A parametric study of laser spot size and coverage on the laser shock peening induced residual stress in thin aluminium samples

Sticchi, M.; Staron, Peter; Sano, Yuji; Meixer, M.; Klaus, Manuela; Rebelo-Kornmeier, Joana; Huber, N.; Kashaev, Nikolai

doi:10.1049/joe.2015.0106

Cited by 17 publications

(13 citation statements)

References 30 publications

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“…To generate tailored residual stress distributions, it is necessary to gain knowledge of the residual stress influencing LP process parameters. The result of the LP process is influenced by laser parameters like the energy input and the size of the laser focus [6,7] as well as the geometry of the laser focus [8]. The achievable maximum residual stress values are limited by the material's yield strength.…”

Section: Introductionmentioning

confidence: 99%

Effect of Laser Peening Process Parameters and Sequences on Residual Stress Profiles

Kallien

Keller

Ventzke

et al. 2019

Metals

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Laser Peening (LP) is a surface modification technology that can induce high residual stresses in a metallic material. The relation between LP process parameters, in particular laser sequences, as well as pulse parameters and the resulting residual stress state was investigated in this study. The residual stress measurements, performed with the hole drilling technique, showed a non-equibiaxial stress profile in laser peened AA2024-T3 samples with a clad layer for certain parameter combinations. Shot overlap and applied energy density were found to be crucial parameters for the characteristic of the observed non-equibiaxial residual stress profile. Furthermore, the investigation showed the importance of the advancing direction, as the advancing direction influences the direction of the higher compressive residual stress component. The direction of higher residual stresses was parallel or orthogonal to the rolling direction of the material. The effect was correlated to the microstructural observation obtained via electron backscattered diffraction. Additionally, for peening with two sequences of different advancing directions, the study showed that the order of applied advancing directions was important for the non-equibiaxiality of the resulting residual stress profile.

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Section: Introductionmentioning

confidence: 99%

Effect of Laser Peening Process Parameters and Sequences on Residual Stress Profiles

Kallien

Keller

Ventzke

et al. 2019

Metals

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“…In this work, LSP is assumed to be a purely mechanical process, so the increase in temperature in the substrate material is negligible. This assumption is also presented in various pieces of literature [26,27]. Thus, the temperature softening effect in the J–C model was not considered.…”

Section: Fem Simulation and Proceduresmentioning

confidence: 99%

Simulation and Experimental Study on Residual Stress Distribution in Titanium Alloy Treated by Laser Shock Peening with Flat-Top and Gaussian Laser Beams

Luo

et al. 2019

Materials

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The residual stress introduced by laser shock peening (LSP) is one of the most important factors in improving metallic fatigue life. The shock wave pressure has considerable influence on residual stress distribution, which is affected by the distribution of laser energy. In this work, a titanium alloy is treated by LSP with flat-top and Gaussian laser beams, and the effects of spatial energy distribution on residual stress are investigated. Firstly, a 3D finite element model (FEM) is developed to predict residual stress with different spatial energy distribution, and the predicted residual stress is validated by experimental data. Secondly, three kinds of pulse energies, 3 J, 4 J and 5 J, are chosen to study the difference of residual stress introduced by flat-top and Gaussian laser beams. Lastly, the effect mechanism of spatial energy distribution on residual stress is revealed.

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“…The combination of Artificial intelligence (AI) techniques has been found to be very useful for prediction and optimisation problems, for instance, the application of ANNs and GA within an integrated system is reported in a range of manufacturing processes [25][26][27]. Sticchi et al [28] reported a parametric study showing the effect of laser spot size and coverage on the LSP-induced residual stresses. Such studies can also be undertaken using ANNs by generating data from artificial single-variable experiments that could provide valuable insights into understanding the relationships existing in the data.…”

Section: Introductionmentioning

confidence: 99%

Machine Learning-Based Prediction and Optimisation System for Laser Shock Peening

et al. 2021

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Laser shock peening (LSP) as a surface treatment technique can improve the fatigue life and corrosion resistance of metallic materials by introducing significant compressive residual stresses near the surface. However, LSP-induced residual stresses are known to be dependent on a multitude of factors, such as laser process variables (spot size, pulse width and energy), component geometry, material properties and the peening sequence. In this study, an intelligent system based on machine learning was developed that can predict the residual stress distribution induced by LSP. The system can also be applied to “reverse-optimise” the process parameters. The prediction system was developed using residual stress data derived from incremental hole drilling. We used artificial neural networks (ANNs) within a Bayesian framework to develop a robust prediction model validated using a comprehensive set of case studies. We also studied the relative importance of the LSP process parameters using Garson’s algorithm and parametric studies to understand the response of the residual stresses in laser peening systems as a function of different process variables. Furthermore, this study critically evaluates the developed machine learning models while demonstrating the potential benefits of implementing an intelligent system in prediction and optimisation strategies of the laser shock peening process.

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A parametric study of laser spot size and coverage on the laser shock peening induced residual stress in thin aluminium samples

Cited by 17 publications

References 30 publications

Effect of Laser Peening Process Parameters and Sequences on Residual Stress Profiles

Effect of Laser Peening Process Parameters and Sequences on Residual Stress Profiles

Simulation and Experimental Study on Residual Stress Distribution in Titanium Alloy Treated by Laser Shock Peening with Flat-Top and Gaussian Laser Beams

Machine Learning-Based Prediction and Optimisation System for Laser Shock Peening

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