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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:

Recent advances in machine learning-assisted fatigue life prediction of additive manufactured metallic materials: A review
Hao Wang, Shanglin Gao, Boyi Wang, et al.
Journal of Material Science and Technology (2024) Vol. 198, pp. 111-136
Closed Access | Times Cited: 31

Showing 1-25 of 31 citing articles:

Review of progress in calculation and simulation of high-temperature oxidation
Dongxin Gao, Zhao Shen, Kai Chen, et al.
Progress in Materials Science (2024) Vol. 147, pp. 101348-101348
Closed Access | Times Cited: 64
Evaluating fatigue onset in metallic materials: Problem, current focus and future perspectives
Enrico Salvati
International Journal of Fatigue (2024) Vol. 188, pp. 108487-108487
Open Access | Times Cited: 17
Critical physics informed fatigue life prediction of laser 3D printed AlSi10Mg alloys with mass internal defects
Yanan Hu, Yufeng She, Shengchuan Wu, et al.
International Journal of Mechanical Sciences (2024), pp. 109730-109730
Closed Access | Times Cited: 9
Physics-informed machine learning for loading history dependent fatigue delamination of composite laminates
Liaojun Yao, Jiexiong Wang, Mingyue Chuai, et al.
Composites Part A Applied Science and Manufacturing (2024), pp. 108474-108474
Closed Access | Times Cited: 6
A generalized machine learning framework to estimate fatigue life across materials with minimal data
Dharun Vadugappatty Srinivasan, Morteza Moradi, Panagiotis Komninos, et al.
Materials & Design (2024), pp. 113355-113355
Open Access | Times Cited: 5
Machine-Learning Synergy in High-Entropy Alloys: A Review
Sally Elkatatny, Walaa Abd‐Elaziem, Tamer A. Sebaey, et al.
Journal of Materials Research and Technology (2024) Vol. 33, pp. 3976-3997
Closed Access | Times Cited: 5
Barriers to Adoption of Artificial Intelligence in Metal Additive Manufacturing
Wayne E. King
(2025)
Closed Access
Fatigue failure mechanisms and life prediction of additive manufactured metallic lattices: a comprehensive review
Hao Xin, Dingcheng Tang, Linwei Dang, et al.
Virtual and Physical Prototyping (2025) Vol. 20, Iss. 1
Open Access
A Dual-Purpose Data-Model Interactive Framework for Multi-Sensor Selection and Prognosis
Huiqin Li, Zhengxin Zhang, Xiaosheng Si
Reliability Engineering & System Safety (2025), pp. 110904-110904
Closed Access
Study of Hybrid Machine Learning Multiaxial Low‐Cycle Fatigue Life Prediction Model of CP‐Ti
Tian‐Hao Ma, Wei Zhang, Le Chang, et al.
Fatigue & Fracture of Engineering Materials & Structures (2025)
Closed Access
Hybrid clustering-enhanced interpretable machine learning for fatigue life prediction across various cyclic stages in laser powder bed fused Ti-6Al-4V alloy
Aihua Yu, Qingjun Zhou, Yu Pan, et al.
International Journal of Fatigue (2025), pp. 108995-108995
Closed Access
Vacuum-assisted HPDC lightweight Al-based entropy alloy with ultrahigh strength and exceptional thermal stability at elevated temperatures
Wenhui Bai, Haidong Zhao, Bo Chen, et al.
Materials Science and Engineering A (2025), pp. 148363-148363
Closed Access
Using Machine Learning Methods to Predict the Ductile-to-Brittle Transition Temperature Shift in RPV Steel Under Different Pulse Current Parameters
Yating Zhang, Biqian Li, Li Shu, et al.
Acta Metallurgica Sinica (English Letters) (2025)
Closed Access
A novel fatigue life prediction method for the laser deposition repaired TA15 component with annealing heat treatment
Song Zhou, Zhaoxing Qian, Zhenjun Zhang, et al.
Engineering Failure Analysis (2025), pp. 109649-109649
Closed Access
Rapid prediction of effective absorption bandwidth in PEEK/CF additive manufacturing metastructure via interpretable machine learning
Shuailong Gao, Huaiyu Dong, Yuhui Zhang, et al.
Journal of Material Science and Technology (2025)
Closed Access
A path-dependent adaptive physics-informed neural network for multiaxial fatigue life prediction
H. Liao, Jun Pan, Xinren Su, et al.
International Journal of Fatigue (2024) Vol. 193, pp. 108799-108799
Closed Access | Times Cited: 3
Multi-objective optimization of laser powder bed fused titanium considering strength and ductility: A new framework based on explainable stacking ensemble learning and NSGA-II
Aihua Yu, Yu Pan, Fucheng Wan, et al.
Journal of Material Science and Technology (2025)
Closed Access
Fatigue Short Crack Growth Prediction of Additively Manufactured Alloy Based on Ensemble Learning
Qing Yi Huang, Dianyin Hu, Rongqiao Wang, et al.
Fatigue & Fracture of Engineering Materials & Structures (2025)
Open Access
Data-driven fatigue assessment of welded steel joints based on transfer learning
Jan Schubnell, Sascha Fliegener, Johannes Rosenberger, et al.
Welding in the World (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
Damage tolerance performance of high strength and toughness titanium alloys formed by additive manufacturing in aerospace: A review
Guozheng Liu, Qinyang Zhao, Weiju Jia, et al.
(2025), pp. 100003-100003
Open Access
Evolution behavior of competing fatigue failure and life prediction related to defect, stress and temperature for laser powder bed fused superalloy with solution aging treatment
Chuanwen Sun, Wei Li, Gang Liu, et al.
International Journal of Fatigue (2025), pp. 109029-109029
Closed Access
From mechanism empirical to physics-informed: a comprehensive review of multiaxial non-proportional low-cycle fatigue life prediction
Wanqi Yu, Xingyue Sun, Xu Chen
International Journal of Structural Integrity (2025)
Closed Access
Interpretable prediction of sample size–dependent fatigue crack formation lifetime using deep symbolic regression and polycrystalline plasticity models
Bo Dong, Tang Gu, Yong Zhang, et al.
International Journal of Fatigue (2025), pp. 109057-109057
Closed Access
Statistical analysis for the strength and thermal shock behavior of MoAlB
Hang Yin, Kebin Qin, Xiaodong He, et al.
Journal of the American Ceramic Society (2025)
Closed Access
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