Quantifying Easy-to-Repair Displacement Ductility and Lateral Strength of Scoured Bridge Pile Group Foundations in Cohesionless Soils: A Classification–Regression Combination Surrogate ModelSource: Journal of Bridge Engineering:;2023:;Volume ( 028 ):;issue: 011::page 04023080-1DOI: 10.1061/JBENF2.BEENG-6201Publisher: 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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contributor author | Jingcheng Wang | |
contributor author | Aijun Ye | |
contributor author | Xiaowei Wang | |
date accessioned | 2024-04-27T20:59:23Z | |
date available | 2024-04-27T20:59:23Z | |
date issued | 2023/11/01 | |
identifier other | 10.1061-JBENF2.BEENG-6201.pdf | |
identifier uri | http://yetl.yabesh.ir/yetl1/handle/yetl/4296394 | |
description 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. | |
publisher | ASCE | |
title | Quantifying Easy-to-Repair Displacement Ductility and Lateral Strength of Scoured Bridge Pile Group Foundations in Cohesionless Soils: A Classification–Regression Combination Surrogate Model | |
type | Journal Article | |
journal volume | 28 | |
journal issue | 11 | |
journal title | Journal of Bridge Engineering | |
identifier doi | 10.1061/JBENF2.BEENG-6201 | |
journal fristpage | 04023080-1 | |
journal lastpage | 04023080-15 | |
page | 15 | |
tree | Journal of Bridge Engineering:;2023:;Volume ( 028 ):;issue: 011 | |
contenttype | Fulltext |