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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 on compressive strength of Engineered Cementitious composites using Machine learning approach
N. Shanmugasundaram, S. Praveenkumar, K. Gayathiri, et al.
Construction and Building Materials (2022) Vol. 342, pp. 127933-127933
Closed Access | Times Cited: 42

Showing 1-25 of 42 citing articles:

Prediction of compressive strength and tensile strain of engineered cementitious composite using machine learning
Md Nasir Uddin, N. Shanmugasundaram, S. Praveenkumar, et al.
International Journal of Mechanics and Materials in Design (2024) Vol. 20, Iss. 4, pp. 671-716
Closed Access | Times Cited: 13
Data-driven prediction on critical mechanical properties of engineered cementitious composites based on machine learning
Shuangquan Qing, Chuanxi Li
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access | Times Cited: 9
ANN-based predictive mimicker for the constitutive model of engineered cementitious composites (ECC)
Umair Jalil Malik, Sikandar Ali Khokhar, Muhammad Hammad, et al.
Construction and Building Materials (2024) Vol. 420, pp. 135530-135530
Closed Access | Times Cited: 7
Multi-objective optimization of engineered cementitious composite based on machine learning and generative adversarial network
Yufei Wang, Junbo Sun, Xiangyu Wang, et al.
Journal of Building Engineering (2024) Vol. 96, pp. 110471-110471
Closed Access | Times Cited: 7
Prediction of compressive strength ultra-high steel fiber reinforced concrete (UHSFRC) using artificial neural networks (ANNs)
Md Minaz Hossain, Md Nasir Uddin, M. A. Hossain
Materials Today Proceedings (2023)
Closed Access | Times Cited: 15
Performance prediction and analysis of engineered cementitious composites based on machine learning
Wenguang Chen, Роман Федюк, Jie Yu, et al.
Developments in the Built Environment (2024) Vol. 18, pp. 100459-100459
Open Access | Times Cited: 5
Prediction of the mechanical performance of polyethylene fiber-based engineered cementitious composite (PE-ECC)
Shameem Hossain, Md Nasir Uddin, Kang-Tai Yan, et al.
Low-carbon Materials and Green Construction (2024) Vol. 2, Iss. 1
Open Access | Times Cited: 5
Development of Robust Machine Learning Models for Predicting Flexural Strengths of Fiber-Reinforced Polymeric Composites
Abdulhammed K. Hamzat, Umar Salman, Md Shafinur Murad, et al.
Hybrid Advances (2025), pp. 100385-100385
Open Access
A critical analysis of compressive strength prediction of glass fiber and carbon fiber reinforced concrete over machine learning models
K. K. Yaswanth, V. S. Vani, Krupasindhu Biswal, et al.
Multiscale and Multidisciplinary Modeling Experiments and Design (2025) Vol. 8, Iss. 3
Closed Access
Explainable ensemble algorithms with grey wolf optimization for estimation of the tensile performance of polyethylene fiber-reinforced engineered cementitious composite
Mehmet Emin TABAR, Metin Katlav, Kâzım Türk
Materials Today Communications (2025), pp. 112028-112028
Closed Access
New Opportunity: Materials Genome Strategy for Engineered Cementitious Composites (ECC) Design
Wenguang Chen, Long Liang, Fangming Jiang, et al.
Cement and Concrete Composites (2025) Vol. 159, pp. 106009-106009
Closed Access
AI-based constitutive model simulator for predicting the axial load-deflection behavior of recycled concrete powder and steel fiber reinforced concrete column
Aneel Manan, Pu Zhang, Weiyi Chen, et al.
Construction and Building Materials (2025) Vol. 470, pp. 140628-140628
Closed Access
Performance of engineered cementitious composite (ECC) monolithic and composite slabs subjected to near-field blast
Hongyuan Zhou, Jiehao Wu, Xiaojuan Wang, et al.
Engineering Structures (2023) Vol. 279, pp. 115561-115561
Closed Access | Times Cited: 13
An integrated evaluation of graphene-based concrete mixture with copper slag and quarry dust using response surface methodology
S. Divya, S. Praveenkumar
Journal of Building Engineering (2024) Vol. 86, pp. 108876-108876
Closed Access | Times Cited: 4
Using the Response Surface Method and Artificial Neural Network to Estimate the Compressive Strength of Environmentally Friendly Concretes Containing Fine Copper Slag Aggregates
Iman Afshoon, Mahmoud Miri, Seyed Roohollah Mousavi
Iranian Journal of Science and Technology Transactions of Civil Engineering (2023) Vol. 47, Iss. 6, pp. 3415-3429
Closed Access | Times Cited: 11
Predicting the compressive strength of engineered geopolymer composites using automated machine learning
Mahmoud Anwar Gad, Ehsan Nikbakht, Mohammed Gamal Ragab
Construction and Building Materials (2024) Vol. 442, pp. 137509-137509
Closed Access | Times Cited: 3
Comparative study of corrosion-based service life prediction of reinforced concrete structures using traditional and machine learning approach
Amgoth Rajender, Amiya K. Samanta, Animesh Paral
International Journal of Structural Integrity (2024)
Closed Access | Times Cited: 3
Machine learning (ML) algorithms for seismic vulnerability assessment of school buildings in high-intensity seismic zones
Muhammad Zain, Ulrike Dackermann, Lapyote Prasittisopin
Structures (2024) Vol. 70, pp. 107639-107639
Closed Access | Times Cited: 3
Influence of manufactured sand gradation and water cement ratios on compressive strength of engineered cementitious composites
N. Shanmugasundaram, S. Praveenkumar
Materials Today Proceedings (2023)
Closed Access | Times Cited: 9
Smart self-healing bacterial concrete for sustainable goal
Md Nasir Uddin, T. Tafsirojjaman, N. Shanmugasundaram, et al.
Innovative Infrastructure Solutions (2022) Vol. 8, Iss. 1
Closed Access | Times Cited: 14
Compressive strength prediction of metakaolin based high-performance concrete with machine learning
Amgoth Rajender, Amiya K. Samanta
Materials Today Proceedings (2023)
Closed Access | Times Cited: 8
Adhesive characteristics of novel greener engineered cementitious composite with conventional concrete substrate
N. Shanmugasundaram, S. Praveenkumar
Construction and Building Materials (2023) Vol. 407, pp. 133591-133591
Closed Access | Times Cited: 8
Harden and Self-Sensing Properties of Engineered Cementitious Composite Reinforced With Nano-Carbon
S. Divya, S. Praveenkumar, N. Shanmugasundaram, et al.
Advances in chemical and materials engineering book series (2024), pp. 87-105
Closed Access | Times Cited: 2
Eco-friendly modified engineered cementitious composites: a study on mechanical, durability and microstructure characteristics
N. Shanmugasundaram, S. Praveenkumar
Materials and Structures (2024) Vol. 57, Iss. 5
Closed Access | Times Cited: 2
A review on the fresh properties, mechanical and durability performance of graphene-based cement composites
Kingshuk Mukherjee, Amgoth Rajender, Amiya K. Samanta
Materials Today Proceedings (2023)
Closed Access | Times Cited: 7
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