Modeling high temperature deformation characteristics of AA7020 aluminum alloy using substructure-based constitutive equations and mesh-free approximation method. (January 2019)

• Record Type: Journal Article
• Authors: Eivani, A.R.; Vafaeenezhad, H.; Nikan, O.; Zhou, J.
• Is Part Of: Mechanics of materials. Volume 129(2019)
• Page Start: 104
• Page End: 112
• Publication Date: 2019-01
• Subjects: Radial Basis Function -- Hot deformation -- Constitutive equation -- Aluminum alloy; Strength of materials -- Periodicals; Mechanics, Applied -- Periodicals; Résistance des matériaux -- Périodiques; Mécanique appliquée -- Périodiques; Mechanics, Applied; Strength of materials; Periodicals; Electronic journals; 620.11
• DOI: 10.1016/j.mechmat.2018.11.011
• Languages: English
• ISSNs: 0167-6636

Abstract

Highlights: Hot deformation behavior of the AA7020 alloy was modeled using substructure based (SSB) model. Substructure was significantly influenced by deformation parameters and degrades the predictions of the SSB model. RBF model was developed for assessing the hot deformation behavior of the alloy. The proposed RBF model can precisely predict the flow stress-strain curves of the alloy. The RBF method showed outstanding predictive potential. Abstract: This research was aimed to assess the potential of a radial basis function (RBF) approximation method against the dislocation substructure-based constitutive model in predicting high-temperature deformation behavior of the AA7020 aluminum alloy. Hot compression tests were performed over a range of strain rate of 0.1–100 s −1 and a range of temperature of 350–500 °C up to a strain of 0.6. The hot deformation behavior of the alloy was first described by a substructure kinetic-based constitutive equation, with the effects of strain, strain rate and temperature together with dynamic recovery parameters taken into consideration. A RBF approximation method was then developed to model the flow behavior of the material. The RBF model, as a kind of novel mesh-free function estimation approach, was trained and tested with the obtained datasets from the hot compression tests. The performance of the developed analytical and neural computational models was evaluated using statistical criteria. The results showed that the RBF model was more proficient and accurate in predicting the hot deformation behavior of this aluminum alloy than the substructure-based constitutive model.