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    Modeling Earthquake-Induced Landslide Risk for Mountain Railway Alignment Optimization

    Source: ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering:;2024:;Volume ( 010 ):;issue: 002::page 04024005-1
    Author:
    Taoran Song
    ,
    Hao Pu
    ,
    T. Y. Yang
    ,
    Paul Schonfeld
    ,
    Xinjie Wan
    ,
    Wei Li
    ,
    Zhihui Zhu
    ,
    Hong Zhang
    ,
    Jianping Hu
    DOI: 10.1061/AJRUA6.RUENG-1179
    Publisher: ASCE
    Abstract: Construction investment and geological risk of a railway project are significantly influenced by the alignment design. Thus, for railways in earthquake-prone regions, the seismic risks should be addressed at the alignment decision-making stage. However, this is a challenging problem that should balance cost and risk appropriately. Especially in mountainous regions, besides direct ground shaking, earthquake-induced landslides greatly threaten railways’ construction and operation. Unfortunately, no existing studies in this field have accounted for that factor. In this paper, a novel potential earthquake-induced landslide risk model is proposed for mountain railway alignment optimization. In this model, a probabilistic seismic hazard analysis, critical acceleration computation, and landslide displacement estimation are first integrated. Together with the consideration of railway structures’ damage states, damage ratios, and restoration functions, the direct and indirect monetary losses caused by landslides to railways with specified alignments are evaluated. Then, the aforementioned analyses are incorporated into a previous cost-risk model and solved with a particle swarm optimization (PSO) algorithm. Finally, the model’s effectiveness is tested in a complex railway example. It is found that the studied region is landslide prone, and railway structures, especially bridges, are vulnerable to landslides. Also, a biobjective analysis reveals the alignments can be more sensitive to risks than to costs. Lastly, according to the detailed engineering outputs, the computer-generated alignment is 11.8% less expensive and 27.2% safer than the best manually designed solution.
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      Modeling Earthquake-Induced Landslide Risk for Mountain Railway Alignment Optimization

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    • ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering

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    contributor authorTaoran Song
    contributor authorHao Pu
    contributor authorT. Y. Yang
    contributor authorPaul Schonfeld
    contributor authorXinjie Wan
    contributor authorWei Li
    contributor authorZhihui Zhu
    contributor authorHong Zhang
    contributor authorJianping Hu
    date accessioned2024-04-27T22:42:18Z
    date available2024-04-27T22:42:18Z
    date issued2024/06/01
    identifier other10.1061-AJRUA6.RUENG-1179.pdf
    identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4297300
    description abstractConstruction investment and geological risk of a railway project are significantly influenced by the alignment design. Thus, for railways in earthquake-prone regions, the seismic risks should be addressed at the alignment decision-making stage. However, this is a challenging problem that should balance cost and risk appropriately. Especially in mountainous regions, besides direct ground shaking, earthquake-induced landslides greatly threaten railways’ construction and operation. Unfortunately, no existing studies in this field have accounted for that factor. In this paper, a novel potential earthquake-induced landslide risk model is proposed for mountain railway alignment optimization. In this model, a probabilistic seismic hazard analysis, critical acceleration computation, and landslide displacement estimation are first integrated. Together with the consideration of railway structures’ damage states, damage ratios, and restoration functions, the direct and indirect monetary losses caused by landslides to railways with specified alignments are evaluated. Then, the aforementioned analyses are incorporated into a previous cost-risk model and solved with a particle swarm optimization (PSO) algorithm. Finally, the model’s effectiveness is tested in a complex railway example. It is found that the studied region is landslide prone, and railway structures, especially bridges, are vulnerable to landslides. Also, a biobjective analysis reveals the alignments can be more sensitive to risks than to costs. Lastly, according to the detailed engineering outputs, the computer-generated alignment is 11.8% less expensive and 27.2% safer than the best manually designed solution.
    publisherASCE
    titleModeling Earthquake-Induced Landslide Risk for Mountain Railway Alignment Optimization
    typeJournal Article
    journal volume10
    journal issue2
    journal titleASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering
    identifier doi10.1061/AJRUA6.RUENG-1179
    journal fristpage04024005-1
    journal lastpage04024005-15
    page15
    treeASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering:;2024:;Volume ( 010 ):;issue: 002
    contenttypeFulltext
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