A damage-based uniaxial fatigue life prediction method for metallic materials

Determining the fatigue behaviour of metallic materials using standardised testing methods is costly and time-consuming. Therefore, several methods have been proposed to shorten the testing time and improve the fatigue optimisation of materials and components. This work presents a new fatigue testing method based on fatigue damage monitoring that allows determining the fatigue resistance in a short time and with few specimens. The presented method, named as the stiffness method, monitors the inelas-tic strains as an indicator of fatigue damage evolution. Strain measurements were carried out by digital image correlation techniques and showed to effectively follow damage evolution during fatigue tests. Results are convincing and more evident to obtain and discuss than other monitoring techniques, like temperature dissipation. In addition, the method overcomes the main limitations of the existing fast test-ing methods by avoiding the utilisation of complex apparatus, like infrared cameras or acoustic emission sensors. The approach has been validated in ten different metallic materials, as titanium and aluminium alloys, carbon steels, and stainless steels. The estimated fatigue limit was compared with values obtained following standardised tests, showing excellent agreement. Results allow pointing out the stiffness method as an efficient and effective tool for rapidly determining the fatigue behaviour of metallic materials. & COPY; 2023 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

Automated summary

This article presents a new fatigue testing method based on fatigue damage monitoring, which allows determining the fatigue resistance of metallic materials in a short time and with few specimens. The method, named as the stiffness method, monitors the inelastic strains as an indicator of fatigue damage evolution. Digital image correlation techniques are used for strain measurements, which provide more convincing and evident results than other monitoring techniques.