(11)
where k is the permeability, r is the
radius of the PFC particles, c is the K–C constant,
which was 5 in this study, and εi is
the porosity of each fluid element. The permeability coefficient was
taken as the upper limit of porosity, which was 70%. When the porosity
of the element exceeded 70%, most particles in the fluid element were
washed away, and the permeability coefficient was taken as a fixed
value.
PHYSICAL TEST
A vertical erosion test device was developed for this study. The device
can simulate the action of a constant water head and load on a sample in
the saturated state to ensure the formation of a dynamic seepage network
in soil–rock mixtures.
3.1 Device Design
The set of devices included a sample saturation device, an erosion
simulation device with a constant head, a particle collection device,
and data collection devices. The erosion simulation device was divided
into five layers, which was convenient for analysing the changes in FC
at different heights after the test, as shown in Fig. 3.
The sample saturation device was a
transparent plexiglass water tank. The water tank was composed of five
transparent plexiglass plates with a thickness of 1 cm. The erosion
simulation device was composed of five transparent plexiglass cylinders,
which could be easily disassembled and assembled. The fifth plexiglass
cylinderwas a constant head control part with a height of 25 cm, and an
overflow drain was installed 5 cm away from the top of the fifth
cylinder to keep the head height constant at 10 cm (the global hydraulic
gradient, i , was 0.2). The five transparent plexiglass
cylinders were installed by a flange connection, and they were sealed
and impervious during the test.
The height of the first plexiglass cylinder was 25 cm. A perforated
plexiglass plate and wire mesh were embedded on the inner wall 15 cm
away from the bottom of the particle collection device to separate the
collection and erosion simulation devices (Fig. 3). The perforated
plexiglass plate had a diameter of 19.5 cm and was filled with round
holes with a diameter of 1 cm, and the wire mesh had an aperture of 1
cm. The narrow gap between the perforated plate and the erosion
simulation device was filled with geotextiles to eliminate the boundary
effect of the particles as much as possible. Two circular holes with a
diameter of 5 cm were arranged on relative positions in the pipe wall to
form a hydraulic connection between the water tank and the erosion
simulation device during the saturation and erosion tests. The two
circular holes and the bottom of the erosion particle collection chamber
were sealed with non-woven geotextiles, and only water exchange was
allowed between the sample and the water tank (Fig. 3).
The data collection devices used in
this test included the following: pore water pressure gauge, dial
indicator, and DH3816N data acquisition and analysis system. The pore
water pressure gauge was installed in each ring of the erosion
simulation device, and the gap between the conductor of the pore water
pressure gauge and the hole was sealed with waterproof mastic to avoid
the formation of a seepage channel (see Fig. 4). Moreover, a perforated
plexiglass plate with a diameter of 20 cm and weight of 1 kg filled with
round holes with a diameter of 1 cm was placed on the upper surface of
the sample. A dial indicator for measuring the displacement was
positioned at the centre of the weight to measure the settlement
displacement of the sample.
3.2 Particle Size
Distribution
The research object of this test was
soil–rock mixtures with grap-graded PSDs. The particle size at the
boundary between the coarse and fine particles was selected according to
the British Standard (1990) and the Ministry of Water Resources of the
People’s Republic of China (1999). At the same time, considering the
test operability and data analysis, 2 mm was chosen as the boundary
particle size of the coarse and fine particles. Quartz sand with a
particle size of 0.5–2 mm was selected as the fine particles.
Meanwhile, the maximum particle size of the sample should not be greater
than 1/5 of the test size (Ministry of Water Resources of the People’s
Republic of China, 1999). Therefore, sandstone with a particle size of
10–30 mm was selected as the coarse material, which was obtained from a
quarry near Chongqing, China. The ratio of the coarse to fine particles
was 5:60.
Based on the fine particle content,
Vallejo et al. (2001) and Liu (2006) divided the soil skeleton into
coarse, coarse–fine, and fine particle skeleton structures. In the
coarse–fine particle skeleton structure, the FC was approximately
30%–40% (Minh et al., 2014; Lopez et al., 2016). Coarse particles act
as soil skeletons and bear most of the load, whereas fine particles fill
the pores between the coarse particles and transfer part of the
effective stress. However, under rainfall conditions, infiltration
destroys the strong interaction between the coarse and fine particles,
and as the FC decreases, the skeleton structure becomes unstable.
