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A soil moisture estimation method using actively heated fiber Bragg grating sensors
Accepted Manuscript A soil moisture estimation method using actively heated fiber Bragg grating sensors
Ding-feng Cao, Bin Shi, Hong-hu Zhu, Hilary I. Inyang, Guangqing Wei, Chao-zhe Duan PII: DOI: Reference:
S0013-7952(17)30377-0 doi:10.1016/j.enggeo.2018.05.024 ENGEO 4856
To appear in:
Engineering Geology
Received date: Revised date: Accepted date:
7 March 2017 2 March 2018 25 May 2018
Please cite this article as: Ding-feng Cao, Bin Shi, Hong-hu Zhu, Hilary I. Inyang, Guangqing Wei, Chao-zhe Duan , A soil moisture estimation method using actively heated fiber Bragg grating sensors. Engeo (2017), doi:10.1016/j.enggeo.2018.05.024
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ACCEPTED MANUSCRIPT A soil moisture estimation method using actively heated fiber Bragg grating sensors Ding-feng Cao1, 2, Bin Shi1*, Hong-hu Zhu1*, Hilary I. Inyang3, Guang-qing Wei4, Chao-zhe Duan1 1 School 2
of Earth Sciences and Engineering, Nanjing University, Nanjing 210023, China
Department of Civil and Environmental Engineering Department, Engineering College, University of Wisconsin-
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Madison, Madison, WI,53706, USA
Global Education and Infrastructure Services LLC, Charlotte, North Carolina, USA
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Suzhou NanZee Sensing Technology Co. Ltd, Suzhou 215123, China
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Corresponding author1*:Bin Shi, School of Earth Sciences and Engineering, Nanjing University, Nanjing 210023, China Tel :86-025-89680317, Fax: 86-025-83686016, Email: [email protected]
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Corresponding author2*: Hong-hu Zhu, School of Earth Sciences and Engineering, Nanjing University, Nanjing
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210023, China Tel :86-025-89681137, , Email: [email protected]
ACCEPTED MANUSCRIPT Abstract Although many methods of soil moisture measurement exist, there remains a lack of soil moisture sensor with small volume, high precision, excellent real-time performance and distributed monitoring capability. In this paper, a fiber Bragg grating (FBG)-based carbon fiber
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heated sensor (CFHS) that can counter deficiencies in soil moisture movement is proposed. The
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CFHS consists of a carbon fiber rod with a diameter of 5 mm, quasi-distributed FBG sensors on an
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optical fiber, a coating, two binding posts, and two electric cables. Laboratory calibration tests
have been conducted to establish an empirical piece-wise relationship between the temperature
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characteristic value and soil moisture for sand, silt and clay. A laboratory validation test under
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normal gravitational conditions and a centrifuge test under overweight conditions, have been performed to verify the feasibility of this technique for soil moisture monitoring. Test results
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show that the CFHS can (i) accurately record soil moisture under normal gravitational and
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overweight conditions and (ii) track the evolution of capillary zones, and the generation and migration of moisture transition zones under centrifuge acceleration. During a response period
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of 5 minutes, the accuracy is 0.033 m3/m3 under 1g condition, and 0.047 m3/m3 under
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overweight condition. With the advantages of small sensor size, low disturbance of soil mass and wide adaptability in physical model tests, the proposed method can achieve distributed soil moisture measurement at different scales and high efficiency. Keywords: Soil moisture, fiber Bragg grating (FBG), carbon fiber heated sensor (CFHS), fiber optic sensing
ACCEPTED MANUSCRIPT 1 Introduction According to the measurement mode, commonly used soil moisture monitoring methods can be divided into two groups: those for point measurements and those for distributed measurements. The first group includes the thermo-gravimetric method, time domain reflectometry (TDR),
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frequency domain reflectometry (FDR), and capacitance and frequency domain techniques. The
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major distributed techniques are ground penetrating radar (GPR), remote sensing, infrared detector,
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and actively heated fiber optic cable (AHFO) (Cao et al. 2014, 2015; Sourbeer and Loheide 2015; Sayde et al. 2015; Striegl and Loheide 2012; Sayde et al. 2010). Some of these methods such as the
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thermo-gravimetric method, require the destruction of soil structure. TDR and FDR involve probes
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that are too large for laboratory use. The spatial resolution of AHFO is insufficient for small-scale model tests. GPR, infrared ray and remote sensing have low measurement accuracy and can hardly
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detect soil moisture profiles with good reliability. Therefore, it is necessary to develop an automatic,
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compact-size, and high-accuracy monitoring technique for in-situ soil moisture. In recent years, the fiber Bragg grating (FBG) sensor has been widely used for monitoring
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geotechnical structures due to the advantages of small size, anti-electromagnetic interference,
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corrosion resistance and high sensitivity (Huang et al. 2012; Zhu et al. 2012, 2014, 2017). Some scholars have successfully employed it to develop soil humidity sensors (Alwis et al. 2013, Yeo et al. 2008). Based on the sensing mechanism, FBG soil moisture sensors can be divided into two categories. The first one focuses on measurement of the strain induced by the changes in soil moisture. The Bragg gratings of these sensors are coated with water-sensitive materials such as Polyimide (PI). These materials swell after absorbing water and shrink upon dehydration. Soil moisture can then be determined from its correlation relationship with the strain-induced Bragg
ACCEPTED MANUSCRIPT wavelength measurement. (Alwis et al. 2013; Berruti et al. 2013; Yeo et al. 2008; Huang et al. 2007). The second type of FBG soil moisture sensor utilizes the influence of water molecules on the refractive index of Bragg gratings. In these sensors, photosensitive materials (i.e., cobalt chloride, cobalt oxide and electro-chromic polymers) are added to the Bragg gratings or on their surface. Soil
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moisture can be determined by use of the relationship between water absorption amount and the
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incident light spectrum (Yeo et al. 2008). However, the use of both kinds of sensors for real-time
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soil moisture monitoring is difficult for the following reasons: firstly, the water-sensitive and photosensitive materials have time lags, and these materials are difficult to dewater synchronously
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with soil, especially, during the drainage process, and secondly, although both kinds of sensors
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require full contact with the surrounding soil to keep sufficient exposure of the added sensitive materials to the soil, the sensors themselves are too fragile to be directly placed in the soil. In
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addition, water-sensitive materials are also very sensitive to ambient temperature—expanding with
(Yeo et al. 2008).
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heat and contracting with cold which seriously affects the measurement accuracy of soil moisture
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The design of an FBG-based carbon fiber heated sensor (CFHS) for monitoring in-situ soil
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moisture profiles is analyzed and presented in this paper. Laboratory calibration tests were performed to acquire data on the basic parameters of the CFHS. A laboratory validation test under
normal gravitational conditions and a centrifuge test under overweight conditions, were performed to verify the feasibility of using CFHS in soil moisture monitoring.
2 Theory 2.1 Basic principle The principle of CFHS is based on observed correlation between the thermal responses of the
ACCEPTED MANUSCRIPT heated sensor and the moisture content of the surrounding soil. When measurement starts, the CFHS is heated under a constant current, and the temperature variation of the CFHS is recorded by an FBG interrogator during heating. Based on a series of calibration tests, a temperature characteristic value (Tt) can then be used to calculate the soil moisture (θ) (Cao et al. 2014, 2015).
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The FBG quantifies temperature through measurement of the thermal sensitivity of the
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backscattered Bragg wavelength drift. When a beam of incident light is emitted into the optical fiber,
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some back-reflected light is produced (Bragg light) due to the filter of the Bragg gratings. The Bragg wavelength of an FBG is given by (Huang et al. 2007; Erdogan 1997):
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B 2neff
(1)
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where neff is the effective refractive index (dimensionless), is the spatial period of the FBG (nm), and B is the Bragg wavelength (nm). The drift of B is determined by strain and
where
(1 Pe ) z ( F F )T
(2)
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B
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temperature of the FBG (Huang et al. 2007):
represents the drift of B (nm), Pe is the effective elasto-optical coefficient
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(dimensionless) of the FBG, z is the axial strain (dimensionless), F and F represent the
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coefficient of thermal expansion (1/°C) and thermal-optical coefficient (1/°C) of the single mode fiber, respectively, and T is the temperature change (°C).
2.2 Soil moisture calculation For the purpose of theoretical analysis, a homogeneous and isotropic soil is considered. For a line heat source such as CFHS buried in a boundless soil medium, the temperature T measured by the FBG sensor, satisfies the following relationship (Sayde et al. 2010; Florides and Kalogirou 2008; Carslaw and Jaeger 1959):
ACCEPTED MANUSCRIPT T
q ' 4 t ln T0 4π r 2
(3)
where q ' is the heat power per unit time per unit length (J m-1 s-1), r is the distance from the line source (m), t is the heating time (s), 𝜆 is the thermal conductivity (W m-1 °C-1), k is the thermal diffusivity (m2 s-1), is Euler’s constant (= 0.5772), and T0 is the initial ambient temperature
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(C°).
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Literature searches indicate that the theoretical relationship between soil thermal conductivity
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and soil moisture has not been established so far, and there are only some empirical and semiempirical models (Ciocca et al. 2012). The most widely used piece-wise function model was
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adopted here. When the soil moisture is lower than the threshold level, a linear function is used, and
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if it is higher, the relationship follows a logarithmic function:
z1 z2 ln( z3 ) 0 Tt 0 k b
(4)
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where Tt is the temperature characteristic value (°C), which is defined as the average temperature during the heating period (min), 0 is the threshold moisture (m3/m3) (Cao et al. 2014, 2015). 0
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is related to soil composition and grain size which can be obtained by laboratory tests (m3/m3). z1 ,
z 2 , z3 , k and b are constants that are dependent on the soil structure and the soil types, because
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the distances among solid particles are dependent on soil structure and type. The influence of soil moisture on thermal conductivity is accounted for the saturation of water bridges that is determined by distances among solid particles. To get these values, calibration tests must be performed and the actual soil moisture contents of samples must be measured by the thermo-gravimetric method. Thereafter, the least square method can be used to relate Tt to .
