Modelling unsteady self-excited wind force on slender prisms in a turbulent flow

Chen, Zengshun; Tse, Kam Tim; Kwok, K.C.S.; Kim, Bubryur; Kareem, Ahsan

doi:10.1016/j.engstruct.2019.109855

Cited by 24 publications

(14 citation statements)

References 32 publications

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“…A test model in a SMPSS test should be rigid enough to avoid evident wind-induced vibration so that the pressure measured in the test is precise [25]. Furthermore, in order to reduce the impact of pressure tap tubes on the signal, the length of the tube is usually less than 1.4 m.…”

Section: Smpss Testmentioning

confidence: 99%

“…Furthermore, the system was used for two-dimensional deck sections and cannot be used for three-dimensional prisms. Besides, Chen et al [25,43] developed a mathematical model to quantify the unsteady self-excited forces acting on a slender by HAFB wind tunnel tests, and found that the forces obtained from the tests can be used to predict the galloping response. Most recently, Gao and Zhu [41,42] devised a spring-suspended system ( Figure 7) that can observe unsteady base forces and aeroelastic vibrations of a two-dimensional test model.…”

Section: Hybrid Aeroelastic-force Balance Test Techniquementioning

confidence: 99%

Section: Hybrid Aeroelastic-force Balance Test Techniquementioning

confidence: 99%

“…Most recently, Gao and Zhu [41,81] have identified the unsteady galloping force of two-dimensional cylinders by using the aforementioned hybrid aeroelastic-force experimental system (Figure 7). Chen et al [25] measured the unsteady aerodynamic force and galloping response of a prism from a HAFB wind tunnel test. The unsteady aerodynamic force measured form the hybrid aeroelastic-pressure balance test includes galloping force components and buffeting force components.…”

Section: Unsteady Self-excited Forcementioning

confidence: 99%

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Wind Tunnel Measurement Systems for Unsteady Aerodynamic Forces on Bluff Bodies: Review and New Perspective

Chen

Huang

et al. 2020

Sensors

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Wind tunnel tests have become one of the most effective ways to evaluate aerodynamics and aeroelasticity in bluff bodies. This paper has firstly overviewed the development of conventional wind tunnel test techniques, including high frequency base balance technique, static synchronous multi-pressure sensing system test technique and aeroelastic test, and summarized their advantages and shortcomings. Subsequently, two advanced test approaches, a forced vibration test technique and hybrid aeroelastic- force balance wind tunnel test technique have been comprehensively reviewed. Then the characteristics and calculation procedure of the conventional and advanced wind tunnel test techniques were discussed and summarized. The results indicated that the conventional wind tunnel test techniques ignored the effect of structural oscillation on the measured aerodynamics as the test model is rigid. A forced vibration test can include that effect. Unfortunately, a test model in a forced vibration test cannot respond like a structure in the real world; it only includes the effect of structural oscillation on the surrounding flow and cannot consider the feedback from the surrounding flow to the oscillation test model. A hybrid aeroelastic-pressure/force balance test technique that can observe unsteady aerodynamics of a test model during its aeroelastic oscillation completely takes the effect of structural oscillation into consideration and is, therefore, effective in evaluation of aerodynamics and aeroelasticity in bluff bodies. This paper has not only advanced our understanding for aerodynamics and aeroelasticity in bluff bodies, but also provided a new perspective for advanced wind tunnel test techniques that can be used for fundamental studies and engineering applications.

