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Prediction of temperature and velocity distributions during hot rolling using finite elements and neural network

Serajzadeh, S ; Sharif University of Technology | 2006

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  1. Type of Document: Article
  2. DOI: 10.1243/09544054JEM493
  3. Publisher: 2006
  4. Abstract:
  5. Temperature and velocity distributions during hot strip rolling of a low-alloy steel are determined using a finite element method together with a neural network model. The finite element method is utilized to solve the governing equations of heat conduction and plastic deformation; at the same time a neural network model is employed for assessing flow stress of the metal being deformed. In this way, the effects of temperature, strain, and strain rate on flow stress could be included in the finite element analysis. In order to examine validity of the mathematical model, laboratory hot rolling experiments are carried out where the surface temperature and roll force are recorded. Comparison between the experimental and the predicted results shows a good consistency. © 2006 IMechE
  6. Keywords:
  7. Effects of temperature ; Finite Element ; Finite element analysis ; Flow stress ; Flow stress modelling ; Governing equations ; Hot-strip rolling ; Low alloy steels ; Neural network model ; On flow ; Roll force ; Surface temperatures ; Conducting polymers ; Hot rolling ; Hot rolling mills ; Metal analysis ; Metal working ; Neural networks ; Plastic flow ; Strain rate ; Strip metal ; Velocity control ; Finite element method
  8. Source: Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture ; Volume 220, Issue 7 , 2006 , Pages 1069-1075 ; 09544054 (ISSN)
  9. URL: https://journals.sagepub.com/doi/10.1243/09544054JEM493