Constitutive Modeling of the Hot Deformation Behavior in 6082 Aluminum Alloy
- 1. Central South University, School of Material Science and Engineering (China)
- 2. Suntown Technology Group Co., Ltd. (China)
- 3. Guangdong Fenglu Aluminum Co., Ltd. (China)
Description
The hot compressive tests of 6082 aluminum alloy were conducted on a Gleeble-3500 thermomechanical simulator at temperature ranges of 380-530 °C and strain rate range of 0.01-10 s−1. The constitutive analysis and microstructural evolution of the alloy were investigated. It was indicated that the peak stress increased with increasing strain rate and decreasing temperature. Dynamic recovery and dynamic recrystallization lead to the softening behavior of the alloy. In order to characterize the flow behavior of this alloy, some models were established based on the experimental data including the phenomenological Arrhenius-type model, the physically based Estrin and Mecking (EM) model for work hardening and dynamic recovery, and the EM model, which was combined with the Avrami equation for dynamic recrystallization. An artificial neural network model was also established to predict the flow stress. The results indicate that the Arrhenius-type model is more simple and more efficient than the EM + Avrami model. Moreover, the well-trained ANN model has the best predicting performance.
Additional details
Identifiers
Publishing Information
- Journal Title
- Journal of Materials Engineering and Performance
- Journal Volume
- 28
- Journal Issue
- 2
- Journal Page Range
- p. 981-994
- ISSN
- 1059-9495
- CODEN
- JMEPEG
Conference
- Title
- 2017 Materials Science and Technology Conference
- Dates
- 8-12 Oct 2017
- Place
- Pittsburgh, PA (United States)
INIS
- Country of Publication
- United States
- Country of Input or Organization
- International Atomic Energy Agency (IAEA)
- INIS RN
- 52010939
- Subject category
- S36: MATERIALS SCIENCE;
- Resource subtype / Literary indicator
- Conference
- Descriptors DEI
- ALUMINIUM ALLOYS; EQUATIONS; FLOW STRESS; NANOSTRUCTURES; NEURAL NETWORKS; SIMULATION; STRAIN HARDENING; STRAIN RATE
- Descriptors DEC
- ALLOYS; HARDENING; STRESSES
Optional Information
- Copyright
- Copyright (c) 2019 ASM International