Probabilistic fragility assessment method of structural intervention schemes

Seong Hoon Jeong, Amr S. Elnashai

Research output: Contribution to journalArticlepeer-review

4 Scopus citations

Abstract

It is desirable to use probabilistic performance targets for decision-making as it relates to intervention methods, because of high uncertainties of structure responses under earthquake loadings. This is based on the probabilistic performance assessment of structures with various retrofit options. Extensive computer simulations to account for the randomness in both input motion and response characteristics have been a serious obstacle to the adoption of the probabilistic performance assessment in the decision of seismic intervention schemes. This study presents an approach whereby a fragility assessment result with known reliability is derived based on the fundamental response quantities of stiffness, strength and ductility. An exact solution for a generalised single-degree-of-freedom system is employed to construct a response database of maximum responses. Once the fundamental response quantities of a wide range of structural systems are defined, the fragility assessment for various limit states can be constructed without recourse to further simulation. By virtue of its instantaneous nature, the proposed method is especially useful for practical application of the analytical fragility assessment that includes the planning of seismic rehabilitation and regional earthquake mitigation, where fast estimation of probabilities of reaching damage states for a large number of structural configurations and different mitigation measures is required. For cases of selection between different retrofitting options, the proposed approach gives rapid estimates of probabilities of various damage levels inflicted on the structures under consideration, given only the stiffness, strength and ductility for each alternative retrofitting scheme. The presented fragility contour and constant fragility spectra enable the engineer to use visualised data sets to practically and conveniently investigate the probabilistic performance of every retrofit option.

Original languageEnglish (US)
Pages (from-to)928-938
Number of pages11
JournalStructure and Infrastructure Engineering
Volume8
Issue number10
DOIs
StatePublished - Oct 2012

All Science Journal Classification (ASJC) codes

  • Civil and Structural Engineering
  • Building and Construction
  • Safety, Risk, Reliability and Quality
  • Geotechnical Engineering and Engineering Geology
  • Ocean Engineering
  • Mechanical Engineering

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