RESEARCH PAPER Exploring desiccation cracks in soils using a 2D profile laser device Marcelo Sanchez • Alvis Atique • Sewon Kim • Enrique Romero • Marcin Zielinski Received: 22 November 2012 / Accepted: 26 August 2013 / Published online: 12 October 2013 Ó Springer-Verlag Berlin Heidelberg 2013 Abstract The study of desiccation cracks in soils has been a subject of increasing attention in recent research. This paper presents the use of a 2D profile laser that is coupled with a motion controller (that allows scanning the overall surface of a drying soil) and electronic balance (to measure the water loss). The aim is to accurately track the three most relevant variables associated with the behavior of soils during desiccation: volume change, water loss and evolving crack network’s morphology. The paper presents the methodology to obtain a digital model of the soil using the experimental setup described above. The main results of a natural soil subjected to drying are presented and discussed, including evolution of cracks aperture; evolution of cracks depth, surface contour levels (at different times); and evolution of volume change. It is shown that the pro- posed methodology provides very useful information for studying the behavior of soils subjected to desiccation. Keywords Drying cracks Laser scanner Soil desiccation Volume shrinkage 1 Introduction The presence of desiccation cracks strongly affects hydraulic and mechanical properties of soils. Desiccation cracks act as a preferential path for water flow and pollu- tant transport (e.g., [5, 12, 15, 37, 41]); they also affect the performance of landfill cover and clay liners (e.g., [1, 11, 28, 45, 55]). In earth embankments, cracking reduces strength and may lead to seepage and percolation problems. The presence of desiccation cracks can also trigger land- slides. Deep vertical cracks during prolonged and intense draught increases infiltration capacity of the soil, which in turn mobilizes the shrinkage or swelling potential of deeper soils. Vital infrastructure affected by soil cracking includes levees, road embankments and engineered barriers (e.g., [7, 13, 19, 21, 42]). The formation and propagation of cracks is a highly complex phenomenon due to the strong coupling between the hydraulic and mechanical behavior of soils. Water loss during evaporation induces a rise in capillary forces. The water transfer process in drying soils is basically controlled by the hydraulic properties of the soil mass, which in turn affects the mechanical behavior, because the soil tends to contract under increasing suction [38]. During shrinkage, the changes in the stress state tend to re-accommodate the soil particles and, at a certain point of the drying process, crack generation begins. The actual physical mechanisms involved in the crack initiation and its subsequent propa- gation are the current topics of active research and open discussions (e.g., [4, 8, 17, 21, 24, 26, 31, 32, 36, 38, 43, 48, 49]). Current experimental investigations in this area pri- marily concentrate on the study of slurries prepared in plates and subjected to drying under controlled laboratory conditions (e.g., [24, 33, 36, 38]). In those tests, quite M. Sanchez (&) S. Kim M. Zielinski Zachry Department of Civil Engineering, Texas A&M University, College Station, TX 77843-3136, USA e-mail: [email protected]A. Atique M. Zielinski Department of Civil and Environmental Engineering, University of Strathclyde, Glasgow, UK E. Romero Department of Geotechnical Engineering and Geosciences, Universitat Polite `cnica de Catalunya, Barcelona, Spain 123 Acta Geotechnica (2013) 8:583–596 DOI 10.1007/s11440-013-0272-1
Transcript
RESEARCH PAPER
Exploring desiccation cracks in soils using a 2D profile laser device
Marcelo Sanchez • Alvis Atique • Sewon Kim •
Enrique Romero • Marcin Zielinski
Received: 22 November 2012 / Accepted: 26 August 2013 / Published online: 12 October 2013
� Springer-Verlag Berlin Heidelberg 2013
Abstract The study of desiccation cracks in soils has
been a subject of increasing attention in recent research.
This paper presents the use of a 2D profile laser that is
coupled with a motion controller (that allows scanning the
overall surface of a drying soil) and electronic balance (to
measure the water loss). The aim is to accurately track the
three most relevant variables associated with the behavior
of soils during desiccation: volume change, water loss and
evolving crack network’s morphology. The paper presents
the methodology to obtain a digital model of the soil using
the experimental setup described above. The main results
of a natural soil subjected to drying are presented and
discussed, including evolution of cracks aperture; evolution
of cracks depth, surface contour levels (at different times);
and evolution of volume change. It is shown that the pro-
posed methodology provides very useful information for
studying the behavior of soils subjected to desiccation.
