The study of universality of a method for predicting surface nanocrystallization after high energy shot peening based on finite element analysis

Huang, Haiming; Wang, Zhou; Gan, Jin; Yang, Ying; Wang, Xiaoli; He, Jiaxi; Gan, Xueping

doi:10.1016/j.surfcoat.2018.11.075

Cited by 17 publications

(6 citation statements)

References 31 publications

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“…The Johnson-Cook model is suitable for describing materials with high strain rate deformations and the model has a simple structure and is easy to compute, so the Johnson-Cook principal model was chosen for this paper, as shown in equation (1) [17].…”

Section: Establish De-fe Random Multi-shot Analysis Model 221 Materia...mentioning

confidence: 99%

Optimization of parameters for the best shot peening effect based on surface response and neural network model

Wang,

Kim

2024

Mater. Res. Express

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To optimize the peening effect of different shot peening process parameters on metal surfaces, the mapping relationship between different shot peening process parameters and metal surface integrity was obtained. In this paper, ABAQUS software was used to establish a DE-FE (Discrete element-Finite element) random multi-shot analysis model to simulate shot peening, then optimize the shot peening process parameters based on the surface response method(RSM), and finally validate it through experiments and BP(back propagation) neural network model. The result shows that when the shot velocity is 70 m/s, the impact angle of shot is 61.45°, and the shot diameter is 0.78 mm, the shot peening effect is the best, the surface roughness value is reduced by 101.84%, and the arc height value is increased by 54.66%; the error between the predicted results of BP neural network and the results of numerical analysis is less than 8%. Therefore, the optimized process parameters significantly improve the shot peening effect, but also shows that the BP neural network prediction model can more accurately predict the mapping relationship between the input parameters of shot velocity, shot diameter, and impact angle of shot and the output parameters of roughness value and arc height value.

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Section: Establish De-fe Random Multi-shot Analysis Model 221 Materia...mentioning

confidence: 99%

Optimization of parameters for the best shot peening effect based on surface response and neural network model

Wang,

Kim

2024

Mater. Res. Express

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“…At present, there are two methods to simulate the Almen intensity test: representative elementary volumes , and the direct simulation method of real shot numbers . In this study, the simulation strategy presented by Wang et al was applied to simulate realistic peening data from the Almen intensity test.…”

Section: Current Approach For Shot Velocity Measurementsmentioning

confidence: 99%

Study on the Measurement Method of Shot Velocity and Mechanical Properties Based on Conventional Shot Peening

et al. 2022

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Shot velocity is a crucial control parameter that is closely related to the shot peening effect. However, the traditional measurement method of shot velocity corresponding to air pressure is complicated and cannot reflect shot peening parameters (impingement angle, etc.). This study proposes a robust method to measure shot velocity by coupling simulations and experiments. By developing the measurement method presented in this paper, we can quickly and easily derive the linear shot velocity formulas corresponding to a series of impingement angles. The validity is verified and characterized by the arc height, surface roughness, residual stresses, and existing literature. The measured shot velocity can be applied to predict the effect of shot peening by the simulation method in aerospace and automotive industries. In addition, optimization of process parameters in terms of microstructure, microhardness, and mechanical properties is discussed in the context of experiments. This study shows that shot velocity is linearly related to shot peening pressure and is affected by impingement angles. The air pressure and exposure time should not be too large, and no microcracks should be created. The ultimate strength reaches the maximum, and the yield strength is significantly improved.

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“…Since very high strain rates are involved in the shot peening process, rate-dependent properties must be considered in the target component model. There are many well-verified mathematical models that consider strain rates in evaluating the stress–strain relations (Huang, Wang [ 24 ]). Based on the work of Jebahi and Gakwaya [ 15 ], the isotropic hardening approach with rate-dependent properties correctly predicts the mechanical response of an Almen strip undergoing shot peening.…”

Section: The Improved Dem–fem Approachmentioning

confidence: 99%

An Improved Approach to Direct Simulation of an Actual Almen Shot Peening Intensity Test with a Large Number of Shots

et al. 2020

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In existing simulations of the Almen intensity test, arc height is indirectly obtained by an equivalent method including a representative cell, a few shots and equivalent loading. Most of these equivalent methods cannot consider the transverse deformation of the strip, the complex stress state of the plastic hardening layer and process parameters, resulting in deviation from the actual test. This paper introduces an improved and experimentally validated discrete element model (DEM)-finite element model (FEM) to predict the actual Almen intensity. The improvement of this model is mainly reflected in the large and real number of shots involved in the actual Almen intensity test, shot–shot interactions, and real-size solid finite element model of the Almen strip. A new method for calculating the shot stream is proposed based on the test and considering test process parameters such as the mass flowrate, nozzle movement speed and nozzle–workpiece distance. The shot stream impacting the strip with a fully restrained underside was first simulated in improved DEM-FEM to bring the forming energy. As a second step, an implicit solver of the Almen strip FEM calculates the spring-back to simulate strip removal from the holder. The results achieved by the present approach are compared with the results obtained by the experimental results and those in the literature. The results show that the arc height and Almen intensity obtained by the present approach match much better with the literature than the traditional method. Some new results obtained by the improved coupling DEM-FEM method are presented. The influences of the transverse deformation and surface plastic layer on the deformation of the Almen strip are discussed. This improved method provides an alternative characterization method for precision peen forming simulation.

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The study of universality of a method for predicting surface nanocrystallization after high energy shot peening based on finite element analysis

Cited by 17 publications

References 31 publications

Optimization of parameters for the best shot peening effect based on surface response and neural network model

Optimization of parameters for the best shot peening effect based on surface response and neural network model

Study on the Measurement Method of Shot Velocity and Mechanical Properties Based on Conventional Shot Peening

An Improved Approach to Direct Simulation of an Actual Almen Shot Peening Intensity Test with a Large Number of Shots

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