Prediction of Earthquakes

Fraser, Euan Macpherson (1997) Prediction of Earthquakes. MSc(R) thesis, University of Glasgow.

Full text available as:
[img]
Preview
PDF
Download (12MB) | Preview

Abstract

We start by introducing the reader to the mechanisms behind earthquake production, including the Elastic Rebound Theory and the theory of Plate Tectonics. We also discuss the quantification of earthquakes in terms of magnitude, intensity and energy released. A short review of the history of earthquake prediction is also given, along with a discussion of some of the latest attempts at discovering seismic precursors. The VAN method, and the controversy surrounding it are discussed in some depth in chapter 5, while the theory of Seismic Gaps is introduced in chapter 6. Experiments using cellular automata to model earthquake production are performed in chapter 7, and the resulting analysis presented. The use of mechanical models is explored in chapter 8, where the slider block model is analysed. The Hurst analysis of a time series is introduced, and real earthquake data analysed in detail. A short discussion of fractal dimensions is given in chapter 10, where we present some classic fractals such as the Sierpinski gasket and the Koch curve. The Hausdorff dimension is introduced, and the idea of Box counting dimension discussed. The calculation of the correlation dimension is then presented. This is then used in chapter 11, where we present a new prediction method, based upon fluctuations in the correlation dimension. The results obtained using this method are outlined, as are some hopes for the future of earthquake prediction.

Item Type: Thesis (MSc(R))
Qualification Level: Masters
Additional Information: Adviser: S G Hoggar
Keywords: Geophysics
Date of Award: 1997
Depositing User: Enlighten Team
Unique ID: glathesis:1997-76451
Copyright: Copyright of this thesis is held by the author.
Date Deposited: 19 Nov 2019 14:19
Last Modified: 19 Nov 2019 14:19
URI: http://theses.gla.ac.uk/id/eprint/76451

Actions (login required)

View Item View Item

Downloads

Downloads per month over past year