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OpenAlex Citation Counts

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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:

A neural network-based material cell for elastoplasticity and its performance in FE analyses of boundary value problems
Shaoheng Guan, Xue Zhang, Sascha Ranftl, et al.
International Journal of Plasticity (2023) Vol. 171, pp. 103811-103811
Open Access | Times Cited: 11

Showing 11 citing articles:

Physics-informed Neural Networks (PINN) for computational solid mechanics: Numerical frameworks and applications
Haoteng Hu, Lehua Qi, Xujiang Chao
Thin-Walled Structures (2024) Vol. 205, pp. 112495-112495
Closed Access | Times Cited: 19
A Hybrid Finite Element Implementation of Two-Potential Constitutive Model of Dielectric Elastomers
Kamalendu Ghosh, Bhavesh Shrimali
(2025)
Closed Access
Extended Minimal State Cells (EMSC): Self-Consistent Recurrent Neural Networks for Rate- and Temperature Dependent Plasticity
Julian N. Heidenreich, Dirk Mohr
International Journal of Plasticity (2025), pp. 104305-104305
Closed Access
Review of empowering computer-aided engineering with artificial intelligence
Xuwen Zhao, Xingyu Tong, Fangwei Ning, et al.
Advances in Manufacturing (2025)
Open Access
Study on Tensile Properties of Q235B / Q345qE Dissimilar Steel T‐joints
Jiangning Pei, Shuai Dong, Xinzhi Wang, et al.
ce/papers (2025) Vol. 8, Iss. 2, pp. 160-171
Closed Access
Distinguish the calibration of conventional and data-driven constitutive model: the role of state boundary surfaces
Zhihui Wang, Roberto Cudmani, Andrés Alfonso Peña Olarte
Journal of the Mechanics and Physics of Solids (2025), pp. 106122-106122
Closed Access
Identification of failure behaviors of underground structures under dynamic loading using machine learning
Chun Zhu, Yingze Xu, Manchao He, et al.
Journal of Rock Mechanics and Geotechnical Engineering (2024)
Open Access | Times Cited: 2
Machine learning-based constitutive modelling for material non-linearity: A review
Arif Hussain, Amir Hosein Sakhaei, Mahmood Shafiee
Mechanics of Advanced Materials and Structures (2024), pp. 1-19
Open Access | Times Cited: 2
Estimation of macroscopic failure strength of heterogeneous geomaterials containing inclusion and pore with artificial neural network approach
Jing Xue, Yajun Cao, Zhen‐Yu Yin, et al.
Computers and Geotechnics (2024) Vol. 170, pp. 106294-106294
Open Access | Times Cited: 1
Machine Learning Aided Modeling of Granular Materials: A Review
Mengqi Wang, Krishna Kumar, Y.T. Feng, et al.
Archives of Computational Methods in Engineering (2024)
Open Access | Times Cited: 1
Training of a Physics-based Thermo-Viscoplasticity Model on Big Data for Polypropylene
Benoit Jordan, Dirk Mohr
International Journal of Plasticity (2024), pp. 104179-104179
Open Access
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