Therefore, it is necessary to analyse the changes in the skeleton
structure with FC ranging from 30% to 40% under the effect of
infiltration. In this study, three FCs, 30%, 35%, and 40%, were
selected to analyse the seepage deformation of grap-graded soil–rock
mixtures. The original particle size distribution of the test material
is shown in Fig. 5. The specific gravity of the raw-material soil
particles was regarded as approximately 2.65 g/cm3.
The height of the filled samples was 50 cm, and the bottom area was
314.16 cm2. Table 1 summarises the relevant parameters
of the materials used in this study.
3.3 Preparation and Test
Procedure
A batch layered preparation method was
used to reshape the sample (Bendahmane et al., 2008), and a sample with
uniform mixing of coarse and fine particles was obtained. The specific
steps are as follows:
- The total mass of each batch of materials under dry conditions was 2.0
kg, and the corresponding masses of the quartz sand and sandstone were
weighed separately according to the different proportions of coarse
and fine particles in each test.
- Water with a slightly lower standard than that of the optimal water
content was added into the quartz sand and stirred.
- According to the set proportion, sandstone was added into the quartz
and water mixture and stirred to obtain the final soil–rock mixture.
If too many soil–rock mixtures are prepared at once, it is easy to
cause a large separation between the fine and coarse particles at this
stage.
The soil–rock mixture was poured into the erosion simulation device and
stirred several times. Although some fine particles in the first batch
passed through the wire mesh into the particle collection device before
the test, there was almost no particle loss afterwards, which was also
consistent with the test phenomenon of Moffat et al. (2006). The water
inlet pipe was close to the inner wall of the water tank to ensure that
the water level slowly infiltrated the sample from bottom to top to
minimise the impact of seepage force on the stability of the fine
particles. The method of static saturation (Ministry of Water Resources
of the People’s Republic of China, 1999) was adopted to ensure that the
sample remained for 12 h. Based on the observation, there were no
bubbles visible to the naked eye in the saturated sample.
This test adopted the seepage mode of the constant head
(I = 0.2) and constant load (1.0 kg) and was carried out
approximately 2 h after saturation. When the test was completed, the
drain valve at the bottom of the water tank was opened to allow all the
water in the tank and erosion simulation device to be discharged.
Afterwards, different samples were collected from the five layers of the
erosion simulation device and stored separately. After drying and
weighing, the distribution changes in each layer were analysed.
3.4 Test Results
3.4.1 Pressure Gradient
Variation
Fig. 6 shows the pressure gradient variation of the five layers in the
erosion simulation device during the test, where
ijk represents the local hydraulic
gradient variation between the j-th and
k-th pore pressures.
For FC = 30% and 35% in Figs. 6(a) and (b), respectively,
△i1-2 and
△i4-5 (bottom and top of the sample)
were greater than △i2-3 and
△i3-4 (middle of the sample). In
particular, △i3-4 slightly changed
during the test. This may be due to the loss of fine particles and
internal latent corrosion of the first, second, fourth and fifth layers.
Although the fine particles in the third and fourth layers also
migrated, they were supplemented from the top of the sample (fifth
layer). Moreover, under the coupling mechanism of particle loss and
particle supplementation, the pressure gradient variation slightly
changed. The changes in the two samples remained stable after
approximately 1500 and 2000 s, respectively. The larger the FC, the more
the particles, and the longer the stabilisation time. Furthermore,
△i1-2 and
△i2-3 (upstream of the sample) were
greater than △i3-4 and
△i4-5 (downstream of the sample), which
is also consistent with the test phenomenon of Jiang et al. (2018). For
FC = 40%, as shown in Fig. 6(c), △i1-2and △i2-3 were greater than
△i3-4 and
△i4-5 . However,
△i3-4 increased after 1200 s and
continued to expand at the end of the test, which may be because the
seepage channel of the sample with FC = 40% is more difficult to
stabilise, causing the erosion at the top of the sample to develop to
the middle part.
3.4.2 Changes in Fine Particles in Each
Layer
Fig. 7 shows the changes in fine
particles in each layer after the test. It was found that the top change
of fine particles in the erosion simulation (first layer) was the
largest, followed by the bottom change (fifth layer), and then the
middle change (second, third, and fourth layers). The greater the FC,
the greater the change in fine particles over the entire height.
Moreover, the loss of fine particles in the sample with FC = 40% in the
fifth layer reached a maximum of 5.3%.
After fine particle migration under the action of infiltration, the
vertical section of the sample was divided into three areas according to
changes in fine particles: top, middle uniform, and bottom loss areas.
