ARTICLE IN PRESS
International Journal of Rock Mechanics & Mining Sciences 41 (2004) 1329–1364
www.elsevier.com/locate/ijrmms
A bonded-particle model for rock
D.O. Potyondya,,1, P.A. Cundallb
a
University of Toronto, Department of Civil Engineering and Lassonde Institute, Toronto, Ont., Canada M5S 1A4
b
Itasca Consulting Group Inc., 111 Third Avenue South, Suite 450, Minneapolis, MN 55401, USA
Accepted 9 September 2004
Available online 27 October 2004
Abstract
A numerical model for rock is proposed in which the rock is represented by a dense packing of non-uniform-sized circular or
spherical particles that are bonded together at their contact points and whose mechanical behavior is simulated by the distinctelement method using the two- and three-dimensional discontinuum programs PFC2D and PFC3D. The microproperties consist of
stiffness and strength parameters for the particles and the bonds. Damage is represented explicitly as broken bonds, which form and
coalesce into macroscopic fractures when load is applied. The model reproduces many features of rock behavior, including elasticity,
fracturing, acoustic emission, damage accumulation producing material anisotropy, hysteresis, dilation, post-peak softening and
strength increase with confinement. These behaviors are emergent properties of the model that arise from a relatively simple set of
microproperties. A material-genesis procedure and microproperties to represent Lac du Bonnet granite are presented. The behavior
of this model is described for two- and three-dimensional biaxial, triaxial and Brazilian tests and for two-dimensional tunnel
simulations in which breakout notches form in the region of maximum compressive stress. The sensitivity of the results to
microproperties, including particle size, is investigated. Particle size is not a free parameter that only controls resolution; instead, it
affects the fracture toughness and thereby influences damage processes (such as notch formation) in which damage localizes at
macrofracture tips experiencing extensile loading.
r 2004 Elsevier Ltd. All rights reserved.
Keywords: Rock fracture; Distinct-element method; Numerical model; Micromechanics
1. Introduction
In this paper, we argue that rock behaves like a
cemented granular material of complex-shaped grains in
which both the grains and the cement are deformable
and may break, and that such a conceptual model can,
in principle, explain all aspects of the mechanical
behavior. Various numerical models have been proposed that mimic such a system with differing levels of
fidelity. The bonded-particle model for rock (referred to
hereafter as the BPM) directly mimics this system and
Corresponding
author.
Tel.:
+1 416 978 3115;
fax:
+1 416 978 6813.
E-mail addresses:
[email protected] (D.O. Potyondy),
[email protected] (P.A. Cundall).
1
Formerly with Itasca.
1365-1609/$ - see front matter r 2004 Elsevier Ltd. All rights reserved.
doi:10.1016/j.ijrmms.2004.09.011
thus exhibits a rich set of emergent behaviors that
correspond very well with those of real rock. The BPM
provides both a scientific tool to investigate the
micromechanisms that combine to produce complex
macroscopic behaviors and an engineering tool to
predict these macroscopic behaviors.
The mechanical behavior of rock is governed by the
formation, growth and eventual interaction of microcracks. Microscopic observations of rock [1–5] reveal
detailed information about initial defects and loadinduced cracks, such as length, density, aspect ratio and
orientation. Acoustic-emission (AE) based observations
of rock [6] record the acoustic signals that are generated
spontaneously from this microcracking, thereby providing information about the size, location and deformation mechanisms of the acoustic events as well as
properties of the medium through which the acoustic
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waves travel (e.g., velocity, attenuation and scattering).
Experimental observations reveal that most of the
compression-induced cracks nucleate at the initial
defects, such as grain boundaries or crack-like, lowaspect-ratio cavities, and that all compression-induced
cracks are almost parallel to the direction of the
maximum compression. The micromechanism responsible for the formation of these cracks is not understood
fully; however, many possible models exist (e.g., sliding
deformation between the faces of initial defects inclined
to the direction of maximum compression leading to
formation of a wing crack at each of the two defect tips)
that can reproduce many of the essential features of the
brittle fracture phenomenon [1,7–15]. Kemeny [10]
asserts that:
Although the actual growth of cracks under compression may be due to many complicated mechanisms, as
revealed by laboratory tests, it appears that they can
all be approximated by the crack with a central point
load. The origins of these ‘‘point’’ loads in rock under
compression are small regions of tension that develop
in the direction of the least principal stress.
Kemeny and Cook [11] emphasize the importance of
producing compression-induced tensile cracks:
Laboratory testing of rocks subjected to differential
compression have revealed many different mechanisms for extensile crack growth, including pore
crushing, sliding along pre-existing cracks, elastic
mismatch between grains, dislocation movement, and
hertzian contact. Because of the similarity in rock
behavior under compression in a wide range of rock
types, it is not surprising that micromechanical
models have many similarities. This may explain the
success of models based on certain micromechanisms
(such as the sliding crack and pore models) in spite of
the lack of evidence for these mechanisms in
microscopic studies.
One mechanism [16] for the formation of compression-induced tensile cracks is shown in Fig. 1(c), in
which a group of four circular particles is forced apart
by axial load, causing the restraining bond to experience
tension. These axially aligned ‘‘microcracks’’ occur
during the early loading stages of compression tests on
bonded assemblies of circular or spherical particles.
Similar crack-inducing mechanisms occur even when
different conceptual models for rock microstructure are
used. For example, ‘‘wedges’’ and ‘‘staircases’’ also
induce local tension if angular grains replace circular
grains—see Fig. 1(a) and (b). In addition to the
formation and growth of microcracks, the eventual
interaction of these cracks is necessary to produce
localization phenomena such as axial splitting or
rupture-zone formation during unconfined or confined
compression tests. Thus, any model intending to
Fig. 1. Physical mechanisms for compression-induced tensile cracking
(a and b) and idealization as bonded assembly of circular particles (c).
reproduce these phenomena must allow the microcracks
to interact with one another.
Rock can be represented as a heterogeneous material
comprised of cemented grains. In sedimentary rock,
such as sandstone, a true cement is present, whereas in
crystalline rock, such as granite, the granular interlock
can be approximated as a notional cement. There is
much disorder in this system, including locked-in
stresses produced during material genesis, deformability
and strength of the grains and the cement, grain size,
grain shape, grain packing and degree of cementation
(i.e., how much of the intergrain space is filled with
cement). All of these items influence the mechanical
behavior, and many of them evolve under load
application.
The mechanical behavior of both rock and a BPM is
driven by the evolution of the force-chain fabric, as will
be explained here with the aid of Fig. 2. An applied
macroscopic load is carried by the grain and cement
skeleton in the form of force chains that propagate from
one grain to the next across grain contacts, some of
which may be filled with cement. The force chains are
similar to those that form in a granular material [17].
The cement-filled contacts experience compressive,
tensile and shear loading and also may transmit
a bending moment between the grains, whereas the
empty contacts experience only compressive and shear
loading. Thus, applied loading produces heterogeneous
force transmission and induces many sites of tension/
compression oriented perpendicular to the compression/
tension direction—for the reasons illustrated in
Fig. 1(c). In addition, the force chains are highly nonuniform, with a few high-load chains and many lowload chains. The chain loads may be much higher than
the applied loads, such that a few grains will be highly
loaded while others will be less loaded or carrying no
load (see Fig. 5(b))—because the forces will arch around
these grains, thereby forming chains with a fabric that is
larger than the grain size, as seen in the compression
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Fig 2. Force and moment distributions and broken bonds (in
magenta) in a cemented granular material with six initial holes
idealized as a bonded-disk assembly in the post-peak portion of an
unconfined compression test. (Blue is grain–grain compression, while
black and red are compression and tension, respectively, in the cement
drawn as two lines at the bond periphery. Line thicknesses and
orientations correspond with force magnitude and direction, respectively, and the moment in the cement contributes to the forces at the
bond periphery.)
rings in Fig. 6.2 (The existence of such large-scale
features in the force chains provides evidence that, in
general, the mechanism shown in Fig. 1(c) will be
operative at a length scale larger than the grain size.) It
is these microforces and micromoments that provide the
local loading to produce grain and/or cement breakage,
which, in turn, induces global force redistribution
(because damaged material is softer and sheds load to
stiffer, undamaged material) and the eventual formation
of macroscopic fractures and/or rupture zones. As more
and more grains and cement are broken, the material
behaves more and more like a granular material with
highly unstable force chains. The key to explaining
material behavior is the evolving force-chain fabric,
which is related in a complex way to the deformability
and strength of the grains and the cement, the grain size,
grain shape, grain packing and degree of cementation.
Computational models of rock can be classified into
two categories, depending on whether damage is
represented indirectly, by its effect on constitutive
relations or, directly, by the formation and tracking of
many microcracks. Most indirect approaches idealize
the material as a continuum and utilize average
measures of material degradation in constitutive rela2
Figs. 5(b) and 6 are discussed in detail in Section 2.5, Materialgenesis procedure.
1331
tions to represent irreversible microstructural damage
[18], while most direct approaches idealize the material
as a collection of structural units (springs, beams, etc.)
or separate particles bonded together at their contact
points and utilize the breakage of individual structural
units or bonds to represent damage [19–22]. Most
computational models used to describe the mechanical
behavior of rock for engineering purposes are based on
the indirect approach, while those used to understand the
behavior in terms of the progress of damage development and rupture are based on the direct approach.
