Ausgabe 6/2024
Special Issue on Artificial Intelligence and Emerging Computational Approaches for Tribology
Inhalt (16 Artikel)
Guest editorial: Special Issue on Artificial Intelligence and Emerging Computational Approaches for Tribology
Zhinan Zhang, Shuaihang Pan, Bart Raeymaekers
AI for tribology: Present and future
Nian Yin, Pufan Yang, Songkai Liu, Shuaihang Pan, Zhinan Zhang
Comparison-embedded evidence-CNN model for fuzzy assessment of wear severity using multi-dimensional surface images
Tao Shao, Shuo Wang, Qinghua Wang, Tonghai Wu, Zhifu Huang
Atomistic understanding of rough surface on the interfacial friction behavior during the chemical mechanical polishing process of diamond
Song Yuan, Xiaoguang Guo, Hao Wang, Renke Kang, Shang Gao
Low-viscosity oligoether esters (OEEs) as high-efficiency lubricating oils: Insight on their structure–lubricity relationship
Hanwen Wang, Ying Wang, Ping Wen, Lin Ma, Mingjin Fan, Rui Dong, Chunhua Zhang
Classification and spectrum optimization method of grease based on infrared spectrum
Xin Feng, Yanqiu Xia, Peiyuan Xie, Xiaohe Li
A new method to solve the Reynolds equation including mass-conserving cavitation by physics informed neural networks (PINNs) with both soft and hard constraints
Yinhu Xi, Jinhui Deng, Yiling Li
A new 3D plastoelastohydrodynamic lubrication model for rough surfaces
Shengyu You, Jinyuan Tang, Qiang Wang
Optimized Mask-RCNN model for particle chain segmentation based on improved online ferrograph sensor
Shuo Wang, Miao Wan, Tonghai Wu, Zichen Bai, Kunpeng Wang
Scuffing failure analysis based on a multiphysics coupling model and experimental verification
Bugao Lyu, Xianghui Meng, Jiabao Yin, Yi Cui, Chengen Wang
Prediction of ball-on-plate friction and wear by ANN with data-driven optimization
Alexander Kovalev, Yu Tian, Yonggang Meng
Prediction of contact resistance of electrical contact wear using different machine learning algorithms
Zhen-bing Cai, Chun-lin Li, Lei You, Xu-dong Chen, Li-ping He, Zhong-qing Cao, Zhi-nan Zhang
Bayesian inference-based wear prediction method for plain bearings under stationary mixed-friction conditions
Florian König, Florian Wirsing, Georg Jacobs, Rui He, Zhigang Tian, Ming J. Zuo
Generating synthetic as-built additive manufacturing surface topography using progressive growing generative adversarial networks
Junhyeon Seo, Prahalada Rao, Bart Raeymaekers
Predicting the coefficient of friction in a sliding contact by applying machine learning to acoustic emission data
Robert Gutierrez, Tianshi Fang, Robert Mainwaring, Tom Reddyhoff
Modeling and prediction of tribological properties of copper/aluminum-graphite self-lubricating composites using machine learning algorithms
Huifeng Ning, Faqiang Chen, Yunfeng Su, Hongbin Li, Hengzhong Fan, Junjie Song, Yongsheng Zhang, Litian Hu