- Full paper
- Open Access

# Mechanical and hydraulic behavior of a rock fracture under shear deformation

- Satoshi Nishiyama
^{1}Email author, - Yuzo Ohnishi
^{2}, - Hisao Ito
^{3}and - Takao Yano
^{4}

**66**:108

https://doi.org/10.1186/1880-5981-66-108

© Nishiyama et al.; licensee Springer. 2014

**Received:**27 February 2014**Accepted:**22 August 2014**Published:**4 September 2014

## Abstract

With regard to crystalline rock that constitutes deep geology, attempts have been made to explore its hydraulic characteristics by focusing on the network of numerous fractures within. As the hydraulic characteristics of a rock are the accumulation of hydraulic characteristics of each fracture, it is necessary to develop the hydraulic model of a single fracture to predict the large-scale hydraulic behavior. To this end, a simultaneous permeability and shear test device is developed, and shear-flow coupling tests are conducted on specimens having fractures with varied levels of surface roughness in the constant normal stiffness conditions. The results show that the permeability characteristics in the relation between shear displacement and transmissivity change greatly at the point where the stress path reaches the Mohr-Coulomb failure curve. It is also found that there exists a range in which transmissivity is not proportional to the cube of mechanical aperture width, which seems to be because of the occurrence of channeling phenomenon at small mechanical aperture widths. This channeling flow disappears with increasing shear and is transformed into a uniform flow. We develop a simulation technique to evaluate the macroscopic permeability characteristics by the lattice gas cellular automaton method, considering the microstructure of fracture, namely the fracture surface roughness. With this technique, it is shown that the formation of the Hagen-Poiseuille flow is affected by the fracture microstructure under shear, which as a result determines the relationship between the mechanical aperture width and transmissivity.

## Keywords

- Shear-flow coupling test
- Constant normal stiffness
- Fracture surface roughness
- Mohr-Coulomb failure
- Lattice gas cellular automaton
- Modified cubic law
- Hagen-Poiseuille flow

## Background

In fractured rock such as granite in the Earth's crust, the hydraulic characteristics are dominated by the inherent fluid flows through fractures within the dense matrix. Research has been performed regarding the actual flow speed of groundwater inside such fractures, and regarding the hydraulic characteristics of rock by focusing on the network of fractures. As the hydraulic characteristics of rock are the accumulation of the hydraulic characteristics of each fracture, it is necessary to develop a hydraulic model of a single fracture to predict a large-scale hydraulic behavior (e.g., Raven and Gale 1985; Yeo et al. 1998; Chen et al. 2000; Olsson and Barton 2001; Kim and Inoue 2003; Watanabe et al. 2008; Chen et al. 2009; Watanabe et al. 2009). When a shear displacement takes place in a rock fracture having rough surfaces, it may cause significant changes in the pore structure (e.g., Mitsui et al. 2012). In terms of an evaluation technique for permeability characteristics, research has been conducted in order to confirm that the permeability through the fracture increases in proportion to the cube of the mechanical aperture width, namely the cubic law flow model (e.g., Brown 1987; Oron and Berkowitz 1998; Brush and Thomson 2003; Konzuk and Kueper 2004; Qian et al. 2011a). Furthermore, research conducted so far has shown that non-cubic law flows in complex fracture models may be caused by the heterogeneity of fractured media (e.g., Zimmerman et al. 1992; Qian et al. 2006; Qian et al. 2012). However, there has been no research that has dealt with how each fracture's permeability characteristics (such as the cubic law flow model) can be expressed in the presence of shear deformations. This study develops a hydraulic model to represent the permeability characteristics inside a single fracture under shear, through shear-flow coupling experiments on fractured specimens. In general, the shear-flow coupling testing on rock fractures is performed under either constant normal load conditions (CNL tests), or constant normal stiffness conditions (CNS tests) (e.g., Mourzenko et al. 1995; Brown et al. 1998; Nicholl and Detwiler 2001; Auradou 2009). We need to estimate strength parameters *c* and *ϕ* to understand the shear behavior of rock fractures. CNL tests are usually performed to calculate these strength parameters, at various levels of normal stress. Alternatively, when using CNS tests, it is possible to describe the failure curve of a specimen by obtaining the strength parameters *c* and *ϕ* with a single specimen, avoiding the need to prepare many specimens. In this study, we carried out CNS tests combined with permeability tests to show that the hydraulic model of each fracture (cubic or non-cubic model) constituting a fracture network can be expressed to account for both the shear state and changes in the pore structure.

