Modern society’s very existence is tied to the proper and reliable functioning of its Critical Infrastructure (CI) systems. In the seismic risk assessment of an infrastructure, taking into account all the relevant uncertainties affecting the problem is crucial. While both aleatory and epistemic uncertainties affect the estimate of seismic risk to an infrastructure and should be considered, the focus herein is on the latter. After providing an up-to-date literature review about the treatment of and sensitivity to epistemic uncertainty, this paper presents a comprehensive framework for seismic risk assessment of interdependent spatially distributed infrastructure systems that accounts for both aleatory and epistemic uncertainties and provides confidence in the estimate, as well as sensitivity of uncertainty in the output to the components of epistemic uncertainty in the input. The logic tree approach is used for the treatment of epistemic uncertainty and for the sensitivity analysis, whose results are presented through tornado diagrams. Sensitivity is also evaluated by elaborating the logic tree results through weighted ANOVA. The formulation is general and can be applied to risk assessment problems involving not only infrastructural but also structural systems. The presented methodology was implemented into an open-source software, OOFIMS, and applied to a synthetic city composed of buildings and a gas network and subjected to seismic hazard. The gas system’s performance is assessed through a flow-based analysis. The seismic hazard, the vulnerability assessment and the evaluation of the gas system’s operational state are addressed with a simulation-based approach. The presence of two systems (buildings and gas network) proves the capability to handle system interdependencies and highlights that uncertainty in models/parameters related to one system can affect uncertainty in the output related to dependent systems.

Seismic risk of infrastructure systems with treatment of and sensitivity to epistemic uncertainty / Cavalieri, F.; Franchin, P.. - In: INFRASTRUCTURES. - ISSN 2412-3811. - 5:11(2020), pp. 1-22. [10.3390/infrastructures5110103]

Seismic risk of infrastructure systems with treatment of and sensitivity to epistemic uncertainty

Franchin P.
Secondo
2020

Abstract

Modern society’s very existence is tied to the proper and reliable functioning of its Critical Infrastructure (CI) systems. In the seismic risk assessment of an infrastructure, taking into account all the relevant uncertainties affecting the problem is crucial. While both aleatory and epistemic uncertainties affect the estimate of seismic risk to an infrastructure and should be considered, the focus herein is on the latter. After providing an up-to-date literature review about the treatment of and sensitivity to epistemic uncertainty, this paper presents a comprehensive framework for seismic risk assessment of interdependent spatially distributed infrastructure systems that accounts for both aleatory and epistemic uncertainties and provides confidence in the estimate, as well as sensitivity of uncertainty in the output to the components of epistemic uncertainty in the input. The logic tree approach is used for the treatment of epistemic uncertainty and for the sensitivity analysis, whose results are presented through tornado diagrams. Sensitivity is also evaluated by elaborating the logic tree results through weighted ANOVA. The formulation is general and can be applied to risk assessment problems involving not only infrastructural but also structural systems. The presented methodology was implemented into an open-source software, OOFIMS, and applied to a synthetic city composed of buildings and a gas network and subjected to seismic hazard. The gas system’s performance is assessed through a flow-based analysis. The seismic hazard, the vulnerability assessment and the evaluation of the gas system’s operational state are addressed with a simulation-based approach. The presence of two systems (buildings and gas network) proves the capability to handle system interdependencies and highlights that uncertainty in models/parameters related to one system can affect uncertainty in the output related to dependent systems.
2020
Confidence interval; Flow analysis; Fragility model; Logic tree; Monte Carlo simulation; Parameter correlation; Tornado diagram; Weighted ANOVA
01 Pubblicazione su rivista::01a Articolo in rivista
Seismic risk of infrastructure systems with treatment of and sensitivity to epistemic uncertainty / Cavalieri, F.; Franchin, P.. - In: INFRASTRUCTURES. - ISSN 2412-3811. - 5:11(2020), pp. 1-22. [10.3390/infrastructures5110103]
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/1501304
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