A review of advances in tribology in 2020–2021
Y Meng, J Xu, L Ma, Z Jin, B Prakash, T Ma, W Wang - Friction, 2022 - Springer
Abstract Around 1,000 peer-reviewed papers were selected from 3,450 articles published
during 2020–2021, and reviewed as the representative advances in tribology research …
during 2020–2021, and reviewed as the representative advances in tribology research …
The role of machine learning in tribology: A systematic review
The machine learning (ML) approach, motivated by artificial intelligence (AI), is an inspiring
mathematical algorithm that accurately simulates many engineering processes. Machine …
mathematical algorithm that accurately simulates many engineering processes. Machine …
Machine learning based layer roughness modeling in robotic additive manufacturing
Abstract Wire Arc Additive Manufacturing (WAAM) is a manufacturing technique that
deposits metal layer upon layer to manufacture 3D parts based on welding processes. Most …
deposits metal layer upon layer to manufacture 3D parts based on welding processes. Most …
Hybrid artificial neural network based on a metaheuristic optimization algorithm for the prediction of reservoir temperature using hydrogeochemical data of different …
Due to the increase in the changes in global climate in recent years and the depletion of
fossil fuels, the interest in renewable energy sources in many developed countries is …
fossil fuels, the interest in renewable energy sources in many developed countries is …
A novel hybrid multilayer perceptron neural network with improved grey wolf optimizer
O Altay, E Varol Altay - Neural Computing and Applications, 2023 - Springer
The multilayer perceptron (MLP), a type of feed-forward neural network, is widely used in
various artificial intelligence problems in the literature. Backpropagation is the most common …
various artificial intelligence problems in the literature. Backpropagation is the most common …
Solid particle erosion prediction in elbows based on machine learning and swarm intelligence algorithm
Continuous impact of solid particles causes severe pipeline wear, and may result in leakage
in directional change areas such as elbows. Accurate prediction of erosion is essential in the …
in directional change areas such as elbows. Accurate prediction of erosion is essential in the …
AI for tribology: Present and future
With remarkable learning capabilities and swift operational speeds, artificial intelligence (AI)
can assist researchers in swiftly extracting valuable patterns, trends, and associations from …
can assist researchers in swiftly extracting valuable patterns, trends, and associations from …
Process modeling and parameter optimization of surface coatings using artificial neural networks (ANNs): State-of-the-art review
UMR Paturi, S Cheruku, SR Geereddy - Materials Today: Proceedings, 2021 - Elsevier
Thin-film coatings and surface engineering procedures have a significant role in developing
materials with extended mechanical, thermal and tribological properties. Advancement in …
materials with extended mechanical, thermal and tribological properties. Advancement in …
Optimization and prediction of tribological behaviour of filled polytetrafluoroethylene composites using Taguchi Deng and hybrid support vector regression models
This study presents optimization and prediction of tribological behaviour of filled
polytetrafluoroethylene (PTFE) composites using hybrid Taguchi and support vector …
polytetrafluoroethylene (PTFE) composites using hybrid Taguchi and support vector …
Interpretable ensemble machine learning framework to predict wear rate of modified ZA-27 alloy
This study investigates the impact of adding manganese (Mn) to ZA-27 alloy on
microstructure and tribological properties. The Mn content varied from 0.2% to 1 …
microstructure and tribological properties. The Mn content varied from 0.2% to 1 …