The BPM is an example of a direct modeling
approach in which particles and bonds are related
to similar objects observed microscopically in rock
[23–30]. Alternative rock models in which the material
is represented as a continuum include those in
Refs. [31,32], where a network of weak planes is
superimposed on an otherwise homogeneous elastic
continuum, and those in Refs. [33,34], where the
stiffness and strength of elements in a continuum with
initial heterogeneous strength are allowed to degrade
based on a strength failure criterion in the form of an
elastic–brittle–plastic constitutive relation. These rock
models exhibit more realistic responses in terms of shear
and post-failure behavior than most lattice models,
because they can carry compressive and shear forces
arising from loading subsequent to bond breakage,
whereas most lattice models retain no knowledge of the
particles after each bond has broken. Comprehensive
review articles [35,36] summarize rock models and
approaches for simulating crack growth, and [37]
provides additional discussion of the BPM and its
relation to other rock models.
The micromechanisms occurring in rock are complex
and difficult to characterize within the framework of
existing continuum theories. Microstructure controls
many of these micromechanisms. The BPM approximates rock as a cemented granular material with an
inherent length scale that is related to grain size and
provides a synthetic material that can be used to test
hypotheses about how the microstructure affects the
macroscopic behavior. This is a comprehensive model
that exhibits emergent properties (such as fracture
toughness, which controls the formation of macroscopic
fractures) that arise from a small set of microproperties
for the grains and cement. The BPM does not impose
theoretical assumptions and limitations on material
behavior as do most indirect models (such as models
that idealize the rock as an elastic continuum with many
elliptical cracks—in the BPM, such cracks form, interact
and coalesce into macroscopic fractures automatically).
Behaviors not encompassed by current continuum
theories can be investigated with the BPM. In fact,
continuum behavior itself is simply another of the
emergent properties of a BPM when averaged over the
appropriate length scale.
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The remainder of the paper is organized as follows.
The formulation of the BPM, which includes a microproperty characterization expressed in terms of grain
and cement properties and a material-genesis procedure,
is presented in the next section. In Sections 3 and 4, the
measured macroscopic properties of a BPM for Lac du
Bonnet granite are presented and discussed. In Section 3,
the focus is on laboratory-scale behavior (during biaxial,
triaxial and Brazilian tests), and Section 4 focuses on
field-scale behavior (involving damage formation adjacent to an excavation). In both sections, the effect of
particle size on model behavior is investigated. In
Section 5, the emergent properties of the BPM are
listed, and the general source of some of these behaviors
is identified. As a particular example, a formal
equivalence between the mechanisms and parameters
of the BPM and the concepts and equations of linear
elastic fracture mechanics (LEFM) is established and
then used to explain the effect of particle size on model
behavior. The capabilities and limitations of the BPM,
as well as suggestions for overcoming these limitations,
are presented in the conclusion. For completeness,
the algorithms used to measure average stress and
strain within the BPM, to install an initial stress field
within the BPM, to create a densely packed BPM
with low locked-in forces to serve as the initial material
and to perform typical laboratory tests on the BPM
are described in Appendix A. Throughout the paper,
all vector and tensor quantities are expressed using
indicial notation.
2. Formulation of the BPM
The BPM simulates the mechanical behavior of a
collection of non-uniform-sized circular or spherical
rigid particles that may be bonded together at their
contact points. The term ‘‘particle’’, as used here, differs
from its more common definition in the field of
mechanics, where it is taken as a body of negligible size
that occupies only a single point in space; in the present
context, the term ‘‘particle’’ denotes a body that
occupies a finite amount of space. The rigid particles
interact only at the soft contacts, which possess finite
normal and shear stiffnesses. The mechanical behavior
of this system is described by the movement of each
particle and the force and moment acting at each
contact. Newton’s laws of motion provide the fundamental relation between particle motion and the
resultant forces and moments causing that motion.
The following assumptions are inherent in the BPM:
1. The particles are circular or spherical rigid bodies
with a finite mass.
2. The particles move independently of one another and
can both translate and rotate.
3. The particles interact only at contacts; because the
particles are circular or spherical, a contact is
comprised of exactly two particles.
4. The particles are allowed to overlap one another, and
all overlaps are small in relation to particle size
such that contacts occur over a small region (i.e., at
a point).
5. Bonds of finite stiffness can exist at contacts, and
these bonds carry load and can break. The particles at
a bonded contact need not overlap.
6. Generalized force–displacement laws at each contact
relate relative particle motion to force and moment at
the contact.
The assumption of particle rigidity is reasonable when
movements along interfaces account for most of the
deformation in a material. The deformation of a
packed-particle assembly, or a granular assembly such
as sand, is described well by this assumption, because
the deformation results primarily from the sliding and
rotation of the particles as rigid bodies and the opening
and interlocking at interfaces—not from individual
particle deformation. The addition of bonds between
the particles in the assembly corresponds with the
addition of real cement between the grains of a
sedimentary rock, such as sandstone, or notional cement
between the grains of a crystalline rock, such as granite.
The deformation of a bonded-particle assembly, or a
rock, should be similar, and both systems should exhibit
similar damage-formation processes under increasing
load as the bonds are broken progressively and both
systems gradually evolve toward a granular state. If
individual grains or other microstructural features are
represented as clusters of bonded particles, then grain
crushing and material inhomogeneity at a scale larger
than the grain size can also be accommodated by this
model [38–40].
2.1. Distinct-element method (DEM)
The BPM is implemented in the two- and threedimensional discontinuum programs PFC2D and PFC3D
[41] using the DEM. The DEM was introduced by
Cundall [42] for the analysis of rock-mechanics problems
and then applied to soils by Cundall and Strack [43].
Thorough descriptions of the method are given in Refs.
[44,45]. The DEM is a particular implementation of a
broader class of methods known as discrete-element
methods, which are defined in Ref. [46] as methods that
allow finite displacements and rotations of discrete bodies,
including complete detachment, and recognize new
contacts automatically as the calculation progresses.
Current development and applications of discrete-element
methods are described in Ref. [47].
In the DEM, the interaction of the particles is treated
as a dynamic process with states of equilibrium
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developing whenever the internal forces balance. The
contact forces and displacements of a stressed assembly
of particles are found by tracing the movements of the
individual particles. Movements result from the propagation through the particle system of disturbances
caused by wall and particle motion, externally applied
forces and body forces. This is a dynamic process in
which the speed of propagation depends on the physical
properties of the discrete system. The calculations
performed in the DEM alternate between the application of Newton’s second law to the particles and a
force–displacement law at the contacts. Newton’s
second law is used to determine the translational and
rotational motion of each particle arising from the
contact forces, applied forces and body forces acting
upon it, while the force–displacement law is used to
update the contact forces arising from the relative
motion at each contact.
The dynamic behavior is represented numerically by a
time-stepping algorithm in which the velocities and
accelerations are assumed to be constant within each
time step. The solution scheme is identical to that used by
the explicit finite-difference method for continuum
analysis. The DEM is based on the idea that the time
step chosen may be so small that, during a single time
step, disturbances cannot propagate from any particle
farther than its immediate neighbors. Then, at all times,
the forces acting on any particle are determined exclusively by its interaction with the particles with which it is
in contact. Because the speed at which a disturbance can
propagate is a function of the physical properties of the
discrete system (namely, the distribution of mass and
stiffness), the time step can be chosen to satisfy the above
constraint. The use of an explicit, as opposed to an
implicit, numerical scheme provides the following advantages. Large populations of particles require only modest
amounts of computer memory, because matrices are not
stored. Also, physical instability may be modeled without
numerical difficulty, because failure processes occur in a
realistic manner—one need not invoke a non-physical
algorithm, as is done in some implicit methods.
2.2. Damping of particle motion
Because the DEM is a fully dynamic formulation,
some form of damping is necessary to dissipate kinetic
energy. In real materials, various microscopic processes
such as internal friction and wave scattering dissipate
kinetic energy. In the BPM, local non-viscous damping
is used by specifying a damping coefficient, a: The
damping formulation is similar to hysteretic damping
[48], in which the energy loss per cycle is independent of
the rate at which the cycle is executed. The damping
force applied to each particle is given by
F d ¼ ajF j signðV Þ;
(1)
1333
where jF j is the magnitude of the unbalanced force on
the particle and signðV Þ is the sign (positive or negative)
of the particle velocity. This expression is applied
separately to each degree-of-freedom.
A common measure of attenuation or energy loss in
rock is the seismic quality factor, Q. The quality factor is
defined as 2p times the ratio of stored energy to
dissipated energy in one wavelength
Q ¼ 2pðW =DW Þ;
(2)
where W is energy [49]. For a single degree-of-freedom
system, or for oscillation in a single mode, the quality
factor can be written as [41]
Q ¼ p=2a:
(3)
All BPMs described in this paper were run with a
damping coefficient of 0.7, which corresponds with a
quality factor of 2.2. The quality factor of Lac du
Bonnet granite in situ is about 220 [50]; therefore, the
models were heavily damped to approximate quasistatic conditions. Hazzard et al. [49] ran similar models
using a damping coefficient corresponding with a quality
factor of 100 and found that the energy released by
crack events (i.e., bond breakages) may have a
significant influence on the rock behavior, because the
waves emanating from cracks are capable of inducing
more cracks if nearby bonds are close to failure.