Keywords Drying cracks � Laser scanner � Soil
desiccation � Volume shrinkage
1 Introduction
The presence of desiccation cracks strongly affects
hydraulic and mechanical properties of soils. Desiccation
cracks act as a preferential path for water flow and pollu-
tant transport (e.g., [5, 12, 15, 37, 41]); they also affect the
performance of landfill cover and clay liners (e.g., [1, 11,
28, 45, 55]). In earth embankments, cracking reduces
strength and may lead to seepage and percolation problems.
The presence of desiccation cracks can also trigger land-
slides. Deep vertical cracks during prolonged and intense
draught increases infiltration capacity of the soil, which in
turn mobilizes the shrinkage or swelling potential of deeper
soils. Vital infrastructure affected by soil cracking includes
levees, road embankments and engineered barriers (e.g., [7,
13, 19, 21, 42]).
The formation and propagation of cracks is a highly
complex phenomenon due to the strong coupling between
the hydraulic and mechanical behavior of soils. Water loss
during evaporation induces a rise in capillary forces. The
water transfer process in drying soils is basically controlled
by the hydraulic properties of the soil mass, which in turn
affects the mechanical behavior, because the soil tends to
contract under increasing suction [38]. During shrinkage,
the changes in the stress state tend to re-accommodate the
soil particles and, at a certain point of the drying process,
crack generation begins. The actual physical mechanisms
involved in the crack initiation and its subsequent propa-
gation are the current topics of active research and open
general terms, it was shown that the results obtained from
digital and manual measurements matched well. However,
the measurement of displacements from digital images is
not very precise from only one camera. Moreover, the use
of image processing technique to estimate volume change
in drying soils has a number of limitations. For example,
the shadow (in the ‘‘crack valleys’’) makes it difficult to
detect the actual (3D) geometry of the cracks from a digital
image (i.e., crack depth and variation in crack aperture with
depth are difficult to measure).
Laser scanners have been used with success for mea-
suring the volume of solids [56] and in soil and rock testing
to measure displacements (e.g., [18, 39, 40]). However, its
584 Acta Geotechnica (2013) 8:583–596
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application to study the process of desiccation cracks in
soils has not been done yet. The use of this device for
studying soil drying is presented in the following section.
2.3 Setup description
The desiccation process in soils is a strongly coupled
hydromechanical problem. Thus, an accurate measurement
of the volume change induced by the water loss is a crucial
component when studying the behavior of drying soils. The
setup proposed in this research was designed to gather
simultaneous information during desiccation associated with
these two variables: water loss and volume change.
The basic experimental setup consists of the following
main components: (1) compact 2D/3D scanner; (2) laser
motion controller; (3) electronic balance with the soil sample
on it; (4) relative humidity and temperature sensor; (5) digital
camera; and (6) a computer with data acquisition system
(DAS). Figure 2 presents a schematic representation of this
setup, and the main components are briefly described below.
A 2D/3D laser scanner ScanControl 2700-100 from
Micro-Epsilon [29] was used in this research. This device is
based on the triangulation principle for a two-dimensional
acquisition of a height profile of various target surfaces. A
laser line is generated by special lenses and projected onto the
target surface. The working principles are illustrated in
Fig. 1. A high-quality optical system projects the diffusely
reflected light of this laser line back onto a highly sensitive
sensor matrix. The controller integrated into the sensor head
uses this matrix image to calculate the position along the laser
line (y-axis) and the vertical distance (z-axis). Figure 2 pre-
sents a schematic representation of this setup, and the main
components are briefly described below.
The laser unit was fixed to the wall using a frame designed
to allow positioning the laser at different heights (see Fig. 2).
To obtain a 3D representation of the sample, the laser was
coupled with a motion controller (model OWIS PS-10) that
moves horizontally (x-axis) at a constant speed perpendicular
to the laser line. This is a single axis position controller with a
two-phase stepper motor including open-loop functionality
which has an USB interface to communicate with the com-
puter. The software tool OWISoft was used to configure and
control this unit. The soil profiles were transferred to the
computer as an array of points and were processed using the
software ICONNECT from Micro-Epsilon [29]. Each of
these profiles consists of a certain number of calibrated
measuring points, including additional information such as
intensity, time and counter information.
