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Title: Advances in computational modelling of turbidity currents using the finite-element method
Author: Parkinson, Samuel
ISNI:       0000 0004 5922 8560
Awarding Body: Imperial College London
Current Institution: Imperial College London
Date of Award: 2016
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Turbidity currents are one of the main processes by which sediment is moved from the continental shelf to the deep ocean. They are a potential environmental hazard and they form a significant component of the stratigraphic record. Computational modelling is an important tool for understanding turbidity current dynamics, for augmenting experimental analyses, and for interpreting data that is collected in the field. This work begins by presenting a depth-averaged turbidity current model that is differentiated to facilitate the use of gradient-based optimisation algorithms. These optimisation algorithms are applied in selecting model parameters to best fit model output with data obtained in the field. To the best of the author's knowledge this is the first published work where optimisation of input parameters is applied to turbidity current modelling. The work also presents the first high resolution three-dimensional simulation of a turbidity current using the finite element method. One of the key benefits of the finite element method is the ability to easily accommodate complex domain geometries. As such this model is uniquely capable of producing high resolution simulations of turbidity currents in unconstrained complex domains. Methods of reducing the computational cost of these very expensive simulations are explored. The use of Large Eddy Simulation is shown to provide some improvements at moderate simulation resolutions. Unstructured mesh optimisation is shown to reduce the cost of these simulations by approximately two orders of magnitude when compared to a fixed mesh simulation. The savings afforded by the use of these techniques make the problem tractable using finite elements and will enable simulation of turbidity currents in complex and expansive domains where DNS modelling was previously unachievable.
Supervisor: Piggott, Matthew ; Allison, Peter Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral