Influence of the number of dynamic analyses on the accuracy of structural response estimates

Pierre Gehl, John Douglas, Darius M. Seyedi

Research output: Contribution to journalArticle

27 Citations (Scopus)
97 Downloads (Pure)

Abstract

Nonlinear dynamic analysis is of ten used to develop fragility curves within the framework of seismic risk assessment and performance-based earthquake engineering. In the present article, fragility curves are derived from randomly generated clouds of structural response results by using least squares and sum-of -squares regression, and maximum likelihood estimation. Different statistical measures are used to estimate the quality of fragility functions derived by considering varying numbers of ground motions. Graphs are proposed that can be used as guidance regarding the number of calculations required for these three approaches. The effectiveness of the results is demonstrated by their application to a structural model. The results show that the least-squares method for deriving fragility functions converges much faster than the maximum likelihood and sumof -squares approaches. With the least-squares approach, a few dozen records might be sufficient to obtain satisfactory estimates, whereas using the maximum likelihood approach may require several times more calculations to attain the same accuracy.

Original languageEnglish
Pages (from-to)97-113
Number of pages17
JournalEarthquake Spectra
Volume31
Issue number1
DOIs
Publication statusPublished - 1 Feb 2015

Keywords

  • nonlinear dynamic analysis
  • fragility curves
  • risk assessment
  • statistical measures

Fingerprint Dive into the research topics of 'Influence of the number of dynamic analyses on the accuracy of structural response estimates'. Together they form a unique fingerprint.

  • Cite this