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Investigating Resiliency of Transportation Network Under Targeted and Potential Climate Change Disruptions

Date Issued
December 1, 2024
Author(s)
Rahimitouranposhti, Maedeh
Advisor(s)
Xueping Li
Additional Advisor(s)
Hongyu Zheng, Bharat Sharma
Abstract

for the continuity and reliability of global logistics. These systems are vulnerable to various disruptions, including natural disasters and technical failures. Despite significant research on freight transportation resilience, investigating the robustness of the system after targeted and climate-change driven disruption remains a crucial challenge. Drawing on network science methodologies, this study models the interdependencies within the rail and water transport networks and simulates different disruption scenarios to evaluate system responses. We use the data from the US Department of Energy Volpe Center for network topology and tonnage projections. The proposed framework includes a theoretical risk of infrastructure failure and disruption due to climate change using the Earth System Model output. The findings highlight the importance of robustness measures, resilience planning and quantifying the potential loss of freight carrying capacity of the disruption. We show that the disruptions of a few nodes could have a larger impact on the total tonnage of freight transport than on network topology. For example, the removal of targeted 20 nodes can bring the total tonnage carrying capacity to 30% with about 75% of the rail freight network intact. This research advances the theoretical understanding of transportation resilience and provides practical applications for infrastructure managers and policymakers. By implementing these strategies, stakeholders and policymakers can better prepare for and respond to unexpected disruptions, ensuring sustained operational efficiency in the transportation networks.

Subjects

Transportation Resili...

Freight Transport Sys...

Climate Change Disrup...

Targeted Disruptions

Robustness Analysis

Disciplines
Industrial Engineering
Transportation Engineering
Degree
Master of Science
Major
Industrial Engineering
File(s)
Thumbnail Image
Name

thesis_third_MR.pdf

Size

2.42 MB

Format

Adobe PDF

Checksum (MD5)

0bfc6536855305e02cea744647cc4b00

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