Z-axis resolution corresponds to the elevation resolution
(i.e., the one concerning the distance from the surface to
the sensor). Points in the surface point cloud separated by
this amount, or more, can be identified by the scanner. The
laser setup used in this research has a z-axis resolution of
15 lm with a reference line of 320 points. This means that
the sensor is able to measure the difference in a vertical
direction up to 15 lm height. This resolution is obtained
when the ‘‘laser line’’ is adopted equal to ‘‘manufactured
specified standard measuring range’’ [29]. Y-axis resolution
corresponds to the resolution along the laser line (Fig. 1).
Higher resolution means a greater amount of acquired data
along the laser line, hence more information about the
surface. The adopted laser has a predefined parameter for
this purpose, which is in the form of points/profile. The
width of the laser line depends on the actual distance from
the sensor to the target. For example, for surface–laser
distance of 400 mm, the laser line width is 100 mm (i.e.,
the manufactured standard measuring range). X-axis reso-
lution corresponds to the resolution normal to laser line
axis. This resolution depends mainly on the number of
profiles scanned per second (profiles/s); higher pro-
file(s) gives higher x-axis resolution.
A high-capacity precision weighing balance (Mettler
Toledo model SB-8001) was used to gather the water loss
during soil desiccation. It features 8.1 kg of maximum
weighing capacity, which offers 1 9 10-4 kg readability.
The balance was connected to a computer and programmed
(using Windmill software) for continuous monitoring.
A data logger (Model RH520) connected to a computer
was used for relative humidity (RH) and temperature
(T) measurements. The RH measurement range is from 10
to 95 % and T from -28 to 60 �C. The basic accuracy is
3 % RH and 1 �C. A 12.1 MP digital camera was mounted
Light source
Receiver
Fig. 1 3D view showing the laser scan, laser line, soil sample and
adopted reference system. It can be observed how the system projects
the diffusely reflected light of this laser line back onto a highly
sensitive sensor matrix
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on the laboratory stand to take images of the sample during
desiccation. A desktop computer was used for data acqui-
sition and device control.
2.4 Procedure
The desiccation tests were performed in a small room under
controlled temperature and relative humidity conditions.
The room has no windows, and the lighting was strictly
controlled to facilitate constant conditions during testing.
The soil sample was prepared close to its liquid limit and
allowed to dry in a circular desiccation plate (diameter
9.689 E-02). A glass plate with a smooth bottom and a
height of 1.292 E-02 was used for this test for preparing the
sample. The moisture content was determined before the
test (57.7 %) and after it (6.2 %). The temperature and
relative humidity of the room were continuously monitored
via the humidity data logger. The average temperature
during the test was 19.5 �C (±0.30 �C), and the average RH
was 37 % (±4 %). Figure 3 presents the time evolution of
RH and temperature in the room during the test.
The sample was placed on the top of the balance that
was programmed to record continuous water loss. The laser
was attached to the motion control unit for scanning on the
move. The laser was operated to move at a speed of
3.88 9 10-3 m/s, which allowed taking linear measure-
ments at 38-lm increments (i.e., distance between profiles
in the ‘‘X’’-direction). Moreover, with a standard laser line
width of 100 mm, it produces a 312.5 lm distance between
points in the ‘‘Y’’-direction. The sample was scanned at
time intervals depending on the crack appearance in the
sample. The whole experimental setup remained untouched
until the end of the test, allowing for the accurate recording
of experimental data during the test without perturbation of
the sample position and condition.
The 3D data obtained with the laser scanner represents
regularly distributed set of points. The scanned data was
processed using the Surfer� software [44] to create a uni-
formly spaced grid from the uniformly spaced vectors (X, Y,
Z). To achieve a high definition, the data sets were
10
15
20
25
30
Tem
pera
ture
(o C
)
Temperature
0 10 20 30 40 50 60
Time (hours)
0
20
40
60
80
100
Rel
ativ
e hu
mid
ity
(%)
Relative humidity
Fig. 3 Time evolution of room temperature and relative humidity
during test
Data acquisition pad for motion
controller
Laser scan
Soil specimen
Electronic balance
Motion controller
Digital camera
Motion bracket
PC
Mold
Fig. 2 Top right photograph of the experimental setup. Bottom left schematic representation showing the experimental setup for the laser 2D/3D
scanner. The digital camera is not part of the laser setup; it is used just for taking photographs of the cracked soil to compare them with the laser outputs
586 Acta Geotechnica (2013) 8:583–596
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additionally densified in both the x- and y-directions during
gridding. This is a standard feature of Surfer which facilitates
the creation of a very fine grid. Equal spacing of 40 lm in x-
and y-axis was used. The surface was then interpolated at the
points specified by uniformly spaced grid using natural
neighbor linear interpolation method. It calculates the
weighted average of neighboring observations using weights
determined by Voronoi polygon concepts [35]. Nearest-
neighbor algorithm is useful for converting regularly spaced
(X, Y, Z) dense data sets to Surfer grid files. The final output of
this step is a ‘‘digital model of the soil,’’ in which the grid
points (with coordinates X, Y, Z) represent the volume of the
soil sample. Digital models are obtained for the different
times of the analysis.
