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

This research by Paolo Bocchini and Dan M. Frangopol unveils a groundbreaking technique that combines structural fragility analysis with random field theory to explore how bridge damage affects transportation networks during extreme events. It highlights the critical influence of damage correlation on network performance, opening new avenues for analysis.

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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 network performance sensitivity 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 over correlation for parametric analysis. Numerical examples demonstrate that damage correlation significantly impacts network performance, highlighting the importance of considering this correlation in analyses.

Publisher

Probabilistic Engineering Mechanics

Published On

Dec 09, 2010

Authors

Paolo Bocchini, Dan M. Frangopol

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