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http://dx.doi.org/10.12989/sem.2016.60.6.953

Statistical evaluation of drift demands of rc frames using code-compatible real ground motion record sets  

Kayhan, Ali Haydar (Department of Civil Engineering, Pamukkale University)
Demira, Ahmet (Department of Civil Engineering, Pamukkale University)
Publication Information
Structural Engineering and Mechanics / v.60, no.6, 2016 , pp. 953-977 More about this Journal
Abstract
Modern performance-based design methods require ways to determine the factual behavior of structures subjected to earthquakes. Drift ratio demands are important measures of structural and/or nonstructural damage of the structures in performance-based design. In this study, global drift ratio and interstory drift ratio demands, obtained by nonlinear time history analysis of three generic RC frames using code-compatible ground motion record sets, are statistically evaluated. Several ground motion record sets compatible with elastic design spectra defined for the local soil classes in Turkish Earthquake Code are used for the analyses. Variation of the drift ratio demands obtained from ground motion records in the sets and difference between the mean of drift ratio demands calculated for ground motion sets are evaluated. The results of the study indicate that i) variation of maximum drift ratio demands in the sets were high; ii) different drift ratio demands are calculated using different ground motion record sets although they are compatible with the same design spectra; iii) the effect of variability due to random causes on the total variability of drift ratio demands is much larger than the effect of variability due to differences between the mean of ground motion record sets; iv) global and interstory drift ratio demands obtained for different ground motion record sets can be accepted as simply random samples of the same population at %95 confidence level. The results are valid for all the generic frames and local soil classes considered in this study.
Keywords
drift ratio demands; ground motion record sets; nonlinear time history; statistical evaluation;
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