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This document is downloaded at: 2020-08-05T21:07:18Z
Title Failure Mechanism and Its Induced Movement Simulation of
Large-scaleSlope
Author(s) 史, 嘯
Citation Nagasaki University (長崎大学), 博士(工学) (2017-03-21)
Issue Date 2017-03-21
URL http://hdl.handle.net/10069/37312
Right
NAOSITE: Nagasaki University's Academic Output SITE
http://naosite.lb.nagasaki-u.ac.jp
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Doctoral Thesis
Failure Mechanism and Its Induced Movement
Simulation of Large-scale Slope
March 2017
Graduate School of Engineering
Nagasaki University
Xiao Shi
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I
ACKNOWLEDGEMENTS
I would like to express my gratitude to all those who helped me
during the writing of this
thesis. My deepest gratitude goes first and foremost to Prof.
Yujing Jiang, my supervisor,
in the faculty of civil engineering, Nagasaki University, for
his constant encouragement
and guidance throughout my studies in master course in Nagasaki
University. Without his
patient instruction, insightful criticism and expert guidance,
the completion of this thesis
would not have been possible. He taught me how to think about a
problem independently,
how to become more confident, more passionate, more aware of
what I am striving after,
and to think about how well beyond. Acknowledgements are due to
Assistant Professor
Bo Li who always kindly teaches me how to write the thesis and
how to revise my English
and Japanese. Acknowledgements are also due to Assistant
Professor Satoshi Sugimoto
who gives me many supports in my study and daily life.
I would like to thank Prof. Akihide Tada and Prof. Kiyoshi Omine
in Nagasaki
University for their generous help and continuous supports for
my research. I would like
to express my appreciation to all the professors, associate
professors and assistants in
Graduate School of Engineering and all the students studying now
and graduated from
Nagasaki University for their supports and for the inspiring
atmosphere they have created.
I wish to thank my friends in China and the Chinese friends in
Japan for their
supports and encouragement during my study in Japan. My grateful
thanks should be
given to Dr. Richeng Liu, Dr. Xiaoshan Wang, Dr. Qu Wang, Dr.
Xuezhen Wu, Dr.
Jianhua Wang, Dr. Na Huang, Dr. Chen Wang, Dr. Xuepeng Zhang,
Dr. Jian Zheng,
Mr. Hao Huang, Mr. Han Xia, Mr. Kai Liu, Miss Ying Li and Miss
Xuening Guo. I am
always encouraged by our great friendships. I also thank Dr.
Santos Chicas, Dr. Yukihiro
Higashi and Dr. Junpei Ishida and I will always remember the
wonderful time we spent
together.
I should finally like to express my deepest gratitude to my
beloved parents who have
always been helping me out of difficulties and supporting
without a word of complaint. I
definitely can’t smoothly finish my doctoral study without their
love and supports.
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II
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Xiao Shi Nagasaki University
III
Abstract
In this study, failure mechanism research of the large-scale
slope and its induced
movement research, including (1) insufficient inventory mapping
of slope failure, (2)
selecting method in stability analysis of large-scale slope and
(3) movement simulating
methods of large-scale slope was reviewed. Slope failure is a
complicated system, for the
purpose of slope failure mitigation, the simulation of slope
failure should be conducted
in the scale of region area. However, a problem is that the
stratum mechanics
characteristics and surface topography in a large-scale slope
are some degree difficult to
grasp. Slope failure or movement usually occurs in a short
period of time and the
destructive power can cause great damage and loss of life. Few
researches took the
prediction of slope failure and movement into account.
Slope failure simulation are studied with finite difference
method (FDM), which is
a mesh-based method in stability analysis of large-scale slope.
The FLAC3D is an FDM
software and used in this study. For a large-scale slope, how to
judge the stability of slope
is difficult. The high accuracy terrain data is hard to be
obtained. Airborne laser scanning
is an effective method to measure terrain data in a large-scale
region. The airborne laser
data and FDM modeling are applied to analyze the mechanism of
Aso-Ohashi landslide
during 2016 Kumamoto earthquake. In this case, Aso-Ohashi
landslide was reproduced
by using numerical simulation. The Shear Strength Reduction
Method (SSRM) was
adopted and earthquake wave was input to explore the mechanism
of Aso-Ohashi
landslide. From the result of simulation, we could estimate
that:
1) Earthquake wave reduced strength of rock and made collapsed
rock liquefaction.
2) The foreshock simulated by SSRM indicated that, critical
values of strength were
c = 16 kPa and φ = 33.87 degree.
3) The passive collapsed region was gently dipping region where
failure of slope
was hardly occurred. The primary triggering factor of slide
might shear force produced
when mass of active collapsed region flew past.
Another case is to analyze the stability of lava dome in Unzen
volcano. The
appearance, growth, and stability of Heisei Lava Dome in Unzen
volcano, Japan was
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Failure Mechanism and Its Induced Movement Simulation of
Large-scale Slope
IV
analyzed. A new division method of lava dome was presented. Lava
dome was divided
into 10 PCBs (potential collapsed blocks) by the surface
distribution and the deep of PCBs
was calculated by airborne laser data in different period. From
stability analysis, if slide
plane was not considered, the reduction rate would be 30% (c was
120 kPa, φ was 23.2
degree), the model was likely to be unstable. That meant it was
hard to induce slope
failure and movement. But if slide plane was considered, the
model without earthquake
input would be unstable when reduction rate was 70% (c of PCBs
was 280 kPa, φ of PCBs
was 46.0 degree, c of interface was 168 kPa, and φ of interface
was 17.3 degree). The
critical reduction rate of unstable status was 76%, 81%, 84%,
90%, 95%, 99%, 100%
when intensity scale respectively was 1, 2, 3, 4, 5, 6 and 7.
Potential failure in maximum
volume was inferred from lobes 1 to 11 and including PCBs 1 ~
9.
For the movement of failure of slope, a Bingham model is
developed in which the
movement is assumed to be continuous, incompressible, unsteady
flow. The model which
is based on the continuity equations and Navier-Stokes equations
can simulate the
propagation and deposition of movement across the three
dimensional complex terrain.
Raster grid networks of digital elevation model in GIS
(Geographic Information System)
provide a uniform grid system to describe complex topography. As
the raster grid can be
used as the finite difference mesh, the continuity and momentum
equations are solved
numerically using the finite difference method. The accuracy of
model was verified
through the comparison of simulation results with the
experimental results obtained from
the U.S. Geological Survey debris flow flume between 1994 and
2004. The model
achieved reasonable results in comparison with experiment. The
numerical model is
applied to simulate the earthquake-induced movement occurred in
Aso-Ohashi landslide.
Through simulation of movement caused by failure of slope, it
was verified that the mass
had an initial velocity. Therefore, the active collapsed region
caused by earthquake wave.
In another case, the prediction of the potential pyroclastic
flow in lava dome, Unzen
volcano shows that the total volume of failure region would be
1.46×107 m3. Pyroclastic
flows caused by that were estimated based on a Bingham model and
the average velocity
would be approximately 20 m/s, the flow travels approximately
8.5 km. That means in
approximately 7 minutes, the pyroclastic flow will submerge the
downstream city.
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Xiao Shi Nagasaki University
V
Contents ACKNOWLEDGEMENTS
..................................................................................................................
I
Abstract
...............................................................................................................................................
III
CHAPTER 1
.........................................................................................................................................
1
Introduction
...........................................................................................................................................
1
1.1 Background and objectives
.....................................................................................................
1
1.2 Thesis arrangement and outline
..............................................................................................
8
References
...................................................................................................................................
11
CHAPTER 2
.......................................................................................................................................
15
Review of slope stability analysis research and slope movement
research ........................................ 15
2.1 Insufficient slope failure inventory mapping
........................................................................
15
2.2 Selecting method in slope failure susceptibility
....................................................................
16
2.3 Simulating methods of slope movement
...............................................................................
17
References
...................................................................................................................................
24
CHAPTER 3
.......................................................................................................................................
31
Finite difference method and its application to the study of
stability analysis on large-scale slope ... 31
3.1 Introduction
...........................................................................................................................
31
3.2 Terrain data from airborne laser scanning system
.................................................................
31
3.3 Description of finite difference method (FDM) and FLAC3D
............................................... 33
3.4 FDM simulation of three dimensional model
.......................................................................
34
3.4.1 Shear Strength reduction method
...............................................................................
36
3.4.2 Earthquake loading
....................................................................................................
37
3.5 Conclusions
...........................................................................................................................
42
References
...................................................................................................................................
43
CHAPTER 4
.......................................................................................................................................
45
GIS-based numerical simulation of slope movement: a Bingham
model ........................................... 45
4.1 Introduction
...........................................................................................................................
45
4.2 Governing equations
.............................................................................................................
46
4.3 Geographic Information System (GIS)
.................................................................................
48
4.3.1 Basic concept of
GIS..................................................................................................
48
4.3.2 Introduction of GIS structure
.....................................................................................
50
4.4 Incorporation of numerical simulation with GIS
..................................................................
