Abstract
Despite the increasing interest in progressive collapse-resistant design and analysis of reinforced concrete buildings that was triggered by accidental and man-made extreme events occurred over the last couple of decades, only few studies, especially numerical ones, have been carried out so far on the role of masonry infill walls. Just like in the case of first earthquake engineering applications, infills are usually considered as non-structural or architectural elements and, hence, their resistance is commonly ignored, given also that current design guidelines do not provide specific indications concerning this point. Although such an assumption leads to an ease in both design and assessment of structures, it may also give rise to misleading and overly conservative results, as the presence of masonry infills may result in extra vertical resistance.Thus, this paper presents the outcomes of a large number of progressive collapse simulations aimed at quantifying the effects of infill walls on the vertical load-carrying capacity of reinforced concrete frames for different levels of damage, thus allowing evaluation of the interaction between these structural elements and the surrounding frame for different regimes/stages of the response. To this end, a macro-model concept was first developed and its effectiveness was then evaluated by comparing numerical results to experimental data from a past test on a one-third scaled planar structure featuring full-height infill walls. After validation, the proposed model was used to predict behavioural changes in the response of infilled reinforced concrete structures as a consequence of parametric variations in the geometry of the selected prototypes. Counterpart bare frames were also analysed in order to present a twofold comparison, in terms of resistance and dissipated energy. Finally, the manuscript describes the results of a further set of analyses, in which uncertainties in the mechanical properties of the masonry infills were modelled and propagated through fibre modelling and pushdown analysis techniques.
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