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气候适应型铁路网络:一种资源感知框架。

Climate-resilient railway networks: a resource-aware framework.

作者信息

Tafur Anibal, Argyroudis Sotirios A, Mitoulis Stergios A, Padgett Jamie E

机构信息

Department of Civil and Environmental Engineering, Rice University, Houston TX, USA.

Department of Civil and Environmental Engineering, Brunel University London, London, UK.

出版信息

Commun Eng. 2025 Aug 21;4(1):157. doi: 10.1038/s44172-025-00493-4.

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.

摘要

沿海灾害和气候变化对铁路系统的恢复力构成重大威胁,给全球货运、供应链和经济稳定带来越来越大的压力。在系统恢复力方面,资源可用性和分配已被证明是导致停机时间和损失的主要因素,同时还存在对极端负荷的物理脆弱性。为了支持对系统恢复力的量化和追求,我们在此提出一个概率框架,以解决铁路系统恢复力建模方面的差距。具体而言,它系统地整合了针对基础设施组合的定制结构损伤和修复模型,同时用替代的恢复资源分配方法对网络层面的功能随时间进行比较评估。应用于阿拉巴马州莫比尔县和鲍德温县的铁路网络,该框架估计损伤状态、修复成本和时间,对网络功能的下降和恢复进行建模。研究结果表明,海平面上升对服务恢复有很大影响,与飓风同时发生时,恢复力指数降低高达80%。资源分配策略也会影响恢复力,不同的策略会导致恢复力估计值相差高达75%。这些结果强调了在恢复力规划中考虑资源限制和海平面上升的必要性,提供细致入微的恢复力量化,以支持减灾和应对策略的决策,使政策制定者、基础设施管理者、保险公司和机构受益。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a9e8/12371024/5020beabc776/44172_2025_493_Fig1_HTML.jpg

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