An experimental and numerical coupled method to predict grain refinement and mechanical properties of gradient microstructure material by shot peening

In this paper, an innovative method is proposed to predict the microstructure evolution of the material during shot peening, in which a coupled model uses the finite element method (FEM) and cellular automaton (CA) in DEFORM software. The model can obtain the macroscopic (stress-strain response) and microscopic (texture) properties of the material during shot peening. A coupled experimental and numerical method is proposed to establish the relationship between shot peening process parameters and grain size by equivalent plastic strain. The model takes into account the number of shot in the actual process on a large scale. This new coupling method enables rapid prediction of the grain size distribution of the surface layer and improvement of the constitutive model of grade materials. Then, taking aluminum alloy as the object, the grain refinement, grain size distribution, and plastic behavior induced by shot peening were investigated using this method. The results show that the stresses induced by shot peening have a significant influence on the mechanical behavior and grain size evolution of gradient materials.

Automated summary

In this paper, an innovative method combining finite element method (FEM) and cellular automaton (CA) is proposed to predict the microstructure evolution of materials during shot peening. The model can obtain both macroscopic (stress-strain response) and microscopic (texture) properties of the material. A coupled experimental and numerical approach is used to establish the relationship between shot peening process parameters and grain size. The results show that shot peening-induced stresses have a significant impact on the mechanical behavior and grain size evolution of gradient materials.