Development of a post-form strength prediction model for a 6xxx aluminium alloy in a novel forming process

Abstract

Accurate prediction of the post-form strength of structural components made from 6xxx series aluminium alloys has been a challenge, especially when the alloy undergoes complex thermo-mechanical processes such as the Fast light Alloys Stamping Technology (FAST). This process involves ultra-fast heating, high temperature plastic deformation, rapid quenching and is followed by multi-stage artificial ageing heat treatment.

The strength of the material evolves with the formation of second phase precipitates during the entire process. The widely accepted precipitation sequence is SSSS - clusters - β” - β’ - β. However, due to the complexity of deformations and thermal profile during the process, the classic theory is not applicable. Therefore, in this research, precipitation behaviour during ultra-fast heating, viscoplastic behaviour, effect of residual dislocations generated during high temperature deformation, quenching sensitivity and multi-stage artificial ageing response have been comprehensively studied. A set of experiments, including ultra-fast heating tests, uniaxial tensile tests, pre-straining uniaxial tensile tests, quenching tests, artificial ageing tests and TEM observations were conducted to provide a thorough understanding of the novel forming technology.

The underlying mechanisms for the FAST process were investigated through the in-depth analysis of experimental results. ·Under ultra-fast heating conditions, most of the precipitates are dissolved and the spherical pre-β” precipitates are formed and finely dispersed in the aluminium matrix, which are beneficial to accelerate the subsequent precipitation process. ·The residual dislocations, generated during plastic deformation, strengthen the material and act as nucleation sites for precipitates. The peak strength is reduced owing to the uneven accumulation of precipitates around dislocations. ·The coarse β’ and β precipitates induced due to the insufficient quenching are detrimental to precipitation response. These quench-induced precipitates consume both solute atoms and vacancies, which are unable to be reversely transferred to the preferred needle-shaped β” precipitates.

Based on the scientific achievements, a mechanism-based unified post-form strength (PFS) prediction model was developed ab-initio to predict the strength evolution of the material during the entire complex FAST process with highly efficient computation. Constitutive equations were proposed to model the viscoplastic behaviour at elevated temperature. Important microstructural parameters, including dislocation density, volume fraction, radius of precipitates and solute concentration were correlated to predict the material strength. The particle size distribution (PSD) sub-model was further established to accurately interpret the detailed microstructural changes during the complex thermo-mechanical processes.

Furthermore, the model has been programmed into an advanced functional module ‘Tailor’ and implemented into a cloud based FEA platform. The predictive capability of the module was verified by conducting forming tests of a U-shaped component in a dedicated pilot production line. It was found that the ‘Tailor’ module was able to precisely predict the post-form strength in agreement with experiments, with a deviation of less than 7% compared to experimental results.