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:

Predicting concrete strength through packing density using machine learning models
Pallapothu Swamy Naga Ratna Giri, Rathish Kumar Pancharathi, Rakesh Janib
Engineering Applications of Artificial Intelligence (2023) Vol. 126, pp. 107177-107177
Closed Access | Times Cited: 25

Showing 25 citing articles:

Evaluating enhanced predictive modeling of foam concrete compressive strength using artificial intelligence algorithms
Mohamed Abdellatief, Leong Sing Wong, Norashidah Md Din, et al.
Materials Today Communications (2024) Vol. 40, pp. 110022-110022
Closed Access | Times Cited: 24
Use of interpretable machine learning approaches for quantificationally understanding the performance of steel fiber-reinforced recycled aggregate concrete: From the perspective of compressive strength and splitting tensile strength
S. Y. Zhang, Wenguang Chen, Jinjun Xu, et al.
Engineering Applications of Artificial Intelligence (2024) Vol. 137, pp. 109170-109170
Closed Access | Times Cited: 21
Grey wolf optimizer integrated within boosting algorithm: Application in mechanical properties prediction of ultra high-performance concrete including carbon nanotubes
Aybike Özyüksel Çiftçioğlu, Farzin Kazemi, Torkan Shafighfard
Applied Materials Today (2025) Vol. 42, pp. 102601-102601
Closed Access | Times Cited: 1
Prediction of non-uniform shrinkage of steel-concrete composite slabs based on explainable ensemble machine learning model
Shiqi Wang, Jinlong Liu, Qinghe Wang, et al.
Journal of Building Engineering (2024) Vol. 88, pp. 109002-109002
Closed Access | Times Cited: 11
Integrating particle packing approach with ML techniques to optimise the compressive strength of RCA based concrete mixes
Pallapothu Swamy Naga Ratna Giri, Rathish Kumar Pancharathi, Layasri Midathada
Journal of Building Engineering (2024) Vol. 94, pp. 109994-109994
Closed Access | Times Cited: 7
Explainable artificial intelligence framework for FRP composites design
Mostafa Yossef, Mohamed Noureldin, Aghyad Alqabbany
Composite Structures (2024) Vol. 341, pp. 118190-118190
Open Access | Times Cited: 5
Probabilistic machine leaning models for predicting the maximum displacements of concrete-filled steel tubular columns subjected to lateral impact loading
Dade Lai, Cristoforo Demartino, Yan Xiao
Engineering Applications of Artificial Intelligence (2024) Vol. 135, pp. 108704-108704
Closed Access | Times Cited: 5
Proposal of a sequential machine learning modelling approach for optimal cementitious composites
Elyas Asadi Shamsabadi, Saeed Mohammadzadeh Chianeh, Daniel Dias‐da‐Costa
Engineering Applications of Artificial Intelligence (2025) Vol. 143, pp. 109837-109837
Open Access
Integrating Experimental Analysis and Gradient Boosting for the Durability Assessment of Lime-Based Mortar in Acidic Environment
Ali Taheri, Nima Azimi, Daniel V. Oliveira, et al.
Buildings (2025) Vol. 15, Iss. 3, pp. 408-408
Open Access
A review on properties and multi-objective performance predictions of concrete based on machine learning models
Bowen Ni, Md Zillur Rahman, Shuaicheng Guo, et al.
Materials Today Communications (2025), pp. 112017-112017
Closed Access
Exploring failure mechanisms in reinforced concrete slab-column joints: Machine learning and causal analysis
Aybike Özyüksel Çiftçioğlu
Engineering Failure Analysis (2025), pp. 109549-109549
Closed Access
Failure node prediction study of in-service tunnel concrete for sulfate attack by PSO-LSTM based on Markov correction
Kunpeng Cao, Dunwen Liu, Yu Tang, et al.
Case Studies in Construction Materials (2024) Vol. 20, pp. e03153-e03153
Open Access | Times Cited: 4
Predicting concrete strength early age using a combination of machine learning and electromechanical impedance with nano-enhanced sensors
Huang Ju, Lin Xing, Alaa H. Ali, et al.
Environmental Research (2024) Vol. 258, pp. 119248-119248
Closed Access | Times Cited: 3
Understanding and predicting micro-characteristics of ultra-high performance concrete (UHPC) with green porous lightweight aggregates: Insights from machine learning techniques
Lingyan Zhang, Wangyang Xu, Dingqiang Fan, et al.
Construction and Building Materials (2024) Vol. 446, pp. 138021-138021
Closed Access | Times Cited: 3
Determination of concrete compressive strength from surface images with the integration of CNN and SVR methods
Gaffari Çelik, Muhammet Ozdemir
Measurement (2024) Vol. 238, pp. 115331-115331
Closed Access | Times Cited: 2
Predicting bond strength of corroded reinforced concrete after high-temperature exposure: A stacking model and feature selection
Peng Ge, Ou Yang, Xugang Hua, et al.
Construction and Building Materials (2024) Vol. 456, pp. 139290-139290
Closed Access | Times Cited: 2
Prediction and prevention of concrete chloride penetration: machine learning and MICP techniques
Lianqiang Li, Van Su Le, Bingchuan Guo, et al.
Frontiers in Materials (2024) Vol. 11
Open Access | Times Cited: 1
Weather-aware energy management for unmannedaerial vehicles: a machine learning application with global data integration
Abhishek G. Somanagoudar, Walter Mérida
Engineering Applications of Artificial Intelligence (2024) Vol. 139, pp. 109596-109596
Closed Access | Times Cited: 1
Sensitivity Analysis of Influencing Factors and Two-Stage Prediction of Frost Resistance of Active-Admixture Recycled Concrete Based on Grey Theory–BPNN
Chun Lin Fu, Ming Li
Materials (2024) Vol. 17, Iss. 8, pp. 1805-1805
Open Access
Potential Utilization of Spent Coffee Waste in Permeable Concrete
Khong Sheh Ching, Siew Choo Chin
The Open Construction and Building Technology Journal (2024) Vol. 18, Iss. 1
Open Access
Predictive Methods for the Evolution of Oil Well Cement Strength Based on Porosity
Yuhao Wen, Zi Chen, Yuxuan He, et al.
Research Square (Research Square) (2024)
Open Access
Predictive methods for the evolution of oil well cement strength based on porosity
Yuhao Wen, Zi Chen, Yuxuan He, et al.
Materials and Structures (2024) Vol. 57, Iss. 10
Closed Access
Valorization of textile sludge for use as supplementary cementitious material – Benefiting processes, pozzolanic activity, and application in no-slump concrete
Igor Vieira Fernandes, Victor Marcelo Estolano de Lima, Carlos Fernando Gomes do Nascimento, et al.
Construction and Building Materials (2024) Vol. 458, pp. 139619-139619
Closed Access
Predictive modeling of rheological, mechanical and durability characteristics of hybrid fiber-reinforced self-compacting concrete
Achal Agrawal, Narayan R. Chandak
Innovative Infrastructure Solutions (2024) Vol. 9, Iss. 5
Closed Access
Cement Equivalent Factor of Ground Zeolite for Flowability, Cohesiveness, Rheological Properties and Strength of Concrete
Jiajian Chen, Wenxue Wang
KSCE Journal of Civil Engineering (2024), pp. 100012-100012
Open Access
Page 1

Scroll to top