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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:

Neural network integrated with symbolic regression for multiaxial fatigue life prediction
Peng Zhang, Keke Tang, Anbin Wang, et al.
International Journal of Fatigue (2024) Vol. 188, pp. 108535-108535
Closed Access | Times Cited: 9

Showing 9 citing articles:

Data-driven prediction of critical diameter for deterministic lateral displacement devices: an integrated DPD-ML approach
Shuai Liu, Peng Zhang, Anbin Wang, et al.
Engineering Applications of Computational Fluid Mechanics (2025) Vol. 19, Iss. 1
Open Access
Variance integral method for predicting in-plane biaxial fatigue life under asynchronous sinusoidal loading
Youzhi Liu, Yunlong Li, Jing-Long Zhao, et al.
International Journal of Fatigue (2025), pp. 108905-108905
Closed Access
A TCN-based feature fusion framework for multiaxial fatigue life prediction: Bridging loading dynamics and material characteristics
Peng Zhang, Keke Tang
International Journal of Fatigue (2025), pp. 108915-108915
Closed Access
A GAN-based stepwise full-field mechanical prediction model for architected metamaterials
Yujie Xiang, Jixin Hou, Xianyan Chen, et al.
International Journal of Mechanical Sciences (2024) Vol. 284, pp. 109771-109771
Closed Access | Times Cited: 2
In-plane biaxial fatigue life prediction model for high-cycle fatigue under synchronous sinusoidal loading
Youzhi Liu, Qianyang Sun, Dahai Zhang, et al.
International Journal of Fatigue (2024), pp. 108618-108618
Closed Access | Times Cited: 1
Graphical Feature Construction-Based Deep Learning Model for Fatigue Life Prediction of AM Alloys
Hao Wu, Anbin Wang, Zhiqiang Gan, et al.
Materials (2024) Vol. 18, Iss. 1, pp. 11-11
Open Access
Image-driven prediction of fatigue crack growth in metal materials via spatiotemporal neural network
J.M. Liang, Yin Yu, Yile Hu, et al.
Engineering Fracture Mechanics (2024) Vol. 310, pp. 110442-110442
Closed Access
Multiaxial Fatigue Lifetime Estimation Based on New Equivalent Strain Energy Damage Model under Variable Amplitude Loading
Zhiqiang Tao, Xiangnan Pan, Zi-Ling Zhang, et al.
Crystals (2024) Vol. 14, Iss. 9, pp. 825-825
Open Access
A fatigue perspective on damage accumulating in lithium-ion batteries under dynamic cycling
Jin Liu, Zhenghua Chang, Chunguang Chen, et al.
International Journal of Fatigue (2024), pp. 108773-108773
Closed Access
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