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In this paper, the laser shot peening (LSP) technology of H13 steel is studied to improve the friction and wear performance of shield machine hob. And to utilize the LSP experiment and simulation analysis, the influence of LSP parameters on the friction and wear performance of H13 steel after strengthening is studied. The numerical simulation study reveals the variation law of laser parameters on residual stress and stress layer depth. Study on friction and wear characteristics of H13 steel after LSP. The results show that the maximum residual stress of H13 steel is 911 MPa, and the hardness is 650.7 HV, when there are three times of black paint absorption and LSP. Compared with the raw material, the residual stress is increased by 125%, and the hardness is increased by 18%. And its friction coefficients and wear volume were relatively lower than other schemes. The average friction coefficient and wear volume were reduced by 10.8% and 57.2% respectively. [ABSTRACT FROM AUTHOR]

• The synergetic effect of shot peening (SP) and laser shot peening (LSP) on the fatigue behavior of 30CrMnSiA steel compared with a baseline SP treatment was investigated. • A fatigue life transition was observed in the S N curves, which indicates different fatigue mechanisms and the enhancement of SP and SP + LSP specimens in HCF and LCF. • Different microstructural evolutions of SP and SP + LSP spceimens were observed. • The short crack incubation and initial propagation were retarded explaining the fatigue life transition behavior. The synergetic effect of shot peening (SP) and laser shot peening (LSP) on the fatigue behavior of a medium carbon steel was investigated. A fatigue life transition was observed in the S N curve, where the fatigue performance of the SP + LSP specimen was improved only at lower stress levels. This result is consistent with the short crack propagation behavior observed in the near-threshold region. The heterogeneous structures comprised by ultra-fine grains, dislocation tangles, and more high-angle grain boundaries were responsible for this behavior which effectively retard the short crack propagation. [ABSTRACT FROM AUTHOR]

• The effects of load ratios on the gain of AA2524′s fatigue life after laser shot peening were thoroughly studied. • The crack closure model has been used to eliminate the R -effect of the peened specimens' FCGR. • The data driven approach has been used to predict the fatigue crack growth behavior, an ANN model and a SVR model based on particle swarm optimization algorithm were trained by FCGR data, and the fatigue crack growth life is predicted through these well-trained models. Laser shot peening is a relatively novel surface treatment technology generating deep compressive residual stress and further retarding fatigue crack growth rate (FCGR). Meanwhile, the load ratio, R , plays an important role in fatigue crack growth behavior. Evaluating the remaining life of components accurately is essential to damage tolerance design, many efforts have been applied to correlate the R -effect. In this paper, the effect of load ratio on the gain of AA2524′s fatigue life after laser shot peening have been thoroughly studied. Initially, the fatigue crack growth rate of AA2524 after laser shot peening was measured under different load ratios. Subsequently, a comparative analysis between the FCGR for AA2524 before and after laser shot peening was thoroughly conducted. Then, the crack closure model has been applied to correlate the R- effect of peened specimens, but the results are unsatisfied due to the ignore of compressive residual stress. To address this issue, a novel method of predicting crack growth life considering compressive residual stress was proposed. The artificial neural network model and support vector regression model based on particle swarm optimization algorithm were trained by the FCGR data, and the fatigue crack growth life is predicted by a cycle-by-cycle method. The result shows the artificial neural network model is more accurate than the support vector regression model, and this intelligent algorithm can be a potentially effective way to predict fatigue crack growth behavior. [ABSTRACT FROM AUTHOR]

The aim of this paper is to study the effect of microstructure heterogeneity upon elasto-plastic wave propagation generated during laser shot peening. We consider a simplified elasto-plastic laminate specimen subjected to uniaxial strain. The microstructure is composed of two phases alternating periodically and perfectly bonded together. The associated PDE system is solved using a high-resolution Godunov scheme, allowing to study the wave propagation in the heterogeneous structure. It is found that, even for a small mechanical contrast between the two phases, the considered laminate microstructure has a significant effect on the distribution of plastic strain. In addition, an elasto-plastic homogenization of the laminate has been carried out, and the resulting Homogeneous Equivalent Medium (HEM) has been used to decrease the computation time of the wave propagation. The HEM-based model is able to reproduce accurately the full-field solution in terms of distribution of mean plastic strain within the specimen and its fluctuation between the two phases. [ABSTRACT FROM AUTHOR]