51
4.4.1 Digital elevation model based on GIS
.......................................................................
51
4.4.2 Numerical scheme
......................................................................................................
52
4.4.3 Bingham determine statement
....................................................................................
54
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Failure Mechanism and Its Induced Movement Simulation of
Large-scale Slope
VI
4.5 Comparison of simulation results of Bingham model with the
experimental results ............ 55
4.6 Conclusions
...........................................................................................................................
58
References
...................................................................................................................................
60
CHAPTER 5
.......................................................................................................................................
65
Simulation of the initiation and motion of seismically induced
Aso-Ohashi landslide during 2016
Kumamoto earthquake
........................................................................................................................
65
5.1 Introduction
...........................................................................................................................
65
5.1.1 Summary of 2016 Kumamoto earthquake
.................................................................
67
5.1.2 Earthquake-induced landslides and outline of Aso-Ohashi
landslide ........................ 68
5.2 Geologic background
............................................................................................................
69
5.3 Comparison of terrain before and after earthquake
...............................................................
70
5.4 FDM Modeling and reproduction of destruction process
..................................................... 72
5.5 Stability analysis of foreshock by using shear strength
reduction method ........................... 75
5.6 Stability analysis of mainshock by seismic inputs
................................................................
78
5.7 Motion simulation of slide mass in the slope failure
............................................................ 81
5.8 Conclusions
...........................................................................................................................
83
References
...................................................................................................................................
85
CHAPTER 6
.......................................................................................................................................
89
Growth and potential collapse of the lava dome in Unzen volcano
and the estimation on slope
movements
..........................................................................................................................................
89
6.1 Introduction
...........................................................................................................................
89
6.1.1 Formation and Growth of lava dome
.........................................................................
91
6.1.2 Temporal variation of volcanic activity
.....................................................................
92
6.2 Division of lava dome
...........................................................................................................
95
6.2.1 Airborne laser data available
......................................................................................
95
6.2.2 Block division in the surface
......................................................................................
99
6.2.3 Evaluation of elevation change
................................................................................
100
6.2.4 Depth of collapsed blocks
........................................................................................
102
6.2.5 Reconstruction of the buried terrain of lobe
4.......................................................... 104
6.2.6 Conclusions
..............................................................................................................
107
6.3 Modeling and analysis of failures
.......................................................................................
108
6.3.1 Evaluation method of slope stability
........................................................................
108
6.3.2 Stability analysis without considered slip plane
...................................................... 109
6.3.3 Stability analysis considered slip plane
....................................................................
116
6.4 Potential pyroclastic flow simulation of Heisei Lava Dome
............................................... 128
6.4.1 Rheological model and input parameters
.................................................................
128
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Xiao Shi Nagasaki University
VII
6.4.2 Quantitative evaluating the influence of pyroclastic flow
by the collapse of lava dome
..........................................................................................................................................
129
6.5 Conclusions
.........................................................................................................................
133
References
.................................................................................................................................
135
CHAPTER 7
.....................................................................................................................................
139
Summaries and conclusions
..............................................................................................................
139
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Failure Mechanism and Its Induced Movement Simulation of
Large-scale Slope
VIII
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Xiao Shi Nagasaki University
1
CHAPTER 1
Introduction
1.1 Background and objectives
Failure of slope involving rock, mud, and its induced movement
are dominant
geomorphic processes in humid foreland environments worldwide.
The environmental
variables governing failure of slope, however, are not well
known because most mass
movement studies have been confined to areas influenced by human
activities. By
studying patterns of failure of slope in natural ecosystems,
government officials, policy
makers, engineers, geologists and others will become better
informed about likely success
of prevention or amelioration programs in risk-prone areas.
Increased population and economic pressures have focused failure of
slope research
on those areas where failure of slope has the potential to
affect human lives and
infrastructure (Turner and Shuster, 1996). According to Cruden
and Varnes (1996),
various factors control failure of slope. These include
geological, morphological, physical
and human causes. Geological causes include: material properties
such as: weakness,
sensitivity, degree of weathering, shear strength, jointing,
bedding, schistosity, thrusts,
faults, unconformities, contrast in permeability, and contrast
in stiffness (Varnes, 1978).
Morphological causes involve: tectonic or volcanic uplift,
glacial rebound, fluvial, glacial
or wave erosion of slope toe, erosion of lateral margin and
deposition and vegetation
removal. Similarly, physical causes involve: intense rainfall,
rapid snow melt, prolonged
exceptional precipitation, rapid drawdown, earthquake, volcanic
eruptions, thawing, and
shrink-and-swell weathering. Although the human causes are
negligible in this study area
as there are no significant human activities, there are several
human-induced failure of
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Failure Mechanism and Its Induced Movement Simulation of
Large-scale Slope
2
slope triggered all over the world. Human causes may be
excavation of slope, loading of
slope, drawdown or reservoirs, deforestation, irrigation,
mining, artificial vibration, water
leakage from utilities, etc.
According to Keller (2000), failure of slope causes can be
grouped as external causes
or internal causes. External causes include: loading of a slope
by erosion or excavation,
and earthquake shocks. Internal causes produce failure of slope
without any recognized
external changes and include such changes as increase in
pore-water pressure or decrease
in cohesion of the slope materials. Some causes of failure of
slope are intermediate,
having some attributes of both external and internal causes. For
example, rapid
groundwater drawdown involves an increase in the shear stress
accompanied by decrease
in shear strength caused by high pore water pressure.
The Andean Amazon foreland basin is prone to failure of slope
activities. Indeed,
the South American Andean Mountains have been subjected to a
number of major failure
of slope catastrophes. In 1962, Ancasa in Peru had a major
failure of slope called
Huscarac debris avalanche with a net volume of 13 × 106 m3. It
killed 4,000 - 5,000 people
and much of Ranrahirca village was destroyed (Guadango and
Zampelli, 2000). Although
the triggering factor was unknown at the time, it is believed
that the failure of slope was
triggered by heavy rain. Similarly, in 1966 in Rio de Janeiro,
Brazil a major failure of
slope of avalanches debris and mud flows occurred. That was
triggered by heavy rainfall
and killed approximately 1000 people. The Nevados Huascara
rock/debris avalanche in
Peru, in 1970, was triggered by an earthquake of magnitude 7.7,
killing 1,800 people and
destroyed the town of Yungay (Guadango and Zampelli, 2000).
These examples show
that the tectonically active regions with high rainfall are
prone to failure of slope activities.
Several past and present failure of slope of San Francisco were
also triggered either by
heavy rain or by earthquakes resulting from tectonic activity
(Griffiths, 2005).
Failure of slope range from simple rock/mud fall to complex
slides and flows.
According to Dikau et al. (1996) landslides are classified as
fall, topple, slide, spread and
flow. Fall and topple include detachment due to pre-existing
discontinuities or tension
failure surfaces. These landslides may be free fall, break up,
bounce, slide or flow down
slopes and may involve fluidization, liquefaction, cohesion less
grain flow, heat
generation or other secondary effects. Slide movement includes
rotational or non-
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Xiao Shi Nagasaki University
3
rotational and translational. In slides, the toe area may deform
in a complex way. The
ground can bulge, the slide may creep or even flow. Flow, bulge
or slide can override
existing failures. Failure might be retrogressive or
progressive, and a graben often
develops at the head of the landslide or it may include a toe
failure. Spreads are lateral
spreading of deformed ductile or soft material. Lateral
spreading can develop sudden
spreading failures in quick clays when the slope opens up in
blocks and fissures followed
by liquefaction. Sometimes, there might be a slow movement
associated with
denudational unloading. Flows are defined as debris movement by
flow from unconfined
and/or channeled failure surfaces. Flows involve a complex
runout mechanism and these
may be catastrophic in effect and may move in sheets or lobes.
The form of movement is
a function of the rheological properties of the material (Dikau
et al., 1996).
The occurrence of different kinds of failure of slope depends on
the causes behind
them and the triggering factors. Brunsden (1993) explains how
different factors trigger
failure of slope. Physical, chemical and biological weathering
cause changes in the
physical and chemical properties in soil and rock. Triggering
factors create changes in
grading, cation exchange, and cementation. These changes cause
formation of weak
discontinuities and increased depth of low strength materials.
Eventually, there are
changes in density, strength, permeability and pore water
pressure in the soil and rock.
Another type of weathering, which also changes the slope
geometry, is associated with
fluvial, glacial or coastal erosion. The changes in slope
relief, slope height, length, angle
and aspect results the changes in stress, strength and
permeability along the slope and
eventually triggers failure of slope.
Erosion and weathering can also undermine soils and rocks
resulting in mechanical
disintegration, solution, loss of cementing materials, leaching,
and seepage. Undermining
creates loss of support, consolidation of materials, changes in
pore water pressure and
loss of strength. Similarly, deposition of material by fluvial,
glacial or mass movement
processes creates long-term loading in drained areas and
short-term loading in undrained
areas, causing changes in relief, slope height, length, angle,
and aspect of the terrain
(Brunsden, 1993). Deposition of material eventually creates
changes in permeability,
strength and pore water pressure. Changes in water storage in
groundwater can also
trigger failure of slope. This change may cause rising or
falling groundwater, development
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Failure Mechanism and Its Induced Movement Simulation of
Large-scale Slope
4
of perched water tables, surface saturation and flooding. The
typical changes in this case
could be floods, lake bursts, intense precipitation, snow and
ice melts and rapid drawdown.
