A new residual stress prediction model for laser-assisted burnishing inconel718

• A fully coupled thermo-mechanical model is established to predict residual stress distribution of the laser-assisted burnishing (LAB). • The isotropic-kinematic hardening behaviors and initial residual stress were incorporated into the finite element model via the VUMAT and SIGINI user-subroutine, respectively. • The simulated results show good agreement with the overall trend of experiments results. • The effects of LAB process variables on the distribution characteristics of residual stress were discussed. • Mechanisms of residual stress formation under thermo-mechanical coupling effect were revealed. In the burnishing of nickel-based superalloy Inconel 718, the extent of surface plastic deformation and its interaction with material’s work-hardenability play a critical role in generating and distributing compressive residual stress (CRS). However, once plastic deformation exceeds a certain threshold, the work-hardened surface layer acts as a rigid shell that restricts further improvement in CRS magnitude and depth. Ductility enhancement through an in-situ thermal assistance, namely laser-assisted burnishing (LAB), is a promising solution. Designing an efficient LAB process that achieves a targeted CRS profile, however, requires a comprehensive understanding of interaction between the elastic and plastic stress states during processing that can be well identified through a physics-based model. To this regard, development a comprehensive model that can predict the distribution of residual stress in LAB process remained as an open issue that merits further studies. This work proposed a fully coupled thermo-mechanical-based finite element model to analyze the impact of LAB process factors on residual stress distribution through considering the hardening behavior during the machining process. The obtained results have been then verified using comparison of measured and predicted residual stress profile taking into account surface residual stress, magnitude and the depth of maximum CRS, and the depth a which the CRS becomes zero. It was found from the results, that over the 10 benchmark tests, the average prediction error for the foresaid residual stress indices is 8.5 %, 9.1 % and 10.3 %, respectively.