PSI - Issue 78

Carpanese Pietro et al. / Procedia Structural Integrity 78 (2026) 536–543

543

advanced scientific risk models and operational insurance needs, promoting a culture of risk awareness and preparedness in a country with high exposure to catastrophic events. Future developments may include the refinement of PERIL’s AI components, the addition of other hazards and of additional building types with different uses, and the integration of monitoring and remote sensing to achieve dynamic risk analysis. In this way, PERIL will be able to support a broader adoption in the insurance and public risk management sectors. Acknowledgements This work was developed within the Uni-Impresa project “ PERIL ” , co-funded by RiskApp, with valuable support and expertise provided by the specialists of the working groups in PE3 Return and ReLUIS. References DEI Tipografia del Genio Civile, 2023. Prezzi Tipologie Edilizie 2024. Di Ludovico, M., De Martino, G., Prota, A., Manfredi, G., Dolce, M., 2022. Relationships between empirical damage and direct/indirect costs for the assessment of seismic loss scenarios. Bull Earthquake Eng 20, 229–254. https://doi.org/10.1007/s10518 - 021 - 01235 - 5 Dolce, M., Prota, A., Borzi, B., da Porto, F., Lagomarsino, S., Magenes, G., Moroni, C., Penna, A., Polese, M., Speranza, E., Verderame, G.M., Zuccaro, G., 2021. Seismic risk assessment of residential buildings in Italy. Bull Earthquake Eng 19, 2999–3032. https://doi.org/10.1007/s10518 - 020 - 01009 - 5 Dolce, M., Speranza, E., Giordano, F., Borzi, B., Bocchi, F., Conte, C., Di Meo, A., Faravelli, M., Pascale, V., 2019. Observed damage database of past Italian earthquakes: the Da.D.O. WebGIS. Bollettino di Geofisica Teorica ed Applicata 60, 141–164. https://doi.org/10.4430/bgta0254 Donà, M., Carpanese, P., Follador, V., Sbrogiò, L., da Porto, F., 2021. Mechanics - based fragility curves for Italian residential URM buildings. Bull Earthquake Eng 19, 3099–3127. https://doi.org/10.1007/s10518 - 020 - 00928 - 7 Dottori, F., Figueiredo, R., Martina, M.L.V., Molinari, D., Scorzini, A.R., 2016. INSYDE: a synthetic, probabilistic flood damage model based on explicit cost analysis. Nat. Hazards Earth Syst. Sci. 16, 2577–2591. https://doi.org/10.5194/nhess - 16 - 2577 - 2016 European Union, 2009. Directive 2009/138/EC of the European Parliament and of the Council of 25 November 2009 on the taking - up and pursuit of the business of Insurance and Reinsurance (Solvency II). Official Journal of the European Union, L 335, 1–155. FEMA, 2022a. Hazus Inventory Technical Manual. FEMA, 2022b. Hazus Earthquake Model Technical Manual. FEMA, 2022c. Hazus Flood Technical Manual. Galliani, M., Molinari, D., Ballio, F., 2020. Brief Communication: Simple - INSYDE, development of a new tool for flood damage evaluation from an existing synthetic model. Nat. Hazards Earth Syst. Sci. 20, 2937–2941. https://doi.org/10.5194/nhess - 20 - 2937 - 2020 Gurpinar, A., Abali, M., Yucemen, M.S., Yesilcay, Y., 1978. Feasibility of mandatory earthquake insurance in Turkey. Italian Civil Protection Department, 2018. National risk assessment. Overview of the potential major disasters in Italy: seismic, volcanic, tsunami, hydrogeological/hydraulic and extreme weather, droughts and forest fire risks. Italian Ministry of Infrastructures and Transports, 2018. Decreto n.8 2018/01/17. Aggiornamento delle “Norme tecniche per le costruzioni”. (GU n.42 del 20 - 02 - 2018). Italian Ministry of Infrastructures and Transports, 2008. Decreto 2008/01/14. Norme tecniche per le costruzioni. (GU n.29 del 04 - 02 - 2008). Molinari, D., Scorzini, A.R., 2017. On the Influence of Input Data Quality to Flood Damage Estimation: The Performance of the INSYDE Model. Water 9, 688. https://doi.org/10.3390/w9090688 Mori, F., Mendicelli, A., Moscatelli, M., Romagnoli, G., Peronace, E., Naso, G., 2020. A new Vs30 map for Italy based on the seismic microzonation dataset. Engineering Geology 275, 105745. https://doi.org/10.1016/j.enggeo.2020.105745 Perazzini, S., Gnecco, G., Pammolli, F., 2024. A catastrophe model approach for flood risk assessment of Italian municipalities. Ann Oper Res. https://doi.org/10.1007/s10479 - 024 - 06060 - y Pessina, V., Fiorini, E., 2014. A GIS procedure for fast topographic characterization of seismic recording stations. Soil Dynamics and Earthquake Engineering 63, 248–258. https://doi.org/10.1016/j.soildyn.2014.04.002 Rosti, A., Del Gaudio, C., Rota, M., Ricci, Paolo, P., Di Ludovico, M., Penna, A., Verderame, G.M., 2021. Empirical fragility curves for Italian residential RC buildings. Bull Earthquake Eng 19, 3165–3183. https://doi.org/10.1007/s10518 - 020 - 00971 - 4 Sabetta, F., Pugliese, A., 1996. Estimation of response spectra and simulation of nonstationary earthquake ground motions. Bulletin of the Seismological Society of America 86, 337–352. https://doi.org/10.1785/BSSA0860020337 Simonyan, K., Zisserman, A., 2015. Very Deep Convolutional Networks for Large - Scale Image Recognition. https://doi.org/10.48550/arXiv.1409.1556 UNISDR, 2017. Annual Report 2017. Xu, X., Zweifel, P., 2020. A framework for the evaluation of InsurTech. Risk Manage Insurance Review 23, 305–329. https://doi.org/10.1111/rmir.12161 Zuccaro, G., Dolce, M., Perelli, F.L., De Gregorio, D., Speranza, E., 2023. CARTIS: a method for the typological - structural characterization of Italian ordinary buildings in urban areas. Front. Built Environ. 9, 1129176. https://doi.org/10.3389/fbuil.2023.1129176