Hazzard and coworkers showed that the effect of this
dynamically induced cracking was to decrease the
unconfined compressive strength by up to 15%. In
addition, if low numerical damping is used, then seismic
source information (such as magnitude and mechanism)
can be determined for every modeled crack [51].
2.3. Grain-cement behavior and parameters
The BPM mimics the mechanical behavior of a
collection of grains joined by cement. The following
discussion considers each grain as a PFC2D or PFC3D
particle and each cement entity as a parallel bond. The
total force and moment acting at each cemented contact
is comprised of a force, F i ; arising from particle–particle
overlap, denoted in Fig. 3 as the grain behavior, and a
force and moment, F̄ i and M̄ i ; carried by the parallel
bond and denoted as the cement behavior. These
quantities contribute to the resultant force and moment
acting on the two contacting particles. The force–displacement law for this system will now be described, first
for the grain behavior and then for the cement behavior.
Note that if a parallel bond is not present at a contact,
then only the grain-based portion of the force–displacement behavior occurs.
The grain-based portion of the force–displacement
behavior at each contact is described by the following
six parameters (see Fig. 3): the normal and shear
stiffnesses, kn and ks ; and the friction coefficient, m; of
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Fig. 3. Force–displacement behavior of grain-cement system.
the two contacting particles, which are assumed to be
disks of unit thickness in PFC2D and spheres in
PFC3D. Whenever two particles overlap, a contact is
formed at the center of the overlap region along the
line joining the particle centers (xðcÞ
i in Fig. 3), and two
linear springs are inserted (with stiffnesses derived from
the particle stiffnesses assuming that the two particle
springs act in series) along with a slider in the
shear direction.
The contact force vector, F i (which represents the
action of particle A on particle B), can be resolved into
normal and shear components with respect to the
contact plane as
F i ¼ F n ni þ F s ti ;
n
(4)
s
where F and F denote the normal and shear force
components, respectively, and ni and ti are the unit
vectors that define the contact plane. The normal force
is calculated by
F n ¼ K nU n;
(5)
where U n is the overlap and K n is the contact normal
stiffness given by
Kn ¼
ðBÞ
kðAÞ
n kn
;
ðBÞ
kðAÞ
n þ kn
ðBÞ
kðAÞ
n and kn
(6)
with
being the particle normal stiffnesses.
The shear force is computed in an incremental
fashion. When the contact is formed, F s is initialized
to zero. Each subsequent relative shear–displacement
increment, DU s ; produces an increment of elastic shear
force, DF s ; that is added to F s (after F s has been rotated
to account for motion of the contact plane). The
increment of elastic shear force is given by
DF s ¼ ks DU s ;
(7)
where ks is the contact shear stiffness given by
ks ¼
ðBÞ
kðAÞ
s ks
ðBÞ
kðAÞ
s þ ks
;
(8)
with kðAÞ
and kðBÞ
being the particle shear stiffnesses.
s
s
The relative displacement increment during the time step
Dt is given by DU i ¼ V i Dt; where V i is the contact
velocity
V i ¼ x_ ðcÞ
x_ ðcÞ
i
i
B
A
ðBÞ
ðBÞ
ðBÞ
¼ x_ i þ eijk oj xðcÞ
x
k
k
ðAÞ
ðAÞ
ðcÞ
x_ i þ eijk oj xk xðAÞ
;
ð9Þ
k
x_ i and oj are the particle translational and rotational
velocities, respectively, and eijk is the permutation
symbol. The relative shear–displacement increment
vector is
DU si ¼ V si Dt ¼ ðV i V ni ÞDt ¼ ðV i V j nj ni ÞDt:
(10)
If U n p0 (a gap exists), then both normal and shear
forces are set to zero; otherwise, slip is accommodated
by computing the contact friction coefficient
m ¼ min mðAÞ ; mðBÞ ;
(11)
with mðAÞ and mðBÞ being the particle friction coefficients,
and setting F s ¼ mF n if F s 4mF n :
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Note that K n is a secant stiffness in that it relates total
displacement and force, whereas ks is a tangent stiffness
in that it relates incremental displacement and force. In
this paper, an upper-case K denotes a secant stiffness
and a lower-case k denotes a tangent stiffness. Use of a
secant stiffness to compute normal force makes the
computations less prone to numerical drift and able to
handle arbitrary placement of particles and changes in
particle radii after a simulation has begun.
The cement-based portion of the force–displacement
behavior at each cemented contact is described by the
following five parameters that define a parallel bond
(see Fig. 3): normal and shear stiffnesses per unit area,
n
s
k̄ and k̄ ; tensile and shear strengths, s̄c and t̄c ; and
bond-radius multiplier, l̄; such that parallel-bond radius
R̄ ¼ l̄ min RðAÞ ; RðBÞ ;
(12)
with RðAÞ and RðBÞ being the particle radii. A parallel
bond approximates the mechanical behavior of a brittle
elastic cement joining the two bonded particles. Parallel
bonds establish an elastic interaction between these
particles that acts in parallel with the grain-based
portion of the force–displacement behavior; thus, the
existence of a parallel bond does not prevent slip.
Parallel bonds can transmit both force and moment
between particles, while grains can only transmit force.
A parallel bond can be envisioned as a set of elastic
springs uniformly distributed over a rectangular crosssection in PFC2D and a circular cross-section in PFC3D
lying on the contact plane and centered at the contact
point. These springs behave as a beam whose length, L̄
in Fig. 3, approaches zero to approximate the mechanical behavior of a joint.
The total force and moment carried by the parallel
bond are denoted by F̄ i and M̄ i ; respectively, which
represent the action of the bond on particle B. The force
and moment vectors can be resolved into normal and
shear components with respect to the contact plane as
n
s
F̄ i ¼ F̄ ni þ F̄ ti ;
n
s
M̄ i ¼ M̄ ni þ M̄ ti ;
n
s
ð13Þ
n
s
where F̄ ; F̄ and M̄ ; M̄ denote the axial- and sheardirected forces and moments, respectively, and ni
and ti are the unit vectors that define the contact plane.
n
(For the PFC2D model, the twisting moment, M̄ ¼ 0;
s
and the bending moment, M̄ ; acts in the out-of-plane
direction.) When the parallel bond is formed, F̄ i and M̄ i
are initialized to zero. Each subsequent relative
displacement- and
ðDU n ; DU s ; Dyn ;
rotation increment
ðBÞ
ðAÞ
s
Dy with Dyi ¼ oi oi Dt produces an increment
of elastic force and moment that is added to the
current values (after the shear-component vectors have
been rotated to account for motion of the contact
plane). The increments of elastic force and moment
1335
are given by
n
n
DF̄ ¼ k̄ A DU n ;
s
s
DF̄ ¼ k̄ A DU s ;
n
s
s
n
DM̄ ¼ k̄ J Dyn ;
DM̄ ¼ k̄ I Dys ;
ð14Þ
where A; I and J are the area, moment of inertia and
polar moment of inertia of the parallel bond crosssection, respectively. These quantities are given by
(
2R̄t; t ¼ 1; PFC2D;
A¼
2
pR̄ ;
PFC3D;
8
3
2
< R̄ t; t ¼ 1; PFC2D;
3
I¼
:1 4
pR̄ ;
PFC3D;
(4
NA;
PFC2D;
J¼
ð15Þ
4
1
PFC3D:
2 pR̄ ;
The maximum tensile and shear stresses acting on the
parallel-bond periphery are calculated from beam
theory to be
n
s
F̄
jM̄ jR̄
;
þ
¼
s̄
I
A
s
n
jF̄ j jM̄ jR̄
þ
:
ð16Þ
t̄max ¼
A
J
If the maximum tensile stress exceeds the tensile
strength ðs̄max Xs̄c Þ or the maximum shear stress exceeds
the shear strength ðt̄max Xt̄c Þ; then the parallel bond
breaks, and it is removed from the model along with its
accompanying force, moment and stiffnesses.
A simplified form of the BPM represents the cement
using contact bonds instead of parallel bonds. A contact
bond approximates the physical behavior of a vanishingly small cement-like substance lying between and
joining the two bonded particles. The contact bond
behaves, essentially, as a parallel bond of radius zero.
