Behroozi, Mohammad

Olatunbosun, Oluremi

Yang, Xiaoguang

Finite Element (FE) analysis has become the favoured tool in the tyre industry for virtual development of tyres because of the ability to represent the detailed lay-up of the tyre carcass. However, application of FE analysis in tyre design and development is still very time-consuming and expensive. Here, the application of various Artificial Neural Network (ANN) architectures to predicting tyre performance is assessed to select the most effective and efficient architecture, to allow extensive parametric studies to be carried out inexpensively and to optimise tyre design before a much more expensive full FE analysis is used to confirm the predicted performance

University of Birmingham Research Portal

English

A Neural Network Approach to Predicting Car Tyre Micro-Scale and Macro-Scale Behaviour

Xiaoguang Yang

Mohammad Behroozi

Oluremi A. Olatunbosun

Crossref

Journal of Intelligent Learning Systems and Applications

http://pure-oai.bham.ac.uk/ws/files/18405417/JILSA_2014021411350320_Neural_network_approach_to_predicting.pdf

A Neural Network Approach to Predicting Car Tyre Micro-Scale and Macro-Scale Behaviour

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University of Birmingham Research Portal

University of Birmingham Research Portal

Crossref