• Login
    View Item 
    •   Home
    • Theses & Dissertations
    • 2016 - Mines Theses & Dissertations
    • View Item
    •   Home
    • Theses & Dissertations
    • 2016 - Mines Theses & Dissertations
    • View Item
    JavaScript is disabled for your browser. Some features of this site may not work without it.

    Browse

    All of Mines RepositoryCommunitiesPublication DateAuthorsTitlesSubjectsThis CollectionPublication DateAuthorsTitlesSubjects

    My Account

    Login

    Mines Links

    Arthur Lakes LibraryColorado School of Mines

    Statistics

    Display Statistics

    Class of efficient algorithms for stochastic seismic ground motions, A

    • CSV
    • RefMan
    • EndNote
    • BibTex
    • RefWorks
    Thumbnail
    Name:
    Verros_mines_0052N_11062.pdf
    Size:
    6.051Mb
    Format:
    PDF
    Download
    Author
    Verros, Sarah A.
    Advisor
    Ganesh, Mahadevan
    Wald, David J. (David Jay)
    Date issued
    2016
    Keywords
    ground motions
    Karhunen Loeve
    spatial variability
    spherical needlet
    successive conditional simulation
    
    Metadata
    Show full item record
    URI
    https://hdl.handle.net/11124/170317
    Abstract
    Modeling the spatial correlation of ground motion residuals, caused by coherent contributions from source, path, and site, can provide valuable loss and hazard information, as well as a more realistic picture of ground motion intensities. The USGS computer model, ShakeMap, utilizes a deterministic approach to simulate median ground motions based on observed seismic data. ShakeMap based simulations are used to estimate fatalities and economic losses after a seismic event. Incorporating the spatial correlation of ground motion residuals has been shown to improve seismic loss estimation. The method of Park et al. (2007) has been investigated for computing spatially correlated random fields of residuals. However, for large scale ShakeMap models, computational requirements of the method by Park et al. (2007) are prohibitive. In this thesis, for our application-specific seismic ground motion problem, we develop and implement three new computationally efficient methods to model spatially correlated random field of residuals, in conjunction with ShakeMap. First, we develop a memory efficient algorithm to improve the approach proposed by Park et al. (2007). This new, multilevel parallel algorithm is based on decay properties of an associated ground motion correlation function. The first approach is dependent on input grids and the stochastic dimension is induced by the grid size. In the second method, we seek to reduce the dimensionality associated with the computation through global Karhunen Loeve (KL) expansions for random fields on the sphere. In the third method, we use a localized version of the KL representation using needlet approximations. We demonstrate the three approaches using extensive simulations.
    Rights
    Copyright of the original work is retained by the author.
    Collections
    2016 - Mines Theses & Dissertations

    entitlement

     
    DSpace software (copyright © 2002 - 2023)  DuraSpace
    Quick Guide | Contact Us
    Open Repository is a service operated by 
    Atmire NV
     

    Export search results

    The export option will allow you to export the current search results of the entered query to a file. Different formats are available for download. To export the items, click on the button corresponding with the preferred download format.

    By default, clicking on the export buttons will result in a download of the allowed maximum amount of items.

    To select a subset of the search results, click "Selective Export" button and make a selection of the items you want to export. The amount of items that can be exported at once is similarly restricted as the full export.

    After making a selection, click one of the export format buttons. The amount of items that will be exported is indicated in the bubble next to export format.