Modeling Hot Rolling Based on RBF Neural Networks and Thermo-Mechanical Coupling FEM

Zhi Qiang Xiong; You Rong Li; Hong Zhang; Hong Mei Li; Chang Ming Liu

doi:10.4028/www.scientific.net/AMR.443-444.9

Paper Titles

Preface and Organizing Committee

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Modeling Hot Rolling Based on RBF Neural Networks and Thermo-Mechanical Coupling FEM
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Influence of Inner Rubber Bushing Stiffness of the Lateral Rod on Rear Multi-Link Suspension Performance
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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 443-444Modeling Hot Rolling Based on RBF Neural Networks...

Modeling Hot Rolling Based on RBF Neural Networks and Thermo-Mechanical Coupling FEM

Abstract:

In the modeling of rolling process, the result from FEM is influenced by the accuracy of the resistance of deformation model of material which is often from the experiment using isothermal compression at elevated temperatures. But the state under high temperature is unstable in lab. And the flow stress model under the lab condition is not consistent to the hot rolling field condition. This paper will employ the RBF artificial neural networks to train the random sample from the field data and get the relation between the rolling force and the parameters of hot rolling. The array of the rolling force and temperature under special condition can be then obtained and the resistance of deformation model will be built by applying the S.EKLUND formula. Finally, the thermo-mechanical coupling FEM with the resistance of deformation model got from RBF method is used to simulate the hot rolling process. The simulated experiment shows the modeling data is fit to the field data.

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Periodical:

Advanced Materials Research (Volumes 443-444)

Pages:

9-14

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.443-444.9

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Online since:

January 2012

Authors:

Zhi Qiang Xiong, You Rong Li, Hong Zhang, Hong Mei Li, Chang Ming Liu

Keywords:

Finite Element Method (FEM), Hot Rolling, RBF, Resistance of Deformation

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