These changes in water storage also eventually create excess
pore water pressure, changes
in bulk densities and reduction in effective shear strength
(Brunsden, 1993). Human
interference causes similar changes in terrain. The observation
of air photos of the study
area from different years shows that the majority of failure of
slope in my study area are
earth flows, and a few are rotational slides. This observation
is also supported by literature
and historical failure of slope records. According to Chorley et
al., (1984) humid tropical
rainforest areas undergo maximum chemical weathering, episodic
mass wasting,
moderate slope wash and erosion/sedimentation related fluvial
processes and these areas
have high dissolved and suspended loads in rivers.
Morphologically, these areas contain
low gradient rivers, wide, flat floodplains, and steep slopes
arising abruptly from valleys,
stabilized by vegetation and knife edge ridges. To identify the
causes for failure of slope
occurrences, different casual factors and triggering factors
must be studied. According to
Sower and Royster (1978), data for six parameters are necessary
for any detailed failure
of slope investigation: topography, geology, hydrology
(groundwater and surface water),
history of slope changes, weather, and vibration. Topographic
data includes contour maps,
surface drainage, slope profiles and data on topographic
changes. Geological data
includes lithology at the site, geological structure, and nature
and depth of weathering.
Hydrologic data include piezometric levels, variations in
piezometric level, groundwater
chemistry, nature and extent of surface water, seepage and data
on water withdrawal. Data
on history of slope changes means any information on slope
changes due to natural
processes (long term geological changes, erosion, and past
movements), rate of
movement, correlation of movement with other factors such as
surface and groundwater,
weather, and human activity. Weather data include precipitation,
temperature and
barometric changes. Similarly vibration data are seismic data,
and any human induced
vibration data such as blasting and heavy machinery.
Site-specific failure of slope model
which incorporates geology, geomorphology, anthropology and the
range of external
process is also useful (Sower and Royster, 1978). Collecting,
storing, analyzing, and
manipulating the above-mentioned data are important tasks in any
failure of slope study.
Development of GIS and spatial statistical techniques are recent
technological
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Xiao Shi Nagasaki University
5
developments in earth sciences. These tools are constantly being
used to improve
investigation techniques and mitigative measures for the failure
of slope in populated
regions. There is improvement of quantitative methods to assess
the probability of future
failure of slope occurrences (Clerici, 2002). Most GIS-based
failure of slope studies are,
so far, most effectively used in failure of slope susceptibility
studies and failure of slope
hazard/risk mapping. However, some research also focus on the
future prediction of
failure of slope and failure of slope distribution in natural
terrain. Brenning (2005) used
spatial statistics to develop a spatial prediction model for
failure of slope hazards. Guthrie
and Evans (2004), after analyzing failure of slope frequencies
and characteristics in
British Columbia, Canada, concluded that GIS failure of slope
studies must focus on
failure of slope in natural ecosystems.
Dai (2001) used GIS techniques to study and map failure of slope
susceptibility on
the natural terrain. Burton et al., (1998) used spatial
statistics to generate a failure of slope
model, and later they field checked the model. Lan et. al.,
(2005) analyzed the dynamic
characteristics of failure of slope in response to rainfall and
concluded that the water
pressure distribution and slope stability can be used as failure
of slope predictor in GIS.
Some studies even compare the different methods. Suzen and
Doyuran (2004) compare
the GIS based failure of slope susceptibility assessment methods
by using multivariate
and bivariate approaches.
Slope movement is a common and important factor in erosion and
sediment transfer
in mountainous areas, and constitutes an important risk to the
population. Slope
movement happened between July 19th to 20th in 2003 in Kumamoto
prefecture due to
heavy rainfall, which killed 19 people and damaged numerous
properties. Slope
movements can originate either at a single source, typically
from the fluidization of a
failed mass, or by the re-entrainment of sediment accumulated in
a torrential catchment
(Beguería et al., 2009). When slope movements are confined on a
torrent, they can
propagate over very large distances before final spreading over
an alluvial fan. The threats
to human life and property from mud and slope movements is
great, due to their higher
velocity and capacity to propagate even on very gentle slopes
(Iverson and Denlinger,
1987; Takahashi, 1991; Iverson, 1997).
Previous studies have elucidated that rainfall or earthquake is
the triggering factor
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Failure Mechanism and Its Induced Movement Simulation of
Large-scale Slope
6
of slope movement. The slope movement is a gravity-driven flow
with free upper surface
that move across three dimensional terrain, which is rapid,
transient, and includes a steep
front mainly constituted of boulders (Laigle and Coussot, 1997).
Slope movements have
very strong destructive power and bring about extensive property
damage and loss of life
to the communities in their path (Takahashi, 1991; Hunt, 1994;
Huang and Garcia, 1997;
Lien and Tsai, 2003). Up-to-date studies have strongly improved
the ability to estimate
and predict the implications of slope movement. These studies
can be primarily divided
into two groups: 1) physically based theoretical studies, and 2)
field and laboratory studies.
Researchers have proposed different theoretical models to study
the slope movement,
typical ones of which include Newtonian models, Bingham model,
Herschel-Bulkley
model, generalized viscoplastic model, dilatant fluid models,
biviscous modified
Bingham model, and frictional models (Wang et al., 2008). For
in-situ monitoring work
and experiment study, Hungr et al. (1984, 2005) introduced a
concept of yield rate which
denotes the volume eroded per meter of the path and discussed
its range based on data
collection from 14 debris-flow events in the literature.
Rickenmann et al. (2003) adopted
this concept, analyzing six sets of data from in-situ
experiments and pointing out that
slope movements with a high sediment concentration tend to be
less erosive than that with
more fluid mixtures. Wise (1997) collected forensic data of
erosion depth from 449
debris-flow events. Iverson et al. (1987, 1992, 1997 and 2010)
conducted a mass of large-
scale experiments of debris flow at U.S. Geological Survey
(USGS) debris flow flume,
and found that the aggregated data were well-suited for testing
both the conceptual
underpinnings and quantitative predictions of debris flow
models.
In the past formation and motion of large-scale slope
researches, some problems are
remained. First problem is how to do the research
systematically. Failure of slope is a
complicated system, for the purpose of failure of slope
mitigation, the simulation of
failure of slope should be conducted in the scale of region
area. However, a problem is
that the stratum mechanics characteristics and surface
topography in a large scale region
are some degree difficult to grasp. The second problem is that,
failure of slope or slope
movement usually occurs in a short period of time and the
destructive power can cause
great damage and loss of life. Few researches take the
prediction of failure of slope and
slope movement into account.
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Xiao Shi Nagasaki University
7
Slope movement is concerned with rock, soil and water or only
rock and soil. This
thesis cannot contain all types of slope movement (Figure 1.1).
Due to the slope
movement induced by failure of slope, the movement is one of the
types: (1) the type of
movement is flow, (2) the material is complex with rock, soil
and water, (3) the
predominant material is coarse. In this research, we defined the
initial of movement when
collapses happened as “failure of slope” (formation of a slope
movement) and the
movement of rock and soil or the mixtures as “debris flow”
(chapter 4) or “pyroclastic
flow” (which is to describe the slope movement of volcano in
chapter 6). This thesis will
systematically analyze failure of slope and debris flow through
database (data acquisition),
modeling to application. Thus, the objectives of this research
are:
Figure 1.1 Types of slope movement depending on type of motion
and type of
material (Varnes, 1978) as described by Roy and Hirotoka
(2006)
Type of motion Type of material
Bedrock Engineering soil
Predominantly coarse
Predominantly fine
Falls Rock fall Debris fall Earth fall
Topples Rock topple Debris topple Earth topple
Slides Rotational
Rock slide Debris slide Earth slide Translational
Lateral spread Rock spread Debris spread Earth spread
Flows Rock flow
(deep creep) Debris flow (Soil creep)
Earth flow
Complex Combination of two or more principal types of
movement
(1) to understand the mechanism and cause of failure of slope.
Finite difference
method was applied in static mechanical analysis. The terrain
data in a large-
scale slope is from airborne laser data. SSRM and earthquake
loading in FLAC
(Fast Lagrangian Analysis of Continua) was adopted to analysis
slope stability.
(2) to present a useful numerical method to simulate the
propagation and deposition
of slope movement across the three dimensional complex terrain.
To analysis the
velocity and range of influence of slope movement, and to
integrate GIS with the
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Xiao Shi Nagasaki University
9
Chapter 1 introduces background of failure of slope and its
induced slope movement,
and gives an introduction about the definition, causes,
triggering factors and damage.
Objectives and organization of this thesis was also
introduced.