Once the digital model of the soil is obtained following the
procedure outlined above, different pieces of software can be
used to post-process the experimental data and extract useful
information related to cracked soils. For example, to calculate
the changes in volume during drying, two different approa-
ches have been used in this research: (1) the software Surfer
and (2) an in-house program coded in Matlab. As for method
(1), a module in Surfer allows the calculation of the volume
below the interpolated surface. Volume change during two
different times can be then calculated as the difference
between the corresponding volumes. Details about Surfer can
be found elsewhere (e.g., [44]). The Matlab code (2) is
described in the following section. It is worth mentioning that
practically identical results in terms of volume change have
been obtained with these two approaches.
3 Data processing
3.1 Preliminary study on solids of known volume
Before presenting the results obtained from the drying test
in the soil sample, the studies to check the accuracy of the
proposed setup for volume measurement are briefly intro-
duced. A Teflon ring was scanned first. The volume of the
cylinder is 9.68371E-06 m3. In order to challenge the
capabilities of the device, a plastic brick (i.e., Lego type)
was also tested. This piece is highly complex and provides
the opportunity to explore the performance of the proposed
setup when a number of vertical faces and ‘‘valleys’’ have
to be measured. The volume of the brick is 3.66E-05 m3
and was measured by the water displacement method (BS
1,377:1,975). Before measuring its volume by this method,
the void space at the bottom of the brick was filled with a
plastic filler. Figure 4a, b presents the models of these two
pieces obtained with the laser scan following the procedure
explained in the previous section. The calculated volume
for the ring is 9.6308E-06 m3. Comparing this volume with
the measured one, the difference is around 0.55 %. As for
the Lego brick, the volume found was 3.6917E-05 m3.
Hence, the volumetric accuracy per unit area is
1.17 9 10-2 cm3/cm2, which is higher than the volumetric
resolution estimated considering only z-axis resolution
(1.5 9 10-3 cm3/cm2). Assuming as the reference volume
the one calculated via the water immersion method, the
error associated with the volume measurement using this
device is around 0.87 %.
3.2 Soil sample
Figure 5a presents the digital images of the desiccated soils
at three different times: (a) 4 h, (b) 6 h and (b) 24 h.
Figure 5b presents the corresponding 3D graphical models
of the soil obtained with Surfer. From the figures, the
capability of the proposed device to capture the actual
pattern observed in the tests is apparent; only a few small
fissures are not perfectly reproduced by the model.
Once the digital model of the soil is generated, it can be
used to explore other features/properties of drying soils
difficult to study using other available techniques. Figure 6
Fig. 4 3D models obtained after scanning the samples (of known volume) and post-processing them using Surfer: a plastic brick (Lego type) and
b Teflon ring
Acta Geotechnica (2013) 8:583–596 587
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presents the position of two typical sections analyzed in
this work. For example, Fig. 7 presents the evolution of a
typical cross section (i.e., x = 46.398 mm) during drying.
Key information associated with changes in soil properties
and characteristics during drying can be obtained from
these figures, for example, volume change, crack depth,
crack aperture and porosity changes. In this research a
program coded in Matlab was developed to extract this
information. In the following paragraphs, a brief descrip-
tion of this program is presented.
Figure 8a presents the flow diagram associated with the
developed code. The first step is to read the matrix asso-
ciated with the geometry of the sample (i.e., X, Y and Z),
which represents the digital model of the soil for a given
time ‘‘t’’ (with ‘‘t’’ varying between ‘‘1,’’ first scanning, and
‘‘k,’’ final scanning). The data is organized by profiles (as
scanned) of constant coordinate ‘‘X.’’ Figure 8b shows a
schematic representation of the cracked soil at a given time
‘‘t.’’ This figure also indicates the coordinate system
adopted in this analysis for a horizontal plane. The distance
between consecutive profiles (Dh) is 0.038 mm; therefore,
a total of 2,550 profiles were processed per each time step.
In this work, a distinction has been made between crack
and gap. The gap corresponds to the void space generated
during desiccation between soil and container. Crack (as
usual) is the void space developed in the drying soil mass.
