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    Probabilistic Comparative Analysis of Vehicle–Bridge Interaction Models for Predicting Bridge Response under Moving Vehicles

    Source: Journal of Engineering Mechanics:;2024:;Volume ( 150 ):;issue: 003::page 04023121-1
    Author:
    Angelo Aloisio
    ,
    Rocco Alaggio
    DOI: 10.1061/JENMDT.EMENG-7437
    Publisher: ASCE
    Abstract: This paper compares three approaches for predicting the bridge response under moving vehicles. The first approach represents the vehicle as a concentrated moving load, while the second and third approaches simulate the vehicle using single (1-dof) and two (2-dof) degrees of freedom models, respectively. The vehicle–bridge models have been implemented following a finite-difference formulation. These models have been validated against the experimental displacement response of a mid-span prestressed reinforced concrete bridge. Parametric analyses have been conducted to investigate the impact of road roughness on the discrepancies between the models’ predictions. An increasing level of road roughness, modeled according to ISO-8608, tends to conceal the mutual differences between the models’ outcomes. Furthermore, a Monte Carlo simulation has been employed to fit the probability distributions of two indicators, comparing the bridge displacement responses in three roughness scenarios and considering variable velocity and vehicle characteristics. The primary objective is to assess whether there are scenarios where vehicle–bridge interaction modeling becomes indispensable for accurately estimating the vehicle’s effect on the bridge response. The paper presents expressions for four probability density functions of the chosen metric, facilitating the comparison between the 1-dof and 2-dof models with the concentrated load approach.
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      Probabilistic Comparative Analysis of Vehicle–Bridge Interaction Models for Predicting Bridge Response under Moving Vehicles

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    http://yetl.yabesh.ir/yetl1/handle/yetl/4297536
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    • Journal of Engineering Mechanics

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    contributor authorAngelo Aloisio
    contributor authorRocco Alaggio
    date accessioned2024-04-27T22:48:06Z
    date available2024-04-27T22:48:06Z
    date issued2024/03/01
    identifier other10.1061-JENMDT.EMENG-7437.pdf
    identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4297536
    description abstractThis paper compares three approaches for predicting the bridge response under moving vehicles. The first approach represents the vehicle as a concentrated moving load, while the second and third approaches simulate the vehicle using single (1-dof) and two (2-dof) degrees of freedom models, respectively. The vehicle–bridge models have been implemented following a finite-difference formulation. These models have been validated against the experimental displacement response of a mid-span prestressed reinforced concrete bridge. Parametric analyses have been conducted to investigate the impact of road roughness on the discrepancies between the models’ predictions. An increasing level of road roughness, modeled according to ISO-8608, tends to conceal the mutual differences between the models’ outcomes. Furthermore, a Monte Carlo simulation has been employed to fit the probability distributions of two indicators, comparing the bridge displacement responses in three roughness scenarios and considering variable velocity and vehicle characteristics. The primary objective is to assess whether there are scenarios where vehicle–bridge interaction modeling becomes indispensable for accurately estimating the vehicle’s effect on the bridge response. The paper presents expressions for four probability density functions of the chosen metric, facilitating the comparison between the 1-dof and 2-dof models with the concentrated load approach.
    publisherASCE
    titleProbabilistic Comparative Analysis of Vehicle–Bridge Interaction Models for Predicting Bridge Response under Moving Vehicles
    typeJournal Article
    journal volume150
    journal issue3
    journal titleJournal of Engineering Mechanics
    identifier doi10.1061/JENMDT.EMENG-7437
    journal fristpage04023121-1
    journal lastpage04023121-14
    page14
    treeJournal of Engineering Mechanics:;2024:;Volume ( 150 ):;issue: 003
    contenttypeFulltext
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