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Author:

Xu, Kun (Xu, Kun.) | Zhao, Lin (Zhao, Lin.) | Ge, Yaojun (Ge, Yaojun.)

Indexed by:

EI Scopus SCIE

Abstract:

Volterra theory-based reduced-order modeling (ROM) technique is utilized for simulating fluid-structure interactions of bridge decks during vortex-induced vibration (WV). To improve the order of nonlinearity adopted in the Volterra series, sparse form kernels are adopted in this study. To illustrate and validate the performance of ROM in simulating fluid-structure interactions of WV, a real bridge deck is used as a case study. The kernels in the Volterra series are identified using least squares with input output pairs obtained from a CFD approach. Results indicate that ROM can well reproduce the inherent nature of nonlinearities existing in fluid-structure interactions described by the CFD approach. A method for calculating the WV of bridges by combining ROM with the structural finite element model is also proposed. The VIV performance of a real bridge is obtained through the proposed method and is compared with field measurements.

Keyword:

Bridge VIV calculation Reduced-order modeling Vortex-induced vibration

Author Community:

  • [ 1 ] [Xu, Kun]Beijing Univ Technol, Minist Educ, Key Lab Urban Secur & Disaster Engn, Beijing, Peoples R China
  • [ 2 ] [Xu, Kun]Tongji Univ, State Key Lab Disaster Reduct Civil Engn, Shanghai, Peoples R China
  • [ 3 ] [Zhao, Lin]Tongji Univ, State Key Lab Disaster Reduct Civil Engn, Shanghai, Peoples R China
  • [ 4 ] [Ge, Yaojun]Tongji Univ, State Key Lab Disaster Reduct Civil Engn, Shanghai, Peoples R China

Reprint Author's Address:

  • [Zhao, Lin]Tongji Univ, State Key Lab Disaster Reduct Civil Engn, Shanghai, Peoples R China

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Source :

JOURNAL OF WIND ENGINEERING AND INDUSTRIAL AERODYNAMICS

ISSN: 0167-6105

Year: 2017

Volume: 167

Page: 228-241

4 . 8 0 0

JCR@2022

ESI Discipline: ENGINEERING;

ESI HC Threshold:165

CAS Journal Grade:2

Cited Count:

WoS CC Cited Count: 25

SCOPUS Cited Count: 32

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 5

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