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    Uncertainty Analysis and Quantification of the AASHTO Live Load Distribution Model for Moderately Buried–Reinforced Concrete Box Culverts

    Source: Journal of Bridge Engineering:;2025:;Volume ( 030 ):;issue: 007::page 04025042-1
    Author:
    Mohd Firoj
    ,
    David Y. Yang
    ,
    Timothy A. Wood
    ,
    Kevin White
    DOI: 10.1061/JBENF2.BEENG-7393
    Publisher: American Society of Civil Engineers
    Abstract: RC box culverts are buried structures prevalent in transportation systems. The existence of backfill brings in additional challenges to estimate load demands in these structures. The AASHTO LRFD specifications present a practical method to model live load distribution within the backfill and onto the top slab of culverts. However, it is widely acknowledged that this AASHTO live load distribution model may considerably overestimate load demands in culverts, resulting in overly conservative designs or unnecessary load postings. The present study analyzes the model uncertainties associated with this AASHTO model in moderately buried RC box culverts. These uncertainties are characterized by the ratio of load effects obtained from two-dimensional frame and three-dimensional finite-element analyses, respectively. Herein, a moderate backfill refers to a depth that yields consistent model biases not sensitive to the backfill depth. Focusing on the bending moment at barrel midspan, Bayesian regression is conducted to quantify the uncertainty in the model bias. The quantified uncertainty is then compared among culverts with different barrel spans as well as the model uncertainty in conventional girder bridges. The results indicate the need for, and provide the basis for, a reassessment of the structural reliability of moderately buried RC box culverts.
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      Uncertainty Analysis and Quantification of the AASHTO Live Load Distribution Model for Moderately Buried–Reinforced Concrete Box Culverts

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    http://yetl.yabesh.ir/yetl1/handle/yetl/4307145
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    contributor authorMohd Firoj
    contributor authorDavid Y. Yang
    contributor authorTimothy A. Wood
    contributor authorKevin White
    date accessioned2025-08-17T22:35:03Z
    date available2025-08-17T22:35:03Z
    date copyright7/1/2025 12:00:00 AM
    date issued2025
    identifier otherJBENF2.BEENG-7393.pdf
    identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4307145
    description abstractRC box culverts are buried structures prevalent in transportation systems. The existence of backfill brings in additional challenges to estimate load demands in these structures. The AASHTO LRFD specifications present a practical method to model live load distribution within the backfill and onto the top slab of culverts. However, it is widely acknowledged that this AASHTO live load distribution model may considerably overestimate load demands in culverts, resulting in overly conservative designs or unnecessary load postings. The present study analyzes the model uncertainties associated with this AASHTO model in moderately buried RC box culverts. These uncertainties are characterized by the ratio of load effects obtained from two-dimensional frame and three-dimensional finite-element analyses, respectively. Herein, a moderate backfill refers to a depth that yields consistent model biases not sensitive to the backfill depth. Focusing on the bending moment at barrel midspan, Bayesian regression is conducted to quantify the uncertainty in the model bias. The quantified uncertainty is then compared among culverts with different barrel spans as well as the model uncertainty in conventional girder bridges. The results indicate the need for, and provide the basis for, a reassessment of the structural reliability of moderately buried RC box culverts.
    publisherAmerican Society of Civil Engineers
    titleUncertainty Analysis and Quantification of the AASHTO Live Load Distribution Model for Moderately Buried–Reinforced Concrete Box Culverts
    typeJournal Article
    journal volume30
    journal issue7
    journal titleJournal of Bridge Engineering
    identifier doi10.1061/JBENF2.BEENG-7393
    journal fristpage04025042-1
    journal lastpage04025042-12
    page12
    treeJournal of Bridge Engineering:;2025:;Volume ( 030 ):;issue: 007
    contenttypeFulltext
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