This study presents a numerical model for analyzing fatigue crack growth in 42CrMo4 steel pivot bolts under different heat treatments and service loads. The finite element method (FEM) in the ANSYS Workbench environment (version 2019R1) (SMART Crack Growth), along with algorithms based on Paris’s law implemented in MATLAB (version R2016a), was used. The results highlight the significant influence of heat treatment on fatigue resistance and serve as a basis for optimizing design parameters and improving the durability of the structural components.

This study provides a combined numerical and analytical investigation of fatigue crack growth in compact tension specimens made of 42CrMo4 steel. Through simulations in ANSYS Workbench (SMART Crack Growth module) and numerical modeling in MATLAB, the model is validated by comparing its results with the standard ASTM E399 and Paris’ law relationships. The effect of heat treatments and loading on crack growth rate was investigated. The results confirm the model’s applicability in predicting fatigue behavior in the linear–elastic region.

This study investigates the capabilities of modern ultrasonic non-destructive testing (NDT) methods for the detection and sizing of fatigue cracks in hinge bolts used in railway transport. Experimental investigations were conducted using immersion ultrasonic testing combined with advanced signal processing techniques, including PAUT, FMC/TFM, and FMC/PCI. Artificially introduced erosion notches ranging in size from 0.025 mm to 23 mm were used to simulate fatigue defects. The probability of defect detection was evaluated through Hit/Miss analysis and determination of the a90/95 parameter. The results indicate that the FMC/TFM method provides the highest sensitivity for the detection of small defects, while the PAUT technique demonstrates the highest accuracy in defect sizing.