Chapter 2 reviews the failure of slope research and slope
movement research
including (1) insufficient failure of slope inventory mapping,
(2) Selecting method in
failure of slope susceptibility and (3) slope movement
simulating methods.
Chapter 3 introduces finite difference method and its
application to the study of
stability analysis on large-scale slope. Airborne laser scanning
is an effective method to
measure terrain data in a large-scale region. By using airborne
laser scanning data, the
model can be built by finite-difference program FLAC3D. SSRM and
earthquake loading
in FLAC is adopted to analysis slope stability.
Chapter 4 presents a depth-averaged numerical model to
simulation the propagation
and the inundated area of debris flow, and numerical simulation
methods in combination
with GIS-technology were applied. A GIS environment provides a
good platform for
coupling a numerical model of a slope movement. As raster grid
networks of digital
elevation model in GIS can be used as the finite difference
mesh, the continuity and
momentum equations are solved numerically using finite
difference method. All the input
and output data are processed in GIS. The accuracy of model is
verified through the
comparison of simulation results with the experimental results
obtained from the U.S.
Geological Survey slope movement flume between 1994 and
2004.
Chapter 5 is a case study of Aso-Ohashi landslide during 2016
Kumamoto
earthquake. Terrain data is measured by airborne laser scanning.
Aso-Ohashi landslide is
reproduced by using numerical simulation. The SSRM is adopted
and earthquake wave
was input to explore the mechanism of Aso-Ohashi landslide.
Chapter 6 analyzes the appearance, growth, and stability of
Heisei Lava Dome in
Unzen volcano, Japan. A new division method of lava dome is
presented. Lava dome is
divided into 10 PCBs by the surface distribution and the deep of
PCB was calculated by
airborne laser data in different period. From stability
analysis, if slide plane is not
considered and slide plane is considered, the model the critical
status of model is
estimated. The potential collapses in maximum volume and the
total volume of collapsed
region are verified. Slope movements caused by that were
estimated based on a depth-
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Failure Mechanism and Its Induced Movement Simulation of
Large-scale Slope
10
averaged numerical model and the average velocity are
predicted.
Chapter 7 summarizes and concludes the results and achievements
of the study.
Problems are also highlighted for future studies.
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Xiao Shi Nagasaki University
11
References
Beguería, S., Van Asch, T.W.J., Malet, J.P., et al., 2009. A
GIS-based numerical model for
simulating the kinematics of mud and debris flows over complex
terrain.
Brenning, A., 2005. Spatial prediction models for landslide
hazards: review, comparison
and evaluation, European Geosciences Union, Natural Hazards and
Earth System
Sciences 5, 853–862.
Brunsden, D., 1993. The persistence of landforms. Zeitschrift
für Geomorphologie, 13–
28.
Burton, A., Arkell, T.J., Bathurst, J.C., 1998. Field
variability of landslide model
parameters, Environmental Geology Vol. 35, 100-114.
Chorley, R.J., Schumm, S.A., and Sugden, D.E., 1984.
Geomorphology. London,
Muthuen & Co, UK, 605.
Clerici, A., 2002. A GRASS GIS based shell script for landslide
susceptibility zonation
by the conditional analysis method. Proceedings of the open
source GIS-GRASS
user’s conference 2002, Trento, Italy, 11-13.
Cruden, D.M., and. Varnes, D.J., 1996. “Landslide types and
processes,” In: Landslides
Investigation and Mitigation, edited by A. K. Turner, and R. L.
Schuster, Natl. Acad.
Press, Vol. 247, Washington, D. C., 36–75.
Dai, F.C., Lee, C.F., Li, J., Xu, Z.W., 2001. Assesment of
landslide susceptibility on the
natural terrain of Lantau Island, Hong Kong, Environmental
Geology, Vol. 40, issue
3, 381-391.
Dikau, R., Brunsden, D., Ibsen, M.L., and Schrott, L., 1996.
Landslide Recognition:
Identification, Movement and Causes, John Wiley & Sons,
Chichester, UK, 251.
Griffiths, J. S., 2005. “Landslides”, In: Geomorphology for
engineers, edited by Fookes
P.G., M. Lee and G. Milligan, Whittles Publishing, Scotland, UK,
Pp.173-206.
Guadagno, F.M., Zampelli, S. P., 2000. “Triggering Mechanisms of
the landslides that
inundated Sarno, Quindici, siano and Bracigliano (S. Italy) on
May 5-6, 1998,” In:
Landslides in Research, Theory and Practice, edited by E.
Bromhead, N. Dixon, and
M.L. Ibsen, Thomas Telford Ltd., Cardiff, UK, 671-676.
Guthrie, R.H., Evans, S.G., 2004. Analysis of Landslide
Frequencies and Characteristics
in a Natural System, Coastal British Columbia, Earth Surface
Processes and
-
Failure Mechanism and Its Induced Movement Simulation of
Large-scale Slope
12
Landforms, 29, 1321-1339.
Huang, X. and Garc´ıa, M.H., 1997. A perturbation solution for
Binghamplastic mudflows,
J. Hydraul. Eng., ASCE, 123(11), 986–994.
Hungr, O, Morgan, G.C., Kellerhals, R., 1984. Quantitative
analysis of debris torrent
hazards for design of remedial measures. Canadian Geotechnical
Journal, 21(4):
663-677.
Hungr, O., McDougall, S., Bovis. M., 2005. Entrainment of
material by debris flows.
Debris-flow hazards and related phenomena. Springer Berlin
Heidelberg, 135-158.
Hunt, B., 1994. Newtonian fluid Mechanics treatment of debris
flows and avalanches, J.
Hydraul. Eng., ASCE, 120, 1350–1363.
Iverson, R.M., Costa, J.E., LaHusen, R.G., 1992. Debris-flow
flume at HJ Andrews
experimental forest, Oregon. US Geological Survey, Dept. of the
Interior.
Iverson, R.M., Denlinger, R.P., 1987. The physics of debris
flows―a conceptual
assessment. IAHS-AISH publication, 165, 155-165.
Iverson, R.M., Logan, M., LaHusen, R.G., et al., 1997. The
perfect debris flow?
Aggregated results from 28 large-scale experiments. Journal of
Geophysical
Research: Earth Surface (2003–2012), 115(F3).
Iverson, R.M., 1997. The physics of debris flows. Reviews of
geophysics, 35(3), 245-296.
Keller, A. E., 2000. Environmental Geology, Prentice-Hall, Inc.,
NJ, 132-160.
Laigle, D., Coussot, P., 1997. Numerical modeling of mudflows.
Journal of Hydraulic
Engineering, 123(7): 617-623.
Lan, H.X., Lee, C.F., Zhou, C.H., Martin, C.D., 2005. Dynamic
characteristics analysis
of shallow landslides in response to rainfall event using GIS,
Environmental
Geology, 47, 254-267.
Lien, H.P., Tsai, F.W., 2003. Sediment concentration
distribution of debris flow. Journal
of Hydraulic Engineering, 129(12): 995-1000.
Rickenmann, D., Weber, D., Stepanov, B., 2003. Erosion by debris
flows in field and
laboratory experiments. Debris-flow hazards mitigation:
mechanics, prediction, and
assessment, 883-894.
Roy, C.S., Hirotoka O., 2006. Landslides Processes, Prediction
and Land Use. American
Geophysical Union, AGU Books Board Publication, 312.
-
Xiao Shi Nagasaki University
13
Sower, G. F., Royster, D. L., 1978. “ Field Investigation
Landslides: Analysis and Control,”
In:, Transportation Research Board Special Report, edited by R.
L. Schuster and R.J.
Krizek ,Vol.176, 81-111.
Suzen, M.L., Doyuran, V., 2004. A comparison of the GIS based
landslide susceptibility
assessment methods: multivariate versus bivariate, Environmental
Geolgoy, Vol. 45,
665-679. Takahashi T., 1991.Debris flow. Balkema. Turner, A.K.,
Schuster, R.L., 1996. “Landslides: Investigation and Mitigation,”
In: United
States National Research Council, Transportation Research Board,
Special Report,
Vol. 247, Washington DC. 247.
Varnes, D.J., 1978. “Slope movement types and processes”, In:
Landslide Analysis and
Control, edited by M. Clark, Transportation Research Board,
National Academy of
Science, National Res. Council, Special Rep., Vol. 176,
Washington, DC, 11-33.
Wang, C, Li, S., Esaki, T., 2008. GIS-based two-dimensional
numerical simulation of
rainfall-induced debris flow. Natural Hazards and Earth System
Science, 8(1): 47-
58.
Wise, M.P., 1997. Probabilistic modelling of debris flow travel
distance using empirical
volumetric relationships. University of British Columbia.
