Climate-resilient railway networks: a resource-aware framework
Abstract Coastal hazards and climate change significantly threaten the resilience of railway systems, increasing stresses on global freight transportation, supply chains and economic stability. When it comes to system resilience, resource availability and allocation have been proven to be leading co...
Saved in:
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2025-08-01
|
| Series: | Communications Engineering |
| Online Access: | https://doi.org/10.1038/s44172-025-00493-4 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1849226184221523968 |
|---|---|
| author | Anibal Tafur Sotirios A. Argyroudis Stergios A. Mitoulis Jamie E. Padgett |
| author_facet | Anibal Tafur Sotirios A. Argyroudis Stergios A. Mitoulis Jamie E. Padgett |
| author_sort | Anibal Tafur |
| collection | DOAJ |
| description | Abstract Coastal hazards and climate change significantly threaten the resilience of railway systems, increasing stresses on global freight transportation, supply chains and economic stability. When it comes to system resilience, resource availability and allocation have been proven to be leading contributors to downtime and losses, alongside the physical vulnerability to extreme loads. To support the quantification and pursuit of system resilience, here we present a probabilistic framework that addresses gaps in resilience modeling of railway systems. Specifically, it systematically integrates tailored structural damage and restoration models across an infrastructure portfolio, while comparatively assessing network-level functionality over time with alternative approaches to recovery resource allocation. Applied to the railway network in Mobile and Baldwin Counties, Alabama, the framework estimates damage states, restoration costs and times, modeling drop and recovery of network functionality. Findings indicate that sea-level rise considerably affects service reinstatement, reducing resilience index up to 80% when combined with hurricanes. Resource allocation strategies also impact resilience, with variations resulting in up to 75% differences in resilience estimates. These results underscore the need to consider resource constraints and sea-level rise in resilience planning, offering nuanced resilience quantification to support decision-making for mitigation and response strategies, benefiting policymakers, infrastructure managers, insurers, and agencies. |
| format | Article |
| id | doaj-art-0fa173d89e644f1eb33e8e3e8055d524 |
| institution | Kabale University |
| issn | 2731-3395 |
| language | English |
| publishDate | 2025-08-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Communications Engineering |
| spelling | doaj-art-0fa173d89e644f1eb33e8e3e8055d5242025-08-24T11:32:32ZengNature PortfolioCommunications Engineering2731-33952025-08-014111410.1038/s44172-025-00493-4Climate-resilient railway networks: a resource-aware frameworkAnibal Tafur0Sotirios A. Argyroudis1Stergios A. Mitoulis2Jamie E. Padgett3Department of Civil and Environmental Engineering, Rice UniversityDepartment of Civil and Environmental Engineering, Brunel University LondonThe Bartlett School of Sustainable Construction, University College LondonDepartment of Civil and Environmental Engineering, Rice UniversityAbstract Coastal hazards and climate change significantly threaten the resilience of railway systems, increasing stresses on global freight transportation, supply chains and economic stability. When it comes to system resilience, resource availability and allocation have been proven to be leading contributors to downtime and losses, alongside the physical vulnerability to extreme loads. To support the quantification and pursuit of system resilience, here we present a probabilistic framework that addresses gaps in resilience modeling of railway systems. Specifically, it systematically integrates tailored structural damage and restoration models across an infrastructure portfolio, while comparatively assessing network-level functionality over time with alternative approaches to recovery resource allocation. Applied to the railway network in Mobile and Baldwin Counties, Alabama, the framework estimates damage states, restoration costs and times, modeling drop and recovery of network functionality. Findings indicate that sea-level rise considerably affects service reinstatement, reducing resilience index up to 80% when combined with hurricanes. Resource allocation strategies also impact resilience, with variations resulting in up to 75% differences in resilience estimates. These results underscore the need to consider resource constraints and sea-level rise in resilience planning, offering nuanced resilience quantification to support decision-making for mitigation and response strategies, benefiting policymakers, infrastructure managers, insurers, and agencies.https://doi.org/10.1038/s44172-025-00493-4 |
| spellingShingle | Anibal Tafur Sotirios A. Argyroudis Stergios A. Mitoulis Jamie E. Padgett Climate-resilient railway networks: a resource-aware framework Communications Engineering |
| title | Climate-resilient railway networks: a resource-aware framework |
| title_full | Climate-resilient railway networks: a resource-aware framework |
| title_fullStr | Climate-resilient railway networks: a resource-aware framework |
| title_full_unstemmed | Climate-resilient railway networks: a resource-aware framework |
| title_short | Climate-resilient railway networks: a resource-aware framework |
| title_sort | climate resilient railway networks a resource aware framework |
| url | https://doi.org/10.1038/s44172-025-00493-4 |
| work_keys_str_mv | AT anibaltafur climateresilientrailwaynetworksaresourceawareframework AT sotiriosaargyroudis climateresilientrailwaynetworksaresourceawareframework AT stergiosamitoulis climateresilientrailwaynetworksaresourceawareframework AT jamieepadgett climateresilientrailwaynetworksaresourceawareframework |