OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!
If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.
Requested Article:
A data-driven approach for predicting interface bond strength between corroded reinforcement and concrete
Tao Huang, Tingbin Liu, Ning Xu, et al.
Structures (2023) Vol. 57, pp. 105122-105122
Closed Access | Times Cited: 8
Tao Huang, Tingbin Liu, Ning Xu, et al.
Structures (2023) Vol. 57, pp. 105122-105122
Closed Access | Times Cited: 8
Showing 8 citing articles:
A critical review of machine learning algorithms in maritime, offshore, and oil & gas corrosion research: A comprehensive analysis of ANN and RF models
Md Mahadi Hasan Imran, Shahrizan Jamaludin, Ahmad Faisal Mohamad Ayob
Ocean Engineering (2024) Vol. 295, pp. 116796-116796
Closed Access | Times Cited: 18
Md Mahadi Hasan Imran, Shahrizan Jamaludin, Ahmad Faisal Mohamad Ayob
Ocean Engineering (2024) Vol. 295, pp. 116796-116796
Closed Access | Times Cited: 18
Machine learning for design, optimization and assessment of steel-concrete composite structures: A review
Xianlin Wang, Bozhou Zhuang, Danny Smyl, et al.
Engineering Structures (2025) Vol. 328, pp. 119652-119652
Closed Access
Xianlin Wang, Bozhou Zhuang, Danny Smyl, et al.
Engineering Structures (2025) Vol. 328, pp. 119652-119652
Closed Access
Machine learning prediction method for the interface bond strength between fiber reinforced polymer bars and concrete based on multi-feature driven analysis
Tao Huang, Chunfeng Wan, Tingbin Liu, et al.
Materials Today Communications (2024), pp. 110706-110706
Closed Access | Times Cited: 4
Tao Huang, Chunfeng Wan, Tingbin Liu, et al.
Materials Today Communications (2024), pp. 110706-110706
Closed Access | Times Cited: 4
Machine learning to estimate the bond strength of the corroded steel bar‐concrete
Kai‐Lai Wang, Jingyi Li, Li Li, et al.
Structural Concrete (2023) Vol. 25, Iss. 1, pp. 696-715
Closed Access | Times Cited: 10
Kai‐Lai Wang, Jingyi Li, Li Li, et al.
Structural Concrete (2023) Vol. 25, Iss. 1, pp. 696-715
Closed Access | Times Cited: 10
Study the effect of ANN splitting ratios and training functions on the prediction of corroded steel-to-concrete bond strength
Bharat Bhushan, Harish Chandra Arora, Aman Kumar, et al.
Multiscale and Multidisciplinary Modeling Experiments and Design (2024) Vol. 7, Iss. 4, pp. 4203-4228
Closed Access
Bharat Bhushan, Harish Chandra Arora, Aman Kumar, et al.
Multiscale and Multidisciplinary Modeling Experiments and Design (2024) Vol. 7, Iss. 4, pp. 4203-4228
Closed Access
Bond Strength Evaluation of FRP–Concrete Interfaces Affected by Hygrothermal and Salt Attack Using Improved Meta-Learning Neural Network
Yi Wang, Ning Ye, Siyuan Liu, et al.
Applied Sciences (2024) Vol. 14, Iss. 13, pp. 5474-5474
Open Access
Yi Wang, Ning Ye, Siyuan Liu, et al.
Applied Sciences (2024) Vol. 14, Iss. 13, pp. 5474-5474
Open Access
Data-Driven Interpretable Machine Learning Prediction Method for the Bond Strength of Near-Surface-Mounted FRP-Concrete
Fawen Gao, Jiwu Yang, Yanbao Huang, et al.
Buildings (2024) Vol. 14, Iss. 9, pp. 2650-2650
Open Access
Fawen Gao, Jiwu Yang, Yanbao Huang, et al.
Buildings (2024) Vol. 14, Iss. 9, pp. 2650-2650
Open Access
Data-driven prediction of high-temperature bond strength in corroded reinforced concrete
Tao Huang, Chunfeng Wan, Tingbin Liu, et al.
Structures (2024) Vol. 71, pp. 107973-107973
Closed Access
Tao Huang, Chunfeng Wan, Tingbin Liu, et al.
Structures (2024) Vol. 71, pp. 107973-107973
Closed Access