Furthermore, this study sheds light on the mechanism that explains the hydraulic model through simulation. For the simulation of groundwater behavior inside a fracture in particular, it is necessary to develop a methodology to directly incorporate the fracture's physical structure data such as the measured surface profiles and aperture status of the fracture. The lattice gas automaton (LGA) method, which is based on the cellular automata theory, is adopted here to serve this purpose (e.g., Frisch et al. 1987; Pot and Karapiperis 2000; Pot and Genty 2007). Using this technique, we develop a methodology for predicting the behavior of rock that is affected by changes in stress fields.

## Methods

### Outline of permeability-shear tests

This section focuses on fracture surface profiles, in order to examine the relationship between the permeability behavior of a fracture under shear and its microstructure. We conducted shear-flow coupling tests on specimens having a single fracture.

### Specimens

^{−9}cm

^{2}/s. The surface roughness profiles were measured for level differences on a 0.25-mm grid, using a roughness measurement device with a non-contact laser displacement sensor (a spot diameter of 0.1 mm, featuring a 4.0-μm high-resolution semiconductor laser as the light source). Figure 1 shows the surface roughness profiles of the specimens used in this study. Fracture roughness is quantified as joint roughness coefficient (JRC), and JRC was determined by a visual comparison of fracture profile measured with standard roughness profile suggested by Barton and Choubey (1977). Using Z2, a parameter that characterizes the roughness profile of fractures proposed by Tse and Cruden (1979), the JRC values in the figure were obtained by applying the Z2

*-*JRC conversion formula proposed by Yu and Vayssade (1991).

### Outline of the shear-flow coupling tests

In order to clarify the permeability characteristics of rock fractures under shear, this study incorporated permeability and cutoff mechanisms into the conventional shear-flow coupling test device to enable the falling head permeability tests. The device was further modified to allow the inflow and measurement of tracers. The parts of the device used for shear-flow coupling testing and for permeability testing are called the ‘Shearing device part’ and ‘Permeability mechanism part,’ respectively (Barla et al. 2010; Esaki et al. 1999; Jiang et al. 2004; Giger et al. 2011; Qian et al. 2011b).

### Shearing device part

### Permeability mechanism part

Two electric conductivity cells are installed at the upper and lower ends of the shear box such that the sensor heads are at the upper-end and lower-end storage areas, and the gaps between the box and cells is sealed with rubber. In the tracer tests, the concentration of the tracer discharge is obtained by measuring the electric conductivity *R* during the replacement of fluid inside the fracture. The electric conductivity cells used here have a measurement range and accuracy of 0.1 mS/m to 10.0 S/m and 0.1 mS/m, respectively, use platinized electrodes as sensors, and allow the detection of electric conductivity by the two-electrode alternating current method. The tracer is a saline solution with an electric conductivity of 9.5 S/m that has the same viscosity as water, and is designed to measure the change of concentration with time at the upper- and lower-end storage areas.

### Test methods and conditions

Shear-flow coupling tests were performed through shear displacement control at a shearing speed of 0.1 mm/min. Permeability tests were performed by pausing the shearing process in order to take measurements at a constant value of shear displacement *u*, then restarting the shearing process until the next measurement point, continuing in this manner up to a maximum of *u* = 3.0 mm. Before beginning the shearing process, a loading/unloading process (stiffness testing) was repeated up to three times, with a normal stress *σ*_{
v
} value that would not damage the surface roughness of the fracture (from 0.25 up to 4.0 MPa at intervals of 1.0 MPa/min). The tests had originally been intended to be conducted at laboratories to obtain the fracture's normal stiffness *k*_{
n
}. Here, however, the purpose of conducting these tests was to set the same initial conditions, and also to calculate the initial aperture width through the improvement of fracture interlocking.

First, in order to examine how the surface roughness of a fracture would affect its permeability characteristics, three types of specimens having different surface roughness profiles were prepared (Specimens *J055*, *J107*, and *J200*), which have JRC values of 5.5, 10.7, and 20.0, respectively. In the CNS tests, the hydraulic gradient *I* was set at a constant value of 12.5 and initial normal stress *σ*_{
v0
} and normal stiffness *K*_{
v
} at 1.0 MPa and 10.0 GPa/m, respectively; the CNS and NL tests were conducted. ‘NL’ refers to the tests performed at constant normal load conditions, in order to examine the permeability characteristics as the mechanical fracture aperture width *b*_{
m
} value becomes smaller.

Next, in order to examine how *K*_{
v
} would affect the fracture permeability, the CNS tests were conducted on a specimen with the same roughness profile (Specimen *J055*, JRC = 5.5), using constant *I* and *σ*_{
v
} values of 12.5 and 1.0 MPa, respectively, while setting the values of *K*_{
v
} at 10.0, 30.0, and 50.0 GPa/m.

*T*is used to represent fracture permeability characteristics when the flow inside fractures is assumed to follow Darcy's law.

