Dignan, Jack;
(2025)
Smoothed particle hydrodynamics and gaussian process emulation: applications to tsunami modelling.
Doctoral thesis (Ph.D), UCL (University College London).
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Abstract
The overall aim of this thesis is to explore the potential of high-resolution 3D modelling of tsunami flows across complex bathymetry and urban topography, including buildings and structures. The use of Gaussian Process Emulation to speed up the prediction of key output quantities of interest is investigated and reviewed, and their ability to produce meaningful outputs at the fraction of the computational cost of the simulation model is discussed. This learning and prediction is applied to a Non-Linear Shallow Water Equation (NLSWE) landslide-tsunami simulation model to predict maximum tsunami wave heights within the Makassar Strait in Indonesia. The Smoothed Particle Hydrodynamics (SPH) method is reviewed for its applicability for modelling tsunami flows against key tsunami simulation benchmark cases. Following the review of SPH in a range of validation cases, the development of a real-world 3D setup using SPH is documented. The real-world 3D case focuses on the town of Cilacap, Indonesia, including inland waterways, real-world bathymetry and topography, and an accurate representation of coastal buildings. Finally, the Cilacap SPH domain is coupled with a NLSWE solver to create an end-to-end tsunami simulator. This one-way offline coupled model makes use of the computational efficiency of using NLSWE solvers to simulate tsunami generation and propagation, up until shallow water. The SPH domain then simulates late stage runup and inundation, where it is able to capture the complex turbulent flows and wave-structure interactions between the tsunami and buildings. Gaussian Process Emulators are then fitted to the input-output relationship of this coupled model to observe maximum surface elevation and maximum forces on structures.
| Type: | Thesis (Doctoral) |
|---|---|
| Qualification: | Ph.D |
| Title: | Smoothed particle hydrodynamics and gaussian process emulation: applications to tsunami modelling |
| Open access status: | An open access version is available from UCL Discovery |
| Language: | English |
| Additional information: | Copyright © The Author 2025. Original content in this thesis is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0) Licence (https://creativecommons.org/licenses/by-nc/4.0/). Any third-party copyright material present remains the property of its respective owner(s) and is licensed under its existing terms. Access may initially be restricted at the author’s request. |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences > Dept of Statistical Science |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10209716 |
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