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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 the Splitting Tensile Strength of Manufactured Sand Based High-Performance Concrete Using Explainable Machine Learning
Rakesh Kumar, Pijush Samui, Baboo Rai
Iranian Journal of Science and Technology Transactions of Civil Engineering (2024) Vol. 48, Iss. 5, pp. 3717-3734
Closed Access | Times Cited: 16

Showing 16 citing articles:

Prediction of compressive strength of high-volume fly ash self-compacting concrete with silica fume using machine learning techniques
Shashikant Kumar, Rakesh Kumar, Baboo Rai, et al.
Construction and Building Materials (2024) Vol. 438, pp. 136933-136933
Closed Access | Times Cited: 21
Modelling the mechanical properties of concrete produced with polycarbonate waste ash by machine learning
S. Sathvik, Rakesh Kumar, Néstor Ulloa, et al.
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access | Times Cited: 19
Machine learning and nonlinear finite element analysis of fiber‐reinforced polymer‐confined concrete‐steel double‐skin tubular columns under axial compression
Haytham F. Isleem, Qiong Tang, Naga Dheeraj Kumar Reddy Chukka, et al.
Structural Concrete (2024)
Closed Access | Times Cited: 19
Development of hybrid gradient boosting models for predicting the compressive strength of high-volume fly ash self-compacting concrete with silica fume
Rakesh Kumar, Shashikant Kumar, Baboo Rai, et al.
Structures (2024) Vol. 66, pp. 106850-106850
Closed 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: 18
Analyzing the influence of manufactured sand and fly ash on concrete strength through experimental and machine learning methods
S. Sathvik, Solomon Oyebisi, Rakesh Kumar, et al.
Scientific Reports (2025) Vol. 15, Iss. 1
Open Access | Times Cited: 4
Machine learning approach for predicting the compressive strength of biomedical waste ash in concrete: a sustainability approach
Rakesh Kumar, Shishir Karthik, Abhishek Kumar, et al.
Discover Materials (2025) Vol. 5, Iss. 1
Open Access | Times Cited: 3
Development of a prediction tool for the compressive strength of ternary blended ultra-high performance concrete using machine learning techniques
Rakesh Kumar, Shubhum Prakash, Baboo Rai, et al.
Journal of Structural Integrity and Maintenance (2024) Vol. 9, Iss. 3
Closed Access | Times Cited: 16
Predicting the fire-induced structural performance of steel tube columns filled with SFRC-enhanced concrete: using artificial neural networks approach
Christo George, Edwin Zumba, María Alexandra Procel Silva, et al.
Frontiers in Built Environment (2024) Vol. 10
Open Access | Times Cited: 12
Strength and durability predictions of ternary blended nano-engineered high-performance concrete: Application of hybrid machine learning techniques with bio-inspired optimization
Vikrant S. Vairagade, Boskey V. Bahoria, Haytham F. Isleem, et al.
Engineering Applications of Artificial Intelligence (2025) Vol. 148, pp. 110470-110470
Closed Access | Times Cited: 1
Predicting the compressive strength of polymer-infused bricks: A machine learning approach with SHAP interpretability
S. Sathvik, Rakesh Kumar, Archudha Arjunasamy, et al.
Scientific Reports (2025) Vol. 15, Iss. 1
Open Access | Times Cited: 1
Machine learning prediction of the unconfined compressive strength of controlled low strength material using fly ash and pond ash
K. Lini Dev, Divesh Ranjan Kumar, Warit Wipulanusat
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access | Times Cited: 7
A Robust LightGBM Model for Concrete Tensile Strength Forecast to Aid in Resilience-based Structure Strategies
Chukwuemeka Daniel
Heliyon (2024) Vol. 10, Iss. 20, pp. e39679-e39679
Open Access | Times Cited: 4
Modelling absorbed gamma radiation dose rate from 226Ra, 232Th, and 40K of recycled waste materials: analytical and machine learning approaches
Solomon Oyebisi, Monsuru Akinleye, Sani Reuben, et al.
IOP Conference Series Earth and Environmental Science (2025) Vol. 1492, Iss. 1, pp. 012037-012037
Open Access
Synergistic effects of graphene oxide and limestone calcined clay cement on mechanical properties and durability of concrete
Chava Venkatesh, V. Mallikarjuna, G. Mallikarjuna Rao, et al.
Journal of Building Pathology and Rehabilitation (2024) Vol. 9, Iss. 2
Closed Access | Times Cited: 2
Effect of sulfate freeze-thaw on the stress-strain relationship of recycled coarse aggregate self-compacting concrete: Experimental and machine learning algorithms
Chuanlei Zheng, Yijiang Liu, Luoyin Li, et al.
Construction and Building Materials (2024) Vol. 449, pp. 138383-138383
Closed Access | Times Cited: 2
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