Sara Mozzon, Marco Donà, Michol Rampado, and Francesca da Porto
i PhD candidate, Department ICEA, University of Padova, Padova, Italy, sara.mozzon@unipd.it
ii RTDb, Department of Geosciences, University of Padova, Padova, Italy, marco.dona.1@unipd.it
iii PhD student, Department of Geosciences, University of Padova, Padova, Italy, michol.rampado@phd.unipd.it
iv Full Professor, Department of Geosciences, University of Padova, Padova, Italy, francesca.daporto@unipd.it
ABSTRACT
The built environment, particularly buildings, is susceptible to both structural and economic damage caused by a wide range of catastrophic events, including earthquakes, floods, landslides, debris flows, hurricanes, and tsunamis. In recent decades, the intensity and frequency of some of these natural hazards have increased due to ongoing climate change. Consequently, there is a growing need to investigate the effects of multiple interacting hazards and to adopt a multi-risk perspective. However, to date, the various metrics used in risk assessment for individual hazards are generally not comparable. Therefore, as a first step toward a comprehensive multi-risk evaluation, a multilayer assessment framework integrating different risks represents a significant contribution. Italy is among the countries most affected by natural disasters, highlighting the importance of multidisciplinary approaches for developing multi-vulnerability models that estimate the impacts of such events on the built environment. The predominant structural types of residential buildings in Italy include unreinforced masonry and reinforced concrete, mainly in the form of frames with brick infill. To address this, an analytical model was developed to assess the out-of-plane response of masonry elements such as load-bearing walls and infill panels. The model simulates a dual arching mechanism within the wall thickness using an incremental procedure with out-of-plane displacement control. This model was then integrated into a Monte Carlo simulation, allowing for variability in both the geometric and mechanical properties of walls, which were previously classified into different categories. Finally, a surrogate vulnerability model was derived from the Monte Carlo results.
KEYWORDS: Climate change impact, masonry wall, Monte Carlo analysis, surrogate vulnerability models.
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