ANN for tribological applications
Paper
Paper/Presentation Title | ANN for tribological applications |
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Presentation Type | Paper |
Authors | Nasir, Touqeer (Author), Salih, Nbhan D. (Author), Hui, Liew T. (Author), Wen, Chin Chee (Author) and Yousif, B. F. (Author) |
Editors | Ghia, Urmila |
Journal or Proceedings Title | Proceedings of the 2009 ASME International Mechanical Engineering Congress and Exposition (IMECE 2009) |
ERA Conference ID | 50899 |
Journal Citation | 14, pp. 13-16 |
Article Number | IMECE2009-10161 |
Number of Pages | 4 |
Year | 2010 |
Place of Publication | United States |
ISBN | 9780791843772 |
Digital Object Identifier (DOI) | https://doi.org/10.1115/IMECE2009-10161 |
Conference/Event | 2009 ASME International Mechanical Engineering Congress and Exposition (IMECE 2009) |
International Mechanical Engineering Congress & Exposition | |
Event Details | 2009 ASME International Mechanical Engineering Congress and Exposition (IMECE 2009) Parent ASME International Mechanical Engineering Congress and Exposition (IMECE) Event Date 13 to end of 19 Nov 2009 Event Location Florida, United States of America |
Event Details | International Mechanical Engineering Congress & Exposition IMECE |
Abstract | The current work is an attempt to investigate the possibility of using artificial neural network (ANN) modelling as a tool for friction coefficient prediction. The ANN model was trained at various configurations with different functions of training to develop the optimal ANN model. The experimental data was obtained from previous works. The results revealed that single layered model has reasonable accuracy in prediction when trained with TrainLM function. The results were acceptable especially in predicting steady-state friction coefficient, which proved ANN technologys ability to predict the friction co-efficient. |
Keywords | artificial neural network; experimental data; friction coefficients; layered model; reasonable accuracy; tribological applications; various configuration |
ANZSRC Field of Research 2020 | 401708. Tribology |
401706. Numerical modelling and mechanical characterisation | |
401204. Computational methods in fluid flow, heat and mass transfer (incl. computational fluid dynamics) | |
Public Notes | Files associated with this item cannot be displayed due to copyright restrictions. |
Byline Affiliations | National University of Computer and Emerging Sciences, Pakistan |
Multimedia University, Malaysia | |
Department of Mechanical and Mechatronic Engineering | |
Institution of Origin | University of Southern Queensland |
https://research.usq.edu.au/item/q0vx4/ann-for-tribological-applications
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