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    Quantifying Easy-to-Repair Displacement Ductility and Lateral Strength of Scoured Bridge Pile Group Foundations in Cohesionless Soils: A Classification–Regression Combination Surrogate Model

    Source: Journal of Bridge Engineering:;2023:;Volume ( 028 ):;issue: 011::page 04023080-1
    Author:
    Jingcheng Wang
    ,
    Aijun Ye
    ,
    Xiaowei Wang
    DOI: 10.1061/JBENF2.BEENG-6201
    Publisher: ASCE
    Abstract: Scoured pile-group foundations in bridges are likely to undergo inelastic deformation during earthquakes, which can be utilized to dissipate seismic energy and withstand seismic loads by the post-yield hardening strength of the foundation. However, limit states and associated ductility indices and post-yield strength indices are yet to be well documented. This study develops a surrogate model, namely, the classification–regression combination model (CRCM), for the efficient, interpretable, and high-confidence quantification of displacement ductility factor (μΔER) and associated strength hardening factor (RFER) of scoured bridge pile-group foundations at the easy-to-repair limit state, where the damage of piles is limited to the aboveground region (thereby being relatively easy to repair). To this end, a proper pushover method from those with different load patterns is first identified for efficient nonlinear analyses of scoured bridge pile groups. A large number of bridge samples are then analyzed to prepare a comprehensive database for the development of CRCM, which first classifies the failure process of scoured bridge pile-group foundations and then regresses μΔER and RFER with variables characterizing the soil–bridge systems. It is found that the pushover method with a two-node load pattern (i.e., load at the superstructure and pile-cap centroids) can very well capture μΔER and RFER and the failure process of bridge pile groups. The data-driven CRCM can efficiently provide reasonable predictions of μΔER and RFER with errors mostly within 20%; it is specifically compared with a regression-only model to demonstrate the necessity of incorporating a classifier in advance of the regression model.
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      Quantifying Easy-to-Repair Displacement Ductility and Lateral Strength of Scoured Bridge Pile Group Foundations in Cohesionless Soils: A Classification–Regression Combination Surrogate Model

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    http://yetl.yabesh.ir/yetl1/handle/yetl/4296394
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    • Journal of Bridge Engineering

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    contributor authorJingcheng Wang
    contributor authorAijun Ye
    contributor authorXiaowei Wang
    date accessioned2024-04-27T20:59:23Z
    date available2024-04-27T20:59:23Z
    date issued2023/11/01
    identifier other10.1061-JBENF2.BEENG-6201.pdf
    identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4296394
    description abstractScoured pile-group foundations in bridges are likely to undergo inelastic deformation during earthquakes, which can be utilized to dissipate seismic energy and withstand seismic loads by the post-yield hardening strength of the foundation. However, limit states and associated ductility indices and post-yield strength indices are yet to be well documented. This study develops a surrogate model, namely, the classification–regression combination model (CRCM), for the efficient, interpretable, and high-confidence quantification of displacement ductility factor (μΔER) and associated strength hardening factor (RFER) of scoured bridge pile-group foundations at the easy-to-repair limit state, where the damage of piles is limited to the aboveground region (thereby being relatively easy to repair). To this end, a proper pushover method from those with different load patterns is first identified for efficient nonlinear analyses of scoured bridge pile groups. A large number of bridge samples are then analyzed to prepare a comprehensive database for the development of CRCM, which first classifies the failure process of scoured bridge pile-group foundations and then regresses μΔER and RFER with variables characterizing the soil–bridge systems. It is found that the pushover method with a two-node load pattern (i.e., load at the superstructure and pile-cap centroids) can very well capture μΔER and RFER and the failure process of bridge pile groups. The data-driven CRCM can efficiently provide reasonable predictions of μΔER and RFER with errors mostly within 20%; it is specifically compared with a regression-only model to demonstrate the necessity of incorporating a classifier in advance of the regression model.
    publisherASCE
    titleQuantifying Easy-to-Repair Displacement Ductility and Lateral Strength of Scoured Bridge Pile Group Foundations in Cohesionless Soils: A Classification–Regression Combination Surrogate Model
    typeJournal Article
    journal volume28
    journal issue11
    journal titleJournal of Bridge Engineering
    identifier doi10.1061/JBENF2.BEENG-6201
    journal fristpage04023080-1
    journal lastpage04023080-15
    page15
    treeJournal of Bridge Engineering:;2023:;Volume ( 028 ):;issue: 011
    contenttypeFulltext
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    DSpace software copyright © 2002-2015  DuraSpace
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