Identifying Topological Credentials of Physical Infrastructure Components to Enhance Transportation Network Resilience: Case of Florida Bridges
Publication: Journal of Transportation Engineering, Part A: Systems
Volume 148, Issue 9
Abstract
Physical infrastructure systems contribute to human civilization significantly and play a key role in the smooth operation of society. However, such systems may experience loss of functionality because of external shocks, i.e., human-made or natural hazards. To enhance the resiliency of the infrastructure systems, network positions or credentials of infrastructure components (e.g., roads, bridges) based on their topology or connectivity need to be assessed. The empirical literature does not provide specific guidance how such topological credentials may contribute to system resilience, i.e., reducing overall adverse impacts as well as recovering from loss of performance. This study emphasized a coordinated and extensive network of experiments at different geographic scales by applying complex network principles to explore the resiliency of Florida road networks. Geographic modeling was used along with Florida road (with bridges) network data to perform network experiments and prioritize certain bridges based on their network credentials. In particular, the study established a systematic approach to rank the topological credentials of bridges based on the connectivity and attributes (i.e., weights) of road networks. Such credentials change significantly when different weights (i.e., vehicular traffic) are introduced to the network topology at different geographic scales. The practical implications for transportation network resilience as well as the scaling effects are examined by quantifying resilience in terms of average network travel time and developing recovery schemes of bridges for a sample road network. The study developed a credible methodology that would benefit states, municipalities, and other transportation authorities to prioritize risk-based recovery strategies.
Practical Applications
This research presents a methodology that can rank the relative importance of bridges in a road network based on their position in the network. Such topological credentials of bridges may change at different geographic scales (i.e., city or county or state) when different network metrics (i.e., centrality) are considered and/or different attributes are introduced as weights (i.e., traffic volume) to network connectivity or topology. The relative importance of different bridges would allow bridge engineers, maintenance personnel, and other practitioners to decide on which bridge should be inspected, maintained, or constructed first based on the position of the bridges in a network setting. Different transportation agencies engage in solving unprecedented problems observed on local roads or bridges. This study provides novel insights on how to go beyond the local context and incorporate a broader network perspective. Bridges are typically inspected every 2 years for regular maintenance purposes. Because of time and budget constraints, inspection of all the bridges may not be possible often in a timely manner. As a result, bridges that would carry more importance in terms of traffic, construction, or other impacts should be given priority. By having a rank of bridges, activities on bridges can be done more systematically.
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Data Availability Statement
Some or all data, models, or code that support the findings of this study are available from the corresponding author upon reasonable request.
Acknowledgments
The authors are grateful to the US Department of Transportation and the Accelerated Bridge Construction University Transportation Center (ABC-UTC) for supporting the research presented in this study. Moreover, the authors greatly appreciate the constructive comments provided by the reviewers, which significantly improved the quality of the research. However, the authors are solely responsible for the findings presented in this study.
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Received: Jun 16, 2021
Accepted: Apr 11, 2022
Published online: Jun 20, 2022
Published in print: Sep 1, 2022
Discussion open until: Nov 20, 2022
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