*T*is given by the following

where *Q* is the flow rate per unit time, *I* is hydraulic gradient, and *w* is the permeation width.

Before applying shear, the process of vertical stress loading and unloading is repeated (up to 4.0 MPa at 1.0 MPa/min) so as not to alter the surface roughness. When the vertical loading-displacemet curve starts to follow the same path, it is considered that the upper and lower surfaces of the specimen have interlocked well enough to be ready for the shear test. Assuming that at this stage any further application of stress will no longer affect the status of the aperture, the initial aperture width is defined as the fracture aperture width before commencing the shear test and is derived from the relation between the change in vertical stress and displacement. The mechanical aperture width *b*_{
m
} is defined as the value obtained by adding the experimentally obtained vertical displacement to the initial aperture width (Bandis et al. 1983; Barton et al. 1985).

- 1)
The flow is constant and of the Hagen-Poiseuille type.

- 2)
As compared with the speed of flow in the direction parallel to the plate, the speed of flow in the direction orthogonal to the plate is negligible.

- 3)
The changes in the speed of flow in the direction parallel to the plate are negligibly small, as compared with those in the direction orthogonal to the plate.

where *Q* is the flow rate, Δ*H* is the head difference, *b* is the aperture width, *g* is the gravity acceleration, *ν* is the dynamic viscosity coefficient of the permeating fluid, *w* is the specimen width in the direction orthogonal to permeation direction, and *l* is the specimen length in the permeation direction.

*f*

_{ c }, which is a deviation from the cubic law model that assumes parallel plates:

Here, *f*_{
c
} represents how the flow inside fractures is affected by the roughness profile of the surface, modifying the cubic law assumption of parallel plates. The closer the *f*_{
c
} value is to one, the smaller the extent of the flow being affected by the fracture, and the smaller the decrease in *Q* from the value for flow between parallel plates. In this study, the modified cubic law model given by Equation 4 is used for the flow in fractures when the cubic law model is discussed in terms of *b*_{
m
} (Vilarrasa et al. 2011; Xiong et al. 2011).

## Results and discussion

### Influences of JRC of fracture on the mechanical and permeability characteristics

*τ*is the shear strength,

*σ*

_{ v }is normal stress,

*c*is apparent cohesion, and

*ϕ*is the internal friction angle. Figure 4 shows the schematic diagram of the relation between the Mohr-Coulomb failure criterion and the

*τ*-

*σ*

_{ v }relation in the CNS tests. By converting the failure criterion shown in Figure 4a using stress ratio

*η*(=

*τ*/

*σ*

_{ v }), the relation becomes a hyperbola, as shown in Equation 5 and Figure 4b:

Therefore, if the measured values are expressed by the *τ*-*σ*_{
v
} relation, the values of *c* and *ϕ* can be predicted based on the hyperbola's curvature and asymptote, by extracting the B-C hyperbola section, as shown in Figure 4b. The point at which the stress path reaches the failure curve (i.e., the maximum *η* value or *η*_{
p
}) is denoted by the point ‘B’ in the figure, and the point ‘C’ can be specified by the critical normal stress *σ*_{
vc
} and critical shear stress *τ*_{
pc
}. Thus, it becomes possible to objectively define the B-C section. The stresses *σ*_{
vc
} and *τ*_{
pc
} are the maximum values that the stress path can migrate to in the Mohr-Coulomb failure criterion.

*τ*and a greater dilation. Figure 5c,d shows the results of applying Equation 6; the applicability of the hyperbola approximation described above is confirmed in Figure 5c, while Figure 5d shows that the stress path accurately represents the Mohr-Coulomb failure criterion, and that the greater the JRC values, the greater the

*c*and

*ϕ*values.

*b*

_{ m }

**-**

*T*relation

*.*The figure also shows the results of NL tests, i.e. the results of the permeability tests where the

*σ*

_{ v }value was set to 1.0, 2.0, 4.0, 8.0, and 16.0 MPa (shown by the black mark in the figure). It is found that the

*T*value rapidly increased near the shear displacement

*u*

_{ l }that corresponds to the proportional limit shown in Figure 5, and then after

*η*

_{ p }showed approximately a linear behavior on both logarithm axes. Thus, it is shown that the application boundary for the modified cubic law model given by Equation 4 is

*η*

_{ p }, and the permeability characteristics in the

*u*-

*T*relationship change greatly before and after reaching the Mohr-Coulomb failure curve, regardless of the fracture surface profiles (Mourzenko et al. 1997; Yeo and Ge 2005).