Thus, a contact bond does not have a radius or shear
and normal stiffnesses, as does a parallel bond, and
cannot resist a bending moment or oppose rolling;
rather, it can only resist a force acting at the contact
point. Also, slip is not allowed to occur when a contact
bond is present. A contact bond is defined by the two
parameters of tensile and shear strengths, fn and fs ;
expressed in force units. When the corresponding
component of the contact force exceeds either of these
values, the contact bond breaks, and only the grainbased portion of the force–displacement behavior
occurs.
max
2.4. Microproperty characterization
In general, the BPM is characterized by the grain
density, grain shape, grain size distribution, grain
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packing and grain-cement microproperties. Each of
these items influences the model behavior. The grain
density, r; does not affect the quasi-static behavior but
is included for completeness. In this paper, we focus on
circular or spherical grains comprised of individual
PFC2D or PFC3D particles, although the effect on the
strength envelope of introducing particle clusters of
complex interlocking shapes into the PFC2D particle
assembly is discussed in Section 3.4. The particle
diameters satisfy a uniform particle-size distribution
bounded by Dmin and Dmax ; and a dense packing is
obtained using the material-genesis procedure of Section 2.5. The packing fabric, or connectivity of the
bonded assembly, is controlled by the ratio ðDmax =Dmin Þ;
for a fixed ratio, varying Dmin changes the absolute
particle size but does not affect the packing fabric. Such
a microproperty characterization separates the effects of
packing fabric and particle size on material behavior
and clearly identifies Dmin as the controlling length scale
of the material. The final item that characterizes the
BPM is the grain-cement microproperties:
E c ; kn =ks ; m ; grain microproperties;
n s
l̄; Ē c ; k̄ =k̄ ; s̄c ; t̄c ; cement microproperties; ð17Þ
where E c and Ē c are the Young’s moduli of the grains
n
s
and cement, respectively; ðkn =ks Þ and ðk̄ =k̄ Þ are the
ratios of normal to shear stiffness of the grains and
cement, respectively; l̄ is the radius multiplier used to set
the parallel-bond radii via Eq. (12); m is the grain friction
coefficient; and s̄c and t̄c are the tensile and shear
strengths, respectively, of the cement. In the analysis
below, the grain and cement moduli are related to the
corresponding normal stiffnesses such that the particle
and parallel-bond stiffnesses are assigned as
(
2tE c ; t ¼ 1; PFC2D;
kn :¼
4RE c ;
PFC3D;
kn
ks :¼
;
ðkn =ks Þ
Ē c
n
;
k̄ :¼ ðAÞ
R þ RðBÞ
n
k̄
s
k̄ :¼ n s ;
ð18Þ
ðk̄ =k̄ Þ
where R is particle radius. The usefulness of these
modulus–stiffness scaling relations is confirmed in
Section 3.5, where it is shown that the macroscopic
elastic constants are independent of particle size for the
PFC2D material and exhibit only a minor size effect for
the PFC3D material.
The deformability of an isotropic linear elastic
material is described by two elastic constants. These
quantities are emergent properties of the BPM and
cannot be specified directly. It is possible, however, to
relate the grain and cement moduli, E c and Ē c ;
Fig. 4. Equivalent continuum material of grain-cement system.
respectively, to the normal stiffnesses by envisioning
the material at each contact as an elastic beam with its
ends at the particle centers, as shown in Fig. 4. The axial
stiffness of such a beam is K ¼ AE=L; where A, E and L
are the cross-sectional area, modulus and length,
respectively, of the beam. For the grain-based behavior,
kn ðLtÞE c
kn
¼
¼ E c t ) E c ¼ ; t ¼ 1; PFC2D;
2
L
2t
kn ðL2 ÞE c
kn
kn
¼
¼ EcL ) Ec ¼
¼
; PFC3D ð19Þ
2
L
2L 4R
by assuming that kn ¼ knðAÞ ¼ kðBÞ
in Eq. (6). For the
n
cement-based behavior,
n
AĒ c
AĒ c
¼ ðAÞ
L
R þ RðBÞ
n
) Ē c ¼ k̄ RðAÞ þ RðBÞ :
k̄ A ¼
ð20Þ
The cement modulus is dependent on particle size; to
achieve a constant cement modulus, parallel-bond
stiffnesses must be scaled with the particle radii. For
the PFC3D material, the grain modulus is dependent on
particle size; to achieve a constant grain modulus,
particle stiffnesses must be scaled with particle radius.
This analysis does not yield a relation between Poisson’s
ratio and particle stiffness at the microlevel; however, a
macroscopic Poisson’s ratio will be observed, and its
value will be affected by grain shape, grain packing and
n
s
the ratios ðkn =ks Þ and ðk̄ =k̄ Þ: For a fixed grain shape
and packing, increasing these ratios increases the
Poisson’s ratio.
2.5. Material-genesis procedure
The BPM represents rock as a dense packing of nonuniform-sized circular or spherical particles that are
joined at their contact points with parallel bonds. The
material-genesis procedure produces this system such
that the particles are well connected and the locked-in
forces are low. Both the packing and the locked-in
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1337
forces are arbitrary and isotropic at a macroscale—i.e.,
when averaged over approximately one dozen adjacent
particles. (This would not occur if the material were
created by gravity compaction—in which case, the force
chains would be aligned vertically and their magnitudes
would increase with depth.) The material-genesis procedure employs the following five-step process (illustrated
in Figs. 5 and 6 for the PFC2D Lac du Bonnet granite
model of Table 1).
1. Compact initial assembly: A material vessel consisting
of planar frictionless walls is created, and an
assembly of arbitrarily placed particles is generated
to fill the vessel. The vessel is a rectangle bounded by
four walls for PFC2D and a rectangular parallelepiped bounded by six walls for PFC3D. The wall
normal stiffnesses are made just larger than the
average particle normal stiffness to ensure that the
particle–wall overlap remains small. The particle
diameters satisfy a uniform particle-size distribution
bounded by Dmin and Dmax : To ensure a reasonably
tight initial packing, the number of particles is
determined such that the overall porosity in the
Fig. 6. Force and moment distributions in PFC2D material after
removal from material-genesis vessel followed by relaxation (color
convention described in Fig. 2).
Fig. 5. Material-genesis procedure for PFC2D model: (a) particle assembly after initial generation but before rearrangement; (b) contact-force
distribution (All forces are compressive, thickness proportional to force magnitude.) after step 2; (c) floating particles (with less than three contacts)
and contacts after step 2; (d) parallel-bond network after step 4.
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Table 1
Model microproperties for Lac du Bonnet granite
Grains
r ¼ 2630 kg=m3
ðDmax =Dmin Þ ¼ 1:66; Dmin varies
62 GPa; PFC2D
Ec ¼
72 GPa; PFC3D
ðkn =ks Þ ¼ 2:5
m = 0.5
vessel is 16% for PFC2D and 35% for PFC3D.
The particles, at half their final size, are placed
randomly such that no two particles overlap. Then,
the particle radii are increased to their final values,
as shown in Fig. 5(a), and the system is allowed
to rearrange under zero friction. The ballgeneration procedure is described in more detail in
Appendix A.
2. Install specified isotropic stress: The radii of all
particles are reduced uniformly to achieve a specified
isotropic stress, s0 ; defined as the average of the
direct stresses. These stresses are measured by
dividing the average of the total force acting on
opposing walls by the area of the corresponding
specimen cross-section. Stresses in the PFC2D
models are computed assuming that each particle is
a disk of unit thickness. When constructing a granite
material, s0 is set equal to approximately 1% of the
uniaxial compressive strength. This is done to reduce
the magnitude of the locked-in forces that will
develop after the parallel bonds are added and the
specimen is removed from the material vessel and
allowed to relax, as shown in Fig. 6. The magnitude
of the locked-in forces (both tensile and compressive)
will be comparable to the magnitude of the compressive forces at the time of bond installation. The
contact-force distribution at the end of this step
is shown in Fig. 5(b). The isotropic stress installation
procedure is described in more detail in the
Appendix A.
3. Reduce the number of ‘‘floating’’ particles: An
assembly of non-uniform-sized circular or spherical
particles, placed randomly and compacted mechanically, can contain a large number (perhaps as high as
15%) of ‘‘floating’’ particles that have less than N f
contacts, as shown in Fig. 5(c), where N f ¼ 3: It is
desirable to reduce the number of floating particles
such that a denser bond network is obtained in step 4.
In our granite models, we wish to obtain a densely
packed and well-connected assembly to mimic a
highly interlocked collection of grains. By setting
N f ¼ 3 and the allowed number of floating particles
Cement
l̄ ¼ 1
62 GPa;
72 GPa;
n
s
ðk̄ =k̄ Þ ¼ 2:5
Ē c ¼
PFC2D
PFC3D
s̄c ¼ t̄c ¼ ðmean std: dev:Þ¼
157 36 MPa;
175 40 MPa;
PFC2D
PFC3D
to zero, we obtain a bonded assembly for which
nearly all particles away from the specimen boundaries have at least three contacts. The floaterelimination procedure is described in more detail
in Appendix A.
4. Install parallel bonds: Parallel bonds are installed
throughout the assembly between all particles
that are in near proximity (with a separation less
than 106 times the mean radius of the two particles),
as shown in Fig. 5(d). The parallel-bond properties
are assigned to satisfy Eqs. (17) and (18), with s̄c and
t̄c picked from a Gaussian (normal) distribution. The
grain property of m is also assigned.
5. Remove from material vessel: The material-genesis
procedure is completed by removing the specimen
from the material vessel and allowing the assembly
to relax. This is done by deleting the vessel walls and
stepping until static equilibrium is achieved. During
the relaxation process, the material expands and
generates a set of self-equilibrating locked-in forces,
as shown in Fig. 6. These are similar to locked-in
stresses that may exist in a free specimen of rock. The
locked-in forces can be divided into two types,
depending upon their existence at a macro- or a
microscale. The macroscale forces exist within selfcontained clusters of approximately one dozen
particles, in which the inner particles are in tension
and the outer particles are in compression, or vice
versa. Such compression rings can be seen in Fig. 6.
