Abstract
Abstract
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.