### Influents of normal stiffness on the mechanical and permeability characteristics

*K*

_{ v }values that are set in the CNS tests on the mechanical and permeability characteristics of rock fractures. With regard to the mechanical characteristics, Figure 7 shows the mechanical behavior observed in the CNS tests. The figure also shows the results of the NL tests. Because the value of

*σ*

_{ v }is constant in the conventional CNL tests, regardless of any changes in

*v*, it possible to compare the results of the NL tests by assuming they are equivalent to a CNS test with a

*K*

_{ v }value of 0. Figure 7a shows the relation between

*u*,

*τ*, and

*b*

_{ m }. Figure 7b is an enlarged view of the

*u-τ*relation. Note that

*σ*

_{v 0}= 1.0 MPa. The

*u*-

*τ*-

*b*

_{ m }relation in Figure 7a,b shows that the greater the value of

*K*

_{ v }, the greater the value of

*τ*, and the

*u-b*

_{ m }relation shows that the greater the value of

*K*

_{ v }, the lower the value of

*b*

_{ m }. Figure 7c shows the results of applying Equation 6, which confirms the applicability of the hyperbola approximation method. Figure 7d is the stress path. When the values of

*c*and

*ϕ*obtained by the hyperbola method are applied, it is shown that while

*c*is highly dependent on the

*K*

_{ v }value,

*ϕ*is approximately independent.

*u-T*relation

*.*It is also shown here that the

*T*value rapidly increased near

*u*

_{ l }in Figure 7, and after,

*η*

_{ p }showed a linear behavior on both logarithm axes. Figure 8b shows the relation between

*b*

_{ m }and

*T*. The figure also shows the results of the NL tests, which are the permeability tests where

*σ*

_{ v }values were set at 1.0, 1.5, 2.0, and 4.0 MPa (denoted by the black marks in the figure). The figure confirms that the smaller the

*b*

_{ m }value, the larger the deviation from the cubic law model and that the value

*η*

_{ p }shown in Figure 7 is the boundary where the modified cubic law model given by Equation 4 is found to be accurate in all specimens. It is also observed that where the fracture profiles are the same, similar permeability characteristics are observed at large and small

*b*

_{ m }values, regardless of any changes in the normal stiffness.

### Results in the tracer tests

*η*

_{ p }shown in Figures 6 and 8 is the boundary of the region where the cubic law model is accurate. The reason for the large deviation from the cubic law model can also be found in the tracer tests. Preliminary tracer tests were conducted on an acrylic specimen with a circular hole, 4.0 mm in diameter and 80.0 mm in length. This acrylic specimen had a uniform pore structure in the permeation direction, where permeation and substance migration occurred. The results of the tracer tests with this acrylic specimen were compared with those with complex pore structure fractures that had the same permeation cross section area as the 4.0-mm-diameter circular hole. As shown in Figure 9, the

*t*-

*R*relationships at the entrance and exit were found to be parallel to each other in the pipe model. For fractures with complex wall profiles, there is a time delay in the substance migration curve. The figure shows that with the parallel plates, the time needed for the injected fluid to reach the exit is constant, while there is a delay in the time needed for the fluid flowing through the void created by the fracture to reach the exit, depending on which path is taken. As pointed out by Piggott and Elsworth (1993), the complex pore structure triggered local migration of the substance inside the fracture. In other words, selective flows are occurring. Figure 10 shows the changes with time in the electric conductivity for each shear displacement

*u*value. Here again, a delay in the curve is observed at the initial shearing stage in accordance with the progress in the shearing process. Therefore, as mentioned before, the channeling phenomenon is presumed to have had a large influence on rapid changes in permeability characteristics before and after reaching the Mohr-Coulomb failure curve (Qian et al. 2011c).

### Simulation of fluid behavior inside the fracture

#### Principle of lattice gas automaton method

The technique of starting from the conventional adoption of differential equations such as the Navier-Stokes formula or the Reynolds equation, in order to obtain the speed or pressure of the fluid in a continuous body, is limited to the understanding of average characteristics within the domain (e.g., Zimmerman and Bodvarsson 1996; Zimmerman et al. 2004; Koyama et al. 2006; Cardenas et al. 2007). However, the technique proposed here, which treats the fluid as an assembly of particles and thus a discontinuous body, can express any chaotic behavior created by particle interactions. Furthermore, it allows the consideration of interactions within rock representing fracture profiles, and this is beneficial for the identification of the relationship between the microstructure and hydraulic characteristics of the fracture. The lattice Boltzmann (LB) method, which has the same cellular automata structure as LGA, has also been used for many kinds of simulations of incompressible viscous flows. In the LGA method, particles are represented by binary digits, whereas in the LB method, real numbers are utilized to represent the local ensemble-averaged particle distribution functions and only the kinetic equation for the distribution function is solved (e.g., Madadi and Sahimi 2003; Eker and Akin 2006). The main advantages of the LGA techniques are stability, easy introduction of boundary conditions, and an effective approach to accurately calculate fluid flow parameters at the microscopic scale, enabling a high-performance computation. Because the LGA method uses Boolean numbers in simulations and is therefore free from round-off error due to floating-point precision, this motivated us to choose the LGA method instead of the LB method.

