No abstract

The effects of shot-peen forming on the fatigue properties of aluminum alloy samples were measured with a mechanical testing & simulation (MTS) tester in atmospheric and salt-spray environments. After shot-peen forming, the fatigue performance of the aluminum alloy sheet was significantly improved in both the atmospheric and the salt spray environment. Compared with the detail fatigue rating (DFR) value in the atmospheric environment, in the salt-spray environment, the DFR value of the original samples decreased to 110.82 MPa, decreasing by 4.47%. The DFR value of the shot-peen-forming samples decreased to 151.03 MPa, decreasing by 11.40%. Fatigue fracture characteristics demonstrate that the number of crack sources decreased after shot peening. However, the corrosion rate test in a neutral saline environment showed that the corrosion resistance of the aluminum alloy sheet decreased after shot peening. In the salt-spray environment, surface residual-stress analysis showed that there was about 30 MPa tensile stress on the original sample, and 100 MPa compressive stress on the shot-peened sample. Therefore, the improvement in the fatigue resistance of the aluminum alloy sheet after shot peening was largely due to the residual compressive stress introduced on the surface of the aluminum alloy.

Shot peening is one of the most widely used surface strengthening processes. The shot peening process involves multiple process parameters, which have a complex and interdependent impact on the peening effects, including compressive residual stress distribution and surface roughness. Accurately predicting the influence of shot peening parameters on the shot peening effect is a tough challenge in the simulation. In this paper, a shot peening simulation model is developed to investigate the influence of peening process parameters. The model encompasses material, target surface, and shot stream modeling. A method is proposed to reconstruct target surface model based on real rough surface data obtained via confocal laser scanning microscope. Unlike similar surface models, such as the Gaussian model, the reconstructed surface model replicates the peaks and valleys of the target surface along with their exact locations. A random multiple-shot model incorporating the reconstructed surface with predefined target coverage is developed via Python in Abaqus. Experimental verification on TC4 titanium alloy targets validates the simulation accuracy. The effects of peening parameters (shot velocity, density, diameter, and initial surface roughness) on residual stress distribution and surface roughness are investigated via the established model. Results reveal the significant influence of shot velocity and the relatively minor impact of other parameters. Increasing the diameter, velocity, and density of the shots result in higher residual stress levels and surface roughness. Notably, excessive initial surface roughness leads to abnormal increases in surface compressive residual stress.