Colombi, M.

Le mappe di rischio sismico nazionale rappresentano un importante strumento per la sua mitigazione e possono essere utilizzate nella valutazione delle priorità di intervento per la messa in sicurezza degli edifici. La realizzazione di queste mappe è possibile valutando la pericolosità sismica, la vulnerabilità per le diverse classi di edifici presenti sul territorio italiano e l’esposizione. In questo articolo, oltre a presentare le nuove mappe di rischio sismico per l’Italia si vuole analizzare l’influenza del fattore di amplificazione litostratigrafica sui risultati ottenuti, mettendo a confronto le mappe di rischio che sono state sviluppate utilizzando sia i fattori di amplificazione litostratigrafica previsti dall’OPCM n°3274 che quelli previsti dalle NTC08. Inoltre, in modo innovativo rispetto agli studi condotti in Italia negli ultimi 10 anni, vengono considerate curve analitiche di vulnerabilità e valori di pericolosità sismica basati sugli spettri di accelerazione.

National seismic risk maps are an important risk mitigation tool as they can be used for the prioritization of regions within a country where retrofitting of the building stock or other risk mitigation measures should take place. The production of a seismic risk map involves the convolution of seismic hazard data, vulnerability predictions for the building stock and exposure data. The seismic risk maps produced in Italy over the past 10 years are compared in this paper with recent proposals for seismic risk maps based on state-of-the-art seismic hazard data and mechanics-based vulnerability assessment procedures. The aim of the paper is to open the discussion for the way in which future seismic risk maps could be produced, making use of the most up-to-date information in the fields of seismic hazard evaluation and vulnerability assessment.

A risk management framework has recently been developed to assign priorities for the rehabilitation of school buildings in Italy, and to give timescales within which retrofit or demolition must take place. Since it is not practical to carry out a detailed assessment of the 60,000 Italian state and public schools, the framework is a multiple-level procedure which aims to identify the highest-risk buildings based on filters of increasing detail, and reduces the size of the building inventory at each step. The first risk ranking is based on a strength deficit, which measures the difference between the current design forces defined for the building site and an estimation of the level of seismic resistance which was required at the time of design. The second ranking is based on lateral strength calculations that are already available for a large portion of the Italian masonry building stock, and that are obtained from a survey form that is familiar to Italian engineers. Finally, a simplified displacement-based methodology is used to give a more accurate assessment of seismic risk based on a limited amount of geometrical and material data. The final assessment leads to a capacity ratio and a risk rating, which are used within a transparent procedure to assign priorities for seismic intervention, and timescales within which detailed assessment leading to retrofit or demolition must take place. The first step of the methodology has been applied herein to the school building stock within two Regions in Italy and preliminary results are presented.

The concerted effort to collect earthquake damage data in Italy over the past 30 years has led to the development of an extensive database from which vulnerability predictions for the Italian building stock can be derived. A methodology to derive empirical vulnerability curves with the aforementioned data is presented herein and the resulting curves have been directly compared with mechanics-based vulnerability curves. However, it has been found that a valid comparison between the empirical and analytical vulnerability curves is not possible mainly due to a number of shortcomings in the database of surveyed buildings. A detailed discussion of the difficulties in deriving vulnerability curves from the current observed damage database is thus also presented.