• Title of article

    Modelling of the rheological behaviour of aluminium alloys in multistep hot deformation using the multiple regression analysis and artificial neural network techniques

  • Author/Authors

    C. Bruni، نويسنده , , A. Forcellese، نويسنده , , A. F. GABRIELLI، نويسنده , , M. Simoncini، نويسنده ,

  • Issue Information
    روزنامه با شماره پیاپی سال 2006
  • Pages
    4
  • From page
    323
  • To page
    326
  • Abstract
    Artificial neural network and multiple regression analysis techniques were applied in modelling the rheological behaviour of AA 6082 aluminium alloy under multistep hot deformation conditions. To this end, multistage torsion tests were carried out in order to obtain the experimental data to be used in the development of the predictive models. The envelope curves predicted by both the ANN- and MRA-based models have shown an excellent fit, in terms of curve shape and stress level, with the experimental ones obtained under the same process conditions, even if the ANN based model has provided the best predictive capability.
  • Keywords
    Multistep deformation test , Artificial neural network , Multiple regression analysis , Flow modelling
  • Journal title
    Journal of Materials Processing Technology
  • Serial Year
    2006
  • Journal title
    Journal of Materials Processing Technology
  • Record number

    1180242