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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:

On the integration of domain knowledge and branching neural network for fatigue life prediction with small samples
Lei Gan, Hao Wu, Zheng Zhong
International Journal of Fatigue (2023) Vol. 172, pp. 107648-107648
Closed Access | Times Cited: 15

Showing 15 citing articles:

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: 11
Machine learning-based fatigue life prediction of lamellar titanium alloys: A microstructural perspective
Y. Zhao, Yujie Xiang, Keke Tang
Engineering Fracture Mechanics (2024) Vol. 303, pp. 110106-110106
Closed Access | Times Cited: 9
High-cycle and very-high-cycle fatigue life prediction in additive manufacturing using hybrid physics-informed neural networks
Isaac Abiria, Chan Wang, Qicheng Zhang, et al.
Engineering Fracture Mechanics (2025), pp. 111026-111026
Closed Access | Times Cited: 1
Recent developments and future trends in fatigue life assessment of additively manufactured metals with particular emphasis on machine learning modeling
Zhixin Zhan, Xiaofan He, Dingcheng Tang, et al.
Fatigue & Fracture of Engineering Materials & Structures (2023) Vol. 46, Iss. 12, pp. 4425-4464
Closed Access | Times Cited: 21
Design and development of coating for metallic bipolar plates in proton exchange membrane fuel cell (PEMFC): A review
Jiansheng Liu, Lijie Zhang, Bin Yuan, et al.
Materials & Design (2024), pp. 113338-113338
Open Access | Times Cited: 4
Prediction of multiaxial fatigue life with a data-driven knowledge transfer model
Lei Gan, Zhi‐Ming Fan, Hao Wu, et al.
International Journal of Fatigue (2024), pp. 108636-108636
Closed Access | Times Cited: 4
Long-term creep life prediction of P91 steel using domain knowledge and back propagation artificial neural network
Chaolu Song, Xing-Jing Liu, Lin Zhu, et al.
Materials at High Temperatures (2025), pp. 1-11
Closed Access
A data-informed knowledge discovery framework to predict fatigue properties of additively manufactured Ti–6Al–4V, IN718 and AlSi10Mg alloys using fatigue databases
Samuel Onimpa Alfred, Mehdi Amiri
Progress in Additive Manufacturing (2025)
Open 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 deep neural network approach combined with Findley parameter to predict fretting fatigue crack initiation lifetime
Sutao Han, Can Wang, Samir Khatir, et al.
International Journal of Fatigue (2023) Vol. 176, pp. 107891-107891
Open Access | Times Cited: 7
Research on vacuum glass insulation performance prediction based on unsteady state multivariate data screening and multi-model fusion self-optimization
Xiaoling Li, Yuanqi Wang, Fuquan Zhou, et al.
Engineering Applications of Artificial Intelligence (2024) Vol. 133, pp. 108237-108237
Closed Access | Times Cited: 2
A stacking ensemble model for predicting the flexural fatigue life of fiber-reinforced concrete
Wan-lin Min, Weiliang Jin, Yen-yi Hoo, et al.
International Journal of Fatigue (2024) Vol. 190, pp. 108599-108599
Closed Access | Times Cited: 1
Physical hierarchical neural network for low cycle fatigue life prediction of compacted graphite cast iron based on small data
Guoxi Jing, Tian Ma, Zengquan Wang, et al.
International Journal of Fatigue (2024) Vol. 188, pp. 108509-108509
Closed Access | Times Cited: 1
Development and performance of data-driven models for the prediction of the high-temperature fatigue life of alloy 617
J. Avila Molina, Ondrej Muránsky, L. Bortolan Neto, et al.
International Journal of Pressure Vessels and Piping (2023) Vol. 206, pp. 105022-105022
Open Access | Times Cited: 1
Multiaxial fatigue life prediction based on modular neural network pretrained with uniaxial fatigue data
Lei Gan, Anbin Wang, Zheng Zhong, et al.
Engineering Computations (2024)
Closed Access
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