Numerical study on laser shock peening of TC4 titanium alloy based on the plate and blade model

Abstract

The compressive residual stresses and grain refinement induced by laser shock peening (LSP) are two very important surface strengthening mechanisms that are responsible for the significant improvements of the mechanical property and fatigue performance of metallic materials. A computation framework linking the dislocation-mechanism-based constitutive model with the dislocation density evolution model was developed and implemented into ABAQUS/Explicit code for numerical simulations of the residual stresses and grain refinement induced by LSP of TC4 titanium alloy. Two kinds of three-dimensional finite element models involving the plate model and TC4 blade model were respectively created to simulate the multi-LSP processes, and the effect of laser spot overlap ratio was accordingly investigated in detail. The obtained results show that with the increase of laser spot overlap ratio, the depths of both the compressive residual stresses and grain refinement increase, and with respect to the same depth, the compressive residual stresses increase and the refined cell size decreases. An attempt was made to employ the artificial neural networks (ANNs) to estimate the residual stresses and grain refinement induced by LSP of the whole TC4 blade model, and the ANNs-estimation approach presents the excellent efficiency in predicting the multi-LSPed results with inexpensive cost of numerical computation.