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 self-supervised learning framework based on physics-informed and convolutional neural networks to identify local anisotropic permeability tensor from textiles 2D images for filling pattern prediction
John M. Hanna, José V. Aguado, Sébastien Comas-Cardona, et al.
Composites Part A Applied Science and Manufacturing (2024) Vol. 179, pp. 108019-108019
Open Access | Times Cited: 7
John M. Hanna, José V. Aguado, Sébastien Comas-Cardona, et al.
Composites Part A Applied Science and Manufacturing (2024) Vol. 179, pp. 108019-108019
Open Access | Times Cited: 7
Showing 7 citing articles:
Application of machine learning for composite moulding process modelling
Yuqi Wang, Shunjian Xu, Kyaw Hlaing Bwar, et al.
Composites Communications (2024) Vol. 48, pp. 101960-101960
Open Access | Times Cited: 39
Yuqi Wang, Shunjian Xu, Kyaw Hlaing Bwar, et al.
Composites Communications (2024) Vol. 48, pp. 101960-101960
Open Access | Times Cited: 39
Comprehensive Composite Mould Filling Pattern Dataset for Process Modelling and Prediction
Boon Xian Chai, Jinze Wang, Thanh Kim Mai Dang, et al.
Journal of Composites Science (2024) Vol. 8, Iss. 4, pp. 153-153
Open Access | Times Cited: 23
Boon Xian Chai, Jinze Wang, Thanh Kim Mai Dang, et al.
Journal of Composites Science (2024) Vol. 8, Iss. 4, pp. 153-153
Open Access | Times Cited: 23
The accurate prediction and further optimization of thermal conductivity for 3D fully ceramic microencapsulated fuel via graph convolutional neural network
Jianhua Hou, Zhanpeng Gong, Xiangdong Ding, et al.
Materials Today Communications (2025) Vol. 42, pp. 111557-111557
Closed Access
Jianhua Hou, Zhanpeng Gong, Xiangdong Ding, et al.
Materials Today Communications (2025) Vol. 42, pp. 111557-111557
Closed Access
An inverse design framework for optimizing tensile strength of composite materials based on a CNN surrogate for the phase field fracture model
Yuxiang Gao, Ravindra Duddu, Soheil Kolouri, et al.
Composites Part A Applied Science and Manufacturing (2025), pp. 108758-108758
Open Access
Yuxiang Gao, Ravindra Duddu, Soheil Kolouri, et al.
Composites Part A Applied Science and Manufacturing (2025), pp. 108758-108758
Open Access
Sensitivity analysis using Physics-informed neural networks
John M. Hanna, José Vicente Aguado, Sébastien Comas-Cardona, et al.
Engineering Applications of Artificial Intelligence (2024) Vol. 135, pp. 108764-108764
Open Access | Times Cited: 4
John M. Hanna, José Vicente Aguado, Sébastien Comas-Cardona, et al.
Engineering Applications of Artificial Intelligence (2024) Vol. 135, pp. 108764-108764
Open Access | Times Cited: 4
Real-time Bayesian inversion in resin transfer moulding using neural surrogates
M.E. Causon, Marco Iglesias, M.Y. Matveev, et al.
Composites Part A Applied Science and Manufacturing (2024) Vol. 185, pp. 108355-108355
Open Access | Times Cited: 1
M.E. Causon, Marco Iglesias, M.Y. Matveev, et al.
Composites Part A Applied Science and Manufacturing (2024) Vol. 185, pp. 108355-108355
Open Access | Times Cited: 1
Comparative research of flow in tube bundle: Source term method and pressure drop method
Yinhui Che, Shuai Zu, Lijun Huang
Process Safety and Environmental Protection (2024) Vol. 204, pp. 390-399
Closed Access
Yinhui Che, Shuai Zu, Lijun Huang
Process Safety and Environmental Protection (2024) Vol. 204, pp. 390-399
Closed Access
