finite element method and the pseudo-excitation method. The aerodynamic coefficients and flutter derivatives of the Tsing Ma suspension bridge deck under skew winds, which are required in the improved buffeting analysis, are then measured in a wind tunnel using specially designed test rigs. The field measurement data, which were recorded during Typhoon Sam in 1999 by the Wind And Structural Health Monitoring System (WASHMS) installed on the Tsing Ma Bridge, are analyzed to obtain both wind characteristics and buffeting responses. Finally, the field measured buffeting responses of the Tsing Ma Bridge are compared with those from the computer simulation using the improved method and the aerodynamic coefficients and flutter derivatives measured under skew winds. The comparison is found satisfactory in general.