3. CFHS design for soil moisture monitoring To overcome the shortcomings of existing FBG moisture sensors, a new sensor (CFHS) was
ACCEPTED MANUSCRIPT designed, as shown in Fig. 1. The CFHS consists of a carbon fiber rod with a diameter of 5 mm, quasi-distributed FBG sensors on an optical fiber, a coating, two binding posts, a direct current (DC) power supply or current converter that can transform alternating current (AC) into DC, and two electric cables. The
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length of the rod is adjustable according to actual needs. The ends of the CFHS and electrodes of
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power supply are connected by electric cables. One cable is used to connect the positive electrode
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and the other one connects with the negative electrode. Here, DC is suggested for use because when compared with AC, DC is more stable and adjustable, especially if the length of CFHS is less than
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1 m.
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The carbon fiber rod is not only as a skeleton of the CFHS, but also conducts the electric current. The resistance of the carbon fiber rod is 26.2 Ω/m, and the heating power per unit length is a constant.
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The FBGs are glued onto the surface of the carbon fiber rod with epoxy resin. The spacing between
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adjacent FBGs, D, can be set according to specific monitoring requirements. After the installment of the FBGs, it is necessary to apply a coating to protect the optical fiber from destruction and power
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leakage. Finally, a binding post is installed at each end of the carbon fiber rod and is connected to
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the power supply by electric cables. The parameters of the CFHS in different soils were obtained in the laboratory calibration tests.
4. Laboratory calibration tests 4.1 Experimental Design To establish the relationship between soil moisture and temperature characteristic values, some calibration tests were performed. These tests were performed in a polyvinyl chloride (PVC) tube which was used to repack soil samples, as shown in Fig. 2. The PVC tube has a length of 1 m and a
ACCEPTED MANUSCRIPT diameter of 15 cm. The upper surface of the tube was cut out to create a groove so as to facilitate the observation of the wetting front, as shown in Fig. 2(b). The removed plate was taken as a cover, which was installed on the PVC tube after soil samples put into it. Four types of soils (medium sand, fine sand, silt and clay) were chosen. Their grain size distributions are shown in Fig. 3.
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Prior to the tests, all the soil samples were dried in an oven for 24 _ 48 hours at the temperature
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of 105 °C to make sure that they dried completely ( 0 ). If the relative soil weight change was
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less than 0.2 % in this period, the soil was considered to be adequately dry. The dried silt and clay samples were passed through a sieve with 2–mm–diameter holes. The clay samples were divided
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into 15 groups, and the other soils were divided into 12 groups. A different quantity of water was
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added to each group’s samples. The required amount of water was calculated according to the dry density of soil and gauged by a graduated cylinder. The dry density was controlled by compaction
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force, which is dependent on soil moisture content. The smaller the difference between the actual
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soil moisture of prepared sample and its optimum moisture content, the less required compaction force. Here, the volume of the test chamber was held constant and completely filled during each test.
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In Table 1, the physical and hydraulic characteristics of the tested soils are provided. During the soil
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samples preparing process, water was added to silt and clay by spraying and stirring soil. All these soil samples were kept for at least 48 hours to ensure uniformity in moisture distribution. For sands with a moisture content of less than 0.15 m3/m3, the sample preparation process was the same as for silt and clay. If it exceeded 0.15 m3/m3, the soil samples with a moisture content of 0.15 m3/m3 was added into the PVC tube first, and the extra water was sprinkled on the surface of the soil samples in the PVC tube. Then, the PVC tube was kept standing for 5 hours to enable the sprinkled water to infiltrate into the soil uniformly (here it is an approximate method, the limitation of which will be
ACCEPTED MANUSCRIPT discussed in Section 5.3). All the soil samples were filled and compacted layer by layer, into the PVC tube using a rubber mallet. When half of the PVC tube was filled with soil, a CFHS was inserted into the middle of the tube, and the other half of the volume was filled as well. The bulk of initially added unconsolidated
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soils is always larger than the quantity in the PVC tube. So, it was necessary to pack the soil volume
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to the same level as that of the PVC tube. After all the soil was filled into the PVC tube, the cover
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(PVC plate) was sealed on the PVC tube with duct tape to prevent water evaporation. When the measurement began, a controller was opened to heat the CFHS and measure
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temperature characteristic values using the FBG interrogator. The total heating time was 300
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seconds and the power was 5.4 W/m. In this study, Tt is the average temperature during the period of 180 _ 300 s in the heating process. To reduce errors and improve data stability for each soil, the
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average temperature of 20 FBGs was taken as the temperature characteristic value. The NZS-FBG-
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A03 FBG interrogator used here was produced by Suzhou NanZee Sensing Technology Co. Ltd, and its basic parameters are shown in Table 2. After each measurement, the soil sample in PVC tube
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was replaced with another soil sample using the same filling procedure. After all the tests were
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completed, the relationships between soil moisture and temperature characteristic values were fitted piecewise in the form of Equation (4) using the least square method.
4.2 Calibration results and discussions Fig. 4 shows the calibrated relationships between soil moisture and the temperature characteristic values for different soils. It can be seen from Fig. 4 that the Tt ~ curves for medium and fine sands are very close. Therefore, these two soils can be considered as one type (collectively referred to as sand), similar to the findings of Rao & Singh (1999). For the sand, 0 is 0.04 m3/m3,
ACCEPTED MANUSCRIPT and for the clay and silt, 0 is 0.06 m3/m3. All the obtained parameters of Equation (4) are provided in Table 3. As mentioned before, for each soil, the Tt ~ relationship was fitted by a liner function and a logarithmic function for 0 and 0 conditions, respectively. When analyzing the Tt ~ relationship, it is always assumed that ellipsoidal soil particles are
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not in intergranular contact and are continuously covered by water. When 0 , water molecules
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are adsorbed to particle surfaces. With increase in θ, the thickness of water films grows; water
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bridges start to form among adjacent soil particles; and λ begins to increase quickly due to the improved contact among particles (Sayde et al., 2010; Lu et al., 2007). When 0 , most particles
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have already been inter-connected together, and fewer new bridges form with the increase of λ to
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cause low Tt . Sayde et al. (2010) also discovered that the accuracy of measured soil moisture varies approximately in a linear fashion with soil moisture due to the sensitivity reduction.
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To quantitatively describe the sensitivity reduction with moisture increase, Sayde et al. (2010)
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proposed an error function, the estimated error (σθ). It is defined as:
=
T df ( ) d t
(5)
is the local slope of the Tt response at θ. As shown in Fig. 5, for all the four soils, σθ increases
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df ( ) d
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where f (θ) is a function that was fitted between Tt and θ, Tt is the standard deviation of Tt, and
nearly linearly with increase in soil moisture content. This is consistent with the results obtained by Sayde et al. (2010). It can also be inferred that σθ not only depends on soil moisture content, but relates with soil type. A larger the largest
df ( ) d
df ( ) d
corresponds to a higher σθ. Among the four soils tested, silt has
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It needs to be emphasized that the measured soil moisture is an apparent value which denotes the average moisture status of the soil column around CFHS. The radius of this column is the
ACCEPTED MANUSCRIPT maximum heat disturbance distance. So, it is important to select an appropriate size of the PVC tube to pack soil. If the radius is too large, the water in the soil (especially, for the sand) will move quickly to the bottom of the PVC tube that has no influence on the heat transfer from CFHS. This will lower the soil moisture content in the effective range around CFHS to levels below the average
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value of the entire sample. However, with an excessively small radius, the active temperature
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disturbance range will exceed the PVC tube. Consequently, outside air convection will interfere
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with the measurements. Under the consistent power heating condition of this study (5.4 W/m heating 20 minutes), the maximum disturbance radius is about 7.3 cm which was gauged by platinum
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resistance thermometers before the calibration tests. So, a PVC tube with a diameter of 7.5 cm was
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used in this test study. It should be emphasized that different soils may have different maximum or minimum heat transfer radii which should be determined before performing the experiments. The
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significance of the parameters in Table 3 and the feasibility of CFHS in soil moisture monitoring
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had to be verified by validation tests.
5. Validation tests
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5.1 Tests design for validation
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To verify the feasibility of CFHS, a laboratory validation test under normal gravitational conditions and a concentric test under overweight conditions were performed. The validation device which can operate under 1g conditions was similar to that used in the calibration process. It was also a PVC tube with a diameter of 15 cm and a length of 1 m but it was positioned vertically instead of horizontally. The CFHS was also installed in the center of the PVC tube. A transparent water level observation pipe was installed on the surface of the PVC tube, the bottom end of which was connected to the soil sample tested. A plastic hose was connected to the bottom of the PVC tube for
ACCEPTED MANUSCRIPT watering or draining the test soil inside it as shown in Fig. 6. The other devices and parameters used were the same as those used for the calibration tests. The soil used in this test was a mixture of medium and fine sand (with the ratio of 1:1). Its initial dry density was 1.38 g/cm3 with a standard deviation of 0.02 g/cm3.
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The test was divided into two stages. During the first (watering) stage, one end of the plastic
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hose was connected to the PVC tube, and the other end was connected to a water tank with a constant
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water height of 1.5 m (regarded the bottom of PVC tube as the reference plane). The total watering time was 6 h to make the soil sufficiently saturated. During the second (drainage) stage, the plastic
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hose was disconnected from the water tank and turned into a drain hose. In this 24 h stage, the water
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in the soil drained due to gravity. During the entire watering and dewatering process, the soil moisture was measured by CFHS. At 10 minutes, 20 minutes and 2 hours of draining, the soil
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columns were extracted through a sampler (as shown in Fig. 6). The arch sample disconnects the
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soil column from the surrounding soil by a rotating cut. Seven positions were chosen to measure soil moisture using the thermo-gravimetric method. The depths of the measurement locations were
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10 cm, 20 cm, 30 cm, 40 cm, 50 cm, 60 cm and 70 cm. At each location, triplicate samples were
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extracted. Soil columns had to be drawn out within a very short period (< 2 seconds) to reduce water discharge during soil extraction. The distance between collected column and CFHS was 4 cm. After each sample column was dragged out, the hole was refilled with saturated soil. If the hole was too close to CFHS, the refilled saturated soil which has different thermal conductivity with the surrounding soil could affect heat transfer from CFHS; but if it approached the PVC tube, the boundary effect could be significant. So, a medium positon (4 cm from CFHS) was selected in this test. After the test, three soil samples each with a volume of 60 cm3, were extracted from the top
ACCEPTED MANUSCRIPT and bottom respectively, using a circular knife. Centrifuge modeling is an advanced geotechnical test method that can apply overload to smallscale models. The CFHS was used to measure the soil moisture of a model slope in a centrifuge test so as to evaluate its performance. The centrifuge test was implemented in a model box (with a
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dimension of 135 cm × 20 cm ×100 cm). The soil for constructing the model slope was silt, the
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same as that used in the calibration test, and the construction procedure was as described by Zhu et
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al. (2015). Its initial moisture concentration was 0.194 m3/m3, and its dry density was 1.50 g/cm3 with a standard deviation of 0.03 g/cm3. The initial soil moisture concentration was controlled by
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added water during the sample preparation process and set as the average value of the entire soil.
