This study describes shot peening effects such as shot hardness, shot size and shot projection pressure, on the residual stress distribution and fatigue life in reversed torsion of a 60SC7 spring steel. There appears to be a correlation between the fatigue strength and the area under the residual stress distribution curve. The biggest shot shows the best fatigue lie improvement. However, for a shorter time of shot peening, small hard shot showed the best performance. Moreover, the superficial residual stresses and the amount of work hardening (characterised by the width of the X-ray diffraction line) do not remain stable during fatigue cycling. Indeed they decrease and their reduction rate is a function of the cyclic stress level and an inverse function of the depth of the plastically deformed surface layer.

A thermodynamically-consistent phase field approach for crack propagation which includes the following novel features is presented. (1) Scale dependency was included by relating the length scale to the number of cohesive interatomic planes at the crack tip. Because of this, the developed theory is applicable from the atomistic to the macroscopic scales. (2) The surface stresses (tension) are introduced by employing some geometrical nonlinearities even in small strain theory. They produce multiple contributions to the Ginzburg-Landau equation for crack propagation. (3) Crack propagation in the region with compressive closing stresses is eliminated by employing a stress-state-dependent kinetic coefficient in the Ginzburg-Landau equation. (4) The importance of analysis of the thermodynamic potential in terms of stress-strain curves is shown. The developed theory includes a broad spectrum of the shapes of stress-strain relationships. The finite element method is utilized to solve the complete system of crack phase field and mechanics equations. The effect of the above novel features is analyzed numerically for various model problems.

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Ultrasonic Testing (UT) is one of the well-known Non-Destructive Techniques (NDT) of spot-weld inspection in the advanced industries, especially in automotive industry. However, the relationship between the UT results and strength of the spot-welded joints subjected to various loading conditions is unknown. The main purpose of this research is to present an integrated search system as a new approach for assessment of tensile strength and fatigue behavior of the spot-welded joints. To this end, Resistance Spot Weld (RSW) specimens of three-sheets were made of different types of low carbon steel. Afterward, the ultrasonic tests were carried out and the pulse-echo data of each sample were extracted utilizing Image Processing Technique (IPT). Several experiments (tensile and axial fatigue tests) were performed to study the mechanical properties of RSW joints of multiple sheets. The novel approach of the present research is to provide a new methodology for static strength and fatigue life assessment of three-sheets RSW joints based on the UT results by utilizing Artificial Neural Network (ANN) simulation. Next, Genetic Algorithm (GA) was used to optimize the structure of ANN. This approach helps to decrease the number of tests and the cost of performing destructive tests with appropriate reliability.

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