The exhaustion of constructive ways for increasing the service life of parts has led to the development of new methods which can improve their material properties during operation under various loading conditions. Laser shock peening (LSP) induces compressive residual stress field which prevents fatigue crack initiation and propagation in components. Characteristics of laser impact and treatment patterns play an important role in efficiency of LSP application for improvement of fatigue properties. This work is devoted to the experimental examination of two LSP patterns to reveal the most optimal scheme from fatigue live improvement point of view. Proposed LSP pattern allowed one to increase the fatigue life of specimens with semi-circular notch by an order of magnitude. The numerical simulation of the LSP was performed to visualize the residual stress field of treated specimen after loading and to give the interpretation of the experimentally observed improvement of fatigue life.

The paper is devoted to the development of the method of laser shock peening (LSP) of metals. To optimize the mode of LSP for Ti-6Al-4V specimens a deep learning model for predicting residual stresses by laser shock peening was developed. A numerical-experimental method was used to carry out the model training, in which an experimental study of the effect of different processing mode on the depth and distribution of residual stresses was carried out. The Johnson-Cook model was used as the governing relationship for modeling the dynamic deformation process. At the second stage, the problem of static equilibrium of a body with a plastically deformed area was numerically solved to determine residual stresses. The results of research on determination of the optimal configuration of the deep learning model showed that when using sinusoidal activation function of the neural network with 4 hidden layers and the number of neurons 10, the best level of accuracy in solving the problem is achieved. The obtained model allows us to optimally determine the LSP mode according to the given limitations of values and depth of residual stresses.

This work is devoted to the experimental investigation of the effect of laser shock peening (LSP) on the thermo-mechanical properties of metals. ARMCO iron was chosen as the model material for the study. Samples were subjected to LSP, and were tested following the procedure of the self-heating (Risitano) technique. To investigate the damage that was induced by heating, the fatigue tests were coupled with infrared thermography measurements. The results of the study showed that the LSP procedure qualitatively changes the temperature evolution in ARMCO iron during cyclic loading. The heating (energy dissipation) of the LSP treated specimen was several times higher than that of the specimen in the initial state. To explain the structural mechanisms of energy dissipation, the microstructure of the specimens was examined using transmission (TEM) and scanning (SEM) electron microscopy, as well as electron backscattering diffraction (EBSD). The results of the structural investigation confirm the qualitative change of defect evolution caused by LSP treatment.