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Dry density at different filled height of soils was measured, using a cutting ring to obtain samples. Fig. 7 shows the positions of extraction of these samples (blue dots).
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Four CFHSs were installed at different positions in the model slope, named CFHS1, CFHS2,
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CFHS3 and CFHS4, with the lengths of 50 cm, 30 cm, 20 cm, and 50 cm, respectively. When the filled soil surface reached the height of the bottom of a CFHS, the CFHS would be fixed at its
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designed position and then, the remaining soil was filled around it. The spacing between adjacent
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FBGs, heating power and heating time were the same as those in the calibration tests. The FBG interrogator, current controller, and other equipment were placed on a platform over the centrifuge facility that would not allow their vibration. The total test duration was 120 minutes which can be divided into the acceleration and deceleration stages. As the centrifuge began to rotate, the model slope was subjected to accelerated overloading, and a maximum acceleration level of 120 g was reached in the test. After reaching this point, the centrifugal machine began to decelerate until the rotation speed dropped to zero. Subject
ACCEPTED MANUSCRIPT to the centrifugal force, the water in the slope migrated in the same direction as the acceleration. During the entire process, the soil moisture contents of the model slope were continuously recorded by the CFHS. During the machine rotation process, it is usually impossible to collect soil samples. When the machine stopped moving, four soil columns were collected to measure their moisture
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profiles using the thermo-gravimetric method. The distance between a CFHS and its adjacent soil
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column was 3 cm. Soil samples at different positions were extracted from the columns from the
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depth of 4 cm to the bottom of a CFHS. The soil columns and sample extraction process were the same as that used in the PVC tube-based validation test. Forty five samples of soil were collected
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from the four columns.
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5.2 Validation test results and discussion
5.2.1 Validation tests under normal gravitational conditions
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For the validation test under normal gravitational conditions CFHS results should be able to
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show soil moisture variation at reasonable levels of accuracy. As shown in Fig. 8, the water table drops quickly during the drainage process but the soil moisture in the unsaturated zone changes only
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slightly. Fig. 8(a) shows the results obtained by CFHS and thermal-gravimetric method at the 10th
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minute, 20th minute and 2nd hour. The results achieved by the two methods have good consistency, with both of them being able to reflect the spatial distribution of water at different times. Below the water table, soil moisture is maintained at the saturated value of 0.38 m3/m3. Considering that the temperature characteristic values collected in the upper 4 cm area are affected by evaporation and air convection, these data were not used when analyzing the distribution of soil moisture here. Fig. 8(b) shows the errors of the CFHS in the static validation test. Considering the data obtained by the thermo-gravimetric method as true values (measured soil moisture), the closer the predicted value
ACCEPTED MANUSCRIPT of CFHS is to the 1:1 line, the higher the accuracy. It can be seen from Fig. 8(b) that the majority of the data are located in the vicinity of 1:1 line, with a R2 of 0.902 and an RMSE of 0.033 m3/m3 which should be acceptable in most cases (Yin et al. 2013; Sayde et al. 2010). The feasibility of using CFHS to measure moving soil moisture needs to be further verified by the centrifugal test.
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5.2.2 Centrifugal test under overweight condition
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Volumetric soil moisture content values measured by the CFHS in the centrifuge test at 0, 40th,
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80th and 120th minute. As shown in Fig. 9, at the zero minute, the soil moisture at each position is the same as the initial moisture (0.194 m3/m3) that was measured before filling. After centrifuging,
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a water transition zone appeared in the soil. It is defined as the zone within which soil moisture
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remains the same as the initial value under overloading conditions. In this zone, the water recharge quantity equals the discharge such that there is a balance. Above the transition zone, water begins
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to move downward under the overweight conditions, and the soil becomes increasingly drier. While
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in the soil under the transition zone, the water begins to accumulate, and the soil moisture increases. This was the observation in our experiments. The transition zones were different for different times
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and locations. Fig. 10 shows the comparison between the results achieved by CFHS and themal-gr
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after the centrifuge test.
The errors of CFHS shown in Fig. 10 increase from 0.033 m3/m3 in normal gravitational test (Fig. 8) to 0.047 m3/m3, R2 decreases from 0.902 to 0.877 in the centrifuge test. Although this regime of results is still acceptable, it is necessary to develop optimization measures (Yin et al. 2013; Sayde et al. 2010) for its improvement. Here, the R2 reduction resulted from two factors. The first one is the dry density difference between calibration and validation tests. Previous experimental results indicate that the dry density versus thermal conductivity relationship is
ACCEPTED MANUSCRIPT significantly affected by soil moisture. Relationships between soil density and thermal conductivity under different moisture content conditions have been established (Cai et al., 2015; Cho et al., 2009; Abu-Hamdeh and Reeder, 2000). For sand that is under the 0.194 m3/m3 moisture content condition, if its density changes from 1.39 g/ cm3 to 1.50 g/cm3, thermal conductivity will
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increase to 0.2 W/mK (Abu-Hamdeh and Reeder, 2000). After substituting 0.2 W/mK into a
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common calibrated relationship between soil moisture and thermal conductivity, it is found that
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0.2 W/mK can cause a soil moisture content deviation of 0.027 m3/m3 (Rao and Singh, 1999).
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The second factor that affects the accuracy of CFHS is soil deformation. As shown in Fig. 10, most data points are located below the 1:1 line which indicates that the recorded temperature
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characteristic values are too small (Wu et al., 2017). According to Equation (2), the Bragg wavelength shifts are not only caused by temperature change but also by compressive deformation.
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This is in agreement with the experimental observations. Therefore, CFHS stiffness should be improved by adding a composite material in the carbon fiber rod, or attaching a steel pipe to it.
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5.3 Uncertainty and applicability analysis
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It has been proven that CFHS is an effective method of measuring soil moisture in the laboratory under normal gravitational and overweight conditions, and the CFHS employed in this method has many advantages: small disturbance, intrinsically safe, small size, lightweight and high sensitivity. The most remarkable advantage of CFHS is that it enables recording of soil moisture in centrifuge tests where other sensors are always difficult to use. In the future, CFHSs could be packed in a probe which could even be a dual or a multi-probe to measure in-situ soil thermal conductivity, specific capacity, diffusion coefficient, soil moisture and seepage velocity.
ACCEPTED MANUSCRIPT However, there are many interference factors that might affect the measurement accuracy of soil moisture. Among them are soil density, salt concentration, particle shape, porosity and organic matter (Côté & Konrad, 2005). Thus for each soil, calibration parameters are needed for introduction into Equation (4) using the control variable method. For a specific soil, the influence is primarily
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caused by soil density. The relationship between soil density and thermal conductivity has been
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investigated in literature (Abuhamdeh and Reeder, 2000). So, if the soil density in practical
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applications is from that obtained from calibration tests, the calibration relations can be used on the basis of the conclusions reached by Abuhamdeh and Reeder (2000).
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6. Conclusions
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Herein, a soil moisture monitoring method that is based on the FBG technology and the carbon fiber heated sensor (CFHS) is presented with tests results. The parameters of the CFHS for sand,
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silt and clay were obtained in laboratory calibration tests. A laboratory validation test under 1g
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normal gravitational conditions and a centrifuge test under overweight conditions were performed to verify the feasibility, effectiveness and reliability of this novel technique. The following
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conclusions are drawn.
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(1) With its advantages of high flexibility and a wide application range, CFHS can be used in laboratory model tests of different scales. The length, sampling interval and spatial resolution of the CFHS are adjustable. (2) A piecewise function can be used to quantify the relationship between the temperature characteristic value measured by CFHS and soil moisture. If the soil moisture is lower than the threshold value, a linear function should be used. Otherwise, a logarithmic function should be used. Based on the Tt ~ 𝜃 relation obtained in calibration tests, the soil moisture distribution in a small
ACCEPTED MANUSCRIPT laboratory model can be determined. (3) The results of validation tests under normal gravitational conditions show that CFHS enables accurate measurement of real-time changes of soil moisture under processes of evaporation, gravity, permeability and capillary rise.
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(4) The centrifugal test results suggest that using the CFHS method can record the water
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distribution changes for the soil in high-speed movement under overweight conditions.
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With a small volume and low disturbance to soil structure, CFHS is suitable for distributed (or quasi-distributed) soil moisture monitoring in laboratory model tests where the existing sensors are
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difficult to use. The successful design of this technique provides a new means for establishing a
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geological disaster early warning system. The soil moisture distribution achieved by CFHS in smallscale model tests provides basic knowledge for studying the mechanism of water migration in soil,
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Acknowledgements
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relationship between water transportation and soil deformation, evolution of landslides, etc.
The authors would like to thank the financial support provided by the State Key Program of National Natural Science of China (Grant No. 41427801, 41230636), Public Science and Technology Research Fund of Ministry of Land and
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Resources (Grant No. 201511055), the Key Laboratory of Earth Fissures Geological Disaster and Ministry of Land and Resources, and Geological Survey of Jiangsu Province (Grant No. 201401). The authors also thank the
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technicians from NanZee Sensing Technology Co., Ltd. during the test, and the scholarship provided by the China Scholarship Council.
