Artificial neural network and multiple regression analysis techniques were applied in modelling the rheological behaviour ofAA6082 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.

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

SIMONCINI, MICHELA
2006-01-01

Abstract

Artificial neural network and multiple regression analysis techniques were applied in modelling the rheological behaviour ofAA6082 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.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11389/1787
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