A Novel Optimisation-Based Approach to Predict the S-N curves Behaviour based on Small Crack Growth in Additively Manufactured Ti-6Al-4V

The structural integrity of Ti-6Al-4V components produced via Selective Laser Melting (SLM) is critically dependent on understanding fatigue behaviour. However, accurately modelling the growth of small cracks originating from inherent manufacturing defects remains a significant challenge. This work introduces a novel methodology for accurately modelling small crack growth in Ti-6Al-4V alloy produced via Selective Laser Melting (SLM). Based on a modification of a S-N curve model proposal, to explore the use of nanotomography as a defect characterisation technique. This study proposes the use of optimisation algorithms, specifically Nelder-Mead and SLSQP, to determine an optimal predictive model. Evaluation against experimental data demonstrates the high predictive capability of the proposed methodology (R² = 99.28%), achieving a performance comparable to the traditional Basquin equation (R² = 99.29%).