References
Abu-Hamdeh, N.H., Reeder, R.C., 2000. Soil thermal conductivity: effects of density, moisture, salt concentration, and organic matter. Soil Science Society of America Journal, 64(4), 1285-1290. doi: 10.2136/sssaj2000.6441285x
Alwis, L., Sun, T., Grattan, K.T.V., 2013. Optical fibre-based sensor technology for humidity and
ACCEPTED MANUSCRIPT moisture measurement: review of recent progress. Measurement, 46(10), 4052-4074. doi: 10.1016/j.measurement.2013.07.030 Berruti, G., Consales, M., Giordano, M., et al., 2013. Radiation hard humidity sensors for high energy physics applications using polyimide-coated fiber Bragg gratings sensors. Sensors and
PT
Actuators B: Chemical, 177, 94-102. doi: 10.1016/j.snb.2012.10.047
RI
Cai, G., Zhang, T., Puppala, A. J., and Liu, S., 2015. Thermal characterization and prediction model
SC
of typical soils in Nanjing area of china. Engineering Geology, 191(9), 23-30. doi: 10.1016/j.enggeo.2015.03.005
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Cao, D.F., Shi, B., Yan, J.F., et al., 2014. Distributed method for measuring moisture content of soils
MA
based on C-DTS. Chinese Journal of Geotechnical Engineering, 36(5), 910-915. doi:10.11779/CJGE201405015 (in Chinese)
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Cao, D., Shi, B., Zhu, H., et al., 2015. A distributed measurement method for in-situ soil moisture
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content by using carbon-fiber heated cable. Journal of Rock Mechanics and Geotechnical Engineering, 7(6), 700-707. doi: 10.1016/j.jrmge.2015.08.003
CE
Carslaw, H.S., Jaeger, J.C., 1959. Conduction of heat in solids. Oxford: Clarendon Press, 1959, 2nd
AC
ed.
Cho, W. J., Kwon, S., and Choi, J. W., 2009. The thermal conductivity for granite with various water contents.
Engineering Geology,
107(3–4), 167-171.
doi:
doi.org/10.1016/j.enggeo.
2009.05.012 Ciocca, F., Lunati, I., Van de Giesen, N., et al., 2012. Heated optical fiber for distributed soilmoisture measurements: A lysimeter experiment. Vadose Zone Journal, 11(4) :1-10. doi:10.2136/vzj2011.0199
ACCEPTED MANUSCRIPT Côté, J., Konrad, J.M., 2005. A generalized thermal conductivity model for soils and construction materials. Canadian Geotechnical Journal, 42(42), 443-458. doi: 10.1139/t04-106 Erdogan, T., 1997. Fiber grating spectra. Journal of Lightwave Technology, 15(8), 1277-1294. doi: 10.1109/50.618322
PT
Florides, G., and Kalogirou, S., 2008. First in situ determination of the thermal performance of a U-
RI
pipe borehole heat exchanger, in Cyprus. Applied Thermal Engineering, 28(2–3), 157-163. doi:
SC
10.1016/j.applthermaleng.2007.03.026
Huang, A.B., Lee, J.T., Ho, Y.T., et al., 2012. Stability monitoring of rainfall-induced deep
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landslides through pore pressure profile measurements. Soils and Foundations, 52, 737–747.
MA
doi: 10.1016/j.sandf.2012.07.013
Huang, X.F., Sheng, D.R., Cen, K.F., & Zhou, H., 2007. Low-cost relative humidity sensor based
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on thermoplastic polyimide-coated fiber Bragg grating. Sensors and Actuators B: Chemical,
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127(2), 518-524. doi: 10.1016/j.snb.2007.05.007 Lu, S., Ren, T.S., Gong, Y.S. Horton, R., 2007. An improved model for predicting soil thermal
CE
conductivity from water content at room temperature, Soil Science Society of America Journal,
AC
71, 8-14. doi: 10.2136/sssaj2006.0041 Rao, M. G., & Singh, D. N, 1999. A generalized relationship to estimate thermal resistivity of soils. Canadian Geotechnical Journal, 36(4), 767-773. doi: 10.1139/t99-037 Sayde, C., Gregory, C., Gil‐Rodriguez, M., et al., 2010. Feasibility of soil moisture monitoring with
heated
fiber
optics.
Water
Resources
Research
46(6),
W06201-8.
doi:
10.1029/2009WR007846 Sayde, C., Buelga, J.B., Rodriguez‐Sinobas, L., et al., 2015. Mapping variability of soil water
ACCEPTED MANUSCRIPT content and flux across 1–1000 m scales using the actively heated fiber optic method. Water Resources Research, 50(9), 7302-7317. doi: 10.1002/2013WR014983 Sourbeer. J,J,, & Loheide, S.P., 2015. Obstacles to long-term soil moisture monitoring with heated distributed
temperature
sensing.
Hydrological
Processes,
30,
1017-1035.
doi:
PT
10.1002/hyp.10615
RI
Striegl, A.M., Loheide, S., 2012. Heated distributed temperature sensing for field scale soil moisture
SC
monitoring. Ground Water, 50(3), 340-347. doi: 10.1111/j.1745-6584.2012.00928.x Tarnawski, V.R. & Wagner, B. 2011. A new computerized approach to estimating the thermal
NU
properties of unfrozen soils, Canadian Geotechnical Journal, 29, 714-720.
MA
Wu, J. H., Shi, B., Cao, D. F., et al., 2017. Model test of soil deformation response to drainingrecharging conditions based on DFOS. Engineering Geology, 226 (30), 107-121, doi:
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10.1016/j.enggeo.2017.04.025
moisture
PT E
Yeo, T.L., Sun, T., & Grattan, K.T.V., 2008. Fibre-optic sensor technologies for humidity and measurement.
Sensors
and
Actuators
A:
Physical,
144(2),
280-295.
CE
doi:10.1016/j.sna.2008.01.017
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Yin, Z., Lei, T., Yan, Q., Chen, Z., & Dong, Y., 2013. A near-infrared reflectance sensor for soil surface moisture measurement. Computers and Electronics in Agriculture, 99, 101-107. doi: 10.1016/j.compag.2013.08.029 Zhu, H.H., Ho, A.N.L., Yin, J.H., et al., 2012. An optical fibre monitoring system for evaluating the performance of a soil nailed slope. Smart Structures and Systems, 9(5), 393-410. Zhu, H.H., Shi, B., Yan, J.F., et al., 2014. Fiber Bragg grating-based performance monitoring of a slope model subjected to seepage. Smart Materials and Structures, 23, 095027.
ACCEPTED MANUSCRIPT Zhu, H.H., Shi, B., and Zhang, C.C., 2017. FBG-based monitoring of geohazards: current status and trends. Sensors, 17, 452. doi: 10.3390/s17030452 Zhu, H. H., Shi, B., Yan, J. F., et al., 2015. Investigation of the evolutionary process of a reinforced model slope using a fiber-optic monitoring network. Engineering Geology, 186, 34-43. doi:
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SC
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doi.org/10.1016/j.enggeo.2014.10.012
ACCEPTED MANUSCRIPT Figure captions Fig. 1 Schematic of the CFHS, (a) internal structure of the CFHS, (b) external structure of the CFHS, and (c) photograph of the CFHS Fig. 2 Laboratory calibration devices, (a) basic configuration of the calibration test, (b) photograph
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of the CFHS installed in the PVC tube, and (c) photograph of the data acquisition system.
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Fig. 3 Particle size distribution of the test soils
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Fig. 4 Relationship between soil moistures and temperature characteristic values Fig. 5 Relationship between calculated error (σθ) and soil moisture content
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Fig. 6 Laboratory validation test device under normal gravitational condition
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Fig. 7 Details of the centrifuge test: (a) sectional profile of the model slope, (b) photograph of the geotechnical centrifuge facility, (c) samplers and sampling method, and (d) photograph of the
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CFHSs installment.
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Fig. 8 Comparison between the results measured using thermo-gravimetric method and CFHS (a) soil moisture profile during the draining process in the validation test under normal
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gravitational test, and (b) results of error analysis.
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Fig. 9 Variation of the soil moisture profiles during the centrifuge test Fig. 10 Results of errors analysis of the CFHS measurements in the centrifuge test
ACCEPTED MANUSCRIPT Table 1 Soil physical and hydraulic properties Soil
Dry bulk density
Standard deviation σd
Sat. Hydr. conductivity
(g/cm3)
(g/cm3)
(m/s)
1.36
0.05
1.23×10-3
0.44
1.39
0.04
8.89×10-4
0.71
0.02
2.85×10-5
0.74
0.06
7.37×10-7
0.66
Medium
Porosity
sand Fine sand Silt
1.45 1.61
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Clay
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Table 2 Basic indexes of NZS-FBG-A03 interrogator Performance parameters
Temperature measure scope (°C)
-40~120
Temperature accuracy (°C)
±0.1
Response time (s)
1~60
Wavelength range (nm)
1527~1568
Demodulation rate (Hz)
1
Wavelength resolution (pm)
1
Dynamic range (dB)
50
Channel number
2
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ACCEPTED MANUSCRIPT Table 3 Calibration results between the temperature characteristic value and soil moisture Linear fit ( 0 )
Soil
Logarithmic fit ( 0 )
b
R2
RMSE
z1
z2
z3
R2
RMSE
Medium sand
-234.5
18.88
0.746
0.006
2.984
1.151
-0.039
0.991
0.023
Find sand
-239.5
19.30
0.814
0.005
3.558
0.992
-0.039
0.982
0.022
Silt
-260.0
21.03
0.846
0.004
0.181
2.058
-0.036
0.982
0.022
Clay
-225.4
24.21
0.997
0.001
-2.460
3.111
-0.047
0.964
0.034
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k
ACCEPTED MANUSCRIPT Highlights
A fiber Bragg grating-based carbon fiber heated sensor (CFHS) for soil moisture monitoring is proposed.
The relationships between soil moisture and thermal response of sand, silt and clay are
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calibrated. The calibrated results were validated under normal gravitational and overweight conditions.
