Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
794486 | Journal of Materials Processing Technology | 2006 | 4 Pages |
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.
Related Topics
Physical Sciences and Engineering
Engineering
Industrial and Manufacturing Engineering
Authors
C. Bruni, A. Forcellese, F. Gabrielli, M. Simoncini,