The identification of the areas with high seismic risk for industrial buildings is of paramount importance for decision-makers to implement risk reduction policies. In this context, this study aims at performing a low-LOD (Level of Detail) code-driven identification of areas in Italy where industrial buildings face high seismic risk. Firstly, the hazard, vulnerability, and exposure models are introduced. Then, such input data are validated by comparing the predictions of the proposed framework with the observational data obtained after the Emilia-Romagna earthquakes of 2012. The validated framework is used to predict the conditional (to a certain return period) and unconditional risk in terms of elements-at-risk and economic losses. The unconditional risk in terms of economic losses expressed in terms of Expected Annual Losses (EAL) is used to rank areas in Italy in terms of seismic risk for industrial buildings. As expected, the area hit by the Emilia-Romagna earthquakes in 2012 is included among those with the highest seismic risk, indicating the predictability of large damage occurred on industrial buildings during the seismic event. Finally, some conclusions are drawn about the implications for future policies and studies for seismic risk reduction of industrial buildings in Italy.

Demartino, C., Monti, G. (2020). Low-LOD code-driven identification of the high seismic risk areas for industrial buildings in Italy. BULLETIN OF EARTHQUAKE ENGINEERING, 18(9), 4421-4452 [10.1007/s10518-020-00867-3].

Low-LOD code-driven identification of the high seismic risk areas for industrial buildings in Italy

Cristoforo Demartino;Giorgio Monti
2020-01-01

Abstract

The identification of the areas with high seismic risk for industrial buildings is of paramount importance for decision-makers to implement risk reduction policies. In this context, this study aims at performing a low-LOD (Level of Detail) code-driven identification of areas in Italy where industrial buildings face high seismic risk. Firstly, the hazard, vulnerability, and exposure models are introduced. Then, such input data are validated by comparing the predictions of the proposed framework with the observational data obtained after the Emilia-Romagna earthquakes of 2012. The validated framework is used to predict the conditional (to a certain return period) and unconditional risk in terms of elements-at-risk and economic losses. The unconditional risk in terms of economic losses expressed in terms of Expected Annual Losses (EAL) is used to rank areas in Italy in terms of seismic risk for industrial buildings. As expected, the area hit by the Emilia-Romagna earthquakes in 2012 is included among those with the highest seismic risk, indicating the predictability of large damage occurred on industrial buildings during the seismic event. Finally, some conclusions are drawn about the implications for future policies and studies for seismic risk reduction of industrial buildings in Italy.
Demartino, C., Monti, G. (2020). Low-LOD code-driven identification of the high seismic risk areas for industrial buildings in Italy. BULLETIN OF EARTHQUAKE ENGINEERING, 18(9), 4421-4452 [10.1007/s10518-020-00867-3].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11590/423589
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