CFHS has the advantages of small sensor size, low disturbance to soil mass, and wide
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adaptability to physical model tests.
Figure 1
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Figure 3
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Figure 9
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Ding-feng Cao, Bin Shi, Hong-hu Zhu, Hilary I. Inyang, Guangqing Wei, Chao-zhe Duan PII: DOI: Reference:
S0013-7952(17)30377-0 doi:10.1016/j.enggeo.2018.05.024 ENGEO 4856
To appear in:
Engineering Geology
Received date: Revised date: Accepted date:
7 March 2017 2 March 2018 25 May 2018
Please cite this article as: Ding-feng Cao, Bin Shi, Hong-hu Zhu, Hilary I. Inyang, Guangqing Wei, Chao-zhe Duan , A soil moisture estimation method using actively heated fiber Bragg grating sensors. Engeo (2017), doi:10.1016/j.enggeo.2018.05.024
This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
ACCEPTED MANUSCRIPT A soil moisture estimation method using actively heated fiber Bragg grating sensors Ding-feng Cao1, 2, Bin Shi1*, Hong-hu Zhu1*, Hilary I. Inyang3, Guang-qing Wei4, Chao-zhe Duan1 1 School 2
of Earth Sciences and Engineering, Nanjing University, Nanjing 210023, China
Department of Civil and Environmental Engineering Department, Engineering College, University of Wisconsin-
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Madison, Madison, WI,53706, USA
Global Education and Infrastructure Services LLC, Charlotte, North Carolina, USA
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Suzhou NanZee Sensing Technology Co. Ltd, Suzhou 215123, China
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Corresponding author1*:Bin Shi, School of Earth Sciences and Engineering, Nanjing University, Nanjing 210023, China Tel :86-025-89680317, Fax: 86-025-83686016, Email: [email protected]
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Corresponding author2*: Hong-hu Zhu, School of Earth Sciences and Engineering, Nanjing University, Nanjing
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210023, China Tel :86-025-89681137, , Email: [email protected]
ACCEPTED MANUSCRIPT Abstract Although many methods of soil moisture measurement exist, there remains a lack of soil moisture sensor with small volume, high precision, excellent real-time performance and distributed monitoring capability. In this paper, a fiber Bragg grating (FBG)-based carbon fiber
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heated sensor (CFHS) that can counter deficiencies in soil moisture movement is proposed. The
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CFHS consists of a carbon fiber rod with a diameter of 5 mm, quasi-distributed FBG sensors on an
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optical fiber, a coating, two binding posts, and two electric cables. Laboratory calibration tests
have been conducted to establish an empirical piece-wise relationship between the temperature
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characteristic value and soil moisture for sand, silt and clay. A laboratory validation test under
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normal gravitational conditions and a centrifuge test under overweight conditions, have been performed to verify the feasibility of this technique for soil moisture monitoring. Test results
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show that the CFHS can (i) accurately record soil moisture under normal gravitational and
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overweight conditions and (ii) track the evolution of capillary zones, and the generation and migration of moisture transition zones under centrifuge acceleration. During a response period
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of 5 minutes, the accuracy is 0.033 m3/m3 under 1g condition, and 0.047 m3/m3 under
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overweight condition. With the advantages of small sensor size, low disturbance of soil mass and wide adaptability in physical model tests, the proposed method can achieve distributed soil moisture measurement at different scales and high efficiency. Keywords: Soil moisture, fiber Bragg grating (FBG), carbon fiber heated sensor (CFHS), fiber optic sensing
ACCEPTED MANUSCRIPT 1 Introduction According to the measurement mode, commonly used soil moisture monitoring methods can be divided into two groups: those for point measurements and those for distributed measurements. The first group includes the thermo-gravimetric method, time domain reflectometry (TDR),
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frequency domain reflectometry (FDR), and capacitance and frequency domain techniques. The
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major distributed techniques are ground penetrating radar (GPR), remote sensing, infrared detector,
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and actively heated fiber optic cable (AHFO) (Cao et al. 2014, 2015; Sourbeer and Loheide 2015; Sayde et al. 2015; Striegl and Loheide 2012; Sayde et al. 2010). Some of these methods such as the
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thermo-gravimetric method, require the destruction of soil structure. TDR and FDR involve probes
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that are too large for laboratory use. The spatial resolution of AHFO is insufficient for small-scale model tests. GPR, infrared ray and remote sensing have low measurement accuracy and can hardly
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detect soil moisture profiles with good reliability. Therefore, it is necessary to develop an automatic,
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compact-size, and high-accuracy monitoring technique for in-situ soil moisture. In recent years, the fiber Bragg grating (FBG) sensor has been widely used for monitoring
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geotechnical structures due to the advantages of small size, anti-electromagnetic interference,
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corrosion resistance and high sensitivity (Huang et al. 2012; Zhu et al. 2012, 2014, 2017). Some scholars have successfully employed it to develop soil humidity sensors (Alwis et al. 2013, Yeo et al. 2008). Based on the sensing mechanism, FBG soil moisture sensors can be divided into two categories. The first one focuses on measurement of the strain induced by the changes in soil moisture. The Bragg gratings of these sensors are coated with water-sensitive materials such as Polyimide (PI). These materials swell after absorbing water and shrink upon dehydration. Soil moisture can then be determined from its correlation relationship with the strain-induced Bragg
ACCEPTED MANUSCRIPT wavelength measurement. (Alwis et al. 2013; Berruti et al. 2013; Yeo et al. 2008; Huang et al. 2007). The second type of FBG soil moisture sensor utilizes the influence of water molecules on the refractive index of Bragg gratings. In these sensors, photosensitive materials (i.e., cobalt chloride, cobalt oxide and electro-chromic polymers) are added to the Bragg gratings or on their surface. Soil
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moisture can be determined by use of the relationship between water absorption amount and the
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incident light spectrum (Yeo et al. 2008). However, the use of both kinds of sensors for real-time
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soil moisture monitoring is difficult for the following reasons: firstly, the water-sensitive and photosensitive materials have time lags, and these materials are difficult to dewater synchronously
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with soil, especially, during the drainage process, and secondly, although both kinds of sensors
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require full contact with the surrounding soil to keep sufficient exposure of the added sensitive materials to the soil, the sensors themselves are too fragile to be directly placed in the soil. In
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addition, water-sensitive materials are also very sensitive to ambient temperature—expanding with
(Yeo et al. 2008).
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heat and contracting with cold which seriously affects the measurement accuracy of soil moisture
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The design of an FBG-based carbon fiber heated sensor (CFHS) for monitoring in-situ soil
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moisture profiles is analyzed and presented in this paper. Laboratory calibration tests were performed to acquire data on the basic parameters of the CFHS. A laboratory validation test under
normal gravitational conditions and a centrifuge test under overweight conditions, were performed to verify the feasibility of using CFHS in soil moisture monitoring.
2 Theory 2.1 Basic principle The principle of CFHS is based on observed correlation between the thermal responses of the
ACCEPTED MANUSCRIPT heated sensor and the moisture content of the surrounding soil. When measurement starts, the CFHS is heated under a constant current, and the temperature variation of the CFHS is recorded by an FBG interrogator during heating. Based on a series of calibration tests, a temperature characteristic value (Tt) can then be used to calculate the soil moisture (θ) (Cao et al. 2014, 2015).
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The FBG quantifies temperature through measurement of the thermal sensitivity of the
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backscattered Bragg wavelength drift. When a beam of incident light is emitted into the optical fiber,
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some back-reflected light is produced (Bragg light) due to the filter of the Bragg gratings. The Bragg wavelength of an FBG is given by (Huang et al. 2007; Erdogan 1997):
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B 2neff
(1)
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where neff is the effective refractive index (dimensionless), is the spatial period of the FBG (nm), and B is the Bragg wavelength (nm). The drift of B is determined by strain and
where
(1 Pe ) z ( F F )T
(2)
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B
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temperature of the FBG (Huang et al. 2007):
represents the drift of B (nm), Pe is the effective elasto-optical coefficient
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(dimensionless) of the FBG, z is the axial strain (dimensionless), F and F represent the
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coefficient of thermal expansion (1/°C) and thermal-optical coefficient (1/°C) of the single mode fiber, respectively, and T is the temperature change (°C).
2.2 Soil moisture calculation For the purpose of theoretical analysis, a homogeneous and isotropic soil is considered. For a line heat source such as CFHS buried in a boundless soil medium, the temperature T measured by the FBG sensor, satisfies the following relationship (Sayde et al. 2010; Florides and Kalogirou 2008; Carslaw and Jaeger 1959):
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q ' 4 t ln T0 4π r 2
(3)
where q ' is the heat power per unit time per unit length (J m-1 s-1), r is the distance from the line source (m), t is the heating time (s), 𝜆 is the thermal conductivity (W m-1 °C-1), k is the thermal diffusivity (m2 s-1), is Euler’s constant (= 0.5772), and T0 is the initial ambient temperature
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(C°).
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Literature searches indicate that the theoretical relationship between soil thermal conductivity
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and soil moisture has not been established so far, and there are only some empirical and semiempirical models (Ciocca et al. 2012). The most widely used piece-wise function model was
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adopted here. When the soil moisture is lower than the threshold level, a linear function is used, and
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if it is higher, the relationship follows a logarithmic function:
z1 z2 ln( z3 ) 0 Tt 0 k b
(4)
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where Tt is the temperature characteristic value (°C), which is defined as the average temperature during the heating period (min), 0 is the threshold moisture (m3/m3) (Cao et al. 2014, 2015). 0
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is related to soil composition and grain size which can be obtained by laboratory tests (m3/m3). z1 ,
z 2 , z3 , k and b are constants that are dependent on the soil structure and the soil types, because
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the distances among solid particles are dependent on soil structure and type. The influence of soil moisture on thermal conductivity is accounted for the saturation of water bridges that is determined by distances among solid particles. To get these values, calibration tests must be performed and the actual soil moisture contents of samples must be measured by the thermo-gravimetric method. Thereafter, the least square method can be used to relate Tt to .
