GNGTS 2019 - Atti del 38° Convegno Nazionale

362 GNGTS 2019 S essione 2.2 and for seismic loads post-1981), are used to define two vulnerability classes, C2 and D, of decreasing vulnerability. Fragility curves for vulnerability classes C2 and D, further subdivid- ed based on the building height (i.e. low-rise: 1-2 stories, mid-rise: 3-4 stories, high-rise: >4 stories), are then obtained by averaging typological fragility functions, using as weights their frequency of occurrence, evaluated at the national scale through census data. The presented empirical model was used, together with others, for assessing seismic risk in Italy (Rosti et al. 2019, Dolce et al. 2019b). Acknowledgments. This work was carried out under the financial support of the Italian Department of Civil Protection within the ReLUIS-DPC 2014-2018 project. This support is gratefully acknowledged. References Del Gaudio C., De Martino G., Di Ludovico M., Ricci P. and Verderame G.M.; 2017: Empirical fragility curves from damage data on RC buildings after the 2009 L’Aquila earthquake. Bull Earthq Eng, 15 , 1425-1450. Dolce M., Speranza E., Giordano F., Borzi B., Bocchi F., Conte C., Di Meo A., Faravelli M. and Pascale V.; 2019a: Observed damage database of past Italian earthquakes: the Da.DO WebGIS . B Geofis Teor Appl, 60(2), 141-164. Dolce M., Borzi B., Da Porto F., Faravelli M., Lagomarsino S., Magenes G., Moroni C., Penna A., Prota A., Speranza E., Zuccaro G. and Verderame G.M.; 2019b: Seismic risk maps for the Italian territory . XVIII National Conference in Earthquake Engineering, September15-19, Ascoli Piceno, Italy. Michelini A., Faenza L., Lauciani V. and Malagnini L.; 2008: Shakemap implementation in Italy . Seismol Res Lett, 79, 688-697. Rosti A., Del Gaudio C., Di Ludovico M., Magenes G., PennaA., Polese M., ProtaA., Ricci P., Rota M. and Verderame G.M.; 2019: Use of empirical fragility curves for assessing seismic risk at the national scale . XVIII National Conference in Earthquake Engineering, September 15-19, Ascoli Piceno, Italy. Rota M., Penna A. and Strobbia C.L.; 2008: Processing Italian damage data to derive typological fragility curves . Soil Dyn Earthq Eng, 28 (10): 933-947. ASSESSMENT OF HIGH SEISMIC RISK AREAS FOR INDUSTRIAL BUILDINGS IN ITALY: PRELIMINARY RESULTS C. Demartino 1 , G. Monti 2 1 Zhejiang University – Univ. of Illinois at Urbana Champaign Institute, Zhejiang University, Haining, China 2 Department of Structural Engineering and Geotechnics, Sapienza Univ. of Rome, Rome, Italy Introduction. Risk consists of the combined consequences of an event or a hazard and its associated occurrence probability (ISO 31010, 2009). Methodologies of risk assessment and databases used for risk computations can be different at different spatial scales (Frolova et al. , 2017), e.g. , country-wise, regional and urban. Complexity issues involved in simulation models application and input data used in all steps of earthquakes loss assessment should be accounted for in the framework. In particular, depending on the spatial scale, different Level Of Detail (LOD) simulation frameworks should be employed to take proper consideration of the diversity of structural types, data availability and simulation scenarios to correctly perform a territorial seismic risk assessment. As suggested by Xiong et al. (2018), a LOD 0 risk analysis ( i.e. , lowest LOD analysis), only requires defining seismic hazard through a scalar intensity measure, vulnerability through fragility curves and exposure through structural type information. Finally, for LOD 0, the visualization can be performed in a GIS environment. Several attempts have been made to assess the seismic risk at the national scale in Italy, mainly with reference to residential buildings and infrastructure systems, e.g. , Crowley et al. (2009). No previous study has investigated the seismic risk assessment of industrial buildings at the national scale in Italy. In this context, this is the first study to undertake a low-LOD