Fatigue resistance similarity

Abstract

This master’s thesis investigates the fatigue resistance similarity between small-scale test specimens and large-scale structures, specifically focusing on steel welded joints. The primary goal is to improve the understanding of how fatigue data from small-scale tests can be reliably applied to predict the performance of full-scale maritime structures, thereby reducing conservatism in design and optimizing material usage without compromising safety. Fatigue resistance is a critical factor in the design and maintenance of maritime structures. Traditional design methods often use S-N curves derived from small-scale specimen tests, which can be overly conservative when applied to full-scale structures. This conservatism, while ensuring safety, leads to increased material use and associated costs. The aim is to identify and quantify the scaling phenomena that influence the transfer of fatigue data from small-scale specimens to full-scale structures. By proving fatigue resistance similarity and understanding these scaling effects, the research seeks to refine the fatigue design process, thereby enhancing efficiency and reducing environmental impact. The research utilizes various fatigue assessment concepts, including the Nominal Stress Concept (NSC), Hot Spot Structural Stress Concept (HSSSC), and the Effective Notch Stress Concept (ENSC). Finite Element (FE) models of large-scale specimens, created using Abaqus, are used to test these concepts. The study also explores the application of mean stress correction models to improve the fit of large-scale data within small-scale data scatter bands. The methods are evaluated based on their ability to incorporate local geometry information and their effectiveness in reducing scatter in fatigue data. The study demonstrates that incorporating local geometry information is crucial for achieving fatigue resistance similarity between small-scale and large-scale specimens. The HSSSC and ENSC, which account for local geometrical variations, provide better fits for large-scale data within the small-scale data scatter bands compared to the NSC. This confirms the hypothesis that local weld geometry plays a significant role in fatigue resistance similarity. Furthermore, applying a mean stress correction improves the alignment of large-scale data with small-scale data, highlighting the importance of considering residual stresses and load ratios in fatigue assessments.
The findings can have practical implications for the design and maintenance of maritime structures. By improving the accuracy of fatigue life predictions, the research supports the development of more efficient and cost-effective designs. The insights gained from this research help address uncertainties and improve design assumptions for vessel fatigue performance. By incorporating local geometry information and applying mean stress corrections, the research provides a more accurate and less conservative approach to fatigue life prediction. These advancements have the potential to reduce material usage and costs in maritime structure design, while maintaining high safety standards.