Open Access Helper

OpenAlex Citation Counts

OpenAlex Citations Logo

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:

Triboinformatic modeling of the friction force and friction coefficient in a cam-follower contact using machine learning algorithms
Hasan Baş, Yunus Emre Karabacak
Tribology International (2023) Vol. 181, pp. 108336-108336
Closed Access | Times Cited: 15

Showing 15 citing articles:

AI for tribology: Present and future
Nian Yin, Pufan Yang, Songkai Liu, et al.
Friction (2024) Vol. 12, Iss. 6, pp. 1060-1097
Open Access | Times Cited: 17
Machine learning-based prediction of friction torque and friction coefficient in statically loaded radial journal bearings
Hasan Baş, Yunus Emre Karabacak
Tribology International (2023) Vol. 186, pp. 108592-108592
Closed Access | Times Cited: 24
Laboratory investigation of GO-SA-MWCNTs ternary hybrid nanoparticles efficacy on dynamic viscosity and wear properties of oil (5W30) and modeling based on machine learning
Mojtaba Sepehrnia, Somayeh Davoodabadi Farahani, Abolfazl Hamidi Arani, et al.
Scientific Reports (2023) Vol. 13, Iss. 1
Open Access | Times Cited: 9
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
Wear on steel tillage tools: A review of material, soil and dynamic conditions
Aysel Yazıcı
Soil and Tillage Research (2024) Vol. 242, pp. 106161-106161
Closed Access | Times Cited: 3
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
Machine-learning-based modeling of saturated flow boiling in pin-fin micro heat sinks with expanding flow passages
Burak Markal, Yunus Emre Karabacak, Alperen Evcimen
International Communications in Heat and Mass Transfer (2024) Vol. 158, pp. 107870-107870
Closed Access | Times Cited: 2
Prediction of friction coefficient and torque in self-lubricating polymer radial bearings produced by additive manufacturing: A machine learning approach
Hasan Baş, Yunus Emre Karabacak
Proceedings of the Institution of Mechanical Engineers Part J Journal of Engineering Tribology (2023) Vol. 237, Iss. 11, pp. 2014-2038
Closed Access | Times Cited: 4
Data-driven design of brake pad composites for high-speed trains
Lingzhi Wu, Peng Zhang, Bin Xu, et al.
Journal of Materials Research and Technology (2023) Vol. 27, pp. 1058-1071
Open Access | Times Cited: 4
Adaptive torque control of wet dual clutch based on dynamic friction coefficient estimation
Antai Li, Datong Qin, Zheng Guo
Mechatronics (2024) Vol. 100, pp. 103175-103175
Closed 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
Investigating the Effects of Oil Additives on the Tribological Performance of Hydrodynamic Journal Bearings: A Study With Hazelnut Oil in Boundary and Mixed Lubrication Regimes
Hasan Baş, Yunus Emre Karabacak
Lubrication Science (2024)
Closed Access
Tribo-Dynamics Digital Twins (TDDTs): Prediction of Friction and Frequency Response Function (FRF) in a Dry Sliding Tribological Contact
Saeid Taghizadeh, Matthew S. Bonney, David Wagg, et al.
Conference proceedings of the Society for Experimental Mechanics (2024), pp. 101-110
Closed Access
Data-Driven Prediction of COF in Wet Friction Components: A Model Development and Interpretability Analysis
Jianpeng Wu, Peng Zhao, Jiahao Cui, et al.
Journal of Tribology (2024) Vol. 147, Iss. 7
Closed Access
Data-driven friction modeling and compensation for rotary servo actuators
Baoyu Li, Xin Xie, Bin Yu, et al.
Frontiers of Mechanical Engineering (2024) Vol. 19, Iss. 6
Closed Access
Page 1

Scroll to top