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  5. Numerical modelling and statistical emulation of landslide induced tsunamis: the Rockall Bank slide complex, NE Atlantic Ocean
 
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Numerical modelling and statistical emulation of landslide induced tsunamis: the Rockall Bank slide complex, NE Atlantic Ocean

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Author(s)
Salmanidou, Dimitra - Makrina 
Advisor(s)
Dias, Frederic 
Uri
http://hdl.handle.net/10197/8603
Date Issued
2017
Date Available
14T02:00:10Z December 2017
Abstract
This thesis studies submarine sliding and tsunami generation at the Rockall Bank, NE Atlantic Ocean through numerical and statistical modelling. Two numerical codes are used to perform the simulations from the submarine sliding to tsunami generation, propagation and inundation. The landslide model is VolcFlow and the tsunami model is VOLNA. Some of the basic rheological regimes used to model submarine landslides are briefly discussed, with a comparison in the case of the Rockall Bank. The latest version of VOLNA is validated against an analytical solution. The brief geological history of the area under study is also given. The numerical simulations explore different scenarios of failure in the area, and assess their tsunamigenic potential and the impact of the tsunamis on the current topography of the Irish shoreline. The results of the simulations exhibit a great variability that derives from the parameters used as input in the landslide model. There is a need to quantify this uncertainty. To do so, a Bayesian calibration of the parameters is initially performed, which leads to the posterior distributions of the input parameters. A statistical emulator, which acts as a surrogate of the numerical process is then built. The emulator can lead to predictions of the process in excessively fast (when compared to the simulations) computational speeds. For the examined case, the emulator propagates the uncertainties in the distributions of the input parameters resulting from the calibration, to the outputs. As a result, the predictions of the maximum free surface elevation at specified locations are obtained.
Type of Material
Doctoral Thesis
Publisher
University College Dublin. School of Mathematics and Statistics  
Qualification Name
Ph.D.
Copyright (Published Version)
2017 the author
Keywords
  • Numerical modelling

  • Statistical emulation...

  • Submarine landslides

  • Tsunami

  • Uncertainty quantific...

Web versions
http://dissertations.umi.com/ucd:10136
Language
English
Status of Item
Peer reviewed
This item is made available under a Creative Commons License
https://creativecommons.org/licenses/by-nc-nd/3.0/ie/
Owning collection
Mathematics and Statistics Theses
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