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Failure Mechanism and Its Induced Movement Simulation of
Large-scale Slope
14
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CHAPTER 2
Review of slope stability analysis research and slope
movement
research
Several issues in quantitative slope risk analysis includes
developing technique in
inventory mapping, particularly in a data scarce environment,
selecting methods for slope
susceptibility assessment, and developing approaches for slope
risk analysis. It varies
depending on the availability of secondary data,
geomorphological characteristic, and
failure of slope typology. The availability of data input is
very important prior to failure
of slope risk analysis. It can affect the overall methodology or
approaches applied in the
failure of slope risk analysis. Despite the availability of
failure of slope inventory,
geomorphological characteristic of the study area should also be
considered prior to
selecting suitable failure of slope susceptibility and risk
analysis. Some approaches in
failure of slope susceptibility and risk analysis can also not
be applied in slope movement
susceptibility and risk analysis. For example, failure of slope
susceptibility assessment
based on GIS and statistics uses failure of slope area
represented by polygon to estimate
susceptibility. Whereas, it is not suitable for slope movement
susceptibility analysis
because the dangerous zone in slope movement is represented by
trajectory line.
2.1 Insufficient inventory mapping of slope failure
Generating slope failure analysis is difficult in some areas
because the unavailable
of the failure of slope inventory map. However, the recent
technology developments such
as the availability of the modern field instrument, high
resolution DTMs, high resolution
satellite imagery, recent development on GIS and remote sensing
technology have made
generating failure of slope map easier. But, the selection of
this technique should be
carefully reviewed based on the purpose, the extent of the study
area, the scale of base
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Failure Mechanism and Its Induced Movement Simulation of
Large-scale Slope
16
maps and analysis, resolution and characteristics of the
available imagery, and the skill
and experience of the interpreter (Guzetti et al., 2000; van
Westen et al., 2006). Slope
failure mapping through field survey is the oldest technique for
failure of slope inventory
mapping and considered as the most accurate technique for
mapping fresh failure of slope
events. But it is difficult, by using field survey, to recognize
old failure of slope in the
field where the natural process (e.g. erosion, vegetation) and
the anthropogenic activities
(e.g. urbanization, road construction, ploughing) are exist.
2.2 Selecting method in slope failure susceptibility
Quantitative statistical analysis has been widely applied as a
standard method for
failure of slope susceptibility zoning in large-scale areas
(regional scale). It includes
bivariate statistic, multivariate statistic and soft computing.
Bivariate analysis assumes
that the presumed controlling factors of failure of slope are
not interrelated each other
(Suzen and Doyuran, 2004). It is a robust and flexible method,
but has several limitations,
including over simplification of input thematic data related to
failure of slope and loss of
data sensitivity of controlling factors (Thiery et al., 2007).
Bivariate statistical methods
can also be used to determine which factors or combination of
factors or combination of
factors play a role in the initiation of failure of slope.
In the other hand, multivariate analysis assumes that the
presumed controlling
factors of failure of slope are interrelated each other. It
determines the relative
contribution of each failure of slope causal factor in the
presence or absence of past failure
of slope events (Dai et al., 2001; Suzen and Douran, 2004;
Ayalew and Yamagishi, 2005;
Nandi and Shakoor, 2009). Multivariate statistical analysis can
be used to predict a result
measured by a binary variable such as the absence or presence of
failure of slope based
on a set of one or more failure of slope causal factors as
independent variables. The
independent variables can be nonlinear, continuous, categorical
or a combination of both
continuous and categorical; and does not to be normally
distributed.
Soft computing techniques were used in assessment of the failure
of slope
susceptibility because of a limitation such as insufficient
knowledge about the area of
interest. Its computing procedure has the ability to handle
imprecise and fuzzy data with
continuous, categorical and binary data without violating
assumptions and also
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Xiao Shi Nagasaki University
17
independent of the statistical distribution of the data. The
purpose of soft computing
technique, i.e. ANN, is to build a model of the data-generating
process so that the network
can generalize and predict outputs from inputs that it has not
previously seen (Lee et al.,
2001).
One of the main advantages of data driven failure of slope
susceptibility is the easy
updating of the failure of slope susceptibility assessment
procedure and also relatively
easy to apply for land-use planning. However, it can be affected
by shortcomings such as
the assumption that failure of slope occur due to the same
combination of factors
throughout a study area, spatial factors can vary widely in
areas with complex
geomorphological settings, and the lack of suitable expert
opinion on failure of slope
processes and causal factors (Corominas et al., 2013). Selecting
method, i.e. either
bivariate, multivariate or soft computing is essential to apply
for land use planning based
on complete failure of slope inventory.
2.3 Simulating methods of slope movement
Several attempts of slope movement susceptibility zoning have
been carried out
through several ways, relatively similar to failure of slope
susceptibility zoning, i.e.
heuristic, statistic and trajectory-energy/velocity approaches.
Heuristic methods involve
geomorphological analysis and rating based approaches. Field
work and photo
interpretation are the main sources of the geomorphological
analysis for determining the
trajectories of slope movement. Geomorphologic elements
connected to slope movement
are taken into account to delineate landscape that is
susceptible to slope movement. It is
subjective and need well experienced geomorphologist. Weight of
each element is also
added to determine the debris susceptibility based on rating
approach (Romana, 1993;
Pierson et al., 1990; Hoek, 2007). The mapping unit used in
geomorphological approach
is usually geomorphological unit or landform. For example,
Sasaki et al. (2000) generated
land condition map showing geomorphologic element which is
susceptible to slope
movement. Statistic approaches such as logistic regression using
pixel/mesh unit was also
applied in slope movement susceptibility zone (Shizadi et al.,
2012). But, it is not widely
applied, as in failure of slope susceptibility zoning, due to
difficulties in delineating debris
affected area. Single slope movement may only affect a narrow
area as a trajectory of
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Failure Mechanism and Its Induced Movement Simulation of
Large-scale Slope
18
slope movement.
The most common method in slope movement susceptibility zoning
is a trajectory-
energy/velocity modeling (Guzzetti et al., 2002; Lan et al.,
2007; Chen, 2003; Agliardi
and Crosta, 2003). It is a quantitative approach employing
computer simulation to
calculate probability of reach, velocity and the kinetic energy
distribution at each point of
the slope. Broadly speaking, a slope movement represents the
gravity-driven flow of a
mixture of various sizes of sediment (from clay to boulders),
water and air, down a steep
slope, often initiated by heavy rainfall and/or landslides.
Here a brief review of the variety of the current work on the
mechanics of granular
materials, and in particular that on slope movements is given.
Since dry granular flows,
avalanches, and slope movements are in principle related
phenomena, the following
survey is not exclusively restricted to the slope movement
literature. Perhaps the most
up-to-date literature source available at the current time on
the mechanics and modeling
of slope movements is Takahashi’s (1991) IAHR monograph, which
gives a fairly critical
account on the mechanisms of slope movements from their onset to
deposition. It
summarizes Takahashi’s own extensive research work, and presents
a detailed
understanding of the mechanics of the flow of a layer of a
particle-fluid mixture under
simple gravity driven shear for Bagnold’s (1954) grain inertia
and macro viscous regimes.
The model equations of the two-constituent model are eventually
simplified to essentially
a one-constituent model, and this view is maintained throughout.
Time dependent
processes, i.e., development of a slope movement hydrograph and
its deformation as well
as snout behavior are also discussed as are inverse grading and
the transportation of large
boulders on the free surface of a slope movement and the
processes of deposition of
sediments in the run-out zone. Considerations are all based on
two-dimensional plane
flow. In a similar spirit is the work of Cheng-Lung Chen (1987).
For simple plane shear
flows under gravity (in which a shear stress and a normal stress
are the only materially
dependent stress variables that are introduced), Chen presents a
detailed analysis of
theological models and deduces with these velocity profiles for
steady gravity driven flow
of a strictly parallel sided slab. We shall discuss these
equations later on. In the slope
movement literature, there appears to be no other work that goes
beyond Takahashi (1991,
and previous work referred to there) and Chen (1987), except
perhaps the in-depth, though
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Xiao Shi Nagasaki University
19
descriptive, account of Iverson & Denlinger (1987). These
authors delineate the range of
applicability of the formulations and, in particular, point out
the severe limitation "that
steady uniform flows can exist only when the debris travels down
a slope with a specific
inclination. Chen (1987) discusses this phenomenon in detail,
but does not seem to be
bothered by this. The reason stated by Iverson & Denlinger
seems to be that the variation
of the grain concentration across the debris flow depth is
ignored. The problem is that
four equations for three unknowns exist in this case; they
mandate a consistency condition
which seems to be the reason for the mentioned peculiarity.
Somewhat hidden in existing
formulations of the rheological behavior of slope movements is
the fact that these
relations cannot uniquely be extended to a three-dimensional
form of the constitutive
relations. In other words, two sets of general constitutive
relations can in plane simple
shear be indistinguishable. When attempting to describe a
dispersion of a channelized
slope movement into the fanned deposition area this might be of
some importance.
