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

Li, Xiang; He, Weifeng; Luo, Sihai; Nie, Xiangfan; Tian, Lihui; Feng, Xiaotai; Li, Rongkai

doi:10.3390/ma12081343

Cited by 33 publications

(12 citation statements)

References 29 publications

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“…Uprising technologies that are currently heavily investigated such as laser shock peening could be considered. A comparison of the three-dimensional FEA carried out by Li et al, also using the JC model to the two-dimensional model, will be considered [60]. Recent work from Dong et al describes the development of a FEA for machining operations [61].…”

Section: Discussionmentioning

confidence: 99%

Machine Learning Driven Prediction of Residual Stresses for the Shot Peening Process Using a Finite Element Based Grey-Box Model Approach

Ralph

Hartl

Sorger

et al. 2021

JMMP

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The shot peening process is a common procedure to enhance fatigue strength on load-bearing components in the metal processing environment. The determination of optimal process parameters is often carried out by costly practical experiments. An efficient method to predict the resulting residual stress profile using different parameters is finite element analysis. However, it is not possible to include all influencing factors of the materials’ physical behavior and the process conditions in a reasonable simulation. Therefore, data-driven models in combination with experimental data tend to generate a significant advantage for the accuracy of the resulting process model. For this reason, this paper describes the development of a grey-box model, using a two-dimensional geometry finite element modeling approach. Based on this model, a Python framework was developed, which is capable of predicting residual stresses for common shot peening scenarios. This white-box-based model serves as an initial state for the machine learning technique introduced in this work. The resulting algorithm is able to add input data from practical residual stress experiments by adapting the initial model, resulting in a steady increase of accuracy. To demonstrate the practical usage, a corresponding Graphical User Interface capable of recommending shot peening parameters based on user-required residual stresses was developed.

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Section: Discussionmentioning

confidence: 99%

Machine Learning Driven Prediction of Residual Stresses for the Shot Peening Process Using a Finite Element Based Grey-Box Model Approach

Ralph

Hartl

Sorger

et al. 2021

JMMP

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“…The peak pressure can be calculated from Equation (7). Here, P peak (GPa) is the peak plasma pressure; α is the correction factor of the internal energy and the thermal energy (usually α ≈ 0.25 ); I (GW • cm −2 ) is the laser pulse power density, where P pulse is the laser pulse power and A peen is the laser spot area at the working point; Z (g • cm −2 s −1 ) is the combined acoustic impedance of the confinement layer Z water (≈0.15 × 10 6 ) of water and the target material Z target (≈4.5 × 10 6 ) of stainless steel [8,12,29,30].…”

Section: Pressure Load Modelmentioning

confidence: 99%

“…Additionally, the 2D pressure load distribution from the beam center to the radial direction is also considered. Depending on the laser beam pulse profile, Gaussian or flat-top models have been suggested [12]. Sun et al [31] proposed a mixed shape of Gaussian and flat-top according to measurements from the beam profiler.…”

Section: Pressure Load Modelmentioning

confidence: 99%

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FE Analysis of Laser Shock Peening on STS304 and the Effect of Static Damping on the Solution

Kim

Suh

Shin

et al. 2021

Metals

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Laser shock peening creates compressive residual stress on the surface of the material, reducing stress corrosion cracking and increasing fatigue life. FE simulation of laser shock peening is an effective way to determine the mechanical effects on the material. In conventional FE simulations of laser shock peening, explicit analysis is used while pressure loads are applied and switched into implicit analysis to dissipate kinetic energy. In this study, static damping was adopted to dissipate kinetic energy without conversion into implicit analysis. Simulation of a single laser shock and multiple shocks was performed, and deformation and minimum principal stress were compared to evaluate the static damping effect. The history of the internal and kinetic energy were analyzed to compare the stabilization time depending on the damping value. Laser shock peening experiments were also performed on stainless steel 304 material. The residual stress of the specimen was measured by the hole drilling method and it was compared to the FE simulation result. The residual stress from the experiment and the simulation results showed similar distributions in the depth direction. Anisotropic residual stress distribution due to the laser path was observed in both results.

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“…The Johnson-Cook (J-C) material model [ 13 , 14 ] was adopted, which is widely used under high strain rate conditions such as high-speed impact and explosion impact. Taking into account the absorption protection layer and water confinement layer on the surface of samples, the thermal effect is ignored [ 15 , 16 ]. The model is rewritten as Equation (1):

where A is the yield strength of the material, B is the work hardening modulus, n is the hardening coefficient, C reflects the strain rate hardening effect of the material,

is the plastic strain, and

is the dimensionless plastic strain rate.…”

Section: Laser Shock Peening Modelmentioning

confidence: 99%

Formation Mechanism and Control Method of Residual Stress Profile by Laser Shock Peening in Thin Titanium Alloy Component

et al. 2021

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In the laser shock peening process of titanium alloy thin blades, a shock wave will be repeatedly reflected and coupled in the blades, resulting in the failure of the formation of a gradient residual compressive stress layer, which is the key to improve fatigue performance and resist foreign object impact. This paper takes TC17 titanium alloy sheet as the research object to reveal the influence mechanism on residual stress-strain profile of shock wave reflection-coupling by shock wave propagation and key position dynamic response. Based on the result of influence mechanism, two wave transmission methods are proposed to regulate shock wave in order to reduce the intensity of shock wave reflection. The analysis shows that the high strength stress be formed when the shock wave is reflected and coupled in the sheet, which causes the re-plastic deformation and the decrease of transverse plastic strain. This eventually leads to residual tensile stress up to 410 MPa being formed within a 0.5 mm radial direction and 0.3 mm deep of the spot range. The use of "soft" and "hard" wave-transmitting layers greatly reduces the shock wave reflection intensity, and under the condition of the "hard" wave-transmitting layer, a better impedance matching is achieved, resulting in a residual compressive stress of about 400 MPa.

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

Cited by 33 publications

References 29 publications

Machine Learning Driven Prediction of Residual Stresses for the Shot Peening Process Using a Finite Element Based Grey-Box Model Approach

Machine Learning Driven Prediction of Residual Stresses for the Shot Peening Process Using a Finite Element Based Grey-Box Model Approach

FE Analysis of Laser Shock Peening on STS304 and the Effect of Static Damping on the Solution

Formation Mechanism and Control Method of Residual Stress Profile by Laser Shock Peening in Thin Titanium Alloy Component

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