- 1)
Divide the analysis target with the polygon lattice and discretize it.

- 2)
Express the fluid as an assembly of virtual particles of unit weight.

- 3)
Allocate the virtual particles on the lattice points. At each lattice point, there should be only one particle, which has a certain speed and direction at a certain time.

- 4)
Let the particles migrate, restricting them to the lattice lines. Each particle migrates to the closest lattice point at each discrete time step. During this process, it respects collision with other particles and scattering. The collisions are performed according to the conservation of mass and momentum.

*n*(

*r*,

*t*) = {

*n*

_{ i }(

*r*,

*t*);

*i*= 1, 2,…,

*b*} is expressed by

*b*= 24 bits, and the particle can go to neighboring points in 24 directions. Here, the affected neighborhood is set at 0, meaning that the collision and scattering of a particle are only affected by the state at the point where the particle is present. As shown in the figure, the four-dimensional axes are denoted by

*X*

_{1,}

*X*

_{2,}

*X*

_{3}, and

*X*

_{4}. When projecting onto a three-dimensional space, the

*X*

_{1,}

*X*

_{2}, and

*X*

_{3}axes correspond to

*X*,

*Y*, and

*Z*axes, while the

*X*

_{4}axis is degenerated.

*t*and

*t*+ 1, assuming that

*c*

_{ i }is a vector of the lattice line between lattice point r and the neighboring point, the mass and momentum conservation laws are given by Equations 7 and 8, respectively:

_{ i }is the particle's migration speed in the

*i*direction. Using a function

*Δ*

_{ i }to represent the collision process, the above equation can be written as Equation 9.

*X*

_{1,}

*X*

_{2}, and

*X*

_{3}directions is given by Equation 10 below:

*X*

_{4}direction, an incident particle on the wall is assumed to undergo specular reflection, the slip condition given by Equation 11 below is adopted:

With these equations, the complex fluid-fracture interactions are represented by the collisions of virtual particles and fracture walls.

### LGA simulation developed in this study

*r*being less than one sixth the injected particle density is found to be true in the motion directions of six particles in the flow direction (+X

_{ i }direction) in the FCHC lattice, namely (1,0,0,±1), (1,0,±1,0), and (1,±1,0,0), then a particle having the corresponding momentum is added to each particle at the upper end. Then, as shown in Figure 12a, the number of the particles flowing into the model becomes equal to the sum of the number of particles flowing out of the model exit and the number of particles flowing out of the model entrance after bouncing inside the model, satisfying the mass conservation law.In this case, however, the motion of particle near the model entrance/exit is affected by the fracture's porous structure and the interaction with the flow there, as well as the interaction with the domain outside the model. Thus, as shown in Figure 12b, this study assumes an imaginary domain to allow a virtual particle to flow outside the model, to perform hydraulic evaluation in the range where the influence of the interaction with the outside of the fracture cannot reach.The viscosity of the fluid flowing through the fracture is given as a function of the number of particles per lattice point. Injecting particles in the fracture surface in the LGA method leads to a different density of particles inside the fracture, and as a result, the viscosity ν is found to be different. To avoid this problem, the pressure difference and viscosity are calculated in the process of calculating the particle collision and scattering, as shown in Figure 13. Then, an algorithm is incorporated to keep a constant value for the injecting particle density inside the fracture. In other words, it was made possible to quantitatively evaluate the fluid behavior represented by particle density while keeping the fluid viscosity constant for various conditions inside the fracture surface.As shown in Figure 14, an example of analyzing the behavior of fluid flowing between two parallel plates in the LGA method is presented here. The aperture between the two parallel plates in the model had 300 lattices in the X direction (flow direction) and 100 in the Y direction (aperture width), with a number that varied between 10 and 30 in the Z direction (aperture thickness direction). The density of the injecting particles at the exit was set at 0, and at the entrance a value of between 0.45 and 0.55, respectively, with 20 lattices in the flow direction in the imaginary domain. In the Z direction, a reflective boundary was assumed in order to produce interactions with the fracture surface, and in the Y direction, there was a cyclic boundary condition.

