Abstract

A hybrid seismic fragility model for territorial-scale seismic vulnerability assessment of masonry buildings is developed and presented in this paper. The method combines expert-judgment and mechanical approaches to derive typological fragility curves for Italian residential masonry building stock. The first classifies Italian masonry buildings in five different typological classes as function of age of construction, structural typology, and seismic behaviour and damaging of buildings observed following the most severe earthquakes occurred in Italy. The second, based on numerical analyses results conducted on building prototypes, provides all the parameters necessary for developing fragility functions. Peak-Ground Acceleration (PGA) at Ultimate Limit State attainable by each building’s class has been chosen as an Intensity Measure to represent fragility curves: three types of curve have been developed, each referred to mean, maximum and minimum value of PGAs defined for each building class. To represent the expected damage scenario for increasing earthquake intensities, a correlation between PGAs and Mercalli-Cancani-Sieber macroseismic intensity scale has been used and the corresponding fragility curves developed. Results show that the proposed building’s classes are representative of the Italian masonry building stock and that fragility curves are effective for predicting both seismic vulnerability and expected damage scenarios for seismic-prone areas. Finally, the fragility curves have been compared with empirical curves obtained through a macroseismic approach on Italian masonry buildings available in literature, underlining the differences between the methods.

Highlights

  • Due to its particular position between the African and Euro-Asiatic plate, Italy is recognized as one of the countries of the Mediterranean basin affected by high-frequency and high-intensity earthquakes

  • In 2006, Kappos et al (2006) presented fragility curves for masonry and Reinforced Concrete (R.C.) buildings in Greece based on a hybrid method; the method combines statistical data derived from earthquake-damaged constructions with the results of nonlinear static or dynamic analyses conducted on a large number of building types

  • A mixed mechanics-based fragility model for Italian unreinforced masonry (URM) building was proposed by Donà et al (2020), based on information derived from the National Institute of Statistics (ISTAT)in combination with expert-judgment observational procedure

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Summary

Introduction

Due to its particular position between the African and Euro-Asiatic plate, Italy is recognized as one of the countries of the Mediterranean basin affected by high-frequency and high-intensity earthquakes. In 2006, Kappos et al (2006) presented fragility curves for masonry and Reinforced Concrete (R.C.) buildings in Greece based on a hybrid method; the method combines statistical data derived from earthquake-damaged constructions with the results of nonlinear static or dynamic analyses conducted on a large number of building types. A mixed mechanics-based fragility model for Italian unreinforced masonry (URM) building was proposed by Donà et al (2020), based on information derived from the National Institute of Statistics (ISTAT)in combination with expert-judgment observational procedure. It divided residential URM buildings in ten classes by age of construction and number of storeys. The software Vulnus 4.0. processes information on buildings features, material strength, types of floors, etc., and calculates maximum bearable Peak-Ground Acceleration (PGA) used to derive fragility for the defined classes (Valluzzi 2009)

Research significance
Methodology
Expert‐judgment contribution
Mechanical contribution
Evolution of the seismic codes in Italy
Structural‐typological classification of URM buildings
Ancient buildings
Improved‐ancient buildings
Modern buildings
Semi‐modern buildings
No code‐conforming buildings
Method for deriving the fragility curves
Dataset for derivation of fragility curves
Fragility function
Fragility curves in terms of PGA
Correlation with Mercalli‐Cancani‐Sieberg scale
Comparison with EMS98
Findings
Conclusions

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