The application of reduced order models (ROMs) in the aerodynamic/aeroelastic analysis of long-span bridges, unlike the aeronautical structures, has not been extensively studied. ROMs are computationally efficient techniques, which have been widely used for predicting unsteady aerodynamic response of airfoils and wings. This paper aims to discuss the application of a reduced order computational fluid dynamics (CFD) model based on the eigensystem realization algorithm (ERA) in the aeroelastic analysis of the Great Belt Bridge (GBB).
The aerodynamic impulse response of the GBB section is used to construct the aerodynamic ROM, and then the aerodynamic ROM is coupled with the reduced DOF model of the system to construct the aeroelastic ROM. Aerodynamic coefficients and flutter derivatives are evaluated and compared to those of the advanced discrete vortex method-based CFD code.
Results demonstrate reasonable prediction power and high computational efficiency of the technique that can serve for preliminary aeroelastic analysis and design of long-span bridges, optimization and control purposes.
The application of a system identification tool like ERA into the aeroelastic analysis of long-span bridges is performed for the first time in this work. Authors have developed their earlier work on the aerodynamic analysis of long-span bridges, published in the Journal of Bridge Engineering, by coupling the aerodynamic forces with reduced DOF of structural system. The high computational efficiency of the technique enables bridge designers to perform preliminary aeroelastic analysis of long-span bridges in less than a minute.
The authors gratefully acknowledge Dr Larsen at COWI for providing the DVMFLOW code along with the generous amount of user-support. This study was funded by National Science Foundation (NSF) under grant number NSF-CMMI-1031036.
Ebrahimnejad, L., Janoyan, K.D., Valentine, D.T. and Marzocca, P. (2017), "Applications of reduced order models in the aeroelastic analysis of long-span bridges", Engineering Computations, Vol. 34 No. 5, pp. 1642-1657. https://doi.org/10.1108/EC-07-2016-0244
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