Figure 8c presents a typical cross section (at constant ‘‘X’’),
identifying the space related to gaps and cracks. The
coordinate system in a vertical plane is also showed in this
picture.
After reading the digital model for a given ‘‘t,’’ the
variables to be used in this step are initialized, and a profile
‘‘i’’ is analyzed (with ‘‘i’’ varying between 1 and ‘‘m’’; with
m = 2,550). Each profile is identified by a (fixed) coordi-
nate ‘‘X.’’ The proposed algorithm calculates the slope
(‘‘h’’) between two consecutive (‘‘Y’’) points along the
profile (Fig. 8c). At the beginning of the test h % 0 (i.e.,
Fig. 7, profile at t = 0); as drying progresses (non-
homogenous), volume changes take place and desiccation
Fig. 5 Images of the soil sample at three different times: 4 h, 6 h and 24 h. a Digital images; b 3D mode after scanning the sample and
processing it with Surfer
X
Y
Δh = 0.038 (mm)
x=81.510
x=46.398
Fig. 6 Scheme of the cracked soil sample indicating the two sections
analyzed in more detail in Figs. 7 and 9
588 Acta Geotechnica (2013) 8:583–596
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cracks start to appear at different stages of the test (i.e.,
Fig. 7, profile at t = 9 h and subsequent ones). Changes in
the gradient of the soil profile allow identifying the position
of the cracks. The proposed algorithm checks the slope
between adjacent points (from left to right). When an
abrupt change in the gradient is detected, the position
‘‘YCSb’’ associated with the beginning of a crack is stored
(where ‘‘Y’’ is related to the position of the crack, ‘‘C’’
refers to crack, ‘‘S’’ refers to start, and ‘‘b’’ identifies crack
number in the analyzed profile, i.e., b = 1, … n, where n is
0
4
8
12
16
Ele
vati
on (
mm
)
0
4
8
12
16
Ele
vati
on (
mm
)
0
4
8
12
16
Ele
vati
on (
mm
)
0
4
8
12
16
Ele
vati
on (
mm
)
-60 -40 -20 0 20 40 60
Y distance to the centre (mm)
0
4
8
12
16
Ele
vati
on (
mm
)
-60 -40 -20 0 20 40 60
Y distance to the centre (mm)-60 -40 -20 0 20 40 60
Y distance to the centre (mm)
t = 0
t = 2 hours
t = 3 hours
t = 4 hours
t = 5 hours
t = 6 hours
t = 7 hours
t = 9 hours
t = 11 hours
t = 13 hours
t = 15 hours
t = 24 hours
t = 21 hours
t = 18 hours
t = 16 hours
Section ( x = 46.398)
Fig. 7 Evolution of typical cross section (x = 46.398 mm) during drying, showing the section profiles at different times
Digital profile at time ( X, Y, Z ) t = 1, k
Variable initialization
Read digital model profiles (Xi , Yi, Zi ) i = 1, m
Select profile [ Xi =fix ] ( Xi , Yj, Zj ) j = 1, n
Crack Find ( XCi , YCi, Zci ) Find and save crack coordinates
Crack Starting Point (XCSβ, YCSβ, ZCSβ) Crack Ending Point (XCEβ, YCEβ, ZCEβ)
Find crack depth [ YCBβ (Xi , Yj) ]
Calculate total area, crack area [ Ai= trapz (YCi, YCBi ) ]
Calculate total volume, crack volume
[ Vi = ×h ]
END
( No )
( Yes )
Time = t
Xi+1 < Xm
Save crack profiles [ XCi , YCi, ZCi, Di , Ai, Vi ]
t = k
( Yes )
( No ) YCSn YCEn YCSβ YCEβYCS1 YCE1
Yl Y1
YCB1
YCBβYCBn
Yj
YGS1 YGE1
GapCrack 1
Crack β Crack n
(Xi, Y1 )
i = 1
i = m
(Xi, Yl )
Time = t
Δh = 0.038 (mm)
X
Y
Y
Z
YCS1
θ
(a) (b)
(c)
Fig. 8 a Flow diagram indicating the basic steps of the post-process program coded in MATLAB; b top view (schematic) showing the cracked
sample and the adopted reference system; c typical cross section identifying the characteristic points used in the analysis and the reference system
Acta Geotechnica (2013) 8:583–596 589
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the maximum number of cracks in a profile). In this work it
has been considered that a crack starts when the change in
slope is equal to or higher than 40�. After detecting YCSb,
the algorithm will be tracking points down the slope
associated with a lateral face of the crack (see zoom in
Fig. 8c). A change in the sign of the gradient implies that
the bottom of the crack has been reached and the corre-
sponding position is stored (identified as YCBb, where ‘‘B’’
is related to the bottom of the crack). Afterward, the
algorithm will track points that are in the other lateral face
of the crack, moving up in Z coordinate. At some point, a
sudden change in the gradient will be detected, now toward
subhorizontal slopes (i.e., small h). This change in slope
corresponds to the end of the crack ‘‘YCEb’’ (where ‘‘E’’
refers to the end of crack). Gaps are detected in a similar
way, but in this case the start (YGSb) or end (YGEb) position
is coincident with the sample container (where ‘‘G’’ refers
to gap). Figure 9 presents the results for another profile
(X = 81.510 mm), showing the time evolution of that cross
section during drying. The position of that section is pre-
sented in Fig. 6.