3. CFHS design for soil moisture monitoring To overcome the shortcomings of existing FBG moisture sensors, a new sensor (CFHS) was
ACCEPTED MANUSCRIPT designed, as shown in Fig. 1. The CFHS consists of a carbon fiber rod with a diameter of 5 mm, quasi-distributed FBG sensors on an optical fiber, a coating, two binding posts, a direct current (DC) power supply or current converter that can transform alternating current (AC) into DC, and two electric cables. The
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length of the rod is adjustable according to actual needs. The ends of the CFHS and electrodes of
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power supply are connected by electric cables. One cable is used to connect the positive electrode
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and the other one connects with the negative electrode. Here, DC is suggested for use because when compared with AC, DC is more stable and adjustable, especially if the length of CFHS is less than
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1 m.
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The carbon fiber rod is not only as a skeleton of the CFHS, but also conducts the electric current. The resistance of the carbon fiber rod is 26.2 Ω/m, and the heating power per unit length is a constant.
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The FBGs are glued onto the surface of the carbon fiber rod with epoxy resin. The spacing between
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adjacent FBGs, D, can be set according to specific monitoring requirements. After the installment of the FBGs, it is necessary to apply a coating to protect the optical fiber from destruction and power
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leakage. Finally, a binding post is installed at each end of the carbon fiber rod and is connected to
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the power supply by electric cables. The parameters of the CFHS in different soils were obtained in the laboratory calibration tests.
4. Laboratory calibration tests 4.1 Experimental Design To establish the relationship between soil moisture and temperature characteristic values, some calibration tests were performed. These tests were performed in a polyvinyl chloride (PVC) tube which was used to repack soil samples, as shown in Fig. 2. The PVC tube has a length of 1 m and a
ACCEPTED MANUSCRIPT diameter of 15 cm. The upper surface of the tube was cut out to create a groove so as to facilitate the observation of the wetting front, as shown in Fig. 2(b). The removed plate was taken as a cover, which was installed on the PVC tube after soil samples put into it. Four types of soils (medium sand, fine sand, silt and clay) were chosen. Their grain size distributions are shown in Fig. 3.
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Prior to the tests, all the soil samples were dried in an oven for 24 _ 48 hours at the temperature
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of 105 °C to make sure that they dried completely ( 0 ). If the relative soil weight change was
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less than 0.2 % in this period, the soil was considered to be adequately dry. The dried silt and clay samples were passed through a sieve with 2–mm–diameter holes. The clay samples were divided
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into 15 groups, and the other soils were divided into 12 groups. A different quantity of water was
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added to each group’s samples. The required amount of water was calculated according to the dry density of soil and gauged by a graduated cylinder. The dry density was controlled by compaction
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force, which is dependent on soil moisture content. The smaller the difference between the actual
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soil moisture of prepared sample and its optimum moisture content, the less required compaction force. Here, the volume of the test chamber was held constant and completely filled during each test.
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In Table 1, the physical and hydraulic characteristics of the tested soils are provided. During the soil
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samples preparing process, water was added to silt and clay by spraying and stirring soil. All these soil samples were kept for at least 48 hours to ensure uniformity in moisture distribution. For sands with a moisture content of less than 0.15 m3/m3, the sample preparation process was the same as for silt and clay. If it exceeded 0.15 m3/m3, the soil samples with a moisture content of 0.15 m3/m3 was added into the PVC tube first, and the extra water was sprinkled on the surface of the soil samples in the PVC tube. Then, the PVC tube was kept standing for 5 hours to enable the sprinkled water to infiltrate into the soil uniformly (here it is an approximate method, the limitation of which will be
ACCEPTED MANUSCRIPT discussed in Section 5.3). All the soil samples were filled and compacted layer by layer, into the PVC tube using a rubber mallet. When half of the PVC tube was filled with soil, a CFHS was inserted into the middle of the tube, and the other half of the volume was filled as well. The bulk of initially added unconsolidated
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soils is always larger than the quantity in the PVC tube. So, it was necessary to pack the soil volume
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to the same level as that of the PVC tube. After all the soil was filled into the PVC tube, the cover
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(PVC plate) was sealed on the PVC tube with duct tape to prevent water evaporation. When the measurement began, a controller was opened to heat the CFHS and measure
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temperature characteristic values using the FBG interrogator. The total heating time was 300
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seconds and the power was 5.4 W/m. In this study, Tt is the average temperature during the period of 180 _ 300 s in the heating process. To reduce errors and improve data stability for each soil, the
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average temperature of 20 FBGs was taken as the temperature characteristic value. The NZS-FBG-
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A03 FBG interrogator used here was produced by Suzhou NanZee Sensing Technology Co. Ltd, and its basic parameters are shown in Table 2. After each measurement, the soil sample in PVC tube
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was replaced with another soil sample using the same filling procedure. After all the tests were
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completed, the relationships between soil moisture and temperature characteristic values were fitted piecewise in the form of Equation (4) using the least square method.
4.2 Calibration results and discussions Fig. 4 shows the calibrated relationships between soil moisture and the temperature characteristic values for different soils. It can be seen from Fig. 4 that the Tt ~ curves for medium and fine sands are very close. Therefore, these two soils can be considered as one type (collectively referred to as sand), similar to the findings of Rao & Singh (1999). For the sand, 0 is 0.04 m3/m3,
ACCEPTED MANUSCRIPT and for the clay and silt, 0 is 0.06 m3/m3. All the obtained parameters of Equation (4) are provided in Table 3. As mentioned before, for each soil, the Tt ~ relationship was fitted by a liner function and a logarithmic function for 0 and 0 conditions, respectively. When analyzing the Tt ~ relationship, it is always assumed that ellipsoidal soil particles are
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not in intergranular contact and are continuously covered by water. When 0 , water molecules
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are adsorbed to particle surfaces. With increase in θ, the thickness of water films grows; water
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bridges start to form among adjacent soil particles; and λ begins to increase quickly due to the improved contact among particles (Sayde et al., 2010; Lu et al., 2007). When 0 , most particles
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have already been inter-connected together, and fewer new bridges form with the increase of λ to
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cause low Tt . Sayde et al. (2010) also discovered that the accuracy of measured soil moisture varies approximately in a linear fashion with soil moisture due to the sensitivity reduction.
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To quantitatively describe the sensitivity reduction with moisture increase, Sayde et al. (2010)
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proposed an error function, the estimated error (σθ). It is defined as:
=
T df ( ) d t
(5)
is the local slope of the Tt response at θ. As shown in Fig. 5, for all the four soils, σθ increases
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df ( ) d
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where f (θ) is a function that was fitted between Tt and θ, Tt is the standard deviation of Tt, and
nearly linearly with increase in soil moisture content. This is consistent with the results obtained by Sayde et al. (2010). It can also be inferred that σθ not only depends on soil moisture content, but relates with soil type. A larger the largest
df ( ) d
df ( ) d
corresponds to a higher σθ. Among the four soils tested, silt has
.
It needs to be emphasized that the measured soil moisture is an apparent value which denotes the average moisture status of the soil column around CFHS. The radius of this column is the
ACCEPTED MANUSCRIPT maximum heat disturbance distance. So, it is important to select an appropriate size of the PVC tube to pack soil. If the radius is too large, the water in the soil (especially, for the sand) will move quickly to the bottom of the PVC tube that has no influence on the heat transfer from CFHS. This will lower the soil moisture content in the effective range around CFHS to levels below the average
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value of the entire sample. However, with an excessively small radius, the active temperature
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disturbance range will exceed the PVC tube. Consequently, outside air convection will interfere
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with the measurements. Under the consistent power heating condition of this study (5.4 W/m heating 20 minutes), the maximum disturbance radius is about 7.3 cm which was gauged by platinum
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resistance thermometers before the calibration tests. So, a PVC tube with a diameter of 7.5 cm was
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used in this test study. It should be emphasized that different soils may have different maximum or minimum heat transfer radii which should be determined before performing the experiments. The
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significance of the parameters in Table 3 and the feasibility of CFHS in soil moisture monitoring
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had to be verified by validation tests.
5. Validation tests
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5.1 Tests design for validation
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To verify the feasibility of CFHS, a laboratory validation test under normal gravitational conditions and a concentric test under overweight conditions were performed. The validation device which can operate under 1g conditions was similar to that used in the calibration process. It was also a PVC tube with a diameter of 15 cm and a length of 1 m but it was positioned vertically instead of horizontally. The CFHS was also installed in the center of the PVC tube. A transparent water level observation pipe was installed on the surface of the PVC tube, the bottom end of which was connected to the soil sample tested. A plastic hose was connected to the bottom of the PVC tube for
ACCEPTED MANUSCRIPT watering or draining the test soil inside it as shown in Fig. 6. The other devices and parameters used were the same as those used for the calibration tests. The soil used in this test was a mixture of medium and fine sand (with the ratio of 1:1). Its initial dry density was 1.38 g/cm3 with a standard deviation of 0.02 g/cm3.
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The test was divided into two stages. During the first (watering) stage, one end of the plastic
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hose was connected to the PVC tube, and the other end was connected to a water tank with a constant
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water height of 1.5 m (regarded the bottom of PVC tube as the reference plane). The total watering time was 6 h to make the soil sufficiently saturated. During the second (drainage) stage, the plastic
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hose was disconnected from the water tank and turned into a drain hose. In this 24 h stage, the water
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in the soil drained due to gravity. During the entire watering and dewatering process, the soil moisture was measured by CFHS. At 10 minutes, 20 minutes and 2 hours of draining, the soil
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columns were extracted through a sampler (as shown in Fig. 6). The arch sample disconnects the
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soil column from the surrounding soil by a rotating cut. Seven positions were chosen to measure soil moisture using the thermo-gravimetric method. The depths of the measurement locations were
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10 cm, 20 cm, 30 cm, 40 cm, 50 cm, 60 cm and 70 cm. At each location, triplicate samples were
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extracted. Soil columns had to be drawn out within a very short period (< 2 seconds) to reduce water discharge during soil extraction. The distance between collected column and CFHS was 4 cm. After each sample column was dragged out, the hole was refilled with saturated soil. If the hole was too close to CFHS, the refilled saturated soil which has different thermal conductivity with the surrounding soil could affect heat transfer from CFHS; but if it approached the PVC tube, the boundary effect could be significant. So, a medium positon (4 cm from CFHS) was selected in this test. After the test, three soil samples each with a volume of 60 cm3, were extracted from the top
ACCEPTED MANUSCRIPT and bottom respectively, using a circular knife. Centrifuge modeling is an advanced geotechnical test method that can apply overload to smallscale models. The CFHS was used to measure the soil moisture of a model slope in a centrifuge test so as to evaluate its performance. The centrifuge test was implemented in a model box (with a
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dimension of 135 cm × 20 cm ×100 cm). The soil for constructing the model slope was silt, the
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same as that used in the calibration test, and the construction procedure was as described by Zhu et
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al. (2015). Its initial moisture concentration was 0.194 m3/m3, and its dry density was 1.50 g/cm3 with a standard deviation of 0.03 g/cm3. The initial soil moisture concentration was controlled by
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added water during the sample preparation process and set as the average value of the entire soil.
