Extreme springing response statistics of a tethered platform by deconvolution

The research examines the motion response and hydrodynamic wave loads of a deep-water Tension Leg Platform (TLP), emphasising the impacts of the wave sum frequency on the restrained modes of heave, roll, and pitch. The stochastic TLP structural reaction in a random sea state was precisely computed u...

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Main Authors: Oleg Gaidai, Yu Cao, Yihan Xing, Rajiv Balakrishna
Format: Article
Language:English
Published: Elsevier 2023-01-01
Series:International Journal of Naval Architecture and Ocean Engineering
Subjects:
Online Access:http://www.sciencedirect.com/science/article/pii/S2092678223000043
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author Oleg Gaidai
Yu Cao
Yihan Xing
Rajiv Balakrishna
author_facet Oleg Gaidai
Yu Cao
Yihan Xing
Rajiv Balakrishna
author_sort Oleg Gaidai
collection DOAJ
description The research examines the motion response and hydrodynamic wave loads of a deep-water Tension Leg Platform (TLP), emphasising the impacts of the wave sum frequency on the restrained modes of heave, roll, and pitch. The stochastic TLP structural reaction in a random sea state was precisely computed using a Volterra series representation of the TLP corner vertical displacement, which was selected as a response process. The wave loading was evaluated using the second-order diffraction code WAMIT and applied to a linear damped mass-spring model representing the dynamic system. Then, platform displacement response at the design low probability level has been determined using a novel deconvolution approach. Since the Volterra series represented the analytical solution, the exact Volterra and the approximated predictions have been compared in this study. The latter provided an accurate way to validate the effectiveness and precision of the proposed novel deconvolution method. Compared to existing engineering techniques, the most attractive advantage of the proposed deconvolution method is that it does not rely on any pre-assumed asymptotic probability distribution class. The latter may be an attractive point for practical engineering design. Thus the primary objective of this work was to validate a novel deconvolution approach using exact quasi-analytical solutions. This work also highlights the limitations of mean up-crossing rate-based extrapolation methodologies for the situation of narrowband effects, including clustering, which are often included in the springing type of response.
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spelling doaj.art-d4d034f41f8249e79614fcdfe1041ae22023-12-24T04:45:08ZengElsevierInternational Journal of Naval Architecture and Ocean Engineering2092-67822023-01-0115100515Extreme springing response statistics of a tethered platform by deconvolutionOleg Gaidai0Yu Cao1Yihan Xing2Rajiv Balakrishna3College of Engineering Science and Technology, Shanghai Ocean University, Shanghai, ChinaCollege of Engineering Science and Technology, Shanghai Ocean University, Shanghai, China; Corresponding author.Department of Mechanical and Structural Engineering and Material Sciences, University of Stavanger, Stavanger, NorwayDepartment of Mechanical and Structural Engineering and Material Sciences, University of Stavanger, Stavanger, NorwayThe research examines the motion response and hydrodynamic wave loads of a deep-water Tension Leg Platform (TLP), emphasising the impacts of the wave sum frequency on the restrained modes of heave, roll, and pitch. The stochastic TLP structural reaction in a random sea state was precisely computed using a Volterra series representation of the TLP corner vertical displacement, which was selected as a response process. The wave loading was evaluated using the second-order diffraction code WAMIT and applied to a linear damped mass-spring model representing the dynamic system. Then, platform displacement response at the design low probability level has been determined using a novel deconvolution approach. Since the Volterra series represented the analytical solution, the exact Volterra and the approximated predictions have been compared in this study. The latter provided an accurate way to validate the effectiveness and precision of the proposed novel deconvolution method. Compared to existing engineering techniques, the most attractive advantage of the proposed deconvolution method is that it does not rely on any pre-assumed asymptotic probability distribution class. The latter may be an attractive point for practical engineering design. Thus the primary objective of this work was to validate a novel deconvolution approach using exact quasi-analytical solutions. This work also highlights the limitations of mean up-crossing rate-based extrapolation methodologies for the situation of narrowband effects, including clustering, which are often included in the springing type of response.http://www.sciencedirect.com/science/article/pii/S2092678223000043TLPWAMITExtreme statisticsVolterra seriesWaves
spellingShingle Oleg Gaidai
Yu Cao
Yihan Xing
Rajiv Balakrishna
Extreme springing response statistics of a tethered platform by deconvolution
International Journal of Naval Architecture and Ocean Engineering
TLP
WAMIT
Extreme statistics
Volterra series
Waves
title Extreme springing response statistics of a tethered platform by deconvolution
title_full Extreme springing response statistics of a tethered platform by deconvolution
title_fullStr Extreme springing response statistics of a tethered platform by deconvolution
title_full_unstemmed Extreme springing response statistics of a tethered platform by deconvolution
title_short Extreme springing response statistics of a tethered platform by deconvolution
title_sort extreme springing response statistics of a tethered platform by deconvolution
topic TLP
WAMIT
Extreme statistics
Volterra series
Waves
url http://www.sciencedirect.com/science/article/pii/S2092678223000043
work_keys_str_mv AT oleggaidai extremespringingresponsestatisticsofatetheredplatformbydeconvolution
AT yucao extremespringingresponsestatisticsofatetheredplatformbydeconvolution
AT yihanxing extremespringingresponsestatisticsofatetheredplatformbydeconvolution
AT rajivbalakrishna extremespringingresponsestatisticsofatetheredplatformbydeconvolution