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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:

Machine learning approach for the prediction of mixed lubrication parameters for different surface topographies of non-conformal rough contacts
Deepak K. Prajapati, Jitendra Kumar Katiyar, Chander Prakash
Industrial Lubrication and Tribology (2023) Vol. 75, Iss. 9, pp. 1022-1030
Closed Access | Times Cited: 9

Showing 9 citing articles:

Predictive modeling of compressive strength for additively manufactured PEEK spinal fusion cages using machine learning techniques
Narain Kumar Sivakumar, Sabarinathan Palaniyappan, Mahdi Bodaghi, et al.
Materials Today Communications (2024) Vol. 38, pp. 108307-108307
Closed Access | Times Cited: 5
Machine Learning-Based Assessment of the Influence of Nanoparticles on Biodiesel Engine Performance and Emissions: A critical review
Chetan Pawar, B Shreeprakash, Beekanahalli Mokshanatha, et al.
Archives of Computational Methods in Engineering (2024)
Closed Access | Times Cited: 4
Enhancing practical modeling: A neural network approach for locally-resolved prediction of elastohydrodynamic line contacts
Josephine Kelley, Volker Schneider, Gerhard Poll, et al.
Tribology International (2024) Vol. 199, pp. 109988-109988
Open Access | Times Cited: 2
Effect of raceway surface topography based on solid lubrication on temperature rise characteristics of HIPSN full ceramic ball bearings
Songhua Li, Shanhang Huang, Chao Wei, et al.
Industrial Lubrication and Tribology (2024) Vol. 76, Iss. 9, pp. 1036-1047
Closed Access | Times Cited: 2
An assessment of the effect of surface topography on coefficient of friction for lubricated non-conformal contacts
Deepak K. Prajapati, Jonny Hansen, Marcus Björling
Frontiers in Mechanical Engineering (2024) Vol. 10
Open Access | Times Cited: 1
A Neural Network for Fast Modeling of Elastohydrodynamic Line Contacts
Josephine Kelley, Volker Schneider, Max Marian, et al.
(2024)
Closed Access | Times Cited: 1
Machine learning-assisted analysis of dry and lubricated tribological properties of Al–Co–Cr–Fe–Ni high entropy alloy
Saurabh Vashistha, Bashista Kumar Mahanta, Vivek K. Singh, et al.
Digital Discovery (2024)
Open Access | Times Cited: 1
Neural network–based transfer learning to improve stiffness modeling of industrial robots with small experimental data sets
Kai Wu, Yuanhui Zhang, Dehua Gao, et al.
The International Journal of Advanced Manufacturing Technology (2024)
Open Access | Times Cited: 1
Integration of machine learning prediction and optimization for determination of the coefficient of friction of textured UHMWPE surfaces
Huihui Feng, Jing Liu, Ron A.J. van Ostayen, et al.
Proceedings of the Institution of Mechanical Engineers Part J Journal of Engineering Tribology (2024)
Closed Access
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