Developing diagnostic methods for fatigue damage assessment

Abstract

Most of the metal’s failure happens because of the fatigue which is associated with metals that is subjected to cyclic loading over time. Fatigue damage detection is one of important technological issues in both academic and industrial fields. Early fatigue damage detection promotes circular economy and sustainability by prolonging the lifespan and durability of metals. In most metals, in low and high cycle fatigue, the stages of fatigue are pre-crack nucleation, crack nucleation, micro and macro crack growth, and final failure. Several techniques have been proposed and developed for detecting fatigue damage in metals. However, comparatively less attention has been given to early fatigue damage detection, specifically targeting the pre-crack nucleation stage. The pre-crack nucleation stage begins with an increase in dislocation density, followed by the formation of dislocation entanglements and ultimately, the development of slip bands. Subsequently, these slip bands induce intrusion and extrusion, serving as nucleation sites for cracks. The identification of these defects plays an important role as it can facilitate the use of appropriate treatment to either eliminate or mitigate the defects, consequently leading to increase in metals lifespan. The use of non-destructive testing (NDT) methods is particularly crucial in this context, given their wide applicability within industrial environments. Thus, in this thesis appropriate NDT methods for early damage detection fatigue in 316L stainless steel had been used. NDT methods enable the detection of fatigue damage without destruction of specimen. Techniques such as electrical resistivity measurement and nonlinear ultrasonic testing are employed to detect these defects. The electrical resistance method operates on the principles of Ohm's law, whereby a current is applied to the metal and the resulting voltage drop is measured to determine its electrical resistance. The resistivity is then calculated based on the sample’s geometry. Structural defects including dislocations, entanglements, slip bands, and cracks contribute to scattering and elevation in electrical resistivity. However, to make this method works effectively, a responsive technique with the capability of nΩ resolution is needed. The used method in this study is a combination of delta mode and four-probe technique that effectively eliminates thermoelectric voltages resulting from temperature variations in the circuit and minimizes the impact of lead resistance. Another approach that is used in this study is nonlinear ultrasonic. In this technique, a wave is propagated through the metal specimen, and upon interaction with defects, higher frequency waves are generated. By detecting and analysing these signals, the presence of defects can be identified. This unique capability enables the detection of early fatigue defects such as dislocations and slip bands evolution, providing improved sensitivity and precision in defect identification. Findings indicate that both electrical resistivity measurement and nonlinear ultrasonic testing proficiently detect early-stage fatigue defects in 316L stainless steel. These methods reveal significant changes in two distinct regions prior to 10% of the component's fatigue life. Following the identification of two distinct regions of significant signal variation prior to 10% of the fatigue life, advanced microscopy techniques were employed to investigate the underlying mechanisms responsible for these observations. Optical microscopy and Scanning Transmission Electron Microscopy with High-Angle Annular Dark Field (STEM-HAADF) imaging were utilized to observe the microstructural evolution in 316L stainless steel. These methods confirmed that the detected signals are correlated with early microstructural changes, specifically the increase in dislocation density, the formation of dislocation tangles, and the onset of cellular structure formation.