The procedure to identify the cracks outlined above
corresponds to cracks with a relatively simple geometry
(see, e.g., Fig. 7, t = 11 h, Fig. 8c). However, sometimes
the geometry of the crack is more complex and could
present two (or more) valleys (see, e.g., Fig. 7, t = 21 h).
The algorithm developed in this work is able to deal with
such complexities; details about these aspects can be found
in [22].
Once all the cracks (and gaps, if any) in a profile are
found, the program calculates the area of each crack (and
gap), and also the total area of the cross section that cor-
responds to cracks (and gaps). It is also possible to calcu-
late the volume associated with the cracks when the area
related to them in two consecutive profiles (separated by a
distance Dh in the X-direction) is known. For further post-
processing, all the information associated with the profile is
stored by the program (i.e., YCSb, YCBb, YCEb, YGSb, YGBb,
YGEb, cracks-area, gaps-area, etc.). The analysis described
above is repeated for all the profiles (i.e., i = 1, m) and for
all the time steps studied (i.e., t = 1, k). Figure 8a illus-
trates the steps involved in the analysis.
4 Results and discussion
The information collected by the program can be post-
processed to learn about key aspects of soils subjected to
drying. For example, volume change during shrinkage can
be associated with:
(a) vertical displacement of the top surface (indicated as
‘‘settlement’’ hereafter);
(b) lateral shrinkage (designated as ‘‘gap’’); and
(c) cracks.
The proposed methodology is capable of quantifying
these three different components of soil shrinkage. Fig-
ure 10a presents schematically these three components of
the shrinkage for a generic cross section. Figure 10b shows
how these components of the shrinkage varied with time
for the profile located at x = 46.398 mm. It is observed
-60 -40 -20 0 20 40 60
Y distance to the centre (mm)
0
4
8
12
16
Ele
vatio
n (m
m)
Time (hours)0
2
7
13
21
24
Section ( x = 81.510 )
Fig. 9 Evolution of typical cross section (x = 81.510 mm) during
drying, showing the section profiles at different times
Gap
Crack 2 Crack 3
Area of crack
Crack 1
Area of Gap
Area of Settlement
Depth
Aperture
0 2 4 6 8 10 12 14 16 18 20 22 24 26
Elapsed Time (hours)
0
100
200
300
400
Are
a ch
ange
(m
m2 )
ShrinkageSection ( x=46.398)
Total
Settlement
Total crack
Crack 1
Crack 2
Crack 3
Gap
(a)
(b)
Fig. 10 a Scheme showing the different components of soil shrink-
age, b time evolution of the different components of soil shrinkage for
a typical section (x = 46.398 mm)
590 Acta Geotechnica (2013) 8:583–596
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that at the beginning, the shrinkage is associated with
settlement only. The first crack appears around 4 h after
drying; the other ones appear around 3 h later. The major
shrinkage is associated with settlement. Only about one-
third of the total shrinkage is related to cracks and gaps.
