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OpenAlex Citation Counts

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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:

Data driven strength and strain enhancement model for FRP confined concrete using Bayesian optimization
Junsong Du, Haixing Ma, Di Sun, et al.
Structures (2022) Vol. 41, pp. 1345-1358
Closed Access | Times Cited: 10

Showing 10 citing articles:

Machine-Learning Methods for Estimating Performance of Structural Concrete Members Reinforced with Fiber-Reinforced Polymers
Farzin Kazemi, Neda Asgarkhani, Torkan Shafighfard, et al.
Archives of Computational Methods in Engineering (2024)
Open Access | Times Cited: 30
Study of the behavior of eccentrically-loaded fiber-reinforced polymer (FRP) confined RC columns using a novel approach based on probabilistic gene expression programming
Mahdi Hosseini, Milan Gaff, Meisam Mahboubi Niazmandi, et al.
Mechanics of Advanced Materials and Structures (2025), pp. 1-31
Closed Access | Times Cited: 1
Performance of concrete under a low-pressure environment
Xiaorui Liu, Zheng Si, Lingzhi Huang, et al.
Construction and Building Materials (2025) Vol. 461, pp. 139862-139862
Closed Access | Times Cited: 1
Designing a reliable machine learning system for accurately estimating the ultimate condition of FRP-confined concrete
Meysam Alizamir, Aliakbar Gholampour, Sungwon Kim, et al.
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access | Times Cited: 5
Integrated deep learning and Bayesian optimization approach for enhanced prediction of high-performance concrete strength
Rupesh Kumar Tipu, Archna Goyal, Digvijay Singh, et al.
Asian Journal of Civil Engineering (2025)
Closed Access
Passive confinement scenarios for strengthening fire-damaged concrete columns: Experimental and analytical research
Javad Shayanfar, João P.C. Pereira, Joaquim A. O. Barros
Structures (2025) Vol. 73, pp. 108375-108375
Closed Access
The data-driven research on bond strength between fly ash-based geopolymer concrete and reinforcing bars
Yue Li, Jiale Shen, Hui Lin, et al.
Construction and Building Materials (2022) Vol. 357, pp. 129384-129384
Closed Access | Times Cited: 16
Optimized extreme gradient boosting machine learning for estimating diaphragm wall deflection of 3D deep braced excavation in sand
Dong Van Nguyen, Dookie Kim, Yun Wook Choo
Structures (2022) Vol. 45, pp. 1936-1948
Closed Access | Times Cited: 12
Optimized Machine Learning Algorithms for Predicting the Punching Shear Resistance of Flat Slabs with Transverse Reinforcement
Huajun Yan, Nan Xie
International Journal of Concrete Structures and Materials (2024) Vol. 18, Iss. 1
Open Access | Times Cited: 2
The Efficiency of Using Machine Learning Techniques in Fiber-Reinforced-Polymer Applications in Structural Engineering
Mohammad Alhusban, Mohannad Alhusban, Ayah A. Alkhawaldeh
Sustainability (2023) Vol. 16, Iss. 1, pp. 11-11
Open Access | Times Cited: 3
Prediction the Chloride Ion Permeation Coefficient of Concrete Based on A Hybrid Intelligent Algorithm
Yuan Cao, Xianguo Wu, Wen Yuan Xu, et al.
Advanced Journal of Engineering (2023), pp. 37-47
Open Access
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