Whilst it is known that mean stress has an effect on the fatigue endurance of steel components, this effect is not considered when designing mooring system components. The S-N and T-N fatigue design curves for mooring chain in the standards are based on tests carried out at a single mean load, which is 20% of the chain minimum breaking load (MBL), and these curves are used to compute the damage of all load cycles regardless of their mean value. Lately it has been found that the effect of the mean load can be larger than probably expected, and that mooring chains exhibit a significant increase of fatigue capacity when cyclically loaded at reduced mean load. In the majority of the floating units, the pre-tension of the moorings without environmental loads is below or well below 15% of the chain MBL, and most, if not all, of the in-service damage is produced at mean loads below 20% MBL. This in practice results in additional conservatism to the fatigue life computed using the existing design curves. Some deepwater units, subjected to high pre-tension level, can experience some or relevant damage occurring at mean loads above 20% MBL, which would be underestimated with the present design approach. The paper provides an insight on the effect of the mean load on the fatigue endurance of mooring chains and quantifies this dependency based on a large number of fatigue tests carried out on different chain diameters between 70 and 171 mm, different grades, and different mean loads ranging between 7% and 20% of the MBL of the tested chains. The Smith-Watson-Topper (SWT) mean stress correction model is used to transform the stress state of the tested chains into different stress states associated to different mean loads. Then regression analyses are performed and correction functions derived for the design curves of both S-N and T-N approaches to account for the mean load while keeping the same confidence of the existing curves.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.