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Wind-induced random vibration of saddle membrane structures: Theoretical and experimental study

  • Rongjie Pan (School of Civil Engineering, Guangzhou University) ;
  • Changjiang Liu (School of Civil Engineering, Guangzhou University) ;
  • Dong Li (School of Civil Engineering, Fuzhou University) ;
  • Yuanjun Sun (School of Civil Engineering, Guangzhou University) ;
  • Weibin Huang (School of Civil Engineering, Guangzhou University) ;
  • Ziye Chen (School of Civil Engineering, Guangzhou University)
  • 투고 : 2022.08.08
  • 심사 : 2023.02.08
  • 발행 : 2023.02.25

초록

The random vibration of saddle membrane structures under wind load is studied theoretically and experimentally. First, the nonlinear random vibration differential equations of saddle membrane structures under wind loads are established based on von Karman's large deflection theory, thin shell theory and potential flow theory. The probabilistic density function (PDF) and its corresponding statistical parameters of the displacement response of membrane structure are obtained by using the diffusion process theory and the Fokker Planck Kolmogorov equation method (FPK) to solve the equation. Furthermore, a wind tunnel test is carried out to obtain the displacement time history data of the test model under wind load, and the statistical characteristics of the displacement time history of the prototype model are obtained by similarity theory and probability statistics method. Finally, the rationality of the theoretical model is verified by comparing the experimental model with the theoretical model. The results show that the theoretical model agrees with the experimental model, and the random vibration response can be effectively reduced by increasing the initial pretension force and the rise-span ratio within a certain range. The research methods can provide a theoretical reference for the random vibration of the membrane structure, and also be the foundation of structural reliability of membrane structure based on wind-induced response.

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과제정보

This work was supported by the National Natural Science Foundation of China (Grant No. 52108121), Guangdong Basic and Applied Basic Research Foundation (Project Number 2019A1515011063), Guangzhou Science and Technology Project (Project number 202102010455), and Science and Technology Project of Guangzhou University (Project number RQ2020100).

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