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Author:

Zhang, Chao (Zhang, Chao.) | Wang, Guang-Yong (Wang, Guang-Yong.) | Xue, Su-Duo (Xue, Su-Duo.) (Scholars:薛素铎) | Li, Xiong-Yan (Li, Xiong-Yan.)

Indexed by:

EI Scopus PKU CSCD

Abstract:

Based on the temperature field and post-fire aseismic performance test results of 8 large-scale steel reinforced concrete (SRC) columns, the load-displacement skeleton model defined by key points including a cracking point, a yield point, a peak point, and an ultimate point is proposed considering the influence of fire duration and axial load ratio. The formulas to calculate these points are recommended through theoretical analysis and data regression. Meanwhile, the relationship between unloading rigidity and elastic rigidity is suggested through data regression. A four-linear restoring force model is put forward on the basis of the above work. It can be concluded that the calculated restoring model agrees well with the test result, which can be applied to estimating the seismic behavior and nonlinear dynamic analysis of post-fire SRC columns. © 2016, Engineering Mechanics Press. All right reserved.

Keyword:

Unloading Fires Rigidity Axial loads Reinforced concrete Concrete construction Composite structures Columns (structural)

Author Community:

  • [ 1 ] [Zhang, Chao]College of Architectural and Civil Engineering, Beijing University of Technology, Beijing; 100124, China
  • [ 2 ] [Wang, Guang-Yong]China Academy of Building Research, Beijing; 100013, China
  • [ 3 ] [Xue, Su-Duo]College of Architectural and Civil Engineering, Beijing University of Technology, Beijing; 100124, China
  • [ 4 ] [Li, Xiong-Yan]College of Architectural and Civil Engineering, Beijing University of Technology, Beijing; 100124, China

Reprint Author's Address:

  • [wang, guang-yong]china academy of building research, beijing; 100013, china

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Source :

Engineering Mechanics

ISSN: 1000-4750

Year: 2016

Issue: 12

Volume: 33

Page: 196-205

Cited Count:

WoS CC Cited Count: 0

SCOPUS Cited Count:

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 6

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