Furthermore, slope movement specialists also generally abstain
from introducing a
variable and associated field equation for the internal
structure, say the fluctuations of the
velocity and particle concentration fields due to grain
collisions and/or possible
turbulence in the interstitial fluid flow. In the granular flow
literature this field is generally
of scalar nature: the collisional fluctuation energy or
so-called granular temperature. From
this point of view, the granular literature should also be
consulted, e.g., Scheiwiller &
Hutter (1982), or Hutter & Rajagopal (1994). Both works
address the formulation of the
constitutive relations for granular materials under rapid
shearing. Both contain extensive
literature reviews on constitutive modelling, but they do not
present formulations of flow
models deduced from a set of constitutive relations. Hutter
& Rajagopal (1994) also do
not address the models suggested by molecular dynamics, in which
a large number
(several thousands) of rigid particles are followed in time
under free motion and colliding
with each other. Interaction rules for collisions are
formulated, the equations of motion of
all the particles integrated, and followed through time, taking
into account the free flow
and collisions. Campbell (1990) reviews these methods, and
Straub (1995) demonstrates
in a voluminous dissertation its use in pyroclastic flows. Its
application to fluid-grain-
grain interaction has not been attempted so far. Consider next
the problem of the
derivation of evolution equations. In particular, hydraulic or
Boussinesqtype theories
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Failure Mechanism and Its Induced Movement Simulation of
Large-scale Slope
20
have been obtained by, for instance, MacArthur & Schamber
(1986), Coussot (1994),
Laigh & Coussot (1993), O’Brien et al. (1993), and
Montefusio (1994), and exclusively
consist in establishing vertically, or cross sectionally,
integrated, balance laws of mass
and momentum in a Cartesian reference frame, in one occasion
restricted to the kinematic
wave approximation. In this approximation, one restricts
considerations to a global mass
balance relation for the mixture as a whole,
0,, xt Qh (2.1)
in which h is flow depth, and Q the volume flux, thh t /, , xQQ
x /, and writes a
constitutive equation for Q, usually by considering steady state
momentum balance to
connect Q with basal and turbulent friction, etc., see, e.g.,
Hutter (1983). Only in a single
case were these balance laws complemented by a balance of mass
for the solids, thus
allowing particle segregation mechanisms and deposition or
erosion along the slope
movement path to be accounted for (Takahashi et al. 1992). In a
single paper by Jenkins
& Askasi (1994), a hydraulic theory for a slope movement is
presented in which the
particle fluctuation energy affects the evolution of the
flow.
The drawbacks of these formulations have been pointed out before
-- use of a
Cartesian formulation requires that the topography is flat,
expressions for the basal drag
cannot clearly be related to constitutive postulates, and
nonlinear advective terms in the
momentum equation cannot be properly estimated. Very similar
concepts, however, have
been developed in the theory of snow and granular avalanches. A
fairly up-to date
summary on this subject is contained in Hutter (1996). Through
comparison of theory and
laboratory experiments it is shown that the curvature of the
topography affects the
solution non-negligibly and thus should not be ignored. Hutter’s
(1996) review also
contains an extensive treatment of powder snow avalanches, which
are two-phase
mixtures with balance laws of mass and momentum for both
constituents. The works
discussed there indicate, how (i) density variations and thus
particle segregation including
deposition and erosion can be dealt with, (ii) how
microstructural effects could be
incorporated (e.g., turbulence) and (iii) how hydraulic models
can be constructed that
amend the above mentioned drawbacks. From another viewpoint, the
existing literature
may be characterized according to whether a model for debris or
granular flows is
formulated, or applied in the context of a physically-relevant
initial-boundary value
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Xiao Shi Nagasaki University
21
problem. In the former category, one finds such works as Chen
(1987), Takahashi (1991),
Hutter & Rajagopal (1994), and Hutter (1995); in these, the
constitutive behaviour of a
granular material that may exhibit slope movement
characteristics is discussed. Such
constitutive models can be formulated on a sound continuum
thermos dynamical basis,
as shown by, e.g., Goodman & Cowin (1972), Passman et al.
(1984), or more recently in
an extended context by Svendsen & Hutter (1995). In the
latter category belongs the work
of, e.g., O’Brien et al. (1993), who present a depth-averaged
hydraulic model for the fan-
flow regime of a slope movement. Focusing on the computer
implementation of their
slope movement model, they do not, unfortunately, invest time in
discussing or
appreciating its theoretical limitations. Such limitations are
discussed, e.g., in the works
of Hutter and his associates (see, e.g., Hutter, 1996). Finally,
it is also perhaps worth
mentioning that no model appears sufficiently general to deal
with processes such as
erosion and/or deposition of sediment. Such processes are
governed predominantly by
turbulence in the fluid and agitation of the solid particles at
the base of the flow.
Consequently, these processes cannot be left out of any model
hoping to address
erosion/deposition. Ideas on how these processes can be modeled
are to be found in the
literature on turbidity currents and powder-snow avalanches, and
are briefly reviewed in
Hutter (1996).
All the debris flows have at least four characters: rainfall or
earthquake is the
triggering factor; a debris flow is a gravity driven flow with
free upper surface that move
across three dimensional terrain; the nature of the flow itself,
which is rapid, transient,
and includes a steep front mainly constituted of boulders
(Laigle and Coussot, 1997); and
debris flows have very strong destructive power and bring about
extensive property
damage and loss of life to the communities in their path
(Takahashi, 1991; Hunt, 1994;
Huang and Garcia, 1997; Lien and Tsai, 2003). As debris-flows
are mixtures of flowing
sediment and water showing complicated flow behavior
intermediate between clear-water
flows and mass movements of solid material, a number of
mathematical rheological
models were developed to simulate the flow behavior. Many
researchers have developed
rheological models for mudflows and debris flows. These models
can be classified as:
Newtonian models (Johnson, 1970; Trunk et al., 1986; Hunt, 1994;
Hungr, 1995;
Rickenmann, 1999), Bingham model (Johnson, 1970; O’Brien and
Julien, 1988; Liu and
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Failure Mechanism and Its Induced Movement Simulation of
Large-scale Slope
22
Mei, 1989; Jan, 1997; Whipple, 1997; Fraccarollo and Papa, 2000;
Pastor et al., 2004),
Herschel-Bulkley model (Huang and Garc´ıa, 1997, 1998; Imran et
al., 2001; Remaˆıtre
et al., 2005; Rickenmann et al., 2006), generalized viscoplastic
model (Chen, 1988),
dilatant fluid models (Bagnold, 1954; Takahashi, 1978, 1991;
Mainali and Rajaratnam,
1994), dispersive or turbulent stress models (Arai and
Takahashi, 1986; O’Brien and
Julien, 1988; Hunt, 1994), biviscous modified Bingham model
(Dent and Lang, 1983),
and frictional models (Iverson, 1997; Chen and Lee, 1999;
Arattano and Franzi, 2003;
Pastor et al., 2004; Rickenmann et al., 2006; Naef et al.,
2006). Takahashi and Tsujimoto
(1984) presented a two dimensional finite difference model for
debris flows based on a
dilatant-fluid model coupled with coulomb flow resistance, and
modified the model to
include turbulence (Takahashi et al., 1991, 1992). O’Brien et
al. (1993) developed a two-
dimensional flooding routing model that is a valuable tool for
delineating flood hazards
and simulating flood wave attenuation, mudflows, debris flows
(FLO-2D). Iverson and
Denlinger (2001) developed a generalization of the
depth-averaged, two-dimensional
grain-fluid mixture model that describes finite masses of
variably fluidized grain-fluid
mixtures that move unsteady across three-dimensional terrain.
Egashira et al. (2003)
presented a method of numerical simulation for 2-D debris flow
on an erodible bed using
the constitutive equations for sediment-water mixture when the
equation of erosion rate
is incorporated in the continuity equation. McDougall and Hungr
(2003) developed a
depth-averaged model for the simulation of rapid landslide
motion across complex 3-D
terrain. Pudasaini and Hutter (2003) presented a two-dimensional
depth-integrated theory
for the gravity-driven free-surface flow of a granular avalanche
over an arbitrarily but
gently curved and twisted topography which is an important
extension of the original
Savage and Hutter (1989) theory. Bouchut and Westdickenberg
(2004) developed a
multidimensional shallow water model for arbitrary topography.
Pastor et al. (2004)
presented a depth-integrated Bingham model which is discretized
using a Taylor-Galerkin
finite element algorithm. Pudasaini and Hutter (2006) provided a
survey and discussion
about the motion of avalanche-like flows from initiation to run
out. Rickenmann et al.
(2006) compared three two-dimensional debris-flow simulation
models with field events,
and these models are based on a Voellmy fluid rheology
reflecting turbulent-like and basal
frictional stresses, a quadratic rheologic formulation including
Bingham, collisional and
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Xiao Shi Nagasaki University
23
turbulent stresses, and a Herschel-Bulkley rheology representing
a viscoplastic fluid.
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Failure Mechanism and Its Induced Movement Simulation of
Large-scale Slope
24
References
Agliardi, F. and Crosta, G. 2003. High resolution
three-dimensional numerical modelling
of rockfalls. Int. J. Rock Mech. Min., Sci., 40, 455-471.
Anderson, S. A. 1995. Analysis of Rainfall-induced debris flows,
J. Hydraul. Eng., ASCE,
121(7), 544–552.