### LGA simulation of fluid behavior inside the fracture

## Conclusions

- (1)
According to the

*u-T*relationship,*T*was found to rapidly increase at*u*_{ l }. In the CNS tests, it was found that the relation showed linear behavior in both logarithmic axes at*η*_{ p }and afterwards. This led to the realization that because*η*_{ p }is the crossings on the Mohr-Coulomb failure curve, the permeability characteristics represented by the*u-T*relationship changed greatly before and after reaching the Mohr-Coulomb failure curve. - (2)
Even when the fractures had the same

*b*_{ m }value, they had different permeability characteristics if their pore structures were different. - (3)
There existed a range in which

*T*was not proportional to the cube of*b*_{ m }where*b*_{ m }was small in the*b*_{ m }*-T*relation. This seems to be caused by the fact that the channeling phenomenon occurred at small*b*_{ m }values, which disappeared in accordance with the progress of shear process and transformed into a uniform flow. - (4)
The findings (3) above were also confirmed in the tracer tests. A delay in the curve was observed at the initial shearing stage, which confirmed that the flow was gradually transformed into the Hagen-Poiseuille flow in accordance with the progress in shearing process.

- (5)
The

*b*_{ m }-*T*relation of the tests with different*K*_{ v }using the same specimens was found to follow the same path in accordance with increases in*b*_{ m }, showing that the same permeability characteristics were observed at large*b*_{ m }values if the fracture profiles were the same.

Furthermore, taking into account the microstructure of fracture, the LGA method has been developed as an analytical technique for hydraulic behavior using a cellular automaton method to evaluate macroscopic permeability characteristics. It is then proved that the formation of Hagen-Poiseuille flow is affected by the microstructure of fracture under shear, which as a result determines the relation between the mechanical aperture width and transmissivity.

