Optimized Mooring Line Simulation Using a Hybrid Method Time Domain Scheme

Niels Hørbye Christiansen, Per Erlend Torbergsen Voie, Jan Høgsberg, Nils Sodahl

    Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

    Abstract

    Dynamic analyses of slender marine structures are computationally expensive. Recently it has been shown how a hybrid method which combines FEM models and artificial neural networks (ANN) can be used to reduce the computation time spend on the time domain simulations associated with fatigue analysis of mooring lines by two orders of magnitude. The present study shows how an ANN trained to perform nonlinear dynamic response simulation can be optimized using a method known as optimal brain damage (OBD) and thereby be used to rank the importance of all analysis input. Both the training and the optimization of the ANN are based on one short time domain simulation sequence generated by a FEM model of the structure. This means that it is possible to evaluate the importance of input parameters based on this single simulation only. The method is tested on a numerical model of mooring lines on a floating offshore installation. It is shown that it is possible to estimate the cost of ignoring one or more input variables in an analysis.
    Original languageEnglish
    Title of host publicationProceedings of the 33rd International Conference on Ocean, Offshore and Arctic Engineering : Offshore Technology
    Number of pages10
    Volume1B
    PublisherThe American Society of Mechanical Engineers (ASME)
    Publication date2014
    Article numberOMAE2014-23939
    ISBN (Print)978-0-7918-4538-7
    DOIs
    Publication statusPublished - 2014
    Event33rd International Conference on Ocean, Offshore and Arctic Engineering - San Francisco, CA, United States
    Duration: 8 Jun 201413 Jun 2014
    http://www.asmeconferences.org/OMAE2014/

    Conference

    Conference33rd International Conference on Ocean, Offshore and Arctic Engineering
    Country/TerritoryUnited States
    CitySan Francisco, CA
    Period08/06/201413/06/2014
    Internet address

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