Arai, M. and Takahashi, T. 1986. The Karman constant of the flow
laden with high
sediment, Proc. 3rd Int. Symp. on River Sedimentation, Univ. of
Mississippi, 824–
833.
Arattano, M. and Franzi, L. 2003. On the evaluation of debris
flows dynamics by means
of mathematical models, Nat. Hazards Earth Syst. Sci., 3,
539–544.
Ayalew, L. and Yamagishi, H. 2005. The application of GIS-based
logistic regression for
landslide susceptibility zoning in the Kakuda-Yahiko Mountains,
Central Japan.
Geomorphology, 65, 15-31.
Bagnold, R.A. 1954. Experiments on a gravity free dispersion of
large solid spheres in a
Newtonian fluid under shear. Proc. R. Soc. London, A
225:49-63.
Bouchut, F. and Westdickenberg, M. 2004. Gravity driven shallow
water models for
arbitrary topography, Comm. Math. Sci., 2(3), 359–389.
Campbell, C.S. 1990. Rapid granular fows. Ann. Rev. Fluid Mech.
22:57-92.
Chen, C. 1988. Generalized viscoplastic modeling of debris flow,
J. Hydraul. Eng., ASCE,
114(3), 237–258.
Chen, C.L. 1987. Comprehensive review of debris flow modeling
concepts in Japan, Geol.
Soc. Am. Rev. Eng Geol. Vol. VII, pp. 13-29.
Chen, G. 2003. Numerical modeling of rock fall using extended
DDA. Chinese Journal
of Rock Mechanics and Engineering, 22(6), 926-931.
Chen, H. and Lee, C.F. 1999. Numerical simulation of debris
flows, Can. Geotech. J., 37,
146–160.
Corominas, j., van Westen, C., Frattini, et al. 2014.
Recommendations for the quantitative
analysis of landslide risk. Bulletin Engineering Geology and the
Environment, 73(2),
209-263.
Coussot, P., 1994. Steady, laminar, flow of concentrated mud
suspensions in open channel.
J. Hydr. Res. 32, vol. 4:535-559.
-
Xiao Shi Nagasaki University
25
Dai, F.C., Lee, C.F., Li, J. and Xu, Z.W. 2001. Assessment of
landslide susceptibility on
the natural terrain of Lantau Island, Hong Kong. Environmental
Geology. 40,381-
391.
Dent, J. D. and Lang, T. E. 1983. A biviscous modified bingham
model of snow avalanche
motion, Annals Glaciology, 4, 42–46.
Egashira, S., Itoh, T., and Miyamoto, K. 2003. Debris flow
simulations for San Julian
torrents in Venezuela, Proc. 3rd IAHR Symposium on River,
Coastal and Estuarine
Morphodynamics. Barcelona, Spain, 1–5 September 2003,
976–986.
Fraccarollo, L. And Papa, M. 2000. Numerical simulation of real
debris flow events, Phys.
Chem. Earth (B), 25(9), 757–763.
Goodman, M.A., Cowin, S.C. 1972. A continuum theory for granular
materials. Arch. Rat.
Mech. Anal. 44:249-266.
Guzzetti, F., Cardinali, M., Reichenbach, P. and Carrara, A.
2000. Comparing landslide
maps: a case study in the upper Tiber River Basin, Central
Italy. Environmental
Management, 25(3), 247-363.
Guzzetti, F., Malamud, B., Turcotte, D.L., Reichenbach, P. 2002.
Power-law correlations
of landslide areas in central Italy. Earth and Planetary Science
Letters, 195,169-183.
Hoek, E. 2007. Practical Rock Engineering. Available online
at
http://www.rocscience.com/hoek/pdf/Practical_Rock_Engineering.pdf
Huang, X. and Garcıa, M.H. 1997. A perturbation solution for
Bingham plastic mudflows,
J. Hydraul. Eng., ASCE, 123(11), 986–994.
Huang, X. and Garc´ıa, M. H. 1998. A Herschel-Bulkley model for
mud flow down a
slope, J. Fluid Mech., 374, 305–333.
Hungr, O. 1995. A model for the runout analysis of rapid flow
slides, debris flows and
avalanches, Can. Geotech. J., 32(4), 610–623.
Hunt, B. 1994. Newtonian fluid Mechanics treatment of debris
flows and avalanches, J.
Hydraul. Eng., ASCE, 120, 1350–1363.
Hutter, K. 1983. Theoretical Glaciology. Reidel, Dordrecht.
Hutter, K. 1996. Avalanche dynamics, a review. In: Hydrology of
Disasters (VP Singh,
ed.) Kluwer Academic Publishers, Amsterdam.
Hutter, K., Rajagopal, K.R. 1994. On flows of granular
materials. Cont. Mech.
-
Failure Mechanism and Its Induced Movement Simulation of
Large-scale Slope
26
Thermodyn. 6, 81-139.
Imran, J., Harff, P., and Parker G. 2001. A number model of
submarine debris-flow with
a graphical user interface, Computer Geosciences, 27, 717–729.
Iverson, R. M. 1997. The physics of debris flows, Rev. Geophys.,
35,245–296. Iverson, R.M. and Denlinger, R.P. 1987. The physics of
debris flows - A conceptual
assessment. In: Erosion and Sedimentation in the Pacific Rim
(Proceedings of the
Corvallis Symposium), IAHS Publ. No. 165:155-165.
Iverson, R. M., and Denlinger R. P. 2001. Flow of variably
fluidized granular masses
across three-dimensional terrain, 1. Coulomb mixture theory, J.
Geophys. Res., 106,
537–552.
Jan, C. D. 1997. A study on the numerical modelling of debris
flow, Debris Flow Hazards
Mitigation, Mech., Pred. and Assessment, ASCE.
Jenkins, J.T. 1994. Hydraulic theory for a debris flow supported
on a collisional shear
layer. Proc. Int. Workshop on 'Floods and Innnndations Related
to Large Earth
Movements, Trento, Italy, IAHR, A6.1-A.610.
Johnson, A. M. 1970. Physical processes in geology, Freeman, San
Francisco.
Laigle, D. and Coussot, P. 1993. Numerical modeling of debris
flow dynamics. Proc. Int.
Workshop on 'Floods and Innundations Related to Large Earth
Movements', Trento,
Italy, IAHR, A11.1-A.11.11.
Laigle, D. and Coussot, P. 1997. Numerical modeling of Mudflows,
J. Hydraul. Eng.,
ASCE, 123, 617–623.
Lan, H., Martin, C.D. and Lim, C.H. 2007. Rockfall analyst: a
GIS extension for three-
dimensional and spatially distributed rockfall hazard modeling.
Computer and
Geoscience. 33,262-279.
Lee, S., Ryu, J., Min, K. and Won, J. 2001. Development of two
artificial neural network
methods for landslide susceptibility analysis. Proceeding of
Geoscience and Remote
Sensing Symposium, IGARSS 01. IEEE 2001 International 5,
2364-2366.
Lien, H. P. and Tsai, F. W. 2003. Sediment concentration
distribution of debris flow, J.
Hydraul. Eng., ASCE, 129(12), 995–1000.
Liu, K. F. and Mei, C. C. 1989. Slow spreading of a sheet of
Bingham fluid on an inclined
plane, J. Fluid Mech., 207, 505–529.
MacArthur, R.C., Schamber, D.R. 1986. Numerical methods for
simulating mudflows.
-
Xiao Shi Nagasaki University
27
Proc. Third Int. Symp. on River Sedimentation, Mississippi, USA,
1615-1623.
Mainali, A. and Rajaratnam, N. 1994. Experimental study of
debris flows, J. Hydraul.
Eng., ASCE, 120(1), 104–123.
McDougall, S. and Hungr, O. 2003. Dynamic modelling of
entrainment in rapid
landslides, Can. Geotech. J., 42(5), 1437–1448.
Montefusco, L. 1994. A possible 2-D vertical model for debris
flow. Proc. Int. Workshop
on 'Floods and lnnundations Related to Large Earth Movements'.
Trento, Italy, IAHR,
A9.1-A.9.9.
Naef, D., Rickenmann, D., Rutschmann, P., and McArdell, B. W.
2006. Comparision of
flow resistance relations for debris flows using a
one-dimensional finite element
simulation model, Nat. Hazards Earth Syst. Sci., 6, 155–165.
Nandi, A. and Shakoor, A. 2009. A GIS-based landslide
susceptibility evaluation using
bivariate and multivariate statistical analyses. Engineering
Geology, 110, 11-20.
O’Brien, J. S. and Julien, P. Y. 1988. Laboratory analysis of
mudflow properties, J. Hydr.
Engrg., ASCE, 114(8), 877–887.
O'Brien, J.S., Julien, P.Y., Fullerton, W.T. 1993.
Two-dimensional water flood and
mudflows simulation. J. Hydr. Eng., ASCE, Vol. 119, No.
2:244-261.
Passman, S.L., Nunziato, J.W., Walsh, E.K. 1984. A theory of
multiphase mixtures. In:
Rational Thermodynamics, C. Truesdell (ed.) Springer-Verlag
1984.
