Abstract
Plastic anisotropy may strongly affect the stress and strain response in metals subjected to multiaxial cyclic loading. This anisotropy evolves due to various microstructural features. We first use simple models to study how such features result in evolving plastic anisotropy. A subsequent analysis of existing distortional hardening models highlights the difference between stress- and strain-driven models. Following this analysis, we conclude that the stress-driven approach is most suitable and propose an improved stress-driven model. It is thermodynamically consistent and guarantees yield surface convexity. Many distortional hardening models in the literature do not fulfill the latter. In contrast, the model proposed in this work has a convex yield surface independent of its parameter values. Experimental results, considering yield surface evolution after large shear strains, are used to assess the model’s performance. We carefully analyze the experiments in the finite strain setting, showing how the numerical results can be compared with the experimental results. The new model fits the experimental results significantly better than its predecessor without introducing additional material parameters.
Highlights
Capturing the evolving plastic anisotropy is essential in several industrial applications, such as sheet metal forming and rolling contact fatigue in railways
The ability of three different models to fit and predict the experimental results are described
These were based on simple numerical examples, highlighting the deformation processes that occur in the microstructure of pearlitic steels
Summary
Capturing the evolving plastic anisotropy is essential in several industrial applications, such as sheet metal forming and rolling contact fatigue in railways. The foundation for modeling evolving anisotropy is found in earlier models that only consider a fixed anisotropy case, such as Papadopoulos and Lu (2001). Several different models that describe the evolution of plastic anisotropy have been presented in the literature. These models range from micro-mechanical, via micro-mechanically motivated, to purely phenomenological models. Despite many recent efforts to decrease the computational costs, see e.g. Wicht et al (2020), they are still too computationally demanding for many industrial applications. The models discussed in the present work are, mainly micro-mechanically motivated or purely phenomenological
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