The loss of fine particles in the top loss area was the largest,
followed by the loss in the bottom loss area, and then the loss in the
middle uniform area. Because fine particles at the top of the sample
were lost to the next layer of the sample without other supplements, the
loss of fine particles was the largest. The bottom layer of the sample
was located in the downstream section of the seepage channel, and the
fine particles were prone to large loss. Meanwhile, the fine particles
in the middle of the sample were lost and received supplements from the
top of the sample; hence, the change in fine particles was the smallest.
Similar phenomena were also observed in the permeability deformation
test (Kenney et al., 1985; Marot et al., 2016; Zhong et al., 2018).
It should be mentioned that because the operation error during the test
resulted in the successful recording of the dial indicator data of only
one of the three samples, there was no comparative analysis of the top
settlement of different samples.
PARTICLE-SCALE NUMERICAL
TEST
4.1 PFC
Model
The numerical test was simplified based on the physical test and the
calculation workload. Only ideal discontinuous grap-graded soil–rock
mixtures with fine (particle size range of 1–2 mm) and coarse particles
(particle size range of 10 mm) were considered. The particle shape used
in the simulation was spherical, and its influence was not considered.
Three types of PSD were selected, and the mass fractions of fine
particles in the three gradations were 30%, 35%, and 40%. During
sample preparation and testing, the gravitational acceleration was set
to 9.81 m/s2, and the direction was vertical and
downward.
The numerical test piece was a cylinder with a diameter of 50 mm and
height of 125 mm. The contact model in the PFC adopts a rolling
resistance linear model, and Table 2 lists the contact parameters of the
PFC particles. In Table 2, a magnitude of 1.5e8 Pa was selected for the
Young’s modulus in this study. Although the elastic models of quartz and
sandstone are, in reality, greater than 1e9 Pa, Chand et al. (2012)
found that a smaller magnitude of Young’s modulus does not significantly
affect the physical response of the particulate system and also allows
for a larger time step, which can considerably save computational
resources.
Presently, there are several methods
of preparing accumulation particle samples using DEM, such as the
falling method (ØREN et al., 2002), pure geometric method (Bagi et al.,
2005), radius amplification method (Itasca Consulting Group I, 2004),
and layered under compaction method (Jiang et al., 2003). The object of
this study belongs to grap-graded PSDs under compaction, that is,
natural accumulation. To simulate this stacking state, the sample was
prepared based on the works of Huang et al. (2015) and Huang et al.
(2020). The specific steps for generating the particle accumulation are
as follows:
Stage 1: Initial particles were
generated. According to the given soil particle distribution curve,
particles were randomly generated in the model by the Monte Carlo method
in the wall, which is twice the height of the target model as the
initial state (Fig. 8(a)). The initial porosity of the generated
particles was set to 0.7, and it was used to control only the number of
initial particles.
Stage 2: Stable particle accumulation
was obtained after gravitational deposition. By applying gravitational
field to the particles, the particles were stably deposited under the
action of self-weight, and their porosities were measured. A servo
pressure of 100 Pa was applied on the deposited particle to compact to
pressurise the model to the preset sample height. Similar to the
physical test, the sample was divided into five layers based on height
(Fig. 8(b)).
Stage 3: The sample was obtained. The
lower wall was removed, and a perforated diaphragm with a circular hole
diameter of 6 mm and spacing of 10 mm was placed (Fig. 8(c)). In this
stage, the porosities of the samples with FC = 30%, 35%, and 40% were
0.39, 0.36, and 0.34, respectively. As shown in Fig. 8(d), the sample
has a coarse–fine particle skeleton structure, and the coarse and fine
particles were stressed together.
4.2 ABAQUS model
ABAQUS/Standard calculation program was introduced to calculate the
seepage in the sample. The shape and size of the ABAQUS calculation grid
were consistent with the DEM samples, and there were 120 elements in
total, as shown in Fig. 9. As in the physical test, the upper boundary
condition of the model was set as the pressure inlet, the lower boundary
was set as the pressure outlet, and the surrounding boundary conditions
were set as the impermeable wall boundary to simulate one-way seepage.
The pressure gradient was set to 0.2. The fluid parameters used in this
study are listed in Table 3. All particle information (including
position, velocity, and drag force) and all contact forces and energies
within the samples were recorded every 0.1 s during each suffusion
simulation, with a total duration of 20 s. Each coupling interval was
approximately 20 min, and with a total of 200-time intervals, it took
approximately 2–3 days on a sample. The calculation was conducted on a
computer with Intel I9-9900K and 32 GB RAM.