The program also allows learning about the changes in
crack aperture and depth. In fact, in its current version, the
code calculates the crack aperture projected on a (vertical)
plane with X = constant. This value is identified AX in this
paper. Figure 11 presents the variation in depth and AX (at
the top of the crack) for the sections presented in Figs. 7
and 9. Section at x = 46.398 mm shows that crack 1
reached the maximum depth, in a very short period of time
(around 1 h), and then remains relatively constant. Around
two-thirds of the aperture of this crack developed also in a
short period of time (around 1 h as well), and the other
one-third opened almost gradually in time, up to around
20 h, after that the aperture and depth remain fairly
0 2 4 6 8 10 12 14 16 18 20 22 24 26
Elapsed time (hours)
X= 81.510Crack 1Crack 2Crack 3
X= 81.510Crack 1Crack 2Crack 3
0 2 4 6 8 10 12 14 16 18 20 22 24 26
Elapsed time (hours)
0
2
4
6
8
10
12
AX (
mm
)
X= 46.398Crack 1Crack 2Crack 3
0
2
4
6
8
10
12
14
16
18D
epth
(m
m)
X= 46.398Crack 1Crack 2Crack 3
Fig. 11 Time evolution of depth crack and aperture for two typical sections (x = 46.398 and x = 81.510 mm). The value AX corresponds to the
projection of the aperture in a vertical plane with constant ‘‘x’’ (in this case x = 46.398 and x = 81.510 mm)
Acta Geotechnica (2013) 8:583–596 591
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constant. Crack 2 developed following a similar pattern to
one explained above. Crack 3 developed also in a similar way
but delayed in time. As for the section located at
x = 81.850 mm, the behavior changes slightly with respect
to the one discussed previously, cracks appeared earlier,
and the opening of the cracks aperture was more gradual in
time.
The behavior described above is perhaps better repre-
sented by the plots shown in Fig. 12. It can be observed
that for both sections, at the beginning, the increase in
depth and AX happened simultaneously, then the depth
remains practically constant, and the aperture continued
increasing up to reaching the steady state after around 18 h
of test. Note that the decrease in depth observed in crack 1
section at x = 81.510 (Fig. 12) at advanced stages of the
drying, around 16th h (Fig. 9), is related to the significant
settlement observed near this crack at that time.
As mentioned in Sect. 2, by integrating the information
from subsequent profiles, the corresponding changes in
volume can be calculated. This is one of the main advan-
tages of the methodology used in this research. Figure 13
presents the volume changes during drying for the three
components of the shrinkage discussed above.
The advantage of knowing the volume changes asso-
ciated with each component is that it allows for the
calculation of the variations in the void ratio (or porosity)
that effectively take place during shrinkage. At a given
time, the total volume associated with the soil sample is
the sum of four main (volume) components: pores
(Vpores), solid (Vsolid), cracks (Vcracks) and gaps (Vgaps).
The volume of pores corresponds to voids in the intact
(dried) soil mass. The net volume of the dried soil is
obtained as the sum of the volume of voids plus the
volume of solid. Figure 14a presents the changes in
porosity. Two different values are plotted: total and net
porosities defined as follows:
Total porosity : nT
¼ Volcracks þ Volgaps þ Volpores
Volcracks þ Volgaps þ Volpores þ Volsolids
ð1Þ
AX (mm)
X= 81.510Crack 1Crack 2Crack 3
0 2 4 6 80 2 4 6 8
AX (mm)
0
2
4
6
8
10
12
Dep
th (
mm
)
X= 46.398Crack 1Crack 2Crack 3
Fig. 12 Concurrent changes in depth and crack aperture for two typical sections (x = 46.398 and x = 81.510 mm). The value AX corresponds to
the projection of the aperture in a vertical plane with constant ‘‘x’’ (in this case x = 46.398 and x = 81.510 mm)
0 2 4 6 8 10 12 14 16 18 20 22 24 26
Elapsed time (hours)
0
5
10
15
20
25
Vol
ume
chan
ge (
cm3 )
ShrinkageTotalSettlementCrackGap
Fig. 13 Changes in the volume of the soil sample during drying
592 Acta Geotechnica (2013) 8:583–596
123
Net porosity : nN ¼Volpores
Volpores þ Volsolids
ð2Þ
It can be observed that both porosities are identical until
the first crack/gap appeared (after approximately 7th h of
drying). Both porosities are associated with relevant
properties of the soil mass. Average properties can be
obtained from the global porosity (i.e., global density),
while properties associated with the intact soil (i.e., the
portions of soil without cracks) can be estimated/updated
from the net porosity, as discussed below. Figure 14b, c
presents the evolution of pores void ratio (ep) and discon-
tinuities void ratio (eD), defined as follows:
Pores void ratio : ep ¼Volpores
Volsolids
ð3Þ
Discontinuities void ratio : eD ¼Volcracks þ Volgaps
Volsolids
ð4Þ
The balance (Fig. 2) has been used to measure the
concurrent water loss that takes place during drying. By
combining information about volume change and water
loss, it is possible to learn about the changes in degree of
saturation during desiccation (Fig. 14d). The inspection of
Fig. 14c, d shows that the onset of crack generation
(around 7th hour) takes place when the soil is practically
fully saturated. This was confirmed in the previous
investigations (e.g., [38]).
