Abstract
The majority of bridge infrastructures in Italy were built in the 1960s and ‘70s without any specific seismic provision being made. As a consequence, it is expected that these bridges would be highly vulnerable if subjected to a significant seismic event. Given this background, it is natural that the rapid and accurate assessment of economic losses incurred to the bridge infrastructure as a result of such an event could play a crucial role in emergency management in the immediate aftermath of an earthquake. Focusing on the infrastructure system of highway bridges in the Campania region in Italy, this paper demonstrates how both state-of-the-art methodologies in portfolio loss assessment and the available data can be used to assess the probability distribution of the repair costs incurred due to the 1980 Irpinia earthquake. Formulating a probabilistic loss assessment for a portfolio of bridges as a standard Monte Carlo simulation problem helps to resolve the spatial risk integral efficiently. One of the specific features of this case study is the use of statistical methods for updating models of: (a) ground motion predictions, (b) vulnerability/fragility and (c) exposure/costs, based on the available data. It has been observed that alternative hypotheses concerning the ground motion correlation structure can significantly affect the distribution of direct economic losses. Furthermore, updating the ground motion prediction based on available recordings may significantly reduce the dispersion in the estimate of the direct economic losses.
Original language | English |
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Pages (from-to) | 699-719 |
Number of pages | 21 |
Journal | Bulletin of Earthquake Engineering |
Volume | 14 |
Issue number | 3 |
DOIs | |
Publication status | Published - 1 Mar 2016 |
Keywords
- Bayesian updating
- Bridge vulnerability
- Loss assessment
- Spatial correlation of ground motion
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Dr Raffaele De Risi
- Department of Civil Engineering - Senior Lecturer
- Earthquake and Geotechnical Engineering
- Cabot Institute for the Environment
Person: Academic , Member