Efficient Mooring Line Fatigue Analysis Using a Hybrid Method Time Domain Simulation Scheme
Dynamic analyses of mooring line systems are computationally expensive. Over the last decades an extensive variety of methods to reduce this computational cost have been suggested. One method that has shown promising preliminary results is a hybrid method which combines finite element analysis and a...
Published in: | Volume 1: Offshore Technology |
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Language: | English |
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The American Society of Mechanical Engineers (ASME)
2013
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Online Access: | https://orbit.dtu.dk/en/publications/b8544935-f067-4274-b3c3-1fa4c47ec402 https://doi.org/10.1115/OMAE2013-10682 |
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ftdtupubl:oai:pure.atira.dk:publications/b8544935-f067-4274-b3c3-1fa4c47ec402 2024-09-15T17:50:32+00:00 Efficient Mooring Line Fatigue Analysis Using a Hybrid Method Time Domain Simulation Scheme Christiansen, Niels Hørbye Voie, Per Erlend Torbergsen Høgsberg, Jan Becker Sødahl, Nils 2013 https://orbit.dtu.dk/en/publications/b8544935-f067-4274-b3c3-1fa4c47ec402 https://doi.org/10.1115/OMAE2013-10682 eng eng The American Society of Mechanical Engineers (ASME) https://orbit.dtu.dk/en/publications/b8544935-f067-4274-b3c3-1fa4c47ec402 urn:ISBN:978-0-7918-5531-7 info:eu-repo/semantics/restrictedAccess Christiansen , N H , Voie , P E T , Høgsberg , J B & Sødahl , N 2013 , Efficient Mooring Line Fatigue Analysis Using a Hybrid Method Time Domain Simulation Scheme . in ASME 2013 32nd International Conference on Ocean, Offshore and Arctic Engineering . vol. 1 , OMAE2013-10682 , The American Society of Mechanical Engineers (ASME) , 32nd International Conference on Ocean, Offshore and Arctic Engineering (OMAE 2013) , Nantes , France , 09/06/2013 . https://doi.org/10.1115/OMAE2013-10682 contributionToPeriodical 2013 ftdtupubl https://doi.org/10.1115/OMAE2013-10682 2024-07-22T23:50:05Z Dynamic analyses of mooring line systems are computationally expensive. Over the last decades an extensive variety of methods to reduce this computational cost have been suggested. One method that has shown promising preliminary results is a hybrid method which combines finite element analysis and artificial neural networks (ANN). The present study presents a novel strategy for selecting, arranging and normalizing training data for an ANN. With this approach one ANN can be trained to perform high speed dynamic response prediction for all fatigue relevant sea states and cover both wave frequency motion and slow drift motion. The method is tested on a mooring line system of a floating offshore platform. After training a full fatigue analysis is carried out. The results show that the ANN with high precision provides top tension force histories two orders of magnitude faster than a full dynamic analysis. Copyright © 2013 by ASME. Article in Journal/Newspaper Arctic Technical University of Denmark: DTU Orbit Volume 1: Offshore Technology |
institution |
Open Polar |
collection |
Technical University of Denmark: DTU Orbit |
op_collection_id |
ftdtupubl |
language |
English |
description |
Dynamic analyses of mooring line systems are computationally expensive. Over the last decades an extensive variety of methods to reduce this computational cost have been suggested. One method that has shown promising preliminary results is a hybrid method which combines finite element analysis and artificial neural networks (ANN). The present study presents a novel strategy for selecting, arranging and normalizing training data for an ANN. With this approach one ANN can be trained to perform high speed dynamic response prediction for all fatigue relevant sea states and cover both wave frequency motion and slow drift motion. The method is tested on a mooring line system of a floating offshore platform. After training a full fatigue analysis is carried out. The results show that the ANN with high precision provides top tension force histories two orders of magnitude faster than a full dynamic analysis. Copyright © 2013 by ASME. |
format |
Article in Journal/Newspaper |
author |
Christiansen, Niels Hørbye Voie, Per Erlend Torbergsen Høgsberg, Jan Becker Sødahl, Nils |
spellingShingle |
Christiansen, Niels Hørbye Voie, Per Erlend Torbergsen Høgsberg, Jan Becker Sødahl, Nils Efficient Mooring Line Fatigue Analysis Using a Hybrid Method Time Domain Simulation Scheme |
author_facet |
Christiansen, Niels Hørbye Voie, Per Erlend Torbergsen Høgsberg, Jan Becker Sødahl, Nils |
author_sort |
Christiansen, Niels Hørbye |
title |
Efficient Mooring Line Fatigue Analysis Using a Hybrid Method Time Domain Simulation Scheme |
title_short |
Efficient Mooring Line Fatigue Analysis Using a Hybrid Method Time Domain Simulation Scheme |
title_full |
Efficient Mooring Line Fatigue Analysis Using a Hybrid Method Time Domain Simulation Scheme |
title_fullStr |
Efficient Mooring Line Fatigue Analysis Using a Hybrid Method Time Domain Simulation Scheme |
title_full_unstemmed |
Efficient Mooring Line Fatigue Analysis Using a Hybrid Method Time Domain Simulation Scheme |
title_sort |
efficient mooring line fatigue analysis using a hybrid method time domain simulation scheme |
publisher |
The American Society of Mechanical Engineers (ASME) |
publishDate |
2013 |
url |
https://orbit.dtu.dk/en/publications/b8544935-f067-4274-b3c3-1fa4c47ec402 https://doi.org/10.1115/OMAE2013-10682 |
genre |
Arctic |
genre_facet |
Arctic |
op_source |
Christiansen , N H , Voie , P E T , Høgsberg , J B & Sødahl , N 2013 , Efficient Mooring Line Fatigue Analysis Using a Hybrid Method Time Domain Simulation Scheme . in ASME 2013 32nd International Conference on Ocean, Offshore and Arctic Engineering . vol. 1 , OMAE2013-10682 , The American Society of Mechanical Engineers (ASME) , 32nd International Conference on Ocean, Offshore and Arctic Engineering (OMAE 2013) , Nantes , France , 09/06/2013 . https://doi.org/10.1115/OMAE2013-10682 |
op_relation |
https://orbit.dtu.dk/en/publications/b8544935-f067-4274-b3c3-1fa4c47ec402 urn:ISBN:978-0-7918-5531-7 |
op_rights |
info:eu-repo/semantics/restrictedAccess |
op_doi |
https://doi.org/10.1115/OMAE2013-10682 |
container_title |
Volume 1: Offshore Technology |
_version_ |
1810292332261539840 |