Residual compressive stress is a critical factor affecting the performance and service life of components. The active introduction and precise control of residual compressive stress have become one of the core technical approaches to improve component reliability and extend service life. Aiming at the difficulties in optimizing shot peening process parameters and insufficient prediction accuracy of residual stress fields for GH4169D superalloy, this work adopts a combined simulation and experimental method for investigation. A multi-shot peening simulation model considering the random distribution characteristics of shot particles is established to analyze the material strain rate as well as the correlation between residual stress and plastic strain under various process conditions, and the accuracy of the random shot peening residual stress model is verified. Shot peening strengthening experiments are carried out based on the response surface methodology. The influence laws of different shot peening intensities and coverage rates on the depth distribution of the residual stress-affected layer are compared, and parametric modeling is performed for the depth distribution of the residual stress-affected layer. The results reveal that the cosine attenuation function can realize parametric modeling of residual stress fields of GH4169D superalloy under diverse shot peening processes, with the fitted determination coefficient R² greater than 0.95. These findings provide an effective method for rapid optimization of shot peening strengthening processes and accurate modeling of residual stress fields of GH4169D superalloy.

Excellent surface integrity is an eternal pursuit in high performance manufacturing, with microstructure being a crucial component of the surface integrity dataset and a key factor controlling surface properties such as fatigue and creep. The multi-physical fields generated by thermo-mechanical loads during high-speed machining act on the processed surface layer, influencing the evolution of microstructures. To investigate the microstructural evolution mechanisms of ATI718 plus during high-speed machining, cutting experiments and techniques such as Electron back scatter diffraction (EBSD), Transmission Kikuchi diffraction (TKD), and Precession electron diffraction (PED) is conducted to quantitatively analyze the microstructures in the chip shear zone and the machined surface. Subsequently, a combined finite element (FE) and cellular automata (CA) model is developed to simulate the microstructure evolution during the cutting process. The discontinuous dynamic recrystallization (DDRX) mechanism is employed to demonstrate the nucleation and growth of grains under the influence of multiple physical fields. The simulation and experimental results show similar dynamic recrystallization (DRX) grain sizes, indicating acceptable accuracy of the CA model in terms of DRX grain size. The comparison between experimental and simulation results confirms the occurrence of both continuous dynamic recrystallization (CDRX) and DDRX during the cutting process. The synergistic competition between CDRX induced grain lamellar refinement and DDRX induced grain growth emerge as the primary mechanism driving microstructural evolution. A layer of ultrafine grains, with a thickness within 20 μm, is formed on the machined surface. Results under different parameters demonstrate that the temperature has a more significant impact on the thickness of the ultrafine grain layer and the diameter of grains within the layer compared to the strain rate.