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:

Machine Learning-Based Predictive Model for Tensile and Flexural Strength of 3D-Printed Concrete
Ammar A. Ali, Raja Dilawar Riaz, Umair Jalil Malik, et al.
Materials (2023) Vol. 16, Iss. 11, pp. 4149-4149
Open Access | Times Cited: 28

Showing 1-25 of 28 citing articles:

Predictive modeling for compressive strength of 3D printed fiber-reinforced concrete using machine learning algorithms
Mana Alyami, Majid Khan, Muhammad Fawad, et al.
Case Studies in Construction Materials (2023) Vol. 20, pp. e02728-e02728
Open Access | Times Cited: 49
Inclusive characterization of 3D printed concrete (3DPC) in additive manufacturing: A detailed review
Raja Dilawar Riaz, Muhammad Usman, Ammar A. Ali, et al.
Construction and Building Materials (2023) Vol. 394, pp. 132229-132229
Closed Access | Times Cited: 36
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
A novel compressive strength estimation approach for 3D printed fiber-reinforced concrete: integrating machine learning and gene expression programming
Md Nasir Uddin, Junhong Ye, M. Aminul Haque, et al.
Multiscale and Multidisciplinary Modeling Experiments and Design (2024) Vol. 7, Iss. 5, pp. 4889-4910
Closed Access | Times Cited: 5
Machine-Learning-Based Predictive Models for Compressive Strength, Flexural Strength, and Slump of Concrete
John F. Vargas, Ana Isabel Oviedo Carrascal, Nathalia Ortega, et al.
Applied Sciences (2024) Vol. 14, Iss. 11, pp. 4426-4426
Open Access | Times Cited: 5
Static and Dynamic Behavior of Novel Y‐Shaped Sandwich Beams Subjected to Compressive Loadings: Integration of Supervised Learning and Experimentation
Ali Khalvandi, Saeed Kamarian, Mahdi Bodaghi, et al.
Advanced Engineering Materials (2025)
Open Access
Data-driven analysis in 3D concrete printing: predicting and optimizing construction mixtures
Rodrigo Teixeira Schossler, Shafi Ullah, Zaid Alajlan, et al.
AI in Civil Engineering (2025) Vol. 4, Iss. 1
Open Access
Research on 3D Printing Concrete Mechanical Properties Prediction Model Based on Machine Learning
Yonghong Zhang, Suping Cui, Bohao Yang, et al.
Case Studies in Construction Materials (2025), pp. e04254-e04254
Open Access
Empirical study and machine learning prediction of tensile strength in 3D printed eco-friendly polylactic acid
J. Nagarjun, N. Saravanakumar, S. Thirumalai Kumaran, et al.
Progress in Rubber Plastics and Recycling Technology (2025)
Closed Access
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
Emerging Applications of Machine Learning in 3D Printing
Izabela Rojek, Dariusz Mikołajewski, Marcin Kempiński, et al.
Applied Sciences (2025) Vol. 15, Iss. 4, pp. 1781-1781
Open Access
Machine learning approach to predict the early-age flexural strength of sensor-embedded 3D-printed structures
Kasra Banijamali, Mary Dempsey, Jianhua Chen, et al.
Progress in Additive Manufacturing (2025)
Open Access
Machine Learning Approaches for Predicting Mechanical Properties of Steel-Fiber-Reinforced Concrete
Huan Huang, Long Lei, Guoxin Xu, et al.
Materials Today Communications (2025), pp. 112149-112149
Closed Access
Advancing mix design prediction in 3D printed concrete: Predicting anisotropic compressive strength and slump flow
Umair Jalil Malik, Raja Dilawar Riaz, Saif Ur Rehman, et al.
Case Studies in Construction Materials (2024) Vol. 21, pp. e03510-e03510
Open Access | Times Cited: 4
Advancing Construction 3D Printing with Predictive Interlayer Bonding Strength: A Stacking Model Paradigm
Dinglue Wu, Qiling Luo, Wu-Jian Long, et al.
Materials (2024) Vol. 17, Iss. 5, pp. 1033-1033
Open Access | Times Cited: 2
Multi-objective optimization of mechanical properties of additively manufactured tri-hexagon pattern specimens using machine learning algorithms
S. N. Tandon, Raghu N. Kacker, Sanjay Kumar Singh, et al.
Progress in Additive Manufacturing (2024)
Closed Access | Times Cited: 2
Incorporating coarse aggregates into 3D concrete printing from mixture design and process control to structural behaviours and practical applications: a review
Dong An, Y.X. Zhang, Chunhui Yang
Virtual and Physical Prototyping (2024) Vol. 19, Iss. 1
Open Access | Times Cited: 2
Augmented Data-Driven Approach towards 3D Printed Concrete Mix Prediction
Saif Rehman, Raja Dilawar Riaz, Muhammad Usman, et al.
Applied Sciences (2024) Vol. 14, Iss. 16, pp. 7231-7231
Open Access | Times Cited: 2
A predictive mimicker for mechanical properties of eco-efficient and sustainable bricks incorporating waste glass using machine learning
Sikandar Ali Khokhar, Adil Khan, A. B. Siddique, et al.
Case Studies in Construction Materials (2023) Vol. 19, pp. e02424-e02424
Open Access | Times Cited: 6
Performance Comparison of Artificial Neural Network and Random Forest Models for Predicting the Compressive Strength of Fibre-Reinforced GGBS-Based Geopolymer Concrete Composites
Shimol Philip, M. Nidhi
Materials Circular Economy (2024) Vol. 6, Iss. 1
Closed Access | Times Cited: 1
Material Extrusion Filament Width and Height Prediction via Design of Experiment and Machine Learning
Xiaoquan Shi, Yazhou Sun, Tian Haiying, et al.
Micromachines (2023) Vol. 14, Iss. 11, pp. 2091-2091
Open Access | Times Cited: 4
Machine learning applications in the development of sustainable building materials to reduce carbon emission
Sikandar Ali Khokhar, Mati Ullah Shah, Fazal Rehman, et al.
Elsevier eBooks (2024), pp. 93-121
Closed Access | Times Cited: 1
Evaluation of Predictive Models for Mechanical Properties of Earth-Based Composites for Sustainable Building Applications
Ifeyinwa Ijeoma Obianyo, Azikiwe Peter Onwualu, Assia Aboubakar Mahamat
Studies in systems, decision and control (2024), pp. 179-190
Closed Access | Times Cited: 1
Polymer material framework for 3D printing using fusion deposition modelling
M K Aravindan, Kumud Kant Awasthi, Prabha Shreeraj Nair, et al.
Progress in Additive Manufacturing (2024)
Closed Access | Times Cited: 1
Development of Prediction Method for Dimensional Stability of 3D-Printed Objects
Kyung‐Eun Min, Jaewon Jang, Je-Sik Shin, et al.
Applied Sciences (2023) Vol. 13, Iss. 19, pp. 11027-11027
Open Access | Times Cited: 3
Page 1 - Next Page

Scroll to top