Pastor, M., Quecedo, M., Gonz´alez, E., Herreros, M. I.,
Fern´andez Merodo, J. A., and
Mira, P. 2004. Simple approximation to bottom friction for
bingham fluid depth
integrated models, J. Hydraul. Eng., ASCE, 130(2), 149–155.
Pierson, L.A., Davis, S.A. and Van Vickle, R. 1990. Rockfall
Hazard Rating System
Implementation Manual, Federal Highway Administration (FHWA)
Report FHWA-
OREG-90-01, FHWA, United States Department of
Transportation.
Pudasaini, S. P. and Hutter, K. 2003. Rapid shear flows of dry
granular masses down
curved and twisted channels, J. Fluid Mech., 495, 193–208.
Pudasaini, S. P. and Hutter, K. 2006. Avalanche
Dynamics:Dynamics of rapid flows of
denses granular avalanches, New York, Springer.
Remaıtre, A., Malet, J., Maquaire, O. Ancey, C., and Locat, J.
2005. Flow behaviour and
runout modelling of Complex debris flow in a clay-shale basin,
Earth Surf. Process.
-
Failure Mechanism and Its Induced Movement Simulation of
Large-scale Slope
28
Landforms, 30, 479–488.
Rickenmann, D. 1999. Empirical relationships for debris flows,
Nat. Hazards, 19(1), 47–
77.
Rickenmann, D., Laigle, D., McArdell, B. W., and H¨ubl, J. 2006.
Comparison of 2D
debris-flow simulation models with field events, Computational
Geosciences, 10,
241–264.
Romana, M. 1993. A geomechanical classification for slopes:
slope mass rating,
Comprehensive Rock Engineering, Oxford, Pergamon.
Savage, S. B. and Hutter, K. 1989. The motion of a finite mass
of granular material down
a rough incline, J. Fluid Mech., 199, 177–215.
Scheiwiller, T., Hutter, K. 1982. Lawinendynamik: Obersicht
tiber Experimente und
theoretische Modelle yon Flieβ- und Staublawinen. Laboratory of
Hydraulics,
Hydrology and Glaciology, Report No. 58, ETH Ztirich,
Switzerland.
Shizadi, A., Saro, L., Joo, O.H. and Chapi, K. 2012. A GIS-based
logistic regression
model in rockfall susceptibility mapping along a mountainous
road: ASalavat Abad
case study, Kurdistan, Iran, Nat. Hazards, 64, 1639-1656.
Stranb, S. 1995. Schneltes granulares Fliegen in subaerischen
pyroklastischen Str6men.
Dissertation an der Bayerischen Julius- Maximilians-Universit~it
Wiirzburg.
Suzen, M.L. and Doyuran, V. 2004. Data Driven Bivariate
Landslide Susceptibility
Assessment Using GIS: a Method and Application to Asarsuyu
Catchment, Turkey.
Engineering Geology, 71, 303-321.
Takahashi, T. 1978. Mechanical characteristics of debris flow,
J. Hydr. Div., ASCE,
104(8), 1153–1169.
Takahashi, T. 1991. Debris flow. 1AHR-AIRH Monograph series. A.
A. Balkema.
Takahashi, T., Nakagawa, H., Harada, T., Yamashiki, Y. 1992.
Routing debris flows with
particle segregation. J. Hydr. Eng., ASCE, Vol. 118, No.
11:1490-1507.
Takahashi, T. and Tsujimoto, H. 1984. Numerical simulation of
flooding and deposition
of a debris flow, Disas. Prev. Res. Inst., Kyoto Univ., 27(B-2),
467–485.
Thierry, Y., Malet, J.P.Sterlacchini, S. Puisant, A., and
Maquaire, O. 2007. Landslide
susceptibility assessment by bivariate methods at large scale:
application to a
complex mountainous environment. Geomorphology, 92, 38-59.
-
Xiao Shi Nagasaki University
29
Trunk, F. J., Dent, J. D., and Lang, T. E. 1986. Computer
modeling of large rock slides, J.
Geotech. Engrg., ASCE, 112(3), 348–360.
Van Westen C.J., Asch T.W.J. and Soeters R. 2006. Landslide
hazard and risk zonation-
why is it still so difficult? Bull. Eng. Geol. Env., 65,
67-184.
Whipple, K. X. 1997. Open-channel flow of Bingham fluids:
applications in debris-flow
research, J. Geol., 105, 243–262.
-
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Large-scale Slope
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CHAPTER 3
Finite difference method and its application to the study of
stability analysis on large-scale slope
3.1 Introduction
Numerical models are mathematical models that use some sort of
numerical time-
stepping procedure to obtain the models behavior over time.
These are computer
programs that represent the mechanical response of a rock mass
subjected to a set of initial
conditions such as in situ stresses and water levels, boundary
conditions and induced
changes such as slope excavation. Slope collapse and landslide
simulation are studied
with some numerical methods, FDM is a mesh-based method in
stability analysis of
landslide. The FLAC3D is an FDM software and used in this study.
For a large-scale slope,
how to judge the stability of slope is difficult. The high
accuracy terrain data is hard to be
obtained. Airborne laser scanning is an effective method to
measure terrain data in a large
scale region.
3.2 Terrain data from airborne laser scanning system
The airborne laser scanning system is ALS60 which is a compact
laser-based system
that designed for acquisition of topographic and return signal
intensity data from a variety
of airborne platforms. The data is computed using range and
return signal intensity
measurements recorded in flight along with position and attitude
data derived from
airborne Global Navigation Satellite System (GNSS) and inertial
measurement unit
(IMU). Laser distance measuring device, IMU and GPS receiver
antenna are installed in
aircraft. GPS antenna measures the position of the aircraft and
IMU measures the attitude.
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Failure Mechanism and Its Induced Movement Simulation of
Large-scale Slope
32
Laser is emitted ten thousand or hundred thousand short bursts
of light every second,
which will measure range to and reflectance of objects on the
earth surface. Schematic
diagram of this system is shown in Figure 3.1.
Airborne laser scanners for recording topographic data have been
used in various
applications (Kraus and Pfeifer, 1998). In contrast to microwave
radar techniques, lasers
are advantageous for wider range measurements because high
energy pulses can be
realized in short intervals and their comparatively short
wavelengths can be highly
collimated using small apertures (Wehr and Lohr 1999). Laser
scanning is not capable of
any direct pointing to particular objects or object features.
The resulting co-ordinates refer
to the footprints of the laser scan as they happen. Laser
scanning is high accuracy, high
sampling densities, and a high degree of automation.
Figure 3.1 Airborne laser scanners. Laser distance measuring
device, IMU and GPS
receiver antenna are installed in aircraft. GPS antenna measures
the position of the
aircraft and IMU measures the attitude. It can offer high
standard geo-information
acquisition and processing services for various
applications.
φ ω κ Laser distance measuring
φ ω κ
GNSS
X Y Z
GPS antenna
Electronic reference point
GNSS
IMU
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33
3.3 Description of finite difference method (FDM) and FLAC3D
Numerical modelling techniques have been widely used to solve
complex slope
problems, which otherwise, could not have been possible using
conventional techniques.
These models are used to simulate rock slope as well soil slope
with complex conditions.
All rock slopes involve many discontinuities such as joint,
fault, bedding plane, etc.
Precise representation of discontinuities in numerical models
depends on the type of
model. Numerical methods of analysis used for rock slope
stability investigations may be
divided into three approaches:
• Continuum modeling
• Discontinuum modeling
• Hybrid modeling
Continuum modeling is best suited for the analysis of slopes
that are comprised of
massive, intact rock, weak rocks, and soil-like or heavily
fractured rock masses.
Continuum codes assume that material is continuous throughout
the body. Discontinuities
are treated as special cases by introducing interfaces between
continuum bodies. Discrete
fractures such as faults and bedding planes can be incorporated
in most continuum models.
However, these models cannot be used to simulate highly fracture
rock mass. Finite
difference method (FDM) is based on this modeling theory. Finite
difference methods are
numerical methods for solving differential equations by
approximating them with
difference equations, in which finite differences approximate
the derivatives. In this
method, the problem domain is discretized into a set of
sub-domains or elements. The
solution procedure may be based on numerical approximations of
the governing equations.
Two-dimensional continuum codes assume plane strain conditions,
which are frequently
not valid in inhomogeneous rock slopes with varying structure,
lithology and topography.
Complex behavior of slope can be modeled using continuum codes.
Groundwater, pore
pressures and dynamic interaction can also be simulated. It
requires input properties such
as constitutive model (e.g. elastic, elasto-plastic, creep
etc.), groundwater characteristics,
shear strength of surfaces and in situ stress state. During
modeling, effects of boundary,
mesh aspect ratios, symmetry, and hardware memory restrictions
are important factors.
Some softwares based on continuum modeling like Phase2
(rocscience), FLAC2D,
FLAC3D (Itasca) and VISAGE (VIPS), PLAXIS are well suited for
slope stability