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A stochastic computational framework for the joint transportation network fragility analysis and traffic flow distribution under extreme events

Engineering and Technology

A stochastic computational framework for the joint transportation network fragility analysis and traffic flow distribution under extreme events

P. Bocchini and D. M. Frangopol

Discover groundbreaking research by Paolo Bocchini and Dan M. Frangopol that integrates structural fragility analysis with network flow and random field theory to evaluate bridge damage during extreme events. This innovative framework reveals how damage correlation influences transportation network performance, presenting two compelling numerical examples that shine a light on the complexities of our infrastructure.

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Playback language: English
Abstract
This paper presents a novel technique that integrates structural fragility analysis, network flow analysis, and random field theory to assess the correlation among bridge damage levels in a transportation network during extreme events and estimate the sensitivity of network performance to correlation distance. A stochastic computational framework combines individual bridge damage levels with network performance evaluation. Random field theory simulates bridge damage levels, allowing direct control of correlation for parametric analysis. Two numerical examples (bridges in parallel and series configurations) demonstrate that damage correlation significantly impacts network performance indicators.
Publisher
Probabilistic Engineering Mechanics
Published On
Dec 09, 2010
Authors
Paolo Bocchini, Dan M. Frangopol
Tags
structural fragility analysis
network flow analysis
random field theory
bridge damage levels
network performance
extreme events
parametric analysis

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