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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:

Prediction of Interface Bond Strength Between Ultra-High-Performance Concrete (UHPC) and Normal Strength Concrete (NSC) Using a Machine Learning Approach
Abdulwarith Ibrahim Bibi Farouk, Jinsong Zhu
Arabian Journal for Science and Engineering (2022) Vol. 47, Iss. 4, pp. 5337-5363
Closed Access | Times Cited: 46

Showing 1-25 of 46 citing articles:

Prediction of pull-out behavior of timber glued-in glass fiber reinforced polymer and steel rods under various environmental conditions based on ANN and GEP models
Mostafa Mohammadzadeh Taleshi, Nima Tajik, Alireza Mahmoudian, et al.
Case Studies in Construction Materials (2024) Vol. 20, pp. e02842-e02842
Open Access | Times Cited: 19
Prediction of mechanical properties of high‐performance concrete and ultrahigh‐performance concrete using soft computing techniques: A critical review
Rakesh Kumar, Baboo Rai, Pijush Samui
Structural Concrete (2024)
Closed Access | Times Cited: 16
Machine Learning Approach for Prediction and Reliability Analysis of Failure Strength of U-Shaped Concrete Samples Joined with UHPC and PUC Composites
Sadi Ibrahim Haruna, Yasser E. Ibrahim, Ibrahim Khalil Umar
Journal of Composites Science (2025) Vol. 9, Iss. 1, pp. 23-23
Open Access | Times Cited: 1
Towards sustainable construction: Machine learning based predictive models for strength and durability characteristics of blended cement concrete
Majid Khan, Muhammad Faisal Javed
Materials Today Communications (2023) Vol. 37, pp. 107428-107428
Closed Access | Times Cited: 38
Prediction of Mechanical Properties of Rubberized Concrete Incorporating Fly Ash and Nano Silica by Artificial Neural Network Technique
Musa Adamu, Andaç Batur Çolak, Yasser E. Ibrahim, et al.
Axioms (2023) Vol. 12, Iss. 1, pp. 81-81
Open Access | Times Cited: 24
Prediction of shear behavior of glass FRP bars-reinforced ultra-highperformance concrete I-shaped beams using machine learning
Asif Ahmed, Md Nasir Uddin, Muhammad Akbar, et al.
International Journal of Mechanics and Materials in Design (2023) Vol. 20, Iss. 2, pp. 269-290
Open Access | Times Cited: 22
Bond behavior between normal concrete and UHPC and PUC layers subjected to different loading conditions coupled with fracture analysis technique
Ali Al-shawafi, Han Zhu, Bo Zhao, et al.
Journal of Building Engineering (2024) Vol. 86, pp. 108880-108880
Closed Access | Times Cited: 10
High-Performance Concrete Strength Prediction Based on Machine Learning
Yanning Liu
Computational Intelligence and Neuroscience (2022) Vol. 2022, pp. 1-7
Open Access | Times Cited: 35
Prediction and uncertainty quantification of ultimate bond strength between UHPC and reinforcing steel bar using a hybrid machine learning approach
Abdulwarith Ibrahim Bibi Farouk, Jinsong Zhu, Jingnan Ding, et al.
Construction and Building Materials (2022) Vol. 345, pp. 128360-128360
Closed Access | Times Cited: 32
Artificial intelligence techniques in advanced concrete technology: A comprehensive survey on 10 years research trend
Ramin Kazemi
Engineering Reports (2023) Vol. 5, Iss. 9
Open Access | Times Cited: 19
The influence of roughness and bond area size on bond shear performance between UHPC and normal strength concrete
Jingjing Lyu, Shuo Feng, Qingsong Zhang
Construction and Building Materials (2024) Vol. 448, pp. 138203-138203
Closed Access | Times Cited: 6
Data driven design of ultra high performance concrete prospects and application
Bryan K. Aylas-Paredes, Taihao Han, Advaith Neithalath, et al.
Scientific Reports (2025) Vol. 15, Iss. 1
