developing an expeditious protocol for a simplified assessment of the seismic risk in seismic zones

This thesis explores how we can better understand and assess earthquake risks in some of Italy’s most seismically active regions. The focus is on evaluating how vulnerable buildings are to earthquakes by developing empirical fragility curves for typical residential structures focusing on reinforced concrete and masonry buildings. These curves are based on extensive post-earthquake damage data collected from events between 1976 and 2012, sourced from the Da.D.O. platform, which offers detailed records on building locations, construction types, and the extent of observed damage. To ensure consistency and quality, the research uses the Rosti framework to refine the fragility curves, for reviewing and validating the input data. Municipalities with incomplete surveys were excluded, leaving the Irpinia 1980 and L’Aquila 2009 earthquake datasets as the most complete and reliable case studies. The modeling process links Peak Ground Acceleration (PGA) values taken (from Da.D.O. shakemaps) to each building’s location and damage report. Damage levels are based on the EMS-98 classification system, which outlines six levels of structural damage. These levels are further adapted to distinguish between structural elements and infill wall damage, allowing for a more accurate picture of building performance during earthquakes. A key innovation in this thesis is the shift from using traditional lognormal distributions to the Generalized Extreme Value (GEV) distribution for fragility modeling, aiming to produce more conservative damage predictions. This change, implemented through custom Python tools, leads to more neat, accurate, and realistic predictions of how buildings are likely to respond to seismic events. The result is a set of redefined fragility curves that can estimate the probability of damage to buildings based on their design level, building height, and the ground motion intensity they experience. These predictive models are not only valuable for seismic design and planning but also offer practical benefits for the insurance industry, allowing for more informed risk assessments and resilience planning.