Dissertation/Thesis Abstract

Determining Bed Failure Depth in Unconsolidated Submarine Sediments Using Particles in Cell Numerical Modeling
by Beck, Alexander J., M.S., University of Louisiana at Lafayette, 2017, 78; 10685053
Abstract (Summary)

The cause for low angle submarine landslide (SML) failures, at slope angles less than 4°, currently cannot be readily predicted using conventional terrestrial sources (i.e. excess pore pressure, weak horizons). Numerous models that have been developed pertaining to mass wasting on continental margins generally fall into two categories: post landslide occurrence (Tsunami wave run-up modeling) on coast lines and core sample description on costal margins. To date, there has been limited research on determining bed failure depth of submarine landslides through modeling. We propose a new method of 2D numerical modeling of rupture surface within unconsolidated sediments using the “Particle in Cell” method in combination with a conservative finite volume scheme. The software is written in Python, using the Numerical Python (NumPy) library to reach compiled-code-like performance. The Particle in Cell method was tested for accuracy, advection, and numerical diffusion. A set of six numerical model simulations are presented in which we investigate the role of material and external properties (i.e. hydraulic diffusivity and sedimentation rate), and geometry in the quest to determine bed failure depth. Through initial modeling simulations, it is confirmed that yield strength, diffusivity and sediment loading all play a role in predicting failure.

Indexing (document details)
Advisor: Morra, Gabriele
Commitee: Gottardi, Raphael, Sidorovskaia, Natalia
School: University of Louisiana at Lafayette
Department: Geology
School Location: United States -- Louisiana
Source: MAI 57/05M(E), Masters Abstracts International
Source Type: DISSERTATION
Subjects: Geophysics, Geological engineering, Marine Geology
Keywords: Computing, Finite volume, Landslides, Numerical modeling, Particle in cell, Python
Publication Number: 10685053
ISBN: 9780355854503
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