## Declarations

## Authors’ Affiliations

## References

- Auradou H: Influence of wall roughness on the geometrical, mechanical and transport properties of single fractures.
*J Phys D*2009, 42: 214015. doi: 10.1088/0022–3727/42/21/214015View ArticleGoogle Scholar - Bandis SC, Lumsden AC, Barton NR: Fundamentals of rock joint deformation.
*Int J Rock Mech Min Sci Geomesh Abstr*1983, 20(6):249–268. 10.1016/0148-9062(83)90595-8View ArticleGoogle Scholar - Barla G, Barla M, Martinotti ME: Development of a new direct shear testing apparatus.
*Rock Mech Rock Eng*2010, 43: 117–122. 10.1007/s00603-009-0041-5View ArticleGoogle Scholar - Barton N, Choubey V: The shear strength of rock joints in theory and practice.
*Rock Mech*1977, 10: 1–54. 10.1007/BF01261801View ArticleGoogle Scholar - Barton N, Bandis S, Bakhtar K: Strength, deformation and conductivity coupling of rock Joints.
*Int J Rock Mech Min Sci Geomesh Abstr*1985, 22(3):121–140. 10.1016/0148-9062(85)93227-9View ArticleGoogle Scholar - Brown SR: Fluid flow through rock joints: the effect of surface roughness.
*J Geophys Res*1987, 92(B2):1337–1347. 10.1029/JB092iB02p01337View ArticleGoogle Scholar - Brown S, Caprihan A, Hardly R: Experimental observation of fluid flow channels in a single fracture.
*J Geophys Res*1998, 103(B3):5125–5132. 10.1029/97JB03542View ArticleGoogle Scholar - Brush DJ, Thomson NR: Fluid flow in synthetic rough-walled fractures: Navier–Stokes, Stokes, and local cubic law simulations.
*Water Resour Res*2003, 39(4):1085. doi: 10.1029/2002WR001346Google Scholar - Cardenas MB, Slottke DT, Ketcham RA, Sharp JM Jr: Navier–Stokes flow and transport simulations using real fractures shows heavy tailing due to eddies.
*Geophys Res Lett*2007., 34: L14404 doi: 10.1029/2007GL030545 L14404Google Scholar - Chen Z, Narayan SP, Yang Z, Rahman SS: An experimental investigation of hydraulic behavior of fractures and joints in granitic rock.
*Int J Rock Mech Min Sci*2000, 37(7):1061–1071. 10.1016/S1365-1609(00)00039-3View ArticleGoogle Scholar - Chen Z, Qian J, Luo S, Zhan H: Experimental study of friction factor to groundwater flow in a single rough fracture.
*J Hydrodyn*2009, 21(6):820–825. 10.1016/S1001-6058(08)60218-8View ArticleGoogle Scholar - Eker E, Akin S: Lattice boltzmann simulation of fluid flow in synthetic fractures.
*Transp Porous Med*2006, 65: 363–384. doi: 10.1007/s11242–005–6085–4View ArticleGoogle Scholar - Esaki T, Du S, Mitani Y, Ikusada K, Jing L: Development of a shear-flow test apparatus and determination of coupled properties for a single rock joint.
*Int J Rock Mech Min Sci*1999, 36: 641–650. 10.1016/S0148-9062(99)00044-3View ArticleGoogle Scholar - Frisch U, d’Humières D, Hasslacher B, Lallemand P, Pomeau Y, Rivet JP,
*et al*.: Lattice gas hydrodynamics in two and three dimensions.*Complex Systems*1987, 1: 649–707.Google Scholar - Gao Y, Sharma MM: A LGA model for fluid flow in heterogeneous porous media.
*Transp Porous Med*1994, 17(1):1–17. 10.1007/BF00624047View ArticleGoogle Scholar - Giger SB, Clennell MB, Harbers C, Clark P, Ricchetti M, Ter Heege JH, Wassing BBT, Orlic B: Design, operation and validation of a new fluid-sealed direct shear apparatus capable of monitoring fault-related fluid flow to large displacements.
*Int J Rock Mech Min Sci*2011, 48: 1160–1172. 10.1016/j.ijrmms.2011.09.005View ArticleGoogle Scholar - Gutfraind R, Hansen A: Study of fracture permeability using lattice gas automata.
*Transp Porous Med*1995, 18(2):131–149. 10.1007/BF01064675View ArticleGoogle Scholar - Jiang Y, Tanabashi Y, Xiao J, Nagaie K: An improved shear-flow test apparatus and its application to deep underground construction.
*Int J Rock Mech Min Sci*2004, 41: 385–386. 10.1016/j.ijrmms.2003.12.046View ArticleGoogle Scholar - Kim HM, Inoue J: Analytical approach for anisotropic permeability through a single rough rock joint under shear deformation.
*J Geophys Res*2003, 108(B8):2366. doi: 10.1029/2002JB002283View ArticleGoogle Scholar - Konzuk JS, Kueper BH: Evaluation of cubic law based models describing single-phase flow through a rough-walled fracture.
*Water Resour Res*2004., 40: W02402 doi: 10.1029/2003WR002356 W02402Google Scholar - Koyama T, Fardin N, Jing L, Stephansson O: Numerical simulation of shear induced flow anisotropy and scale dependent aperture and transmissivity evolutions of fracture replicas.
*Int J Rock Mech Min Sci*2006, 43(1):89–106. 10.1016/j.ijrmms.2005.04.006View ArticleGoogle Scholar - Madadi M, Sahimi M: Lattice Boltzmann simulation of fluid flow in fracture networks with rough, self-affine fractures.
*Phys Rev E*2003, 67: 026309.View ArticleGoogle Scholar - Mitsui Y, Iio Y, Fukahata Y: A scenario for the generation process of the 2011 Tohoku earthquake based on dynamic rupture simulation: role of stress concentration and thermal fluid pressurization.
*Earth Planets Space*2012, 64(12):1177–1187.View ArticleGoogle Scholar - Mourzenko VV, Thovert JF, Adler PM: Permeability of a single fracture: validity of the Reynolds equation.
*J Phys II*1995, 5(3):465. doi: 10.1051/jp2:1995133Google Scholar - Mourzenko VV, Galamay O, Thovert JF, Adler PM: Fracture deformation and influence on permeability.
