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Geotechnical News • June 2012
March 2012
THESIS ABSTRACTS
790 Atlantic Drive, Atlanta, GA, T: 404-894-2285,
E:
Soft Computing Based Spatial Analysis of
Earthquake Triggered Coherent Landslides
Mesut Turel
Mesut Turel, Ph.D., 210 Technology Circle, Savannah, GA 31407,
T: 912-695-9867, E:
Earthquake triggered landslides cause loss of life, destroy
structures, roads, powerlines, and pipelines. Even though
future earthquakes can hardly be predicted, the identification
of areas that are highly susceptible to landslide hazards is
possible. For geographical information systems (GIS) based
landslide hazard analysis, the grid-cell approach has been
commonly used in conjunction with the relatively simple
infinite slope model. The infinite slope model together with
Newmark’s displacement analysis has been widely used to
create seismic landslide susceptibility maps. The infinite
slope model gives reliable results in the case of surficial
landslides with depth-length ratios smaller than 0.1. On
the other hand, the infinite slope model cannot satisfacto-
rily analyze deep-seated coherent landslides. In the case
of coherent landslides, two- or three-dimensional models
are required to accurately analyze both static and dynamic
performance of slopes. These models are rarely used in GIS-
based landslide hazard zonation because they are numeri-
cally expensive compared to one dimensional infinite slope
models. Building metamodels based on data obtained from
computer experiments and using computationally inexpen-
sive predictions based on these metamodels has been widely
used in several engineering applications. With these soft
computing methods, design variables are carefully chosen
using a design of experiments (DOE) methodology to cover
a predetermined range of values and computer experiments
are performed at these chosen points. The design variables
and the responses from the computer simulations are then
combined to construct functional relationships (metamodels)
between the inputs and the outputs. In this study, Support
Vector Machines (SVM) and Artificial Neural Networks
(ANN) are used to predict the static and seismic responses
of slopes. In order to integrate the soft computing methods
with GIS for coherent landslide hazard analysis, an auto-
matic slope profile delineation method from Digital Eleva-
tion Models is developed. The integrated framework is
evaluated using a case study of the 1989 Loma Prieta, CA
earthquake (Mw = 6.9). A seismic landslide hazard analysis
is also performed for the same region for a future scenario
earthquake (Mw = 7.1) on the San Andreas Fault.
Supervisor: Dr. J. David Frost, Georgia Institute of Technology,
790 Atlantic Drive, Atlanta, GA
GIS-enabled Spatial Analysis and Modeling
of Geotechnical Soil Properties for Seismic
Risk Assessment of Levee Systems
Mustafa Saadi
Mustafa Saadi, 914 Briarvista Way NE. Atlanta, GA 30329,
T: 734 474-6841, E:
Flood protection systems are complex, interconnected
engineered systems, where failure at one location means
the failure of the entire system. Earthen levees, the systems’
major component, are at risk from many causes of failure
including seepage, erosion and instability due to seismic
loading, yet there are currently no guidelines available for
the seismic design of levees.
Levees stretch for long distances and are formed through
various geologic processes and human activities over time,
however information regarding soil properties is collected
only at limited point locations and varies significantly both
laterally and with depth. Levee vulnerability analyses are
currently performed only at locations with known soil prop-
erties. Prediction of levee performance in locations where
no soil data is available becomes a limitation for system risk
assessment studies.
A simplified methodology is proposed to predict soil vari-
ability in riverine geologic environments for the seismic
risk assessment of earthen levee systems. A key step in this
methodology is to provide a continuous characterization of
soil conditions throughout the system. The proposed model
correlates soil properties to preselected regional variables
and is implemented, using geostatistical kriging, in a
Geographic Information Systems (GIS) environment. GIS
was crucial in this research and proved to be the appropri-
ate platform for input, manipulation, analysis, and output
presentation of spatial and non-spatial data.
Correlation relationships between soil strength parameters
and geological and river geometry factors are presented for
a pilot study area in California. Global observations that
apply across the study area included the increasing trend of
shear strength, Su, with increasing distance from the river,
and decreasing trend of Su with increasing river Sinuos-
ity Index levels. Only local trends were observed in the
relation of friction angle,
φ
, with Sinuosity Index, as well
as in the relation of Su and
φ
with geological formations.
The proposed methodology also includes steps for seismic
response analysis of levee segments, and flood scenarios in
protected areas. Since seismic response of earthen structures
is controlled primarily by input ground motions, a meth-
odology for selecting ground motions based on their mean
period, Tm, for liquefaction triggering assessment of levees
is also developed.
Sponsor: Adda Athanasopoulos-Zekkos, Ph.D., Assistant Profes-
sor, Civil and Environmental Engineering, The University of Michi-
gan, Ann Arbor,
/, 2362 GG Brown,
