Predictive Crack Growth Technique for Laser Peening Process Development

Abstract

Laser peening (LP) has shown excellent fatigue life extension in numerous tests with typical treatments garnering 2-4 times the fatigue performance of an untreated component. Initially, large test programs were implemented to determine the best LP parameters for a given scenario, eventually being augmented by physics-based modeling due to the large design space available to the LP process. Approval for these processes continues to be on a case-by-case basis, contingent on multiple factors: cost, applicability, time, % fatigue life extension, and ability to track crack growth. Because LP induces compressive residual stresses in the near surface region, the compensatory tensile residual stresses are shifted sub-surface. While an axial tensile load would be mitigated by surface compressive stresses, sub-surface a crack can propagate rapidly via tensile stresses. Current predictive methods lack the ability to track this sub-surface behavior, limiting the accuracy of fatigue crack growth predictions throughout the various design stages of an LP treatment. This work demonstrates a framework that incorporates user-defined geometry, material data, crack growth data, mechanical loading, and residual stresses to predict the crack front shape evolution in 3D solids. A baseline case with no residual stresses is simulated and compared with a closed form solution.