Laser shock peening has become a commonly applied industrial surface treatment, particularly for high-strength steel and titanium components. Effective application to aluminum alloys, especially in the thin sections common in aerospace structures, has proved more challenging. Previous work has shown that some peening conditions can introduce at-surface tensile residual stress in thin Al sections. In this study, we employ finite element modeling to identify the conditions that cause this to occur, and show how these adverse effects can be mitigated through selection of peen parameters and patterning.

PurposeThe purpose of this paper is to develop and implement a structural fatigue life estimation framework that includes laser‐peened (LP) residual stresses and then experimentally validates these fatigue life estimations.Design/methodology/approachA three‐dimensional finite element analysis of an Al 7075‐O three‐point bending coupon being LP was created and used to estimate the fatigue life when loaded. Fatigue tests were conducted to validate these estimations.FindingsThe framework developed for fatigue life estimation of LP‐processed coupons yielded estimates with goodness‐of‐fit between the log‐transformed experimental and analytical data of R2=0.97 for the baseline coupons and R2=0.94 for the LP‐processed coupons.Research limitations/implicationsApproximated ε‐life fatigue parameters were used to calculate the fatigue life resulting from the complex residual stress fields due to the simulated LP process.Originality/valueA fatigue life estimation framework that considers LP residual stress fields has been developed for use on structural components.

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Laser peening (LP) has shown to be a viable method by which the fatigue life of metallic components can be extended. Although current commercial implementation of LP techniques has not developed much beyond a trial-and-error methodology to implement the process, researchers at several institutions have examined various parameters that affect residual stress fields induced by LP, using Finite Element Analysis (FEA) and semi-empirical eigenstrain methods. This research is a preliminary investigation of a potentially under-considered variable in laser peening — material surface roughness. The influence of surface roughness on laser peening has not previously been studied through finite element modeling. The main point of interest for this work is to discover the amount that surface roughness magnitude affects the residual stresses created by LP. The FEA models, used in the exploration of surface roughness effects, had a simulated roughness produced by displacing surface nodes a pre-determined distance orthogonal to the original, smooth model surface. The amount that each node was moved was based on Kernel Density Estimation (KDE), a statistical method used to quantify uncertainties in random variables according to non-standard probability distribution functions. The KDEs were created from surface-roughness measurements taken from three separate 6061-T6 aluminum tubes. Two separate roughness sample sets were tested at magnifications of 1×, 10×, and 20× times the measured average roughness (Ra). Each roughness magnitude was simulated at peening pressures of 2, 2.5 and 3 times the Hugonoit Elastic Limit (HEL) for Al6061-T6. The 10× and 20× magnitude roughness samples produced significant changes in residual stress components relative to a smooth model, for all pressure loadings.

A method is introduced for efficient reliability-based design of laser peening (LP) surface treatment to extend fatigue life of metal components. The method includes nonparametric probability density estimation, surrogate modeling using a new finite element (FE or FEA) approach, and reliability analysis with correlated random variables (RVs). Efficient LP simulation is achieved via a new technique termed single explicit analysis using time-dependent damping (SEATD), which reduces simulation times by a factor of 6. The example study of a three-point bend coupon reveals that fatigue life reliability significantly affects optimal LP design, as 52 laser spots are needed for 99% reliability versus 44 spots for 95%.