Figure 15 represents the simultaneous changes in
moisture and dry density that take place in the soil during
desiccation. It can be observed that at the beginning, the
loss of water is accompanied by a volume change of the
sample up to water content near 25 % (which is quite close
to the shrinkage limit of the soil); then (as expected) drying
continues with practically no changes in volume. To cal-
culate the dry density presented in Fig. 15, the ‘‘net vol-
ume’’ was considered as follows:
Dry density : qd ¼Masssolids
Volsolids þ Volpores
ð5Þ
Detailed information about the shrinkage evolution and
how settlements and cracks are distributed in the soil
sample during drying can easily be obtained from the
digital model of the soil. For example, Fig. 16b presents
the contour levels at three different times, from which it is
possible to study how settlements and cracks evolve during
drying. Figure 16a presents the corresponding digital
1.00
1.20
1.40
1.60
e P
0.00
0.05
0.10
0.15
0.20
0.25
0.30
e D
0 10 20 30 40 50 60Time (hours)
0.00
0.20
0.40
0.60
0.80
1.00
0.48
0.52
0.56
0.60
0.64P
oros
ity
NetTotal
(a)
(b)
(c)
(d)Deg
ree
of s
atur
atio
n
Fig. 14 Time evolution: a porosity (total and net), b pores void ratio
(ep), c discontinuities void ratio (eD) and d degree of saturation
65 60 55 50 45 40 35 30 25 20 15 10 5 0
Water content ( % )
1.50
1.40
1.30
1.20
1.10
1.00
Dry
den
sity
( g
/cm
3)
Drying
Fig. 15 Simultaneous changes in dry density and water content
during drying
Acta Geotechnica (2013) 8:583–596 593
123
pictures. Figure 16c shows 3D cuts of the sample, illus-
trating the volume changes (i.e., settlement, cracks and
gaps) during shrinkage. The initial level (red transparent
surface on the top) is included as a reference.
The results and plots presented above are just examples
of information that can be gathered using the setup and
methodology adopted in this research. It has been shown
that relevant data related to the geometry of the cracks can
be obtained. Such kind of information is very valuable to
gain a better understanding of the drying process in soils
and also to model properly its behavior. For example,
changes in porosity of the intact soil can be used to esti-
mate the changes in its permeability, by using well-known
permeability laws (e.g., Kozeny’s law [6]). The changes in
crack geometry can also be tracked and then used to
develop models accounting for the effect of cracks on flow
and evaporation. Such developments are being carried out
by the authors, but they are outside the scope of this
contribution.
5 Conclusions
A methodology to study the behavior of drying soils based
on a 2D/3D laser scan is presented in this paper. The
proposed device combines the laser scanner with a com-
puterized motion controller and an electronic balance. All
the setup components are connected to a computer to
gather all the relevant experimental information via a data
acquisition system. The paper also presents the proposed
methodology to process the scanned volume and to obtain
the digital model of the soil from the data file containing
the X, Y, Z coordinates of the scanned points.
Very valuable information can be obtained from the
digital model of the soil, such as volume change, distri-
bution of settlements on the soil surface, crack aperture and
morphology in depth. Scans at different times allow
learning about the volume changes at the onset of crack
formation and how the phenomena of crack propagation
evolve in time, in both soil surface and depth. Experimental
Fig. 16 Images of the soil sample at three different times: 4, 6, and 24 h. a Digital images (included for reference), b contour maps and c 3D cuts
of the sample, illustrating the volume changes (i.e., settlement, cracks and gaps) during shrinkage showing the initial level (red transparent
surface on the top) (color figure online)
594 Acta Geotechnica (2013) 8:583–596
123
results obtained from a test in a natural soil have been
presented and discussed.
The experimental outcomes show that the technique
based on laser scanning is able to gather very relevant data
associated with the behavior of drying soils, more infor-
mation than those typically gathered from the current
methods. It is in summary a promising experimental
technique that could assist in advancing of current
knowledge.
Acknowledgments The discussions with Drs Rebecca Lunn and
Minna Karstunen are highly appreciated. The fifth author would like
to acknowledge the financial support provided by the EU-funded