*Phys Rev E*1997, 56(3):3167–3184. 10.1103/PhysRevE.56.3167View ArticleGoogle Scholar - Nicholl MJ, Detwiler RL: Simulation of flow and transport in a single fracture: macroscopic effects of underestimating local head loss.
*Geoph Res Lett*2001, 28(23):4355. doi: 10.1029/2001gl013647View ArticleGoogle Scholar - Olsson R, Barton N: An improved model for hydromechanical coupling during shearing of rock joints.
*Int J Rock Mec Min Sci*2001, 38(3):317–329. 10.1016/S1365-1609(00)00079-4View ArticleGoogle Scholar - Oron AP, Berkowitz B: Flow in rock fractures: the local cubic law assumption reexamined.
*Water Resour Res*1998, 34(11):2811–2825. 10.1029/98WR02285View ArticleGoogle Scholar - Park JW, Song JJ: Numerical method for the determination of contact areas of a rock joint under normal and shear loads.
*Int J Rock Mech Min Sci*2013, 58: 8–22.Google Scholar - Piggott AR, Elsworth D: Laboratory assessment of the equivalent apertures of a rock fracture.
*Geophys Res Lett*1993, 20(13):1387–1390. 10.1029/93GL01384View ArticleGoogle Scholar - Pot V, Genty A: Dispersion dependence on retardation in a real fracture geometry using lattice-gas cellular automaton.
*Adv Water Res*2007, 30: 273–283. 10.1016/j.advwatres.2005.08.011View ArticleGoogle Scholar - Pot V, Karapiperis T: A multi-species lattice-gas automaton model to study passive and reactive tracer migration in 2D fractures.
*Eur Phys J*2000, B13: 387–393.View ArticleGoogle Scholar - Qian J, Liu Y, Wang J, Guan H, Chen S, Wang J: Non-LCL and tracer test for groundwater flow in a single fracture.
*J Hydrodynamics Series B*2006, 18(1):104–108.Google Scholar - Qian J, Chen Z, Zhan H, Guan H: Experimental study of the effect of roughness and Reynolds number on fluid flow in rough-walled single fractures: a check of local cubic law.
*Hydrol Process*2011, 25: 614–622. doi: 10.1002/hyp.7849View ArticleGoogle Scholar - Qian J, Zhan H, Chen Z, Ye H: Experimental study of solute transport under non-Darcian flow condition in a single fracture.
*J Hydrol*2011, 399: 246–254. 10.1016/j.jhydrol.2011.01.003View ArticleGoogle Scholar - Qian J, Chen Z, Zhan H, Luo S: Solute transport in a filled single fracture under non-Darcian flow.
*Int J Rock Mech Min Sci*2011, 48: 132–140. 10.1016/j.ijrmms.2010.09.009View ArticleGoogle Scholar - Qian J, Liang M, Chen Z, Zhan H: Eddy correlations for water flow in a single fracture with abruptly changing aperture.
*Hydrol Process*2012, 26: 3369–3377. doi: 10.1002/hyp.8332View ArticleGoogle Scholar - Raven KG, Gale JE: Water flow in a natural rock fracture as a function of stress and sample size.
*Int J Rock Mech Min Sci*1985, 22(4):251–261. 10.1016/0148-9062(85)92952-3View ArticleGoogle Scholar - Tse R, Cruden DM: Estimating joint roughness coefficients.
*Int J Rock Mech Min Sci*1979, 16: 303–307. 10.1016/0148-9062(79)90241-9View ArticleGoogle Scholar - Vilarrasa V, Koyama T, Neretnieks I, Jing L: Shear-induced flow channels in a single rock fracture and their effect on solute transport.
*Transp Porous Med*2011, 87: 503–523. doi: 10.1007/s11242–010–9698–1View ArticleGoogle Scholar - Watanabe N, Hirano N, Tsuchiya N: Determination of aperture distribution and fluid flow in a rock fracture by high-resolution numerical modeling on the basis of a flow-through experiment under confining pressure.
*Water Resour Res*2008., 44: W06412 doi: 10.1029/2006WR005411 W06412Google Scholar - Watanabe N, Hirano N, Tsuchiya N: Diversity of channeling flow in heterogeneous aperture distribution inferred from integrated experimental-numerical analysis on flow through shear fracture in granite.
*J Geophys Res*2009., 114: B04208 doi: 10.1029/2008JB005959 B04208Google Scholar - Witherspoon PA, Wang JSY, Iwai K, Gale JE: Validity of cubic law for fluid flow in a deformable rock fracture.
*Water Resour Res*1980, 16(6):1016–1024. 10.1029/WR016i006p01016View ArticleGoogle Scholar - Xiong X, Li B, Jiang Y, Koyama T, Zhang C: Experimental and numerical study of the geometrical and hydraulic characteristics of a single rock fracture during shear.
*Int J Rock Mech Min Sci*2011, 48: 1292–1302. 10.1016/j.ijrmms.2011.09.009View ArticleGoogle Scholar - Yeo IW, Ge S: Applicable range of the Reynolds equation for fluid flow in a rock fracture.
*Geosci J*2005, 9(4):347–352. 10.1007/BF02910323View ArticleGoogle Scholar - Yeo IW, De Freitas MH, Zimmerman RW: Effect of shear displacement on the aperture and permeability of a rock fracture.
*Int J Rock Mech Min Sci Geomech Abstr*1998, 35(8):1051–1070. 10.1016/S0148-9062(98)00165-XView ArticleGoogle Scholar - Yu X, Vayssade B: Joint profiles and their roughness parameters.
*Int J Rock Mech Min Sct Geomech Abstr*1991, 28(4):333–336. 10.1016/0148-9062(91)90598-GView ArticleGoogle Scholar - Zimmerman RW, Bodvarsson GS: Hydraulic conductivity of rock fractures.
*Transp Porous Med*1996, 23: 1–30.View ArticleGoogle Scholar - Zimmerman RW, Chen DW, Cook NGW: The effect of contact area on the permeability of fractures.
*J Hydrology*1992, 139(1–4):79–96.View ArticleGoogle Scholar - Zimmerman RW, Al-Yaarubi A, Pain CC, Grattoni CA: Non-linear regimes of fluid flow in rock fractures.
*Int J Rock Mech Min Sci*2004, 41(3):384. doi: 10.1016/j.ijrmms.2003.12.045View ArticleGoogle Scholar

## Copyright

This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited.