Long term extreme analysis of FPSO mooring systems based on Kriging metamodel
Establishing statistical distributions of the response extremes is of particular importance for the design of FPSO mooring systems and the related riser design. Long term time domain simulation is the most accurate design approach to determine the extreme responses. It involves, however, coupled dyn...
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ftustrathclyde:oai:strathprints.strath.ac.uk:52690 2024-04-28T08:04:39+00:00 Long term extreme analysis of FPSO mooring systems based on Kriging metamodel Wang, Aijun Huang, Shan Barltrop, Nigel 2014 https://strathprints.strath.ac.uk/52690/ https://doi.org/10.1115/OMAE2014-24609 unknown American Society of Mechanical Engineers (ASME) Wang, Aijun <https://strathprints.strath.ac.uk/view/author/853089.html> and Huang, Shan <https://strathprints.strath.ac.uk/view/author/22330.html> and Barltrop, Nigel <https://strathprints.strath.ac.uk/view/author/362905.html>; (2014 <https://strathprints.strath.ac.uk/view/year/2014.html>) Long term extreme analysis of FPSO mooring systems based on Kriging metamodel. In: Proceedings of the ASME 2014 33rd International Conference on Offshore Mechanics and Arctic Engineering. American Society of Mechanical Engineers (ASME), USA. ISBN 9780791845387 <https://strathprints.strath.ac.uk/view/isbn/9780791845387.html> Hydraulic engineering. Ocean engineering Book Section NonPeerReviewed 2014 ftustrathclyde https://doi.org/10.1115/OMAE2014-24609 2024-04-10T01:04:04Z Establishing statistical distributions of the response extremes is of particular importance for the design of FPSO mooring systems and the related riser design. Long term time domain simulation is the most accurate design approach to determine the extreme responses. It involves, however, coupled dynamic analysis of FPSO mooring system for a large number of sea states and consequently the task is often prohibitively time consuming. To solve this problem, an approach for the long term extreme analysis based on a metamodel in conjunction with the design of experiment methodology is proposed in the paper. In this approach, Latin Hypercube Sampling (LHS) based on the design of experiment method, is performed to select a sub-set of sea states from all sea states. Short term distributions for this sub-set of sea states are simulated and estimated. Kriging metamodel, which can map the relations between the sea states characteristics and the short term distribution parameters, is then applied. The accuracy of the metamodel is investigated. The long term response distribution of moored FPSO systems for all sea states can be predicted based on the metamodel. This approach for the long term extreme analysis of FPSO mooring systems avoids the response analysis over all sea states and can greatly improve the computational efficiency of the long term extreme analysis of FPSO mooring systems. Book Part Arctic University of Strathclyde Glasgow: Strathprints Volume 1B: Offshore Technology |
institution |
Open Polar |
collection |
University of Strathclyde Glasgow: Strathprints |
op_collection_id |
ftustrathclyde |
language |
unknown |
topic |
Hydraulic engineering. Ocean engineering |
spellingShingle |
Hydraulic engineering. Ocean engineering Wang, Aijun Huang, Shan Barltrop, Nigel Long term extreme analysis of FPSO mooring systems based on Kriging metamodel |
topic_facet |
Hydraulic engineering. Ocean engineering |
description |
Establishing statistical distributions of the response extremes is of particular importance for the design of FPSO mooring systems and the related riser design. Long term time domain simulation is the most accurate design approach to determine the extreme responses. It involves, however, coupled dynamic analysis of FPSO mooring system for a large number of sea states and consequently the task is often prohibitively time consuming. To solve this problem, an approach for the long term extreme analysis based on a metamodel in conjunction with the design of experiment methodology is proposed in the paper. In this approach, Latin Hypercube Sampling (LHS) based on the design of experiment method, is performed to select a sub-set of sea states from all sea states. Short term distributions for this sub-set of sea states are simulated and estimated. Kriging metamodel, which can map the relations between the sea states characteristics and the short term distribution parameters, is then applied. The accuracy of the metamodel is investigated. The long term response distribution of moored FPSO systems for all sea states can be predicted based on the metamodel. This approach for the long term extreme analysis of FPSO mooring systems avoids the response analysis over all sea states and can greatly improve the computational efficiency of the long term extreme analysis of FPSO mooring systems. |
format |
Book Part |
author |
Wang, Aijun Huang, Shan Barltrop, Nigel |
author_facet |
Wang, Aijun Huang, Shan Barltrop, Nigel |
author_sort |
Wang, Aijun |
title |
Long term extreme analysis of FPSO mooring systems based on Kriging metamodel |
title_short |
Long term extreme analysis of FPSO mooring systems based on Kriging metamodel |
title_full |
Long term extreme analysis of FPSO mooring systems based on Kriging metamodel |
title_fullStr |
Long term extreme analysis of FPSO mooring systems based on Kriging metamodel |
title_full_unstemmed |
Long term extreme analysis of FPSO mooring systems based on Kriging metamodel |
title_sort |
long term extreme analysis of fpso mooring systems based on kriging metamodel |
publisher |
American Society of Mechanical Engineers (ASME) |
publishDate |
2014 |
url |
https://strathprints.strath.ac.uk/52690/ https://doi.org/10.1115/OMAE2014-24609 |
genre |
Arctic |
genre_facet |
Arctic |
op_relation |
Wang, Aijun <https://strathprints.strath.ac.uk/view/author/853089.html> and Huang, Shan <https://strathprints.strath.ac.uk/view/author/22330.html> and Barltrop, Nigel <https://strathprints.strath.ac.uk/view/author/362905.html>; (2014 <https://strathprints.strath.ac.uk/view/year/2014.html>) Long term extreme analysis of FPSO mooring systems based on Kriging metamodel. In: Proceedings of the ASME 2014 33rd International Conference on Offshore Mechanics and Arctic Engineering. American Society of Mechanical Engineers (ASME), USA. ISBN 9780791845387 <https://strathprints.strath.ac.uk/view/isbn/9780791845387.html> |
op_doi |
https://doi.org/10.1115/OMAE2014-24609 |
container_title |
Volume 1B: Offshore Technology |
_version_ |
1797575189020540928 |