Simulation of residual stress induced by a laser peening process through inverse optimization of material models

Laser peening (LP) is a surface enhancement technique that induces compressive residual stresses in the surface regions of metallic components to increase fatigue life. Simulation of the LP process is a complex task due to the intensity of the pressure loading (order of GPa) in a very short time period (in nanoseconds). A finite element technique is used to predict the residual stresses induced by the LP process. During the LP process, strain rates could reach as high as 106 s−1, which is very high compared to conventional strain rates. A reliable material model is needed to determine the dynamic response of a material. In this work, an optimization-based approach is developed to obtain the material model constants when there is very little or no experimental data of material behavior available. The approach is presented by comparing the residual stress prediction from simulation with available experimental results for Ti–6Al–4V material. To demonstrate the consistency of the approach, LP experiments have been performed at LSP Technologies on Inconel®718 with different laser power densities, and the residual stress results are compared with the simulation. The Johnson–Cook, the Zerilli–Armstrong, and the Khan–Huang–Liang material models are used during the simulation procedure. The performance of each model is assessed by comparing the residual stress results between simulation and experiments.