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    Quantifying the Relative Change in Maintenance Costs due to Delayed Maintenance Actions in Transportation Infrastructure

    Source: Journal of Performance of Constructed Facilities:;2024:;Volume ( 038 ):;issue: 005::page 04024035-1
    Author:
    Zachary Hamida
    ,
    James-A. Goulet
    DOI: 10.1061/JPCFEV.CFENG-4802
    Publisher: American Society of Civil Engineers
    Abstract: Identifying optimal maintenance policies for transportation infrastructure such as bridges, is a challenging task that requires taking into account many aspects relating to budget availability, resource allocation and traffic rerouting. In practice, it is difficult to accurately quantify all of the aforementioned factors; accordingly, it is equally difficult to obtain network-scale optimal maintenance policies. This paper presents an approach to evaluate the costs associated with deviations from optimal bridge-level maintenance policies, specifically focusing on delays in maintenance actions. Evaluating the cost of maintenance delays is performed using a reinforcement learning (RL) approach that relies on a probabilistic deterioration model to describe the deterioration in the structural components. The RL framework provides estimates for the total expected discounted maintenance costs associated with each maintenance policy over time, allowing comparison of maintenance policies where maintenance actions are delayed against an optimal maintenance policy. The comparisons are performed by probabilistically quantifying the ratio of expected costs associated with each maintenance policy. This ratio represents the trade-offs between performing or delaying maintenance actions over time. Moreover, the proposed approach is scalable, making it applicable to bridges with numerous structural elements. Example of application using the proposed framework is demonstrated using inspection data from bridges in the Quebec province of Canada.
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      Quantifying the Relative Change in Maintenance Costs due to Delayed Maintenance Actions in Transportation Infrastructure

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    http://yetl.yabesh.ir/yetl1/handle/yetl/4298075
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    contributor authorZachary Hamida
    contributor authorJames-A. Goulet
    date accessioned2024-12-24T09:59:04Z
    date available2024-12-24T09:59:04Z
    date copyright10/1/2024 12:00:00 AM
    date issued2024
    identifier otherJPCFEV.CFENG-4802.pdf
    identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4298075
    description abstractIdentifying optimal maintenance policies for transportation infrastructure such as bridges, is a challenging task that requires taking into account many aspects relating to budget availability, resource allocation and traffic rerouting. In practice, it is difficult to accurately quantify all of the aforementioned factors; accordingly, it is equally difficult to obtain network-scale optimal maintenance policies. This paper presents an approach to evaluate the costs associated with deviations from optimal bridge-level maintenance policies, specifically focusing on delays in maintenance actions. Evaluating the cost of maintenance delays is performed using a reinforcement learning (RL) approach that relies on a probabilistic deterioration model to describe the deterioration in the structural components. The RL framework provides estimates for the total expected discounted maintenance costs associated with each maintenance policy over time, allowing comparison of maintenance policies where maintenance actions are delayed against an optimal maintenance policy. The comparisons are performed by probabilistically quantifying the ratio of expected costs associated with each maintenance policy. This ratio represents the trade-offs between performing or delaying maintenance actions over time. Moreover, the proposed approach is scalable, making it applicable to bridges with numerous structural elements. Example of application using the proposed framework is demonstrated using inspection data from bridges in the Quebec province of Canada.
    publisherAmerican Society of Civil Engineers
    titleQuantifying the Relative Change in Maintenance Costs due to Delayed Maintenance Actions in Transportation Infrastructure
    typeJournal Article
    journal volume38
    journal issue5
    journal titleJournal of Performance of Constructed Facilities
    identifier doi10.1061/JPCFEV.CFENG-4802
    journal fristpage04024035-1
    journal lastpage04024035-12
    page12
    treeJournal of Performance of Constructed Facilities:;2024:;Volume ( 038 ):;issue: 005
    contenttypeFulltext
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    DSpace software copyright © 2002-2015  DuraSpace
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