The microscale forces exist within individual parallel
bonds and are mostly tension to equilibrate the
tendency of the contact springs to repel the compressed particles. There is a net energy stored in the
assembly in the form of strain energy in both the
particle–particle contacts and the parallel bonds.
These locked-in forces can have a significant effect
upon behavior (e.g., feeding energy into a rockburst
or causing strain to occur when the assembly is cut).
Holt [52] used a BPM to investigate stress-relief
effects induced during coring of sandstone by setting
s0 equal to the compaction stresses existing at the
time of grain cementation.
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3. Measured macroscopic-properties (laboratory scale)
The BPM consists of a procedure for material genesis
and two independent sets of microproperties for shortand long-term behavior. A set of short-term microproperties are described in Section 2.4, and a set of longterm microproperties are described in Ref. [53]. No
model is complete or fully verifiable [54], but the validity
of the BPM is demonstrated by comparing model
behavior with measured and observed responses of
Lac du Bonnet granite at both laboratory and field
scales in this and the next section.
3.1. Choosing microproperties
For continuum models, the input properties (such as
modulus and strength) can be derived directly from
measurements performed on laboratory specimens. For
the BPM, which synthesizes macroscale material behavior from the interactions of microscale components, the
input properties of the components usually are not
known. The relation between model parameters and
commonly measured material properties is only known
a priori for simple packing arrangements. For the
general case of arbitrary packing of arbitrarily sized
particles, the relation is found by means of a calibration
process in which a particular instance of a BPM—with a
particular packing arrangement and set of model
parameters—is used to simulate a set of material tests,
and the BPM parameters then are chosen to reproduce
the relevant material properties measured in such tests.
The BPM for Lac du Bonnet granite is described by
the microproperties in Table 1. These microproperties
were chosen to match the macroproperties of Lac du
Bonnet granite discussed in Section 3.3. The ratio
ðDmax =Dmin Þ is set greater than 1 to produce an arbitrary
isotropic packing. As ðDmax =Dmin Þ ! 1; the packing
tends toward a crystalline arrangement. Such a uniform
packing exhibits anisotropic macroproperties and is not
representative of the more complex grain connectivity of
a granite. l̄ is set equal to 1 to produce a material with
cement that completely fills the throat between cemented
particles. As l̄ ! 0; the material behavior approaches
that of a granular material. The grain and cement
moduli and ratios of normal to shear stiffness are set
equal to one another to reduce the number of free
parameters. Then, the moduli are chosen to match the
Young’s modulus, and the ratios of normal to shear
stiffness are chosen to match the Poisson’s ratio. Next,
the cement strengths are set equal to one another so as
not to exclude mechanisms that may only be activated
by microshear failure (see below). The ratio of standard
deviation to mean of the cement strengths is chosen to
match the crack-initiation stress (defined in Section 3.3),
and the mean value of the cement strengths is chosen to
match the unconfined compressive strength. The parti-
1339
cle-friction coefficient appears to affect only post-peak
response, and it is not clear to what it should be
calibrated; thus, m ¼ 0:5 is used as a reasonable non-zero
value.
By setting s̄c ¼ t̄c ; both tensile and shear microfailures are possible. If microtensile failure is excluded
(by setting s̄c to infinity), then cracking does not localize
onto a single macrofracture plane under macroscopic
extensile loading. Because this mechanism does occur in
granite, microtensile failure is allowed to occur in the
granite model. The alternative cases for which microshear failure is excluded fully (by setting t̄c to infinity)
or allowed (by setting s̄c ¼ t̄c ) are investigated for the
PFC2D material by Potyondy and Autio [39], who
study damage formation adjacent to a circular hole
subjected to far-field compressive loading. Both materials produce breakout notches in compressive regions
and tensile macrofractures in tensile regions that are
generally similar. The material with s̄c ¼ t̄c allows
more well-defined notches to form than does the
material that can only fail in the microtensile mode
(see Fig. 7). The former material accommodates the
shearing deformation along the notch outline by
forming a string of shear microcracks, whereas the
latter material must form several sets of en echelon
tensile microcracks (which requires that additional
deformation and accompanying damage occur within
the notch region). For the granite model, s̄c ¼ t̄c so as
not to exclude mechanisms that may only be activated
via microshear failure.
3.2. PFC2D model behavior during biaxial and Brazilian
tests
Typical stress–strain response and damage patterns
are shown in Fig. 8 for the PFC2D granite model with
an average particle diameter of 0.72 mm. The testing
procedures are described in Appendix A. The crack
distributions in this and all such figures are depicted as
bi-colored lines (in which red represents tension-induced
parallel-bond failure for which bond tensile strength has
been exceeded and blue represents shear-induced parallel-bond failure for which bond shear strength has been
exceeded) lying between the two previously bonded
particles with a length equal to the average diameter of
the two previously bonded particles. The cracks are
oriented perpendicular to the line joining the centers of
the two previously bonded particles. The damage
mechanisms during biaxial tests are summarized in
observations 1–3, and those during Brazilian tests in
observation 4. Similar observations apply to the PFC3D
granite model subjected to triaxial and Brazilian tests.
1. During the early stages of biaxial loading, relatively
few cracks form, and those that do form tend to be
aligned with the direction of maximum compression.
These cracks are distributed throughout the specimen
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Fig. 7. Damage in the notch region for the same compressive load (acting vertically) for a PFC2D material with (a) microshear failure allowed (3267
cracks) and (b) microshear failure excluded (3800 cracks).
Fig. 8. Stress–strain response and damage patterns formed during biaxial tests at confinements of 0.1, 10 and 70 MPa for a 63.4 126.8 mm2
specimen of the PFC2D granite model with Davg ¼ 0:72 mm: (a) Stress-strain response; (b) Post-peak crack distribution, s3 ¼ 0:1 MPa (1716 cracks,
tensile/shear=1452/264); (c) Post-peak crack distribution, s3 ¼ 10 MPa (2443 cracks, tensile/shear=2035/408); (d) Post-peak crack distribution,
s3 ¼ 70 MPa (3940 cracks, tensile/shear=2800/1140).
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and do not seem to be interacting. The onset of this
early cracking is quantified by the crack-initiation
stress.
2. Near peak load in a biaxial test, one or more
macroscopic failure planes develop that cut across
the specimen. When confinement is low, a set of
secondary macrofractures oriented parallel with the
loading direction form on either side of these failure
planes, as seen in Fig. 8(b). The secondary macrofractures are comprised of tensile microcracks and
suggest an axial-splitting phenomenon. As the confinement increases, the number of failure planes and
their widths increase, as seen in Figs. 8(c) and (d).
3. Damage at peak load is quite similar for all
confinements, and most damage occurs after peak
load as the specimen expands laterally—volumetric
strain is dilational [53]. This observation, combined
with observation 2, suggests that the post-peak
damage-formation process is affected more by confinement than is the pre-peak damage-formation
process. This change in behavior is related in part
to the fact that, as confinement increases, the ratio of
shear microcracks to tensile microcracks increases.
The confinement reduces the tensile forces that
develop in a direction perpendicular to the specimen
axis and thereby causes more shear microcracks
to form.
4. During Brazilian tests, a wedge of cracks forms inside
of the specimen below each platen. Then, one of the
wedges initiates a single macrofracture that travels
across the specimen parallel with the direction of
loading. The macrofracture is comprised of tensile
microcracks and is driven by extensile deformation
across the crack path (similar to an LEFM mode-I
crack). This observation suggests that the Brazilian
strength measured in these tests is related to the
material fracture toughness, as is shown in Section
5.2, and that it may not correspond with the Brazilian
strength measured in a valid Brazilian test on a real
rock specimen. Such difficulties are inherent in tests
that attempt to measure the tensile strength of a rock,
because it is rarely possible to force the failure to
1341
occur simultaneously across the entire final fracture
plane.
3.3. Macroproperties of Lac du Bonnet granite
The following short-term laboratory properties of Lac
du Bonnet granite [55] obtained from 63-mm diameter
specimens with a length-to-diameter ratio of 2.5 are used
to calibrate the short-term response of the granite model
(see Table 2 for mean, standard deviation and number
of tests): (a) the elastic constants of Young’s modulus,
E; and Poisson’s ratio, u; measured from unconfined
compression tests; (b) the unconfined compressive
strength, qu ; (c) the crack-initiation stress, sci ; (d) the
strength envelope for confining pressures in the range
0.1–10 MPa approximated as an equivalent Mohr–Coulomb material with a secant slope, N f ; friction angle, f;
and cohesion, c; and (e) the Brazilian strength, st :
The crack-initiation stress is defined as the axial stress
at which non-elastic dilation just begins, identified as the
point of deviation from linear elasticity on a plot of axial
stress versus volumetric strain.
