| nr |
titel |
auteur |
tijdschrift |
jaar |
jaarg. |
afl. |
pagina('s) |
type |
| 1 |
AI for tribology: Present and future
|
Yin, Nian
|
|
|
12 |
6 |
p. 1060-1097
|
artikel
|
| 2 |
A new 3D plastoelastohydrodynamic lubrication model for rough surfaces
|
You, Shengyu
|
|
|
12 |
6 |
p. 1176-1193
|
artikel
|
| 3 |
A new method to solve the Reynolds equation including mass-conserving cavitation by physics informed neural networks (PINNs) with both soft and hard constraints
|
Xi, Yinhu
|
|
|
12 |
6 |
p. 1165-1175
|
artikel
|
| 4 |
Atomistic understanding of rough surface on the interfacial friction behavior during the chemical mechanical polishing process of diamond
|
Yuan, Song
|
|
|
12 |
6 |
p. 1119-1132
|
artikel
|
| 5 |
Bayesian inference-based wear prediction method for plain bearings under stationary mixed-friction conditions
|
König, Florian
|
|
|
12 |
6 |
p. 1272-1282
|
artikel
|
| 6 |
Classification and spectrum optimization method of grease based on infrared spectrum
|
Feng, Xin
|
|
|
12 |
6 |
p. 1154-1164
|
artikel
|
| 7 |
Comparison-embedded evidence-CNN model for fuzzy assessment of wear severity using multi-dimensional surface images
|
Shao, Tao
|
|
|
12 |
6 |
p. 1098-1118
|
artikel
|
| 8 |
Generating synthetic as-built additive manufacturing surface topography using progressive growing generative adversarial networks
|
Seo, Junhyeon
|
|
|
12 |
6 |
p. 1283-1298
|
artikel
|
| 9 |
Guest editorial: Special Issue on Artificial Intelligence and Emerging Computational Approaches for Tribology
|
Zhang, Zhinan
|
|
|
12 |
6 |
p. 1057-1059
|
artikel
|
| 10 |
Low-viscosity oligoether esters (OEEs) as high-efficiency lubricating oils: Insight on their structure–lubricity relationship
|
Wang, Hanwen
|
|
|
12 |
6 |
p. 1133-1153
|
artikel
|
| 11 |
Modeling and prediction of tribological properties of copper/aluminum-graphite self-lubricating composites using machine learning algorithms
|
Ning, Huifeng
|
|
|
12 |
6 |
p. 1322-1340
|
artikel
|
| 12 |
Optimized Mask-RCNN model for particle chain segmentation based on improved online ferrograph sensor
|
Wang, Shuo
|
|
|
12 |
6 |
p. 1194-1213
|
artikel
|
| 13 |
Predicting the coefficient of friction in a sliding contact by applying machine learning to acoustic emission data
|
Gutierrez, Robert
|
|
|
12 |
6 |
p. 1299-1321
|
artikel
|
| 14 |
Prediction of ball-on-plate friction and wear by ANN with data-driven optimization
|
Kovalev, Alexander
|
|
|
12 |
6 |
p. 1235-1249
|
artikel
|
| 15 |
Prediction of contact resistance of electrical contact wear using different machine learning algorithms
|
Cai, Zhen-bing
|
|
|
12 |
6 |
p. 1250-1271
|
artikel
|
| 16 |
Scuffing failure analysis based on a multiphysics coupling model and experimental verification
|
Lyu, Bugao
|
|
|
12 |
6 |
p. 1214-1234
|
artikel
|
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