NUMERICAL RESULTS
5.1 Pressure Gradient
Variation
Fig. 10 shows the pressure gradient variations of the different samples
during seepage. The fluid element was evenly divided into five parts
according to the physical test. In the numerical test of three samples,
the pressure gradient of the specimen at different parts of the seepage
path was different. This is similar to the phenomenon and law observed
in the physical test, where △i1-2 and
△i4-5 (bottom and top of the sample) was
greater than △i2-3 and
△i3-4 (middle of the sample) and the
pressure gradients of the upper part
(△i3-4 and
△i4-5 ) was less than those of the lower
part (△i1-2 and
△i2-3 ). For the sample with FC = 30%,
the phenomena and laws were obvious. In addition, for the sample with FC
= 40%, the change in pressure gradient
△i3-4 was also obvious, which is similar
to the phenomenon observed in the physical test (Fig. 6(c)). This
indicates that the particle structure changes noticeably and is caused
by the migration of a large number of fine particles.
5.2 Transportation of Fine
Particles
5.2.1 Macroresponses of the Gap-graded
Samples
Fig. 11 shows the variation in the roof settlement and fine particle
loss during the test. Before approximately 3 s, the number of particle
losses was inversely proportional to the fine particle content. The loss
of fine particles in the sample with FC = 30% was the largest, and the
roof settlement of the experimental sample with FC = 40% was the
largest. However, the roof settlement of the sample with FC = 30% was
greater than that of the sample with FC = 35%. This may be because the
skeleton of the sample with FC = 30% was unstable, the loss of fine
particles in the first layer was significant, and the roof settlement
was also large.
For the sample with FC = 30%, the roof settlement and particle loss
stabilized at approximately 2.5 and 2.7 s, respectively. Meanwhile, for
the sample with FC = 35%, the roof settlement and particle loss
stabilized at approximately 3.8 and 7.5 s, respectively. The stability
of the roof settlement and particle loss indicated that the load-bearing
skeleton was stable. For the sample with FC = 40%, there was no
stabilisation time, and the rate of change of sedimentation and particle
loss reduced in 4 s.
5.2.2 Particle
Migration
Based on the analysis of the seepage failure process of each test, some
specific time points were selected for analysis (Fig. 11(b)). Fig. 11
depicts the internal migration of pre-stratified particles at different
times, where the black arrow represents the main infiltration channel.
The figure shows that the coarse particles moved slightly.
Before the test, the number of particles lost in the first layer was the
highest, as shown in Fig. 12(a). As the test progressed, particles in
the second and third layers entered the first layer. Afterwards,
particles in the fourth layer penetrated the third layer but did not
penetrate the second layer. Under the action of the fluid drag force,
almost all the particles in the fifth layer penetrated the fourth layer.
Fig. 12(b) is similar to Fig. 12(a). However, because of the finer
content of the sample, there were more main infiltration channels than
the samples with FC = 30% and 35%. After 7.5 s, the particles in the
second to fifth layers penetrated the first layer.
To further analyse the loss of fine particles in each layer, the number
of fine particles at different heights in the test process was counted.
As shown in Fig. 13(a), before approximately 3 s, the particle loss of
each layer tended to be stable except for the fifth layer, and at
approximately 17 s, the particles in the fourth layer began to enter the
third layer. The particle accumulation in the third layer caused the
number of particles to increase. Thus, Fig. 13(b) is similar to Fig.
13(a). However, no obvious particle accumulation was observed. In Fig.
13(c), all the particles in the fifth layer were lost, and the particle
loss in the other layers was not stable.
Fig. 14 shows the changes in fine particles in each layer after the
test. The vertical section of the sample can also be divided into three
areas according to changes in the fine particle content: top loss,
middle uniform, and bottom loss areas. This phenomenon is similar to
that of the physical experiments. By comparing Figs. 13(a)–(c), it was
found that fine particles with FC = 30% emerged and accumulated in the
middle uniform area (second–fourth layers), causing the number of
particles to increase. Meanwhile, the number of particles in the middle
uniform area with FC = 35% slightly changed, whereas the number of
particles with FC = 40% gradually decreased. This shows that under
natural accumulation, the fine particles are 35% and fill the pores of
large particles.