The strength envelope, which is the relation between
peak strength and confining pressure, is obtained by
fitting the Hoek–Brown strength criterion [56] to results
of triaxial tests at confining pressures up to 70 MPa. The
Hoek–Brown strength criterion is given by
qffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi
sf ¼ s3 ss2c s3 sc m
(21)
where s and m are dimensionless material parameters
and sc is equal to the unconfined compressive strength
when s ¼ 1: The Hoek–Brown parameters for the
strength envelope of Lac du Bonnet granite [57] are sc ¼
213 MPa; m ¼ 31 and s ¼ 1: In general, the strength
envelope will exhibit a decreasing slope for increasing
confinement; however, it can be linearized using a secant
approximation defined by the strength, sf ; at two
confinements, P0 and P1 : If the slope is defined by
Nf ¼
sf ðP1 Þ sf ðP0 Þ
;
P1 P0
(22)
Table 2
Macroproperties of the models and Lac du Bonnet granite
Property
Lac du Bonnet granite
PFC2D model, Davg ¼ 0:72 mm
PFC3D model, Davg ¼ 1:53 mm
E ðGPaÞ
u
qu ðMPaÞ
sci ðMPaÞ
scd ðMPaÞ
Nf
f ðdegÞ
c ðMPaÞ
st ðMPaÞ
69 5:8 ðn ¼ 81Þ
0:26 0:04 ðn ¼ 81Þ
200 22 ðn ¼ 81Þ
90 þ s3 ; s3 o30
150; s3 ¼ 0
13
59
30
9:3 1:3 ðn ¼ 39Þ
70:9 0:9 ðn ¼ 10Þ
0:237 0:011 ðn ¼ 10Þ
199:1 13:0 ðn ¼ 10Þ
71:8 21:8 ðn ¼ 10; s3 ¼ 0:1Þ
NA
3:01 0:60 ðn ¼ 10Þ
29:5 4:8 ðn ¼ 10Þ
58:5 8:5 ðn ¼ 10Þ
44:7 3:3 ðn ¼ 10Þ
69:2 0:8 ðn ¼ 10Þ
0:256 0:014 ðn ¼ 10Þ
198:8 7:2 ðn ¼ 10Þ
86:6 11:0 ðn ¼ 10; s3 ¼ 0:1Þ
190:3 7:5 ðn ¼ 10; s3 ¼ 0:1Þ
3:28 0:33 ðn ¼ 10Þ
32:1 2:4 ðn ¼ 10Þ
55:1 4:2 ðn ¼ 10Þ
27:8 3:8 ðn ¼ 10Þ
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then the friction angle and cohesion can be written
as [58]
1 N f 1
f ¼ sin
;
Nf þ 1
q
c ¼ puffiffiffiffiffiffiffi ;
ð23Þ
2 Nf
where qu is the unconfined compressive strength.
The Brazilian strength is computed via
Ff
;
(24)
pRt
where F f is the peak force acting on the platens, and R
and t are the radius and thickness, respectively, of the
Brazilian disk.
The crack-damage stress, scd ; is defined as the axial
stress at which the volumetric strain reverses direction
and becomes dilational. The crack-damage stress for
saturated Lac du Bonnet granite is related to the
peak strength, sf ; by the following fourth-order polynomial [53]:
scd
¼ 0:75 0:031x þ 0:00285x2
sf
0:000104x3 þ 0:00000138x4 ;
ð25Þ
st ¼
Fig. 9. Typical specimens of the granite model: (a) PFC2D specimen
(4017 particles, 7764 parallel bonds) and (b) PFC3D specimen (19,749
particles, 55,042 parallel bonds).
where x is the confining stress (in MPa). The crackdamage stress is measured for the PFC3D material, but
it is not used in the present calibration.
3.4. Macroproperties of the PFC models
The microproperties in Table 1 with Dmin ¼ 0:55 mm
and Dmin ¼ 1:19 mm were used to produce PFC2D and
PFC3D materials with average particle diameters of 0.72
and 1.53 mm, respectively. Then, 10 rectangular PFC2D
specimens (63.4 31.7 mm2) and 10 rectangular parallelepiped PFC3D specimens (63.4 31.7 31.7 mm3) with
different packing arrangements and microstrengths were
created by varying the seed of the random-number
generator during material genesis. Typical PFC2D/
PFC3D specimens (shown in Fig. 9) contain approximately 4000/20,000 particles and have 44/20 particles
across the specimen width. Biaxial, triaxial and Brazilian
tests were performed upon these specimens to obtain the
model macroproperties shown in Table 2. The testing
procedures are described in Appendix A. The strength
envelopes were obtained by performing a set of biaxial
and triaxial tests at confining pressures of 0.1, 1, 5, 10,
20, 30 and 70 MPa. The test results for the PFC2D
material are shown in Fig. 10, which includes the peak
strength and crack-initiation stress from each test with
lines joining the average values at each confining
pressure. The strength envelope for the PFC3D material
is similar.
The PFC models match the macroproperties of E; n
and qu of the Lac du Bonnet granite, and the variability
Fig 10. Strength envelopes for PFC2D granite model (results of all 10
tests) and Lac du Bonnet granite.
of these macroproperties (expressed as a ratio of
standard deviation to mean) is less than that of the
physical material. The unconfined compressive strength
of the PFC3D material exhibits less variability than that
of the PFC2D material. The model materials also
exhibit the onset of significant internal cracking
(measured by sci ) before ultimate failure. However, the
model strengths only match that of the Lac du Bonnet
granite for stresses near the uniaxial state. The slope of
the strength envelope is too low (3 for both PFC2D and
PFC3D versus 13 for the granite), and the Brazilian
strength is too high (the ratio ðqu =st Þ is 4.5 and 7.2 for
PFC2D and PFC3D, respectively, versus 21.5 for the
granite). This discrepancy may arise from the use of
circular and spherical grains in the present model, and it
could be reduced by using grain shapes that more closely
resemble the complex-shaped and highly interlocked
crystalline grains in granite. A preliminary investigation,
described below, suggests that introducing finitestrength particle clusters of complex interlocking shapes
into the PFC2D particle assembly will increase the slope
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of the strength envelope and will lower the crackdamage stress. A similar effect is expected for the
PFC3D material. If these grains are also allowed to
break, then damage mechanisms that more closely
resemble those in granite will be possible. One mechanism that contributes to the large difference in the
compressive and tensile strengths of granite is suggested
by Mosher et al. [59], who have studied the cracking
within granite thin sections when stressed in tension or
compression under the microscope and have found that
intergranular fractures predominate in tension and
intragranular in compression.
In the preliminary investigation, unbreakable particle
clusters of complex interlocking shapes were introduced
into the PFC2D particle assembly so that cracking is
forced to occur along cluster boundaries (the white dots
in Fig. 11(a)). The clustering algorithm is controlled by
S c ; the maximum number of particles in a cluster. A
cluster is defined as a set of particles that are adjacent to
1343
one another, where adjacent means that a connected
path can be constructed between any two particles in a
cluster by traversing bonded particle–particle contacts.
The algorithm begins with a densely packed bonded
material and identifies particle clusters by traversing the
list of particles. Each cluster is grown by identifying the
current particle as a seed particle and then adding
adjacent particles to the cluster until either all adjacent
particles have been added or the cluster size has reached
S c : The algorithm provides no control over cluster shape
but does produce a collection of complex cluster shapes
that are fully interlocking—similar to the interlocking
grains in a crystalline rock.
The strength-envelope slope for such a material can
be made to exceed that of Lac du Bonnet granite, as
shown in Fig. 11(b), and dilation begins at lower stresses
relative to peak (scd is lowered) as cluster size is
increased. However, the biaxial-test damage does not
localize into discrete macroscopic failure planes, and the
post-peak response is plastic-like and does not exhibit
the abrupt stress drop of Lac du Bonnet granite.
Experiments on Barre granite [4] indicate that, after
loading to approximately 87% of peak strength, almost
all grain boundaries were cracked along their entire
length. Because this had occurred before the peak
strength had been reached, it suggests that additional
damage, in the form of transgranular fracture (or grain
splitting) may be occurring in this loading regime. If a
finite strength were assigned to the bonds within
clusters, then transgranular fractures could form, and
this might produce the desired localization and abrupt
post-peak stress drop. This presents a promising avenue
for further study [60].
3.5. Effect of particle size on macroproperties
Fig. 11. Introducing complex grain-like shapes into the PFC2D
material using particle clusters: (a) clusters of size 7 and bonds (black:
intra-cluster bonds; white: inter-cluster bonds) and (b) effect of cluster
size on strength envelope for unbreakable clusters.
If the BPM is used to predict damage formation
surrounding an excavation, then the absolute size of the
potential damage region is fixed, and successively finer
resolution models can be produced by decreasing Dmin
while keeping all other microproperties fixed. The
investigation in this section demonstrates that particle
size is an intrinsic part of the material characterization
that affects the Brazilian strength (and the unconfined
compressive strength for PFC3D material); thus, particle size cannot be regarded as a free parameter that only
controls model resolution. If the damage mechanisms
involve extensile conditions similar to those existing in a
Brazilian test, then particle size should be chosen to
match the Brazilian strength or another appropriate
property of the rock, perhaps the fracture toughness.
For the PFC3D material, it may not be possible to
match the ratio ðqu =st Þ without introducing nonspherical grains.
Four PFC2D and four PFC3D granite materials were
produced using the microproperties in Table 1 with
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different values of Dmin : The PFC2D and PFC3D
materials have average particle diameters ranging from
2.87 to 0.36 mm and 5.95 to 1.53 mm, respectively. For
each PFC2D and PFC3D material, 10 rectangular
specimens (63.4 31.7 mm2) or 10 rectangular parallelepiped specimens (63.4 31.7 31.7 mm3), respectively,
with different packing arrangements and microstrengths
were created by varying the seed of the random-number
generator during material genesis. Each specimen was
then subjected to a Brazilian test and to two biaxial or
triaxial tests at confinements of 0.1 and 10 MPa. The
PFC3D Brazilian disk thicknesses were chosen to
produce approximately 2.6 particles across the thickness. The test results are presented in Tables 3 and 4 in
terms of the mean and coefficient of variation (ratio of
standard deviation to mean) of each macroproperty.