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Dry density at different filled height of soils was measured, using a cutting ring to obtain samples. Fig. 7 shows the positions of extraction of these samples (blue dots).
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Four CFHSs were installed at different positions in the model slope, named CFHS1, CFHS2,
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CFHS3 and CFHS4, with the lengths of 50 cm, 30 cm, 20 cm, and 50 cm, respectively. When the filled soil surface reached the height of the bottom of a CFHS, the CFHS would be fixed at its
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designed position and then, the remaining soil was filled around it. The spacing between adjacent
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FBGs, heating power and heating time were the same as those in the calibration tests. The FBG interrogator, current controller, and other equipment were placed on a platform over the centrifuge facility that would not allow their vibration. The total test duration was 120 minutes which can be divided into the acceleration and deceleration stages. As the centrifuge began to rotate, the model slope was subjected to accelerated overloading, and a maximum acceleration level of 120 g was reached in the test. After reaching this point, the centrifugal machine began to decelerate until the rotation speed dropped to zero. Subject
ACCEPTED MANUSCRIPT to the centrifugal force, the water in the slope migrated in the same direction as the acceleration. During the entire process, the soil moisture contents of the model slope were continuously recorded by the CFHS. During the machine rotation process, it is usually impossible to collect soil samples. When the machine stopped moving, four soil columns were collected to measure their moisture
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profiles using the thermo-gravimetric method. The distance between a CFHS and its adjacent soil
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column was 3 cm. Soil samples at different positions were extracted from the columns from the
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depth of 4 cm to the bottom of a CFHS. The soil columns and sample extraction process were the same as that used in the PVC tube-based validation test. Forty five samples of soil were collected
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from the four columns.
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5.2 Validation test results and discussion
5.2.1 Validation tests under normal gravitational conditions
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For the validation test under normal gravitational conditions CFHS results should be able to
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show soil moisture variation at reasonable levels of accuracy. As shown in Fig. 8, the water table drops quickly during the drainage process but the soil moisture in the unsaturated zone changes only
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slightly. Fig. 8(a) shows the results obtained by CFHS and thermal-gravimetric method at the 10th
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minute, 20th minute and 2nd hour. The results achieved by the two methods have good consistency, with both of them being able to reflect the spatial distribution of water at different times. Below the water table, soil moisture is maintained at the saturated value of 0.38 m3/m3. Considering that the temperature characteristic values collected in the upper 4 cm area are affected by evaporation and air convection, these data were not used when analyzing the distribution of soil moisture here. Fig. 8(b) shows the errors of the CFHS in the static validation test. Considering the data obtained by the thermo-gravimetric method as true values (measured soil moisture), the closer the predicted value
ACCEPTED MANUSCRIPT of CFHS is to the 1:1 line, the higher the accuracy. It can be seen from Fig. 8(b) that the majority of the data are located in the vicinity of 1:1 line, with a R2 of 0.902 and an RMSE of 0.033 m3/m3 which should be acceptable in most cases (Yin et al. 2013; Sayde et al. 2010). The feasibility of using CFHS to measure moving soil moisture needs to be further verified by the centrifugal test.
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5.2.2 Centrifugal test under overweight condition
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Volumetric soil moisture content values measured by the CFHS in the centrifuge test at 0, 40th,
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80th and 120th minute. As shown in Fig. 9, at the zero minute, the soil moisture at each position is the same as the initial moisture (0.194 m3/m3) that was measured before filling. After centrifuging,
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a water transition zone appeared in the soil. It is defined as the zone within which soil moisture
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remains the same as the initial value under overloading conditions. In this zone, the water recharge quantity equals the discharge such that there is a balance. Above the transition zone, water begins
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to move downward under the overweight conditions, and the soil becomes increasingly drier. While
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in the soil under the transition zone, the water begins to accumulate, and the soil moisture increases. This was the observation in our experiments. The transition zones were different for different times
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and locations. Fig. 10 shows the comparison between the results achieved by CFHS and themal-gr
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after the centrifuge test.
The errors of CFHS shown in Fig. 10 increase from 0.033 m3/m3 in normal gravitational test (Fig. 8) to 0.047 m3/m3, R2 decreases from 0.902 to 0.877 in the centrifuge test. Although this regime of results is still acceptable, it is necessary to develop optimization measures (Yin et al. 2013; Sayde et al. 2010) for its improvement. Here, the R2 reduction resulted from two factors. The first one is the dry density difference between calibration and validation tests. Previous experimental results indicate that the dry density versus thermal conductivity relationship is
ACCEPTED MANUSCRIPT significantly affected by soil moisture. Relationships between soil density and thermal conductivity under different moisture content conditions have been established (Cai et al., 2015; Cho et al., 2009; Abu-Hamdeh and Reeder, 2000). For sand that is under the 0.194 m3/m3 moisture content condition, if its density changes from 1.39 g/ cm3 to 1.50 g/cm3, thermal conductivity will
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increase to 0.2 W/mK (Abu-Hamdeh and Reeder, 2000). After substituting 0.2 W/mK into a
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common calibrated relationship between soil moisture and thermal conductivity, it is found that
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0.2 W/mK can cause a soil moisture content deviation of 0.027 m3/m3 (Rao and Singh, 1999).
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The second factor that affects the accuracy of CFHS is soil deformation. As shown in Fig. 10, most data points are located below the 1:1 line which indicates that the recorded temperature
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characteristic values are too small (Wu et al., 2017). According to Equation (2), the Bragg wavelength shifts are not only caused by temperature change but also by compressive deformation.
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This is in agreement with the experimental observations. Therefore, CFHS stiffness should be improved by adding a composite material in the carbon fiber rod, or attaching a steel pipe to it.
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5.3 Uncertainty and applicability analysis
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It has been proven that CFHS is an effective method of measuring soil moisture in the laboratory under normal gravitational and overweight conditions, and the CFHS employed in this method has many advantages: small disturbance, intrinsically safe, small size, lightweight and high sensitivity. The most remarkable advantage of CFHS is that it enables recording of soil moisture in centrifuge tests where other sensors are always difficult to use. In the future, CFHSs could be packed in a probe which could even be a dual or a multi-probe to measure in-situ soil thermal conductivity, specific capacity, diffusion coefficient, soil moisture and seepage velocity.
ACCEPTED MANUSCRIPT However, there are many interference factors that might affect the measurement accuracy of soil moisture. Among them are soil density, salt concentration, particle shape, porosity and organic matter (Côté & Konrad, 2005). Thus for each soil, calibration parameters are needed for introduction into Equation (4) using the control variable method. For a specific soil, the influence is primarily
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caused by soil density. The relationship between soil density and thermal conductivity has been
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investigated in literature (Abuhamdeh and Reeder, 2000). So, if the soil density in practical
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applications is from that obtained from calibration tests, the calibration relations can be used on the basis of the conclusions reached by Abuhamdeh and Reeder (2000).
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6. Conclusions
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Herein, a soil moisture monitoring method that is based on the FBG technology and the carbon fiber heated sensor (CFHS) is presented with tests results. The parameters of the CFHS for sand,
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silt and clay were obtained in laboratory calibration tests. A laboratory validation test under 1g
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normal gravitational conditions and a centrifuge test under overweight conditions were performed to verify the feasibility, effectiveness and reliability of this novel technique. The following
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conclusions are drawn.
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(1) With its advantages of high flexibility and a wide application range, CFHS can be used in laboratory model tests of different scales. The length, sampling interval and spatial resolution of the CFHS are adjustable. (2) A piecewise function can be used to quantify the relationship between the temperature characteristic value measured by CFHS and soil moisture. If the soil moisture is lower than the threshold value, a linear function should be used. Otherwise, a logarithmic function should be used. Based on the Tt ~ 𝜃 relation obtained in calibration tests, the soil moisture distribution in a small
ACCEPTED MANUSCRIPT laboratory model can be determined. (3) The results of validation tests under normal gravitational conditions show that CFHS enables accurate measurement of real-time changes of soil moisture under processes of evaporation, gravity, permeability and capillary rise.
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(4) The centrifugal test results suggest that using the CFHS method can record the water
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distribution changes for the soil in high-speed movement under overweight conditions.
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With a small volume and low disturbance to soil structure, CFHS is suitable for distributed (or quasi-distributed) soil moisture monitoring in laboratory model tests where the existing sensors are
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difficult to use. The successful design of this technique provides a new means for establishing a
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geological disaster early warning system. The soil moisture distribution achieved by CFHS in smallscale model tests provides basic knowledge for studying the mechanism of water migration in soil,
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Acknowledgements
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relationship between water transportation and soil deformation, evolution of landslides, etc.
The authors would like to thank the financial support provided by the State Key Program of National Natural Science of China (Grant No. 41427801, 41230636), Public Science and Technology Research Fund of Ministry of Land and
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Resources (Grant No. 201511055), the Key Laboratory of Earth Fissures Geological Disaster and Ministry of Land and Resources, and Geological Survey of Jiangsu Province (Grant No. 201401). The authors also thank the
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technicians from NanZee Sensing Technology Co., Ltd. during the test, and the scholarship provided by the China Scholarship Council.
