Open Access Helper

OpenAlex Citation Counts

OpenAlex Citations Logo

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 unified model for predicting the compressive strength of recycled aggregate concrete containing supplementary cementitious materials
Tianyu Xie, Guosong Yang, Xinyu Zhao, et al.
Journal of Cleaner Production (2019) Vol. 251, pp. 119752-119752
Closed Access | Times Cited: 119

Showing 1-25 of 119 citing articles:

Predicting the compressive strength of concrete containing metakaolin with different properties using ANN
Mohammad Javad Moradi, Mohsen Khaleghi, Javid Salimi, et al.
Measurement (2021) Vol. 183, pp. 109790-109790
Closed Access | Times Cited: 152
Mix design and mechanical properties of geopolymer and alkali activated concrete: Review of the state-of-the-art and the development of a new unified approach
Tianyu Xie, Phillip Visintin, Xinyu Zhao, et al.
Construction and Building Materials (2020) Vol. 256, pp. 119380-119380
Closed Access | Times Cited: 140
Efficient estimating compressive strength of ultra-high performance concrete using XGBoost model
Ngoc-Hien Nguyen, Joaquín Abellán García, Seunghye Lee, et al.
Journal of Building Engineering (2022) Vol. 52, pp. 104302-104302
Closed Access | Times Cited: 118
Prediction of Geopolymer Concrete Compressive Strength Using Novel Machine Learning Algorithms
Ayaz Ahmad, Waqas Ahmad, Krisada Chaiyasarn, et al.
Polymers (2021) Vol. 13, Iss. 19, pp. 3389-3389
Open Access | Times Cited: 114
Evaluation of fracture processes under shear with the use of DIC technique in fly ash concrete and accurate measurement of crack path lengths with the use of a new crack tip tracking method
Grzegorz Ludwik Golewski
Measurement (2021) Vol. 181, pp. 109632-109632
Closed Access | Times Cited: 108
To predict the compressive strength of self compacting concrete with recycled aggregates utilizing ensemble machine learning models
Jesús de‐Prado‐Gil, Covadonga Palencia, Neemias Silva-Monteiro, et al.
Case Studies in Construction Materials (2022) Vol. 16, pp. e01046-e01046
Open Access | Times Cited: 94
Comparative measurements of fracture toughgness combined with visual analysis of cracks propagation using the DIC technique of concretes based on cement matrix with a highly diversified composition
Grzegorz Ludwik Golewski
Theoretical and Applied Fracture Mechanics (2022) Vol. 121, pp. 103553-103553
Open Access | Times Cited: 89
An extensive investigations on fracture parameters of concretes based on quaternary binders (QBC) by means of the DIC technique
Grzegorz Ludwik Golewski
Construction and Building Materials (2022) Vol. 351, pp. 128823-128823
Closed Access | Times Cited: 86
Assessing of water absorption on concrete composites containing fly ash up to 30 % in regards to structures completely immersed in water
Grzegorz Ludwik Golewski
Case Studies in Construction Materials (2023) Vol. 19, pp. e02337-e02337
Open Access | Times Cited: 80
Mixture optimization of mechanical, economical, and environmental objectives for sustainable recycled aggregate concrete based on machine learning and metaheuristic algorithms
Kaihua Liu, Jiakai Zheng, Shuxiong Dong, et al.
Journal of Building Engineering (2022) Vol. 63, pp. 105570-105570
Closed Access | Times Cited: 78
Concrete Composites Based on Quaternary Blended Cements with a Reduced Width of Initial Microcracks
Grzegorz Ludwik Golewski
Applied Sciences (2023) Vol. 13, Iss. 12, pp. 7338-7338
Open Access | Times Cited: 70
Mechanical properties and brittleness of concrete made by combined fly ash, silica fume and nanosilica with ordinary Portland cement
Grzegorz Ludwik Golewski
AIMS Materials Science (2023) Vol. 10, Iss. 3, pp. 390-404
Open Access | Times Cited: 69
Performance of recycled aggregate concrete with supplementary cementitious materials (fly ash, GBFS, silica fume, and metakaolin): Mechanical properties, pore structure, and water absorption
Jiabin Wang, Zhihao Che, Kaifeng Zhang, et al.
Construction and Building Materials (2023) Vol. 368, pp. 130455-130455
Closed Access | Times Cited: 65
Prediction and optimization model of sustainable concrete properties using machine learning, deep learning and swarm intelligence: A review
Shiqi Wang, Peng Xia, Keyu Chen, et al.
Journal of Building Engineering (2023) Vol. 80, pp. 108065-108065
Closed Access | Times Cited: 65
Machine learning models for predicting compressive strength of fiber-reinforced concrete containing waste rubber and recycled aggregate
Avijit Pal, Khondaker Sakil Ahmed, FM Zahid Hossain, et al.
Journal of Cleaner Production (2023) Vol. 423, pp. 138673-138673
Closed Access | Times Cited: 64
Enhancement fracture behavior of sustainable cementitious composites using synergy between fly ash (FA) and nanosilica (NS) in the assessment based on digital image processing procedure
Grzegorz Ludwik Golewski
Theoretical and Applied Fracture Mechanics (2024) Vol. 131, pp. 104442-104442
Closed Access | Times Cited: 61
Life cycle assessment of sustainable concrete with recycled aggregate and supplementary cementitious materials
Weiqi Xing, Vivian W.Y. Tam, Khoa N. Le, et al.
Resources Conservation and Recycling (2023) Vol. 193, pp. 106947-106947
Closed Access | Times Cited: 59
Multi-objective optimization of fly ash-slag based geopolymer considering strength, cost and CO2 emission: A new framework based on tree-based ensemble models and NSGA-II
Yimiao Huang, Zehui Huo, Guowei Ma, et al.
Journal of Building Engineering (2023) Vol. 68, pp. 106070-106070
Closed Access | Times Cited: 57
Multi objective optimization of recycled aggregate concrete based on explainable machine learning
Shiqi Wang, Peng Xia, Fuyuan Gong, et al.
Journal of Cleaner Production (2024) Vol. 445, pp. 141045-141045
Closed Access | Times Cited: 54
Effect of Coarse Aggregate Grading on Mechanical Parameters and Fracture Toughness of Limestone Concrete
Grzegorz Ludwik Golewski
Infrastructures (2023) Vol. 8, Iss. 8, pp. 117-117
Open Access | Times Cited: 52
Determination of Fracture Mechanic Parameters of Concretes Based on Cement Matrix Enhanced by Fly Ash and Nano-Silica
Grzegorz Ludwik Golewski
Materials (2024) Vol. 17, Iss. 17, pp. 4230-4230
Open Access | Times Cited: 42
Experimental study on the triaxial compression mechanical performance of basalt fiber-reinforced recycled aggregate concrete after exposure to high temperature
Xianggang Zhang, Youchuan Shen, Yuhui Fan, et al.
Case Studies in Construction Materials (2024) Vol. 20, pp. e03026-e03026
Open Access | Times Cited: 26
Multi-objective optimization design of recycled aggregate concrete mixture proportions based on machine learning and NSGA-II algorithm
Mengtian Fan, Yue Li, Jiale Shen, et al.
Advances in Engineering Software (2024) Vol. 192, pp. 103631-103631
Closed Access | Times Cited: 18
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
Using digital image correlation to evaluate fracture toughness and crack propagation in the mode I testing of concretes involving fly ash and synthetic nano-SiO2
Grzegorz Ludwik Golewski
Materials Research Express (2024) Vol. 11, Iss. 9, pp. 095504-095504
Open Access | Times Cited: 18
Page 1 - Next Page

Scroll to top