It is expected that as particle size continues to
decrease, the coefficients of variation will converge to
specific values. These values should be a true measure of
the effect of both packing and strength heterogeneities
in the model materials, because the number of particles
across the specimen has become large enough to obtain
a representative sampling of the material response. As
the number of particles across the specimen is reduced,
the scatter in measured properties increases. Also, a
sufficient number of particles must be present for the
model to resolve and reproduce the failure mechanisms
that influence the strength properties.
3.5.1. PFC2D material response
The elastic constants appear to be independent of
particle size. The mean values of Poisson’s ratio are
approximately the same for all particle sizes, and the
mean values of Young’s modulus increase slightly
(by less than 5%) as particle size decreases from 2.87
to 0.36 mm. This slight increase in Young’s modulus
may be an artifact of having sampled too few data
points to obtain a true measure of the mean values. If
the elastic constants truly are independent of particle
size, then the characterization of the elastic grain-cement
n
s
microproperties in terms of E c ; Ē c ; ðkn =ks Þ; and ðk̄ =k̄ Þ
provides a size-independent means of specifying the
elastic properties of the material. The size independence
is achieved by scaling the parallel-bond stiffnesses as a
function of particle size via Eq. (18).
The unconfined compressive strength also appears to
be independent of particle size. The mean values differ
by less than 8% and exhibit no clear increasing or
decreasing trend. This behavior may be an artifact of
having sampled too few data points to obtain a true
measure of the mean values; however, the decreasing
coefficients of variation are reasonable and indicate a
possible convergence to a specific value. It is also
reasonable that the variability of qu is greater than the
variability of the elastic constants, because qu measures
a complex critical-state phenomenon involving extensive
damage formation and interaction, whereas the elastic
constants merely measure the deformability of the
particle assembly before any significant damage has
developed.
No definitive statements about the effect of particle
size on friction angle and cohesion can be made based
on the results in Table 3. The mean values of f and c
differ by 19% and 21%, respectively, and exhibit no
Table 3
Effect of particle size on PFC2D macroproperties
Particle size Davg (mm)
2.87
1.44
0.72
0.36
Macroproperty (63.4
31.7 mm2 specimens, n=10, mean and coefficient of variation)
E (GPa, %)
n (, %)
68.3
68.8
70.9
71.5
0.231
0.249
0.237
0.245
10.5
3.3
1.3
0.8
19.0
7.6
4.6
2.9
qu (MPa, %)
f (deg, %)
c (MPa, %)
st (MPa, %)
186.8
184.4
199.1
194.8
34.9
30.3
29.5
33.0
48.5
53.4
58.5
53.3
65.5
54.3
44.7
35.4
12.7
7.9
6.5
4.1
18.1
23.8
16.3
17.3
12.8
18.9
14.5
14.4
26.1
12.2
7.4
7.6
Table 4
Effect of particle size on PFC3D macroproperties
Particle size Davg (mm)
5.95
3.05
2.04
1.53
Macroproperty (63.4
31.7
E (GPa, %)
n (, %)
57.3
64.0
67.6
69.2
0.231
0.254
0.255
0.256
10.0
3.9
1.8
1.2
31.7 mm3 specimens, n=10, mean and coefficient of variation)
21.2
8.1
5.8
5.5
qu (MPa, %)
f (deg, %)
c (MPa, %)
st (MPa, %)
127.9
169.6
186.9
198.8
25.9
30.6
32.3
32.1
40.0
48.4
51.6
55.1
43.6
35.4
33.0
27.1
11.9
3.4
1.5
3.6
14.2
9.8
9.2
7.4
11.4
7.6
6.9
7.6
27.8
26.1
21.9
13.7
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clear increasing or decreasing trends. For the three
smallest particle sizes, f and c exhibit the most
variability of all measured properties.
The Brazilian strength exhibits a clear dependence
upon particle size, with st decreasing from 65.5 to
35.4 MPa as particle size decreases from 2.87 to
0.36 mm. The coefficients of variation have converged
to approximately 7.5%. The variability of st is slightly
greater than that of qu : This suggests that the criticalstate conditions in a Brazilian test are more sensitive
to packing and strength heterogeneities than are
the critical-state conditions in an unconfined compression test.
The measured decrease in Brazilian strength with
decreasing particle size is explained in Section 5.2, where
it is shown that Brazilian strength is proportional to
fracture toughness, which, in turn, is proportional to
particle size. The lack of a similar size effect for qu
suggests that the critical state in an unconfined
compression test on the PFC2D material does not
consist of the unstable growth of a single macrofracture
subjected to extensile conditions. We speculate that a
more complex critical state exists in which a failure
plane and secondary macrofractures form under mixed
compressive-shear conditions, and that such conditions
are not sensitive to particle size.
3.5.2. PFC3D material response
The Poisson’s ratio is independent of particle size. The
Young’s modulus exhibits a clear dependence on
particle size, with E increasing from 57.3 to 69.2 GPa
as particle size decreases from 5.95 to 1.53 mm. The
characterization of the elastic grain-cement micropron
s
perties in terms of E c ; Ē c ; ðkn =ks Þ; and ðk̄ =k̄ Þ provides a
size-independent means of specifying the Poisson’s ratio
of the material, but the Young’s modulus exhibits a
minor size effect.
The unconfined compressive strength exhibits a clear
dependence on particle size, with qu increasing from
127.9 to 198.8 MPa as particle size decreases from 5.95
to 1.53 mm. The coefficients of variation have converged
to approximately 3.5%. The reason for this size effect is
unknown. It corresponds with general observations that
finer-grained rock is stronger than coarser-grained rock
(medium and fine-grained Lac du Bonnet granite
[61,62]). A credible explanation must encompass the
fact that qu of the PFC2D material is independent of
particle size.
No definitive statements about the effect of particle
size on friction angle and cohesion can be made based
on the results in Table 4, although both properties seem
to increase as particle size decreases.
The Brazilian strength exhibits a clear dependence
upon particle size, with st decreasing from 43.6 to
27.1 MPa as particle size decreases from 5.95 to
1.53 mm. The coefficients of variation have not yet
1345
converged. The variability of st is much greater than
that of qu : This suggests that the critical-state conditions
in a Brazilian test are more sensitive to packing and
strength heterogeneities than are the critical-state conditions in an unconfined compression test.
3.6. Effect of stress and damage on elastic constants
The elastic constants of the BPM are affected by both
stress and damage. These effects have been quantified
using a ‘‘strain probe’’, which applies a specified strain
path to the particles at the boundary of an extracted
core and monitors the stress–strain response using
measurement regions within the core. Preliminary
measurements performed upon the granite model
indicate a reasonable correspondence with the properties of Lac du Bonnet granite [53]. The elastic constants
are affected by the stress state as follows. Compressive
loading induces microtensile forces that act orthogonal
to the compressive direction, and the particle motions
that produce these microtensile forces modify the fabric
(distribution of force chains) of the assembly. Increasing
the mean stress increases the coordination number
(average number of contacts per particle), which
modifies the magnitudes of the elastic constants but
does not produce anisotropy. Anisotropy is produced by
deviatoric stresses that modify the directional distribution of the force chains—compressive loading increases
the number of contacts oriented in the compressive
direction and decreases the number of contacts oriented
orthogonal to the compressive direction. These effects
are enhanced by the presence of damage in the form of
bond breakages. The elastic modulus dependence on
mean and differential stress, as identified in PFC
modeling, has been qualitatively supported by in situ
measurements of dynamic modulus [63]. Ongoing work
[64] aims to develop a quantitative link between AE/MS
field measurements of dynamic moduli and rock-mass
damage by comparing the evolution of stress- and
damage-induced modulus anisotropy in the PFC3D
model with the results of both short- and long-term
laboratory tests.
4. Measured macroscopic properties (field scale)
Three sets of boundary-value simulations were
performed to demonstrate the ability of the twodimensional BPM to predict the extent and fabric of
damage that forms adjacent to an excavation and
the effect of this damage on rock strength and
deformability [53]. The boundary-value simulations
were of three experiments at Atomic Energy of Canada
Limited’s (AECL) Underground Research Laboratory
(URL) near Lac du Bonnet, Manitoba, Canada—
namely, the Mine-by Experiment [65,66], the Tunnel
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Sealing Experiment [67] and Stage 1 of the Heated
Failure Test [68]. The Excavation Stability Study [69]
also was simulated using slightly different microproperties. A summary of comparisons between simulations
and in situ observations is provided in Ref. [63].
Extensive work has been done at the URL to
characterize excavation-induced damage [70]. One common feature of this damage is the formation of breakout
notches (apparently in regions where the elastic tangential stress at the excavation boundary exceeds some
critical value). This feature is investigated in the
simulations, which embed the BPM within a larger
continuum model such that only the region of a
single notch is represented by the BPM. Only the results
of the Mine-by Experiment simulations are presented
here.
