%0 PDF
%T Stochastic Modeling Techniques for
Offshore Geohazards.
%A Morgan, Eugene.
%8 2017-04-18
%R http://localhost/files/5h73q681d
%X Abstract: Much
remains to be known about offshore phenomena, despite the potential threat they pose to
coastal communities and economically-important offshore infrastructure. The scientific
and engineering community has a fairly good grasp of the mechanics governing these
geohazards; for instance, we can model tsunami run-ups over entire oceans, evaluate the
stability of slopes, and predict the runout of a given landslide. Much of the
uncertainty arising in applications of such models stems from the sparsity and error in
offshore data. Such datasets are often sparse because the ocean is so large, and contain
values with potentially significant measurement error because of the complexities
involved in collecting data in such extreme conditions (e.g., sampling sediment under
miles of water). Stochastic techniques and statistics quantify these types of
uncertainty. In the first chapter of this dissertation, I apply a stochastic
optimization method to a geophysical model to achieve estimates of sub-seabed gas
concentrations from remotely-sourced seismic reflection data. In the second chapter, I
combine geostatistics and first-order, second-moment uncertainty analysis to map the
probability of slope failure along the entire U.S. Atlantic margin. My third and final
chapter statistically characterizes offshore wind speeds using an unprecedented amount
of data collected over the northwestern
hemisphere.; Thesis (Ph.D.)--Tufts University,
2011.; Submitted to the Dept. of Civil
Engineering.; Advisor: Laurie
Baise.; Committee: Brian McAdoo, Rich Vogel, and
Grant Garven.; Keywords: Civil engineering,
Geophysics, and Geophysical engineering.
%[ 2022-05-07
%9 Text
%~ Tufts Digital Library
%W Institution