There are limited experimental data on VHCF for structural steels for >${10}^7$ cycles. Unalloyed low-carbon steel S275JR+AR is a common structural material for the heavy machinery in minerals, sand and aggregate applications. The purpose of this research is to investigate the fatigue behaviour in the gigacycle domain (>${10}^9$ cycles) for S275JR+AR grade steel. This is achieved using accelerated ultrasonic fatigue testing in as-manufactured, pre-corroded and non-zero mean stress conditions. As internal heat generation is a massive challenge for ultrasonic fatigue testing of structural steels which exhibit a pronounced frequency effect, effective temperature control is crucial for implementation of testing. The frequency effect is assessed by comparing the test data at 20 kHz and 15–20 Hz. Its contribution is significant, as there is no overlap between the stress ranges of interest. The obtained data are intended to be applied to the fatigue assessments of the equipment operating at the frequency for up to ${10}^{10}$ cycles over years of continuous service.

The surface integrity of a turned machined surface is an essential indicator of the fatigue and corrosion performance of a component. A critical descriptor of this property is the residual stress, both on the surface and subsurface of a part. However, experimental determination of vital surface integrity parameters such as surface roughness, hardness, affected microstructure, and residual stresses is costly, time consuming, and involves the destruction of the part. Therefore, prediction of these parameters, such as residual stress versus depth, would be of great value and could aid in the correct machining parameters (cutting speed, feed rate, edge tool radius, rake angle, coolant) for the desired part performance. A study was initiated to determine the influence of a worn tool and multiple cuts on a wide range of cutting speeds on residual stresses induced by machining an outside-turned bar of Ti6Al4V titanium alloy. Thus, a project was initiated to develop a non-linear finite element model to predict the residual stresses thus developed due to the machining manufacturing process.