Open Access
Feature selection approach for failure mode detection of reinforced concrete bridge columns
Nageh M. Ali, Abdulwarith Ibrahim Bibi Farouk, Sadi Ibrahim Haruna, et al.
Case Studies in Construction Materials (2022) Vol. 17, pp. e01383-e01383
Open Access | Times Cited: 27
Enhancing Sustainability of Corroded RC Structures: Estimating Steel-to-Concrete Bond Strength with ANN and SVM Algorithms
Rohan Singh, Harish Chandra Arora, Alireza Bahrami, et al.
Materials (2022) Vol. 15, Iss. 23, pp. 8295-8295
Open Access | Times Cited: 26
Experimental study and machine learning algorithms for evaluating the performance of U-shaped ultra-high performance reinforced fiber concrete under static and impact loads
Ali Al-shawafi, Han Zhu, Sadi Ibrahim Haruna, et al.
Journal of Building Engineering (2023) Vol. 70, pp. 106389-106389
Closed Access | Times Cited: 14
Sensitivity and robustness analysis of adaptive neuro-fuzzy inference system (ANFIS) for shear strength prediction of stud connectors in concrete
Ahmed M. Yosri, Abdulwarith Ibrahim Bibi Farouk, Sadi Ibrahim Haruna, et al.
Case Studies in Construction Materials (2023) Vol. 18, pp. e02096-e02096
Open Access | Times Cited: 13
Data-Driven Prediction of Compressive Strength for Ultra-high Performance Concrete Exposed to Elevated Temperatures
Xiaoqing Yu, Canhui Chen, Jianliang Xie, et al.
Materials Today Communications (2025), pp. 111518-111518
Closed Access
Neural network-based performance prediction of marine UHPC with coarse aggregates
Yunhao Luan, Denise J. Cai, Biao Wang, et al.
Frontiers in Materials (2025) Vol. 12
Open Access
Bond Strength Assessment of Normal Strength Concrete–Ultra-High-Performance Fiber Reinforced Concrete Using Repeated Drop-Weight Impact Test: Experimental and Machine Learning Technique
Sadi Ibrahim Haruna, Yasser E. Ibrahim, Ibrahim Hayatu Hassan, et al.
Materials (2024) Vol. 17, Iss. 12, pp. 3032-3032
Open Access | Times Cited: 3
Intelligent predicting and monitoring of ultra-high-performance fiber reinforced concrete composites − A review
Dingqiang Fan, Ziao Chen, Yuan Cao, et al.
Composites Part A Applied Science and Manufacturing (2024), pp. 108555-108555
Closed Access | Times Cited: 3
Prediction of Chloride Diffusion Coefficient in Concrete Modified with Supplementary Cementitious Materials Using Machine Learning Algorithms
Abdulrahman Fahad Al Fuhaid, Hani Alanazi
Materials (2023) Vol. 16, Iss. 3, pp. 1277-1277
Open Access | Times Cited: 10
Development of hybrid models for shear resistance prediction of grouped stud connectors in concrete using improved metaheuristic optimization techniques
Jinsong Zhu, Abdulwarith Ibrahim Bibi Farouk
Structures (2023) Vol. 50, pp. 286-302
Closed Access | Times Cited: 8
Unveiling optimal half-cell potentials in RCC slabs through cutting-edge ANFIS, ANN and genetic algorithm integration
Shikha Pandey, Sumit Gandhi, Yogesh Iyer Murthy
Anti-Corrosion Methods and Materials (2024) Vol. 71, Iss. 5, pp. 491-505
Closed Access | Times Cited: 2
Enhancing bond strength prediction at UHPC-NC interface: A data-driven approach with augmentation and explainability
Tianyu Hu, Hong Zhang, Nima Khodadadi, et al.
Construction and Building Materials (2024) Vol. 451, pp. 138757-138757
Closed Access | Times Cited: 2
Leveraging Interpretable Ensemble Machine Learning for Predicting Interfacial Bond Strength Between Normal-Strength Concrete Substrate and UHPC Overlays
Sanjog Chhetri Sapkota, Sagar Sapkota, Tushar Bansal, et al.
Arabian Journal for Science and Engineering (2024)
Closed Access | Times Cited: 2
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