Plasticity evolution of an aluminum-magnesium alloy under abrupt strain path changes

Abstract

During the forming and manufacturing of engineering materials, plasticity behavior could be evolving significantly due to complex deformation history. Therefore, this study aims to characterize the plasticity evolution of an aluminum-magnesium alloy under simple monotonic and non-monotonic loading with abrupt strain path changes. Instead of focusing only on one single stress state in the first-step loading for most of the studies in the literature, the current non-monotonic strain path testing program investigates three stress states – uniaxial, plane-strain, and biaxial tension – in the first-step loading and combines them with a second-step uniaxial loading along and orthogonal to the initial loading direction. This combination generates non-monotonic stress–strain data in a quite large and distributed spectrum in terms of the Schmitt parameter. It is found that the aluminum-magnesium alloy shows a unique phenomenon with a lower yield strength at reloading compared to monotonic cases coupled with a steady increase of stress overshooting the monotonic one at large strains. This increase of stress as well as the strain hardening rate lasts till the uniform strain and is therefore referred to as permanent hardening. The comprehensive non-monotonic behavior delivered by the new experimental program in this study could further assist the development of material models and an in-depth understanding of the underlying mechanisms.

Crystal Plasticity Modeling of Al Alloy under Linear and Non-Linear Loading

“…The typical fcc rolling texture is observed with a texture index of 1.24. Detailed information microstructure characterization methods and results is referred to Lian et al [8].…”

“…This RVE is created by the software DREAM3D and can be adjusted in size and resolution. In our previous study [8], further optimization and filtering are needed to avoid exaggerated deviation of microstructure characteristics. Therefore, the microstructural representative evaluation criterion (MRAC), which can reduce the deviation to 0 [10].…”

“…2, which contains 3165 Al grains. The detailed comparisons between optimal RVE and the reference material microstructure are referred to Lian, et al [8] Fig. 2 Grain maps of the optimal RVE.…”

“…However, for aluminum alloys that can be considered as a single phase, the challenges that hinder this study are mainly from the following two aspects: i) necessary to synthesize fine microstructure models, accurately characterize the microstructure of materials and accurately control the microstructure variables, and ii) two models are used to conduct efficient and reliable calibration of aluminum alloy under different stress conditions. Lian, et al [8] developed a calibration strategy for synthetic microstructure and crystal plasticity parameters for producing fine grain structure aluminum alloys, which could systematically and quantitatively analyze the influence of microstructure characteristics.…”

Optimizing crystal plasticity model parameters via machine learning-based optimization algorithms

“…The phenomenological law defines the shear rate formula through empirical observation [2], while the law based on dislocation density derives the shear rate from physical kinetic equations that depend on material properties [3,4]. Previous studies have used these two CP models to predict different types of nonlinear loading deformation with varying success [5][6][7][8][9]. However, the process of determining the constitutive parameters for CP models has been a significant challenge, with current methods relying on either direct chemical composition [10,11], which may lack a certain level of accuracy for specific applications, or inverse fitting of fitting constitutive parameters via a manual procedure that relies on the researcher's experience and is highly subjective and time-consuming.…”