A data-driven approach for predicting interface bond strength between corroded reinforcement and concrete-Reference-Cited by-同舟云学术

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A data-driven approach for predicting interface bond strength between corroded reinforcement and concrete

Published:2023-11 Issue: Volume:57 Page:105122
ISSN:2352-0124
Container-title:Structures
language:en
Short-container-title:Structures

Author:

Huang Tao,Liu Tingbin,Xu Ning,Yue Kangle,Li Yunxia,Liu Xing,Liu Shiyang,Ou Jiaxiang

Publisher

Elsevier BV

Subject

Safety, Risk, Reliability and Quality,Building and Construction,Architecture,Civil and Structural Engineering

Reference41 articles.

1. Study on the mechanical properties of NPR steel bars and the bonding properties with marine concrete;Shao;Constr Build Mater,2022

2. Bond behaviour of normal/recycled concrete and corroded steel bars;Zhao;Constr Build Mater,2013

3. Experimental and analytical study on the effect of different repairing and strengthening strategies on flexural performance of corroded RC beams;Kharma;Structures,2022

4. Experimental study to predict bond-slip behavior of corroded reinforced concrete columns;Yalciner;ACI Struct J,2022

5. Stiffness degradation analysis of reinforced concrete beams under corrosion-fatigue coupling action based on experimental research;Zhang;Structures,2023

Cited by 5 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Data-Driven Interpretable Machine Learning Prediction Method for the Bond Strength of Near-Surface-Mounted FRP-Concrete;Buildings;2024-08-26

2. Bond Strength Evaluation of FRP–Concrete Interfaces Affected by Hygrothermal and Salt Attack Using Improved Meta-Learning Neural Network;Applied Sciences;2024-06-24

3. Study the effect of ANN splitting ratios and training functions on the prediction of corroded steel-to-concrete bond strength;Multiscale and Multidisciplinary Modeling, Experiments and Design;2024-05-24

4. A critical review of machine learning algorithms in maritime, offshore, and oil & gas corrosion research: A comprehensive analysis of ANN and RF models;Ocean Engineering;2024-03

5. Machine learning to estimate the bond strength of the corroded steel bar‐concrete;Structural Concrete;2023-12-28

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