A practice-oriented approach for the assessment of brittle failures in existing reinforced concrete elements

A practice-oriented approach was used to assess shear failures in existing reinforced concrete (RC) elements. A simple tool, in form of non-dimensional domains, is obtained considering the capacity models suggested by European and Italian codes. The reliability of failure domains depend strictly on the reliability of the shear capacity model employed; thus, a critical review of code and literature analytical formulations was also carried out. Sezen and Moehle’s experimental database was, then, used to compare the different shear capacity models considered. The code and literature review of shear capacity models emphasizes differences and affinities of the analytical approaches followed in different countries. The domains carried out can be used as a practical instrument aimed at checking shear–flexure hierarchy in existing RC elements and contextualized in the framework of preliminary assessment given the character of input information required. Preliminary applications of the domains are also provided, and emphasize the effectiveness of the new tool for detailed and large scale assessment of existing RC structures

Engineering seismic demand in the 2012 Emilia sequence: preliminary analysis and model compatibility assessment

<p>The Emilia 2012 sequence featured seven events of moment magnitude (M) &gt;5, five of which occurred between May 20 and May 29, 2012. These earthquakes were structurally damaging over a wide area. The damage included partial or total collapse of industrial precast reinforced-concrete structures, historical masonry, and mainly nonstructural damage to reinforced-concrete buildings; see Section 8 (Data and sharing resources) for damage report repository. These structural typologies are, in principle, sensitive to different ground-motion intensity measures. For example, loss of support requires significant displacement demand at relatively long periods, while infilling damage is due to the ground-motion amplitude at higher frequencies, and masonry structures are comparatively more sensitive to the cyclic content of ground shaking. Moreover, because events were concentrated in time and space, it can be argued that the cumulative effects of the sequence contributed to the damage. As the current seismic code [C.S.LL.PP. 2008] uses a seismic hazard map [Stucchi et al. 2011] to determine the seismic actions for structural design, when a strong earthquake occurs, probabilistic estimates are understandably questioned for their consistency with respect to the observed ground motion. While it is easy to show that in terms of frequency of exceedance of intensity measures, the hazard can hardly be validated via the records of a single earthquake [e.g., Iervolino 2012], on the other hand, it can certainly be verified whether the observations are compatible or atypical with respect to what is predicted by the tools used in best-practice hazard studies. These issues mostly motivated the preliminary analysis briefly presented in this report; i.e., to investigate the engineering seismic demand (peak and cyclic) and to compare this with the prediction models. Both elastic and inelastic demands were considered. Indeed, the inelastic demands are more important from the structural engineering point of view. […]</p

Analytical versus observational fragilities::the case of Pettino (L’Aquila) damage data database

A damage data database of 131 reinforced concrete (RC) buildings, collected after 2009 L’Aquila (Italy) earthquake, is employed for the evaluation of observational fragility curves. The specific interpretation of damage data allowed carrying out fragility curves for slight, moderate, and heavy damage, (i.e., DS1, DS2, and DS3), defined according to EMS 98 macroseismic scale. Observational fragility curves are then employed for the calibration of FAST analytical methodology. FAST method is a spectral based approach, meant for the estimate of fragility curves of infilled RC buildings up to DS3, evaluated, again, according to EMS98. Kullback–Leibler divergence is employed to check the matching between analytical and observational fragilities. FAST input variables can vary in quite large ranges and the calibration provides a valuable suggestion for the application of the method in other cases in which field damage data are not available. Results showed that optimizing values, for the input variables calibrated, are in good agreement with typical values assumed in literature. Analytical results showed a very satisfactory agreement with observational data for DS2 and DS3, while systematical underestimation was found for the case of DS1

Spectral shape-based assessment of SDOF nonlinear response to real, adjusted and artificial accelerograms

The simple study discussed in this paper compared different procedures to obtain sets of spectral matching accelerograms for nonlinear dynamic analysis of structures in terms of inelastic seismic response. Six classes of records were considered: original (unscaled) real records, real records moderately linearly scaled, real records significantly linearly scaled, real records adjusted by wavelets, and artificial accelerograms generated by two different procedures. The study is spectral shape-based; that is, all the considered sets of records, generated or selected, match individually (artificial and adjusted) or on average (real records) the same design spectrum for a case-study site in Italy. This is because spectral compatibility is the main criterion required for seismic input by international codes. Three kinds of single degree of freedom (SDOF) system, non-degrading and non-evolutionary, non-degrading and evolutionary, and both degrading and evolutionary, were used to evaluate the nonlinear response to the compared records. Demand spectra in term of peak and cyclic responses were derived for different strength reduction factors. Results of the analysis show that artificial or adjusted accelerograms may underestimate, in some cases, and at high nonlinearity levels, the displacement response, if compared to original real records, which are considered as a benchmark herein. However, this conclusion does not seem to be statistically significant. Conversely, if the cyclic response is considered, artificial record classes show a significant overestimation of the demand, which does not show up for wavelet-adjusted records. The two classes of linearly scaled records do not show systematic bias with respect to those unscaled for both types of response considered, which seems to confirm that amplitude scaling is a legitimate practice