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Section: Smpss Testmentioning

confidence: 99%

Section: Hybrid Aeroelastic-force Balance Test Techniquementioning

confidence: 99%

Section: Hybrid Aeroelastic-force Balance Test Techniquementioning

confidence: 99%

Section: Unsteady Self-excited Forcementioning

confidence: 99%

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Wind Tunnel Measurement Systems for Unsteady Aerodynamic Forces on Bluff Bodies: Review and New Perspective

Chen

Huang

et al. 2020

Sensors

Self Cite

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“…This class of bridges also attracted some interest, justified by the fact that, after the Tacoma collapse, many existing bridges were torsionally stiffened and the new bridges were designed with stiffer trusses (e.g., the Verrazzano bridge in New York, Tago bridge in Lisbon or the Japanese bridge Akashi Kaikyo). Many works in literature dealt with the galloping instability separately in the beam (see, e.g., [29][30][31][32][33]) and in the cable (see, e.g., [34][35][36][37]). With reference to the class of bridges with high torsional stiffness, the interest was addressed mainly to the galloping control (see, e.g., [38][39][40]).…”

Section: Introductionmentioning

confidence: 99%

Nonlinear Aeroelastic in-Plane Behavior of Suspension Bridges under Steady Wind Flow

Nino

Luongo

2020

Applied Sciences

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The nonlinear aeroelastic behavior of suspension bridges, undergoing dynamical in-plain instability (galloping), is analyzed. A nonlinear continuous model of bridge is formulated, made of a visco-elastic beam and a parabolic cable, connected each other by axially rigid suspenders, continuously distributed. The structure is loaded by a uniform wind flow which acts normally to the bridge plane. Both external and internal damping are accounted for the structure, according to the Kelvin-Voigt rheological model. The nonlinear aeroelastic effects are evaluated via the quasi-static theory, while structural nonlinearities are not taken into account. First, the free dynamics of the undamped bridge are addressed, and the natural modes determined. Then, the nonlinear equations ruling the dynamics of the aeroelastic system, close to the bifurcation point, are tackled by the Multiple Scale Method. This is directly applied to the partial differential equations, and provides the finite-dimensional bifurcation equations. From these latter, the limit-cycle amplitude and its stability are evaluated as function of the mean wind velocity. A case study of suspension bridge is analyzed.

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An Autoencoder‐Based Deep‐Learning Method for Augmenting the Sensing Capability of Piezoelectric Microelectromechanical System Sensors in a Fluid‐Dynamic System

Kazemzadeh,

Mehdipour,

De Vittorio

et al. 2023

Advanced Intelligent Systems

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Herein, an innovative deep‐learning architecture is proposed to enhance the sensing capabilities of a microelectromechanical system (MEMS) used in fluid dynamic applications. The MEMS sensor comprises a polyvinylidene fluoride flexible (PVDF) piezoelectric flag and a bluff body, with vortex generation influenced not only by the bluff body's geometry but also by the input fluid speed. As a result, mechanical vibrations are induced in the piezoelectric flag, leading to charge displacement and the generation of electrical voltage signals. Through the developed deep learning method, accurate extraction of wind speed and successful classification of turbulence are achieved. Experimental tests in a wind tunnel, involving various wind speeds and bluff body geometries, demonstrate the robust correlation between the extracted continuous manifold in Fourier spectra and wind speed. By incorporating a feed‐forward network alongside the autoencoder, wind speed information even under strong turbulence is extracted. Moreover, the deep learning method's ability to classify different bluff bodies, independent of wind speed, is investigated. The findings reveal a unique capability to fingerprint turbulence and distinguish them for various applications. This research showcases the potential of our deep learning‐based MEMS systems for enhancing fluid dynamic sensing and classification tasks.

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Modelling unsteady self-excited wind force on slender prisms in a turbulent flow

Cited by 24 publications

References 32 publications

Wind Tunnel Measurement Systems for Unsteady Aerodynamic Forces on Bluff Bodies: Review and New Perspective

Wind Tunnel Measurement Systems for Unsteady Aerodynamic Forces on Bluff Bodies: Review and New Perspective

Nonlinear Aeroelastic in-Plane Behavior of Suspension Bridges under Steady Wind Flow

An Autoencoder‐Based Deep‐Learning Method for Augmenting the Sensing Capability of Piezoelectric Microelectromechanical System Sensors in a Fluid‐Dynamic System

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