Artificial Neural Networks for Nonlinear Dynamic Response Simulation in Mechanical Systems

Niels Hørbye Christiansen, Jan Becker Høgsberg, Ole Winther

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

    714 Downloads (Pure)

    Abstract

    It is shown how artificial neural networks can be trained to predict dynamic response of a simple nonlinear structure. Data generated using a nonlinear finite element model of a simplified wind turbine is used to train a one layer artificial neural network. When trained properly the network is able to perform accurate response prediction much faster than the corresponding finite element model. Initial result indicate a reduction in cpu time by two orders of magnitude.
    Original languageEnglish
    Title of host publicationProceedings of the 24th Nordic Seminar on Computational Mechanics
    Publication date2011
    Publication statusPublished - 2011
    EventNSCM-24 - Helsinki, Finland
    Duration: 1 Jan 2011 → …

    Conference

    ConferenceNSCM-24
    CityHelsinki, Finland
    Period01/01/2011 → …

    Keywords

    • Nonlinear structural dynamics
    • Artificial neural networks

    Fingerprint

    Dive into the research topics of 'Artificial Neural Networks for Nonlinear Dynamic Response Simulation in Mechanical Systems'. Together they form a unique fingerprint.

    Cite this