Texas A&M University LibrariesTexas A&M University LibrariesTexas A&M University Libraries
    • Help
    • Login
    OAKTrust
    View Item 
    •   OAKTrust Home
    • Colleges and Schools
    • Office of Graduate and Professional Studies
    • Electronic Theses, Dissertations, and Records of Study (2002– )
    • View Item
    •   OAKTrust Home
    • Colleges and Schools
    • Office of Graduate and Professional Studies
    • Electronic Theses, Dissertations, and Records of Study (2002– )
    • View Item
    JavaScript is disabled for your browser. Some features of this site may not work without it.

    Using Genetic Algorithms to Optimize Bathymetric Surveys for Hydrodynamic Model Input

    Thumbnail
    View/ Open
    MANIAN-THESIS.pdf (5.664Mb)
    Date
    2010-07-14
    Author
    Manian, Dinesh
    Metadata
    Show full item record
    Abstract
    The first part of this thesis deals with studying the effect of the specified bathymetric resolution and ideal bathymetric form parameters on the output from the wave and hydrodynamic modules of Delft-3D. This thesis then describes the use of an optimization to effectively reduce the required bathymetric sampling for input to a numerical forecast model, by using the model’s sensitivity to this input. A genetic algorithm is developed to gradually evolve the survey path for a ship, AUV, or other measurement platform to an optimum, with the resulting effect of the corresponding measured bathymetry on the model, used as a metric. Starting from an initial simulated set of possible random or heuristic sampling paths over the given bathymetry using certain constraints like limited length of track, the algorithm can be used to arrive at the path that would provide the best possible input to the model under those constraints. This suitability is tested by a comparison of the model results obtained by using these new simulated observations, with the results obtained using the best available bathymetry. Two test study areas were considered, and the algorithm was found to consistently converge to a sampling pattern that best captured the bathymetric variability critical to the model prediction.
    URI
    https://hdl.handle.net/1969.1/ETD-TAMU-2009-12-7290
    Subject
    bathymetric surveys
    genetic algorithms
    sampling strategy
    Delft-3D model
    NCEX
    Collections
    • Electronic Theses, Dissertations, and Records of Study (2002– )
    Citation
    Manian, Dinesh (2009). Using Genetic Algorithms to Optimize Bathymetric Surveys for Hydrodynamic Model Input. Master's thesis, Texas A&M University. Available electronically from https : / /hdl .handle .net /1969 .1 /ETD -TAMU -2009 -12 -7290.

    DSpace software copyright © 2002-2016  DuraSpace
    Contact Us | Send Feedback
    Theme by 
    Atmire NV
     

     

    Advanced Search

    Browse

    All of OAKTrustCommunities & CollectionsBy Issue DateAuthorsTitlesSubjectsDepartmentTypeThis CollectionBy Issue DateAuthorsTitlesSubjectsDepartmentType

    My Account

    LoginRegister

    Statistics

    View Usage Statistics
    Help and Documentation

    DSpace software copyright © 2002-2016  DuraSpace
    Contact Us | Send Feedback
    Theme by 
    Atmire NV