Abstract

The current generation of seismic design codes is based on a linear elastic force-based approach that includes the nonlinear response of the structure implicitly through a response modification factor (named reduction factor R in American codes or behaviour factor q in European codes). However, the use of a prescribed behaviour factor that is constant for a given structural system may fail in providing structures with the same risk level. In this paper, the behaviour factor of reinforced concrete frame structures is estimated by means of nonlinear static (pushover) and nonlinear incremental dynamic analyses. For this purpose, regular reinforced concrete frames of three, five, seven, and nine storeys designed for high ductility class according to the European and Italian seismic codes are investigated, and realistic input ground motions are selected based on the design spectra. Verified analysis tools and refined structural models are used for nonlinear analysis. Overstrength, redundancy, and ductility response modification factors are estimated, and the effects of some parameters influencing the behaviour factor, including the number of bays and the number of storeys, are evaluated. The results are finally compared with those obtained from a previous paper for steel moment-resisting frames with the same geometry. According to the analysis results, the behaviour factors in the case of pushover analysis are significantly higher than those obtained in the case of nonlinear response history analysis. Thus, according to the pushover analysis, the behaviour factor provided by European and Italian standards seems highly conservative. On the contrary, the more refined nonlinear dynamic analysis shows that the code-prescribed value may be slightly nonconservative for middle-high-rise frame structures due to unfavourable premature collapse mechanisms based on column plastic hinging at the first storey. Thus, some modifications are desirable in local ductility criteria and/or structural detailing of high ductility columns to implicitly ensure that the recommended value of the behaviour factor is conservative.

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