5.3 Coarse-Fine Particle Skeleton
Structure
5.3.1 Particle-Particle
Contacts
There are five types of particle
contact: fine–fine, coarse–coarse, coarse–fine, coarse–wall, and
fine–wall contacts. Owing to the loss of fine particles, the fine–fine
and coarse–coarse contacts of grap-graded soil–rock mixtures change
most significantly during seepage failure. Fig. 15 shows the changes in
the fine–fine and coarse–coarse contacts.
From Fig. 15, the number of fine–fine and coarse–coarse contacts of
the sample with FC = 30% remained stable during the test, indicating
that although there was a certain loss of fine particles under this fine
particle content, it did not affect the change in the load-bearing
skeleton. For the sample with FC = 35%, before approximately 5 s, the
number of fine–fine contacts decreased with the loss of fine particles,
whereas the number of coarse–coarse contacts increased, showing that
the coarse particles in the load-bearing skeleton gradually bear the
load of the lost fine particles. After approximately 5 s, the number of
contacts did not change. For the sample with FC = 40%, the number of
fine–fine contacts decreased throughout the test, whereas the number of
coarse–coarse contacts increased. At the end of the test, the number of
contacts did not remain stable, resulting in the continuous loss of fine
particles and the number of fine–fine contacts being less than that of
samples with FC = 30%.
Fig. 16 shows the axial force
nephogram of fine–fine and coarse–coarse contacts in the load-bearing
skeleton after the test. In Fig. 16(a), the area in which the fine
particles accumulate between the pores of the coarse particles is marked
in red. It is obvious from the figure that the number of fine–fine
contacts in the sample with FC = 35% was the largest, and the stress
distribution was relatively large. In Fig. 16(b), for the sample with FC
= 30%, the force chain of the coarse–coarse contact was more complete
from the top to bottom of the sample. For the sample with FC = 35%, the
force chain of the coarse–coarse contact was missing in the middle from
the top to bottom of the sample, that is, the dense area of fine
particles in Fig. 16(a).
5.3.2 Strong Force Chain
Buckling
Because of the loss of fine particles, the original load-bearing
skeleton collapsed, and a new skeleton eventually formed. The collapse
of the original load-bearing skeleton was mainly induced by strong force
chain buckling. To further understand the evolution characteristics of
the packing of particles of different load-bearing skeletons, the upper
and lower parts (the junction of the first and second layers and the
junction of the third and fourth layers) in each test were selected, as
shown in Fig. 17. The strong force chains and chained particles are
marked in red. The contact forces between the particles were larger than
the average value. Fig. 18 shows the evolution characteristics of the
force chain for samples with different FCs at the selected strong force
chains. For ease of display, the particles were reduced once.
In Fig. 18(a), the axial force decreased in the initial 1 and 2 s of the
samples with FC = 30% and FC = 35%, respectively. Afterwards, the fine
particles in the fifth layer gradually flowed downwards and became lost.
Moreover, the interaction of coarse particles between the fourth and
fifth layers became increasingly obvious, and the strength of the force
chain continuously increased. The samples with FC = 30% and 35%
remained stable (approximately 16 and 13 N) after 15 s. In the sample
with FC = 40%, there is no force chain between the selected coarse
particles in the initial load-bearing structure (the axial force was 0).
With the development of seepage failure and the loss of fine particles,
the axial force of the force chain between the selected coarse particles
increased. After 13 s, the axial force remained relatively stable, that
is, 16–18 N.
In Fig. 18(b), the axial force decreased in the initial 2 and 4 s of the
samples with FC = 30% and 35%, respectively. Subsequently, the axial
force remained stable. The time was the same as the stable time of
particle loss in Fig. 11(b), indicating that the loss of fine particles
stopped and the load-bearing structure of the skeleton remained stable.
In the sample with FC = 40%, the evolution was the same as that in Fig.
18(a). After 13 s, the axial force remained relatively stable, that is,
26–28 N.
DISCUSSION
The relative content of fine particles
is the key property affecting stress transfer through grap-graded
granular materials. The selected FC in this test was 30%–40%, which
is a coarse–fine particle skeleton structure. The sample with FC = 30%
tended to have a coarse particle skeleton structure (fine particles
underfilled the voids between the coarse particles), whereas the sample
with FC = 40% tended to have a fine particle skeleton structure (fine
particles overfilled the voids between the coarse particles).
