Probabilistic seismic assessment of a high-rise URM building

According to the Sendai Framework for Disaster Risk Reduction (2015–2030), disasters have demonstrated that recovery, rehabilitation and reconstruction phase, which needs be prepared ahead of a disaster, is critical opportunity “Build Back Better”, integrating disaster risk reduction into development measures. In this respect, significant number structures, constitute several European urban nuclei, belong old constructive typologies, were designed built without any consideration seismic hazard. One most used typologies exhibiting shortcoming unreinforced masonry (URM). Therefore, an important step towards increasing resilience cities deeply understand behavior frequent typology. order do so properly, detailed probabilistic nonlinear building models should developed. However, including uncertainties associated with typology challenging due heterogeneity different manufacturing techniques, executed under primitive industrial standards, construction are dependent on regional uses criteria in pre-code scenario. The object research twofold. First, quantification related mechanical properties material conducted. Then, influence variability performance representative model Eixample district Barcelona, Spain, analysed. This represents 72% stock average age 90 years, means practice, at time, was only regulated by early council guidelines considered rules. Specifically, approach illustrated case study performed existing seven-story (high-rise) URM. A numerical structure has been developed randomized taking account properties. Accordingly, 1000 generated analysed considering as input sets random variables. compressive strength, Young modulus, shear modulus strength chosen modelled encompass uncertainties. response each variant (i.e. selected set properties) obtained through simplified non-linear static procedure aiming compare categorize building. Results presented terms correlations between damage parameters analysis carried out shows generates URM buildings, leading over or underestimate expected when compared results based approaches not consider nature problem.