MetaTOC stay on top of your field, easily

BP neural network-based springback predictions during creep-age forming of aluminum alloy 2219

Proceedings of the Institution of Mechanical Engineers, Part L: Journal of Materials: Design and Applications

Published online on

Abstract

Proceedings of the Institution of Mechanical Engineers, Part L: Journal of Materials: Design and Applications, Ahead of Print.
To address the challenge of accurately predicting springback during creep-age forming (CAF) of aluminum alloy 2219, a rapid prediction method that integrates a creep-aging constitutive model, finite element analysis (FEA), and a back-propagation neural ...