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Selection of the optimum combination of responses for Wave Buoy Analogy - An approach based on local sensitivity analysis

    • Norwegian University of Science and Technology

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

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    Abstract

    One method to estimate the wave spectrum onboard ships is to use measured ship responses. In this method, known also as Wave Buoy Analogy, amongst various responses that are available from sensor measurements, a couple of responses (at least three) are usually utilized. Selec-tion of the best combination of ship responses is important. Optimally, this selection should not be implemented manually in onboard applications. Therefore, availability of an automatic response selection procedure would be a great advantage for decision support. In this paper, a local sensitivity analysis is applied to evaluate the importance of individual responses in sea state estimation. The sensitivity factor is defined by calculation of the partial derivatives of wave parameters with respect to the variance of individual responses.
    Original languageEnglish
    Title of host publicationProceedings of the 13th International Symposium on PRActical Design of Ships and Other Floating Structures (PRADS' 2016)
    EditorsUlrik Dam Nielsen, Jørgen Juncher Jensen
    Number of pages8
    PublisherTechnical University of Denmark
    Publication date2016
    ISBN (Electronic)978-87-7475-473-2
    Publication statusPublished - 2016
    Event13th International Symposium on Practical Design of Ships and Other Floating Structures (PRADS'2016) - Hotel Crowne Plaza, Copenhagen, Denmark
    Duration: 4 Sept 20168 Sept 2016
    Conference number: 13

    Conference

    Conference13th International Symposium on Practical Design of Ships and Other Floating Structures (PRADS'2016)
    Number13
    LocationHotel Crowne Plaza
    Country/TerritoryDenmark
    CityCopenhagen
    Period04/09/201608/09/2016

    Keywords

    • Wave Buoy Analogy
    • Response selection
    • Sensitivity analysis
    • Derivatives
    • Sensitivity Factors

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