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Extreme wave run-up and pressure on a vertical seawall


Reference:

Ning, D., Wang, R., Chen, L. F., Li, J., Zang, J., Cheng, L. and Liu, S., 2017. Extreme wave run-up and pressure on a vertical seawall. Applied Ocean Research, 67, pp. 188-200.

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    Official URL:

    http://dx.doi.org/10.1016/j.apor.2017.07.015

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    Abstract

    The performance of coastal vertical seawalls in extreme weather events is studied numerically, aiming to provide guidance in designing and reassessing coastal structures with vertical wall. The extreme wave run-up and the pressure on the vertical seawall are investigated extensively. A time-domain higher-order boundary element method (HOBEM) is coupled with a mixed Eulerian-Lagrangian technique as a time marching technique. Focused wave groups are generated by a piston wave-maker in the numerical wave tank using a wave focusing technique for accurately reproducing extreme sea states. An acceleration-potential scheme is used to calculate the transient wave loads. Comparisons with experimental data show that the extended numerical model is able to accurately predict extreme wave run-ups and pressures on a vertical seawall. The effects of the wave spectrum bandwidth, the wall position and the wave nonlinearity on the wave run-up and the maximum wave load on the vertical seawall are investigated by doing parametric studies.

    Details

    Item Type Articles
    CreatorsNing, D., Wang, R., Chen, L. F., Li, J., Zang, J., Cheng, L. and Liu, S.
    DOI10.1016/j.apor.2017.07.015
    Related URLs
    URLURL Type
    http://www.scopus.com/inward/record.url?scp=85026780727&partnerID=8YFLogxKUNSPECIFIED
    Uncontrolled Keywordscoastal vertical seawall,extreme sea states,fully nonlinear potential flow theory,wave pressure,wave run-up,ocean engineering
    DepartmentsResearch Centres & Institutes > Water, Environment and Infrastructure resilience (WEIR) Research Unit
    Faculty of Engineering & Design > Architecture & Civil Engineering
    Research Centres?? WIRC ??
    EPSRC Centre for Doctoral Training in Statistical Mathematics (SAMBa)
    RefereedYes
    StatusPublished
    ID Code57476

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