Fatigue strength assessment of complex welded structures with severe force concentrations along a weld seam

Rautiainen, Matti; Remes, Heikki; Niemelä, Ari; Romanoff, Jani

doi:10.1016/j.ijfatigue.2022.107321

Cited by 4 publications

(1 citation statement)

References 20 publications

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“…This should include the variable transfer functions accounting for, e.g., heading and loading conditions. • update the uncertainty distributions from full-scale fatigue test results (e.g., [41][42][43][44][45]). These specimens should incorporate the redundancy in terms of parallel load paths, as well as the actual residual stress levels and distributions.…”

Section: Discussionmentioning

confidence: 99%

Tailoring the Fatigue Detail Category Class: A Deterministic Implementation of a Probabilistic-Based Approach to Consequence- and Uncertainty-Informed Fatigue Life Prediction of Ships

Deul,

van Battum,

Hoogeland

2023

JMSE

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The fatigue life of ship structures is typically based on deterministic methods in which underlying uncertainties are only implicitly taken into account and not explicitly reflected. Guidance for a probabilistic assessment is provided in class documents, but the methodology is too time consuming to apply in design practice. This paper proposes a novel approach based on DNV-CG-0129 to incorporate uncertainties and consequences explicitly. Using a probabilistic model, tailored deterministic FAT classes are derived to be applied in design practice. A tailored FAT class should be selected based on an acceptable probability of failure related to the severity of the consequences of a failure for the ship. Results show that tailored FAT classes are strongly dependent on the uncertainties provided as input when using the calculation method of DNV-CG-0129. This emphasizes the need for careful consideration and specification of the uncertainties. Furthermore, application of the First Order Reliability Method for a sensitivity study shows that the global model uncertainty is governing over other uncertainties considered in DNV-CG-0129. The proposed approach enables a low-effort and transparent probabilistic-based method, leading to optimized and improved designs due to reduction of overdimensioning in non-critical areas.

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