The mooring lines used for floating offshore platforms experience wide-banded tension loads, in which fatigue damage can be predicted accurately in time domain. This paper reports the results of a feasibility study on the application of an artificial neural network (ANN) to predict wide-banded fatigue damage in the mooring lines of a floating offshore wind turbine platform (FOWT). The assumed three catenary mooring lines provide station-keeping ability for the FOWT. A commercial software was used to perform dynamic analyses of the mooring line in the time domain for limited load cases. The analysis results were used to train a multi-layered ANN model. To validate the performance of the trained ANN model, mooring dynamic simulations are carried out for a set of newly defined load cases. The new simulation results were compared with the predicted ones using the trained ANN model. It is proven that two results were in excellent agreement in terms of the tension range distributions of a mooring line.


    Zugriff

    Zugriff über TIB

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Fatigue damage analysis for a floating offshore wind turbine mooring line using the artificial neural network approach


    Beteiligte:

    Erschienen in:

    Erscheinungsdatum :

    2017




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Print


    Sprache :

    Englisch



    Klassifikation :

    BKL:    50.92 / 50.92 Meerestechnik / 55.40 / 55.40 Schiffstechnik, Schiffbau





    Offshore floating type wind turbine mooring floating body platform

    JIN XIN / CHEN YIMING / LUO MENGJIE et al. | Europäisches Patentamt | 2021

    Freier Zugriff


    Mooring system for floating wind turbine

    BJØRN SKAARE | Europäisches Patentamt | 2022

    Freier Zugriff