References
Abu-Hamdeh, N.H., Reeder, R.C., 2000. Soil thermal conductivity: effects of density, moisture, salt concentration, and organic matter. Soil Science Society of America Journal, 64(4), 1285-1290. doi: 10.2136/sssaj2000.6441285x
Alwis, L., Sun, T., Grattan, K.T.V., 2013. Optical fibre-based sensor technology for humidity and
ACCEPTED MANUSCRIPT moisture measurement: review of recent progress. Measurement, 46(10), 4052-4074. doi: 10.1016/j.measurement.2013.07.030 Berruti, G., Consales, M., Giordano, M., et al., 2013. Radiation hard humidity sensors for high energy physics applications using polyimide-coated fiber Bragg gratings sensors. Sensors and
PT
Actuators B: Chemical, 177, 94-102. doi: 10.1016/j.snb.2012.10.047
RI
Cai, G., Zhang, T., Puppala, A. J., and Liu, S., 2015. Thermal characterization and prediction model
SC
of typical soils in Nanjing area of china. Engineering Geology, 191(9), 23-30. doi: 10.1016/j.enggeo.2015.03.005
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Cao, D.F., Shi, B., Yan, J.F., et al., 2014. Distributed method for measuring moisture content of soils
MA
based on C-DTS. Chinese Journal of Geotechnical Engineering, 36(5), 910-915. doi:10.11779/CJGE201405015 (in Chinese)
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Cao, D., Shi, B., Zhu, H., et al., 2015. A distributed measurement method for in-situ soil moisture
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content by using carbon-fiber heated cable. Journal of Rock Mechanics and Geotechnical Engineering, 7(6), 700-707. doi: 10.1016/j.jrmge.2015.08.003
CE
Carslaw, H.S., Jaeger, J.C., 1959. Conduction of heat in solids. Oxford: Clarendon Press, 1959, 2nd
AC
ed.
Cho, W. J., Kwon, S., and Choi, J. W., 2009. The thermal conductivity for granite with various water contents.
Engineering Geology,
107(3–4), 167-171.
doi:
doi.org/10.1016/j.enggeo.
2009.05.012 Ciocca, F., Lunati, I., Van de Giesen, N., et al., 2012. Heated optical fiber for distributed soilmoisture measurements: A lysimeter experiment. Vadose Zone Journal, 11(4) :1-10. doi:10.2136/vzj2011.0199
ACCEPTED MANUSCRIPT Côté, J., Konrad, J.M., 2005. A generalized thermal conductivity model for soils and construction materials. Canadian Geotechnical Journal, 42(42), 443-458. doi: 10.1139/t04-106 Erdogan, T., 1997. Fiber grating spectra. Journal of Lightwave Technology, 15(8), 1277-1294. doi: 10.1109/50.618322
PT
Florides, G., and Kalogirou, S., 2008. First in situ determination of the thermal performance of a U-
RI
pipe borehole heat exchanger, in Cyprus. Applied Thermal Engineering, 28(2–3), 157-163. doi:
SC
10.1016/j.applthermaleng.2007.03.026
Huang, A.B., Lee, J.T., Ho, Y.T., et al., 2012. Stability monitoring of rainfall-induced deep
NU
landslides through pore pressure profile measurements. Soils and Foundations, 52, 737–747.
MA
doi: 10.1016/j.sandf.2012.07.013
Huang, X.F., Sheng, D.R., Cen, K.F., & Zhou, H., 2007. Low-cost relative humidity sensor based
D
on thermoplastic polyimide-coated fiber Bragg grating. Sensors and Actuators B: Chemical,
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127(2), 518-524. doi: 10.1016/j.snb.2007.05.007 Lu, S., Ren, T.S., Gong, Y.S. Horton, R., 2007. An improved model for predicting soil thermal
CE
conductivity from water content at room temperature, Soil Science Society of America Journal,
AC
71, 8-14. doi: 10.2136/sssaj2006.0041 Rao, M. G., & Singh, D. N, 1999. A generalized relationship to estimate thermal resistivity of soils. Canadian Geotechnical Journal, 36(4), 767-773. doi: 10.1139/t99-037 Sayde, C., Gregory, C., Gil‐Rodriguez, M., et al., 2010. Feasibility of soil moisture monitoring with
heated
fiber
optics.
Water
Resources
Research
46(6),
W06201-8.
doi:
10.1029/2009WR007846 Sayde, C., Buelga, J.B., Rodriguez‐Sinobas, L., et al., 2015. Mapping variability of soil water
ACCEPTED MANUSCRIPT content and flux across 1–1000 m scales using the actively heated fiber optic method. Water Resources Research, 50(9), 7302-7317. doi: 10.1002/2013WR014983 Sourbeer. J,J,, & Loheide, S.P., 2015. Obstacles to long-term soil moisture monitoring with heated distributed
temperature
sensing.
Hydrological
Processes,
30,
1017-1035.
doi:
PT
10.1002/hyp.10615
RI
Striegl, A.M., Loheide, S., 2012. Heated distributed temperature sensing for field scale soil moisture
SC
monitoring. Ground Water, 50(3), 340-347. doi: 10.1111/j.1745-6584.2012.00928.x Tarnawski, V.R. & Wagner, B. 2011. A new computerized approach to estimating the thermal
NU
properties of unfrozen soils, Canadian Geotechnical Journal, 29, 714-720.
MA
Wu, J. H., Shi, B., Cao, D. F., et al., 2017. Model test of soil deformation response to drainingrecharging conditions based on DFOS. Engineering Geology, 226 (30), 107-121, doi:
D
10.1016/j.enggeo.2017.04.025
moisture
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Yeo, T.L., Sun, T., & Grattan, K.T.V., 2008. Fibre-optic sensor technologies for humidity and measurement.
Sensors
and
Actuators
A:
Physical,
144(2),
280-295.
CE
doi:10.1016/j.sna.2008.01.017
AC
Yin, Z., Lei, T., Yan, Q., Chen, Z., & Dong, Y., 2013. A near-infrared reflectance sensor for soil surface moisture measurement. Computers and Electronics in Agriculture, 99, 101-107. doi: 10.1016/j.compag.2013.08.029 Zhu, H.H., Ho, A.N.L., Yin, J.H., et al., 2012. An optical fibre monitoring system for evaluating the performance of a soil nailed slope. Smart Structures and Systems, 9(5), 393-410. Zhu, H.H., Shi, B., Yan, J.F., et al., 2014. Fiber Bragg grating-based performance monitoring of a slope model subjected to seepage. Smart Materials and Structures, 23, 095027.
ACCEPTED MANUSCRIPT Zhu, H.H., Shi, B., and Zhang, C.C., 2017. FBG-based monitoring of geohazards: current status and trends. Sensors, 17, 452. doi: 10.3390/s17030452 Zhu, H. H., Shi, B., Yan, J. F., et al., 2015. Investigation of the evolutionary process of a reinforced model slope using a fiber-optic monitoring network. Engineering Geology, 186, 34-43. doi:
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NU
SC
RI
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doi.org/10.1016/j.enggeo.2014.10.012
ACCEPTED MANUSCRIPT Figure captions Fig. 1 Schematic of the CFHS, (a) internal structure of the CFHS, (b) external structure of the CFHS, and (c) photograph of the CFHS Fig. 2 Laboratory calibration devices, (a) basic configuration of the calibration test, (b) photograph
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of the CFHS installed in the PVC tube, and (c) photograph of the data acquisition system.
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Fig. 3 Particle size distribution of the test soils
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Fig. 4 Relationship between soil moistures and temperature characteristic values Fig. 5 Relationship between calculated error (σθ) and soil moisture content
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Fig. 6 Laboratory validation test device under normal gravitational condition
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Fig. 7 Details of the centrifuge test: (a) sectional profile of the model slope, (b) photograph of the geotechnical centrifuge facility, (c) samplers and sampling method, and (d) photograph of the
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CFHSs installment.
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Fig. 8 Comparison between the results measured using thermo-gravimetric method and CFHS (a) soil moisture profile during the draining process in the validation test under normal
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gravitational test, and (b) results of error analysis.
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Fig. 9 Variation of the soil moisture profiles during the centrifuge test Fig. 10 Results of errors analysis of the CFHS measurements in the centrifuge test
ACCEPTED MANUSCRIPT Table 1 Soil physical and hydraulic properties Soil
Dry bulk density
Standard deviation σd
Sat. Hydr. conductivity
(g/cm3)
(g/cm3)
(m/s)
1.36
0.05
1.23×10-3
0.44
1.39
0.04
8.89×10-4
0.71
0.02
2.85×10-5
0.74
0.06
7.37×10-7
0.66
Medium
Porosity
sand Fine sand Silt
1.45 1.61
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Clay
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Table 2 Basic indexes of NZS-FBG-A03 interrogator Performance parameters
Temperature measure scope (°C)
-40~120
Temperature accuracy (°C)
±0.1
Response time (s)
1~60
Wavelength range (nm)
1527~1568
Demodulation rate (Hz)
1
Wavelength resolution (pm)
1
Dynamic range (dB)
50
Channel number
2
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ACCEPTED MANUSCRIPT Table 3 Calibration results between the temperature characteristic value and soil moisture Linear fit ( 0 )
Soil
Logarithmic fit ( 0 )
b
R2
RMSE
z1
z2
z3
R2
RMSE
Medium sand
-234.5
18.88
0.746
0.006
2.984
1.151
-0.039
0.991
0.023
Find sand
-239.5
19.30
0.814
0.005
3.558
0.992
-0.039
0.982
0.022
Silt
-260.0
21.03
0.846
0.004
0.181
2.058
-0.036
0.982
0.022
Clay
-225.4
24.21
0.997
0.001
-2.460
3.111
-0.047
0.964
0.034
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ACCEPTED MANUSCRIPT Highlights
A fiber Bragg grating-based carbon fiber heated sensor (CFHS) for soil moisture monitoring is proposed.
The relationships between soil moisture and thermal response of sand, silt and clay are
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calibrated. The calibrated results were validated under normal gravitational and overweight conditions.
CFHS has the advantages of small sensor size, low disturbance to soil mass, and wide
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adaptability to physical model tests.
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