The use of chaos metrics to analyze Lagrangian particle diffusion models
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Authors
Jackson, Korey V.
Subjects
Chaos
Particle diffusion
Modeling
Self-affine fractal dimension
Entropy
Lyapunov exponent
Particle diffusion
Modeling
Self-affine fractal dimension
Entropy
Lyapunov exponent
Advisors
Kamada, Ray F.
Date of Issue
1992-06
Date
June 1992
Publisher
Monterey, California. Naval Postgraduate School
Language
en_US
Abstract
Chaos metrics are examined as a tool to analyze atmospheric three-dimensional dispersion models at the individual particle rather than the aggregate level. These include the self-affine fractal dimension, D (^), Shannon entropy, S, and Lyapunov exponent, (^). Intercomparison of these metrics is first performed with the one-dimensional logistics difference and the two-dimensional Henon systems of equations. The fractal dimension and Shannon entropy are then measured as a function of the inverse Monin-Obuhkov length (1/L) for two three-dimensional Lagrangian particle dispersion models, the McNider particle dispersion model and the NPS particle dispersion model now under development. The fractal dimension and Shannon entropy uncover weaknesses in both models which are not obvious with standard geophysical measures. They also reveal similarities and difference between the atmospheric models and simple chaos systems. Combined, these chaos measures may lend detailed insight into the behavior of Lagrangian Monte Carlo dispersion models in general. .
Type
Thesis
Description
Series/Report No
Department
Department of Physics
Organization
Naval Postgraduate School
Identifiers
NPS Report Number
Sponsors
Funder
Format
153 p.
Citation
Distribution Statement
Approved for public release; distribution is unlimited.
Rights
This publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. Copyright protection is not available for this work in the United States.