ANN for tribological applications


Tanzim, Nasir and Nbhan, Salih and Liew, Tze Hui and Chin, Chee Wen and Yousif, B. F. (2009) ANN for tribological applications. In: ASME 2009 International Mechanical Engineering Congress and Exposition. ASME, pp. 13-16. ISBN 978-0-7918-4386-4

Full text not available from this repository.


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 technology’s ability to predict the friction co-efficient.

Item Type: Book Section
Additional Information: Volume 13: New Developments in Simulation Methods and Software for Engineering Applications; Safety Engineering, Risk Analysis and Reliability Methods; Transportation Systems Conference: ASME International Mechanical Engineering Congress and Exposition Location & Date:Lake Buena Vista, Florida, USA, November 13–19, 2009 Conference Sponsors: ASME
Subjects: Q Science > Q Science (General)
Divisions: Faculty of Information Science and Technology (FIST)
Depositing User: Ms Rosnani Abd Wahab
Date Deposited: 23 Jan 2014 03:27
Last Modified: 23 Jan 2014 03:27


Downloads per month over past year

View ItemEdit (login required)