Under the action of vertical infiltration and gravity, the change in
pressure gradient in the middle area was less than that in the upper and
lower areas (Fig. 10). However, as the FC increased, the pressure
gradient in the middle area changed considerably. Because fine particles
play an important role in the load-bearing structure, if the fine
particles are dragged and migrated, the structure will change
significantly, causing the pressure gradient to change with time.
Fine particles were lost at the top and bottom of the three samples;
however, as the FC increased, the particles in the middle soil changed
from a certain accumulation to stability to particle loss (Figs. 12 and
13). Fine particles reasonably fill the voids between coarse particles
and can maintain better stability under the action of the same
infiltration force. Obviously, the finer the particles, the greater the
force shared by the fine particles. Therefore, in the process of fine
particle loss, the samples with FC = 30% and 35% were relatively more
stable during the test process. For the sample with FC = 35%, fine
particles bore more load contribution (with a finer particle contact
number, as shown in Fig. 16(a)). For the samples with FC = 40%, the
initial contact force of the strong link was 0 (Fig. 18), which
indicates that there was poor contact between the coarse particles such
that the coarse particles became an “island” and only a part of the
fine particles around the coarse particles bore the load. Meanwhile, the
coarse particles bore more load with the loss of fine particles.
By comparing the phenomena and results of the physical and numerical
tests, there is a high similarity in the variation process of the
pressure gradient and fine particles in different layers. This shows
that the numerical model can better reproduce meso phenomena such as
particle migration, permeability evolution, and particle recombination
in the physical test. The coupling model of PFC3D and ABAQUS can be used
as an effective means of studying the mechanism of seepage deformation.
However, owing to the defect in calculation efficiency of the numerical
software, the method needs to be further improved to reflect the
irregular characteristics of particles and the influence of micro
disturbances in real situations through GPU/CPU parallel technology.
CONCLUSIONS
In this study, a permeability test for
the stability of gap-graded soil–rock mixtures considering particle
loss was conducted, and the physical process of seepage deformation of
soil–rock mixtures with different FCs was numerically simulated using
the coupling model of PFC3D and ABAQUS. The results showed that this
coupling model has a good effect on the simulation of the particle-scale
movement under seepage. Particle migration causes a change in the soil
particle structure and also induces seepage deformation. Hence, the key
concluding remarks are as follows:
- During the seepage process, fine particle loss occurred at different
sample heights. After seepage, the spatial distribution of fine
particle loss along the height direction can be divided into three
areas: top, middle uniform, and bottom loss areas. The pressure
gradient in the top loss area was smaller than that in the bottom loss
area during the test.
- The “island” effect of coarse particles, which is caused by
excessive fine content and makes the fine particles bear more load,
was eliminated with the loss of fine particles. The fine particle
content remained relatively stable under the actions of infiltration
and vertical gravity. In this preset working condition of coarse and
fine particle diameters, setting FC to 35% may be the best way to
fill the voids between the coarse particles.
- The change processes of the pressure gradient, transportation of fine
particles, and the load-bearing structure were recorded, which clearly
and intuitively expresses the migration trend of particles in the
seepage process. Moreover, the numerical simulation results were
highly consistent with the physical test results. This shows that the
coupling model of PFC3D and ABAQUS can capture both micro- and
macro-characteristics of particles and fluids and has practical
significance in simulating the particle-scale seepage deformation
process of grap-graded soil–rock mixtures.
DECLARATION OF CONFLICTING
INTERESTS
The author(s) declared no potential conflicts of interest with respect
to the research, authorship, and/or publication of this article.
ACKNOWLEDGMENTS
The author(s) disclosed receipt of the following financial support for
the research, authorship, and/or publication of this article: This paper
gets its funding from projects (Grant No. CYB21031) supported by the
graduate research and innovation foundation of Chongqing, China;
(LNTCCMA-20200103; LNTCCMA-20210107) supported by the Key Laboratory of
New Technology for Construction of Cities in Mountain Area. The authors
wish to acknowledge these supports.
REFERENCES
Bagi K (2005) An algorithm to generate random dense arrangements for
discrete element simulations of granular assemblies. Granular
Matter 7(1), 31-43.
Bendahmane F, Marot D and Alexis A (2008) Experimental parametric study
of suffusion and backward erosion. Journal of geotechnical and
geoenvironmental engineering 134(1), 57-67.
BSI (1990). BS1377:1990: Methods of test for soils for civil engineering
purposes, Part 1: General requirements and sample preparation.