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Fatigue analysis of a point-absorber wave energy converter based on augmented data from a WEC-Sim model calibrated with experimental data
Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Electrical Engineering, Electricity. (Wave energy group)ORCID iD: 0000-0002-1165-5569
Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Electrical Engineering, Electricity.ORCID iD: 0000-0001-9213-6447
Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Electrical Engineering, Electricity.ORCID iD: 0000-0002-2031-8134
2022 (English)In: Trends in Renewable Energies Offshore: Proceedings of the 5th International Conference on Renewable Energies Offshore, London: CRC Press, 2022Conference paper, Published paper (Refereed)
Abstract [en]

To avoid over-designing wave energy converters (WECs), their reliability and survivability aspects need to be accurately addressed. The most common failure modes are: instantaneous failure due to high instantaneous loads, and fatigue failure due to the accumulated damage in the structure during years of operation. Here, we present a fatigue analysis of a point-absorber WEC in sea states corresponding to a 50-year environmental contour from the Dowsing site, UK. The data for this analysis is generated by a WEC-Sim model that is calibrated with a 1:30 scaled WEC from a wave tank experiment. In this study, the partial damage in each 1-hour sea state sample is calculated using the rainflow counting and Palmgren-Miner rule. Then, considering the joint probability density function of the sea states, the equivalent two-million cycle load is 2.42 MN for the full-scale system considering the accumulated damage in 50 years of operation. In a comparison of the fatigue limit state (FLS) and ultimate limit state (ULS), it was found that the ULS is the governing limit state in the design of the WEC system here.

Place, publisher, year, edition, pages
London: CRC Press, 2022.
Keywords [en]
Fatigue, Experimental, Numerical, Reliability, FLS, ULS
National Category
Marine Engineering Ocean and River Engineering Energy Engineering Reliability and Maintenance
Identifiers
URN: urn:nbn:se:uu:diva-488398ISBN: 9781003360773 (electronic)OAI: oai:DiVA.org:uu-488398DiVA, id: diva2:1710918
Conference
5th International Conference on Renewable Energies Offshore, RENEW 2022, Lisbon, Portugal, 8–10 November
Available from: 2022-11-15 Created: 2022-11-15 Last updated: 2024-03-12Bibliographically approved
In thesis
1. Survivability control using data-driven approaches and reliability analysis for wave energy converters
Open this publication in new window or tab >>Survivability control using data-driven approaches and reliability analysis for wave energy converters
2024 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Wave energy, with five times the energy density of wind and ten times the power density of solar, offers a compelling carbon-free electricity solution. Despite its advantages, ongoing debates surround the reliability and economic feasibility of wave energy converters (WECs). To address these challenges, this doctoral thesis is divided into four integral parts, focusing on optimizing the prediction horizon for power maximization, analyzing extreme waves' impact on system dynamics, ensuring reliability, and enhancing survivability in WECs.

Part I emphasizes the critical importance of the prediction horizon for maximal power absorption in wave energy conversion. Using generic body shapes and modes, it explores the effect of dissipative losses, noise, filtering, amplitude constraints, and real-world wave parameters on the prediction horizon. Findings suggest achieving optimal power output may be possible with a relatively short prediction horizon, challenging traditional assumptions.

Part II shifts focus to WEC system dynamics, analyzing extreme load scenarios. Based on a 1:30 scaled wave tank experiment, it establishes a robust experimental foundation, extending into numerical assessment of the WEC. Results underscore the importance of damping to alleviate peak forces. Investigating various wave representations highlights conservative characteristics of irregular waves, crucial for WEC design in extreme sea conditions.

Part III explores the computational intricacies of environmental design load cases and fatigue analyses for critical mechanical components of the WEC. The analysis is conducted for hourly sea state damage and equivalent two-million-cycle loads. Finally, a comparison of safety factors between the ultimate limit state and fatigue limit state unfolds, illustrating the predominant influence of the ultimate limit state on point-absorber WEC design.

Part IV, centers on elevating survivability strategies for WECs in extreme wave conditions. Three distinct controller system approaches leverage neural networks to predict and minimize the line force. Distinct variations emerge in each approach, spanning from rapid detection of optimal damping to integrating advanced neural network architectures into the control system with feedback. The incorporation of a controller system, refined through experimental data, showcases decreases in the line force, providing a practical mechanism for real-time force alleviation.

This thesis aims to contribute uniquely to the goal of advancing wave energy conversion technology through extensive exploration.

Place, publisher, year, edition, pages
Uppsala: Acta Universitatis Upsaliensis, 2024. p. 169
Series
Digital Comprehensive Summaries of Uppsala Dissertations from the Faculty of Science and Technology, ISSN 1651-6214 ; 2377
Keywords
power maximization, prediction horizon, extreme wave conditions, wave tank experiment, numerical WEC-Sim analysis, reliability analysis, statistical methods, environmental design load, fatigue analysis, statistical methods, survivability analysis, neural network methods
National Category
Control Engineering Energy Systems Ocean and River Engineering Other Electrical Engineering, Electronic Engineering, Information Engineering Marine Engineering Reliability and Maintenance Energy Engineering
Identifiers
urn:nbn:se:uu:diva-524903 (URN)978-91-513-2077-9 (ISBN)
Public defence
2024-05-17, Häggsalen (10132), Ångströmlaboratoriet, Uppsala, 09:00 (English)
Opponent
Supervisors
Available from: 2024-04-22 Created: 2024-03-12 Last updated: 2024-04-22

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Shahroozi, ZahraGöteman, MalinEngström, Jens

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