Partitioned seismic vulnerability assessment of hyperbolic cooling tower under multi-dimensional earthquakes
CSTR:
Author:
Affiliation:

(School of Civil Engineering, Beijing Jiaotong University, Beijing 100044, China)

Clc Number:

TU279.7+41

Fund Project:

  • Article
  • |
  • Figures
  • |
  • Metrics
  • |
  • Reference
  • |
  • Related
  • |
  • Cited by
  • |
  • Materials
  • |
  • Comments
    Abstract:

    To explore the vulnerability of different part of a reinforced concrete cooling tower in service, numerical simulation analysis was carried out. The software ABAQUS was selected to establish analysis model. According to the field conditions where the structure locates in, a range of reasonable ground motion records were selected and then incremental dynamic analysis was conducted. Material strain and peak ground acceleration were selected as engineering demand and intensity measure parameters, respectively. The structure was divided into 13 regions in the height direction, and the damage states of the structure were divided into five levels. Unidirectional, bidirectional horizontal and three-dimensional seismic action were respectively exerted to the bottom of the structure, the regression analysis on the structure response was performed. The probabilistic seismic demand model of the structure was established, and the partitioned vulnerability curves of different parts were obtained. The analysis results show that: the damage probability of the upper tower is relatively small and the herringbone pillars' damage probability is significantly higher than the other parts of the structure. The herringbone pillars at the bottom are the most injury-prone part, which can be reinforced according to the actual needs, and the seismic performance of the upper tower is excellent.

    Reference
    Related
    Cited by
Get Citation
Related Videos

Share
Article Metrics
  • Abstract:
  • PDF:
  • HTML:
  • Cited by:
History
  • Received:April 01,2016
  • Revised:
  • Adopted:
  • Online: May 16,2017
  • Published:
Article QR Code