Session: 09-02-04 Wind Energy: Moorings II

Submission Number: 157263

On the Reduction of Design Load Cases for Fatigue Assessment of Mooring Lines for Offshore Renewable Energy Systems 

The deployment of floating offshore renewable energy (ORE) systems, such as wind turbines and wave energy converters, presents unique engineering challenges, particularly in the design and fatigue assessment of mooring lines. Mooring lines are subjected to cyclic loading due to environmental forces such as wind, waves, and currents, necessitating a detailed analysis of fatigue damage over their lifespan. Conventional fatigue analysis involves evaluating a wide range of design load cases (DLCs) to capture the variability of environmental conditions. However, this exhaustive approach is computationally expensive and time-consuming, highlighting the need for efficient methods to reduce the number of DLCs while maintaining reliability and accuracy.

This study proposes a novel and systematic methodology to reduce the number of design load cases required for fatigue assessment by leveraging clustering techniques (i.e. k-means technique) and spectral fatigue analysis models, both of which will be openly accessible. Previous studies in the literature use clustering techniques for the reduction of environmental condition combinations, but do not proof the validity of such reductions for designing ORE systems and/or components. Hence, the methodology presented in this paper is structured in two main steps. First, clustering techniques, are applied to environmental data comprising wave height, wave period and wind speed. The clustering process focuses on achieving convergence based on inter-cluster distance, as in the rest of the applications in the literature, enabling the determination of an optimal (minimum) number of representative environmental conditions that covers the whole operational region.

In the second step, a spectral fatigue analysis is employed to evaluate mooring line damage for the different numbers of environmental conditions analysed in the previous step. The convergence is re-assessed, not only using the environmental-based inter-cluster distance, but also based on the accumulated fatigue damage. That way, a new optimal number of clusters that better reflects the actual damage-driving conditions is identified. This approach ensures that the most critical load cases are retained while eliminating redundancies.

Finally, the differences between the two optimal numbers of clusters – the one derived from environmental-based inter-cluster distance and the other based on fatigue damage - are analysed to provide insights into the trade-offs between computational efficiency and design accuracy. The results from this study demonstrate that while clustering using environmental-based inter-cluster distance offers a preliminary estimate of representative conditions, integrating fatigue damage metrics refines the selection, ensuring the reduced DLC set remains robust for engineering design purposes.

The preliminary case study includes a spar-like floating offshore wind turbine with four mooring lines and studies the impact of reducing the analysed DLCs on the final damage and lifetime estimation. This reduction translates into substantial computational savings and a more streamlined design process. Moreover, the methodology can be extended to other offshore renewable energy systems, enhancing its applicability across the sector.

In conclusion, this work introduces a systematic and innovative approach to reducing design load cases for fatigue assessment in mooring lines, balancing computational efficiency with design reliability. The integration of clustering and spectral analysis offers a comprehensive framework to address the challenges of fatigue assessment, contributing to the cost-effective and sustainable development of offshore renewable energy systems.

Presenting Author: Markel Penalba Mondragon University

Presenting Author Biography: Dr. Markel Penalba has a strong academic and industrial research background. After completing his Master studies at ENSTA Bretagne in France and his PhD at the Centre for Ocean Energy Research (COER) in Ireland, in 2019 he joined Mondragon University in the Basque Country as a Post-Doc researcher. Later in 2021 he became full lecturer at the Fluid Mechanichs Department of the Mondragon University and joined the Basque Science Foundation Ikerbasque as Research Fellow, and he was a research visitor at Oregon State University in 2022. He currently leads the Offshore Technologies and Aerodynamics group and collaborates with several international institutions, either in research projects or co-supervising Master and PhD students.

Dr. Penalba has published more than 40 scientific papers and participated in numerous international research conferences. His expertise spans various aspects of marine and offshore renewable energy technologies, including metocean resource assessment and forecasting, wave energy converter and floating offshore wind turbine design optimisation, wave and wind farm operation and maintenance, and green hydrogen production.