The Mine-by Experiment took place on the 420-m
level of the URL in sparsely fractured Lac du Bonnet
granite and consisted of carefully excavating a 3.5-m
diameter circular tunnel subparallel with the direction of
the intermediate principal stress. The tunnel was
excavated in 1-m stages by drilling overlapping holes
about the tunnel perimeter, and then removing the
material using hydraulic rock splitters in closely spaced
drill holes in the tunnel face. During tunnel excavation,
a multistage process of progressive brittle failure
resulted in the development of v-shaped notches, typical
of borehole breakouts, in the regions of compressive
stress concentration in the roof and floor (as shown in
Fig. 12). The major and minor in situ stresses are
approximately 60 and 11 MPa, which produce an elastic
tangential stress of 169 MPa in the roof and floor. This
induced stress is lower than the 200 MPa unconfined
compressive strength of the undamaged granite, and
observation and analysis of other excavations at the
420-m level indicate that notches will form when the
elastic tangential stress in horizontal tunnels exceeds
approximately 120 MPa [69].
Various mechanisms have been suggested to account
for the apparent degradation in material strength
sufficient to cause breakout. Two such mechanisms
include precracking, which results from the local
increase and rotation of stresses ahead of the advancing
tunnel face, and stress corrosion—time-dependent
cracking in rock that depends on load, temperature
and moisture [71,72]. Both of these mechanisms are
investigated in Ref. [73] using a simplified form of the
BPM that represents the cement using contact bonds.
(A contact bond provides tensile and shear strengths
only and behaves like a parallel bond with
n
s
k̄ ¼ k̄ ¼ R̄ ¼ 0:) In that work, a time-dependent
strength-degradation process was included in the simplified BPM by reducing the contact-bond strength at a
specified rate if the contact force was above a specified
microactivation force. It was found that (a) precracking
coupled with uniform strength reduction (choosing
microproperties to match the long-term instead of the
short-term strength of the rock) produced spalling and
not distinct notches, and (b) activation of stress
corrosion (for microproperties that match the shortterm strength of the rock) produced notches that
stabilized after approximately 56 h. Subsequent work,
summarized in Ref. [53], utilized the full BPM that
represents the cement using parallel bonds, which allow
one to mimic more closely the micromechanisms
operative during stress corrosion by reducing the
parallel-bond radius at a specified rate if the maximum
tensile stress in the parallel bond is above a specified
microactivation stress. In such models, notches are
formed either by uniformly reducing the material
strength everywhere or by activating stress corrosion.
The difference in model behavior, particularly the ability
to replicate notch development using a uniform strength
reduction for the parallel bonds, is believed to be related
to the use of parallel versus contact bonds. The parallelbonded material becomes much more compliant in the
damaged region than does the contact-bonded material,
thereby shedding more load to the notch perimeter.
4.1. Coupling the BPM with a continuum model
Fig. 12. Photograph of broken and buckled rock slabs comprising the
notch tip in the floor of the Mine-by Experiment tunnel.
The Mine-by Experiment was simulated using a
coupled PFC2D-FLAC [74] model in which only the
potential damage region is represented by the PFC2D
material. The rectangular sample produced by the
material-genesis procedure is installed into a corresponding rectangular void created in a FLAC grid
adjacent to the tunnel surface, and a circular arc is
removed from the particle assembly, corresponding to
the tunnel boundary (see Fig. 13). The basis of the
coupling scheme is that FLAC controls the velocities of
a layer of particles on three sides of the PFC2D region.
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Fig. 13. PFC2D portion of coupled PFC2D-FLAC Mine-by model
(PFC2D granite model with Davg ¼ 32 mm).
PFC2D returns the unbalanced forces of the same set of
particles, and these are applied as boundary forces to the
FLAC grid. A symmetry line, in the direction of the
major principal stress, is used based on the assumption
that cracking is similar in the roof and floor of the
tunnel. The FLAC grid boundaries are placed at a
distance of 10 times the tunnel radius from the center.
The elastic constants to be used in the FLAC grid are
specified, and the FLAC model is run in large-strain
mode under conditions of plane strain. Coupling occurs
during cycling such that each cycle in PFC2D corresponds with a cycle in FLAC.
Initially, the system is regarded as stress free. There
are no initial stresses in the FLAC model, and the initial
stresses in the PFC2D material are low relative to the
final stresses that will develop as a result of the
excavation. In situ stresses are applied to the outer
boundaries of the FLAC grid, and cycling is performed
until equilibrium is established, indicating that the
excavation-induced stress redistribution is complete.
An alternative procedure would be to initialize stresses
in the FLAC grid and install the same mean stresses in
the PFC2D sample (using the stress-installation procedure described in Appendix A) prior to its connection to
the FLAC grid. The resulting relaxation would correspond to the tunnel being created in a stressed material.
Three PFC2D granite materials were produced using
the microproperties in Table 1 with different values of
Dmin : The PFC2D materials have average particle
diameters of 32, 16 and 8 mm, respectively, and this
corresponds with model resolutions of 33, 66 and 132
particles across the 1.05-m extent of the potential
damage region as shown in Fig. 13. The elastic constants
assigned to the FLAC grid were taken as the average
values of Young’s modulus and Poisson’s ratio from
Table 2. Although the PFC2D particle size that
generated the data in Table 2 was much smaller ðDavg ¼
0:72 mmÞ; the results in Table 3 indicate that particle size
1347
has only a minimal effect on the macroscopic elastic
constants.
The modeling sequence mimics the rock genesis
followed by the tunnel excavation. Two forms of
strength reduction: uniform strength reduction, or
activation of stress corrosion, were then applied to
replicate the lower strength long-term response of the
granite. The uniform strength reduction occurs by
multiplying both the tensile and shear strengths of all
parallel bonds by a specified factor. The activation of
stress corrosion introduces a time scale into the
simulations such that the time evolution of the
damage-formation process can be investigated—and,
in cases where all microtensile stresses fall below the
microactivation stress, a time to full damage stability
can be determined. In this paper, the results from fieldscale simulations using a uniform strength-reduction
factor are presented, whereas the stress-corrosion model
is described elsewhere [53] and is only briefly discussed
in the following sections.
4.2. PFC2D model behavior during excavation-damage
studies
In BPM simulations of the Mine-by Experiment, the
notch-formation process is driven by either (a) monotonically increasing the far-field loading, (b) uniformly
reducing the microstrengths (as shown in Fig. 14, which
includes the outline of the excavation, the outline of the
PFC2D material, and a set of dashed circles spaced at
intervals of R=5; where R is excavation radius), or (c)
activating stress corrosion. The notch forms by a
progressive failure process that starts at the excavation
boundary in the region of maximum compression and
proceeds inward. First, a small notch (group of
Fig. 14. Effect of strength-reduction factor on damage patterns in the
potential damage region of the Mine-by model for PFC2D granite
model with Davg ¼ 8 mm: (a) Strength-reduction factor of 0.75 (177
cracks, tensile/shear=129/48); (b) Strength-reduction factor of 0.60
(3428 cracks, tensile/shear=2865/563); (c) Strength-reduction factor of
0.50 (8076 cracks, tensile/shear=6704/1372).
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microcracks) forms. Wing-cracks form near the notch
tip and extend parallel with the current notch boundary,
eventually curving toward and intersecting the boundary, forming slab-like pieces of material. These slabs do
not detach fully, still being joined to the rock mass by
some unbroken bonds, but do become much softer than
the rock mass and, thus, shed load deeper into the rock
mass. This increased load initiates additional wing
cracks, which combine to extend the notch boundary.
During this process, the notch is in a meta-stable state
and only grows if the far-field load is increased, the
microstrengths are reduced, or stress corrosion is active.
The notch is meta-stable because the notch shape
induces a compressive zone to form at the notch tip,
which effectively strengthens the rock mass by reducing
the microtensions that are driving the wing-crack
growth. If the slabs are removed, the notch grows again
to re-establish a new stable shape.
This meta-stable growth process continues until the
notch reaches a critical depth relative to the tunnel
radius, at which time the wing-cracks do not curve back
toward the notch boundary; instead, they curve away
from the boundary, forming what looks like a macroscopic fracture (see Fig. 14(c)). This secondary fracture
is described in Ref. [39] as a ‘‘shear band’’—an
elongated cluster of microcracks that emanates from
the apex of one or both notches and extends approximately parallel with the excavation surface. Although
there is no clear evidence for, or against, the formation
of a shear band in the Mine-by Experiment, such
features are often observed in laboratory tests. The
rupture zone that formed in both the numerical (using
a simplified BPM that represents the cement using
contact bonds instead of parallel bonds) and laboratory
test of a rectangular prism of Berea sandstone containing a circular hole and loaded in a plane strain
(biaxial) test [75] may be such a feature. Potyondy and
Autio [39] offer the following hypothesis regarding
this feature:
It evolves from a band or ‘‘cloud’’ of microcracks.
The formation of this band seems to be related to a
punching-type failure occurring at the top and/or
bottom of the [excavation], in which the applied
load tries to drive an intact rectangular region of
material into the unloaded region surrounding the
[excavation]. (This unloaded region encompasses
the notch tips and results from the presence of the
notches, which are much more compliant than the
surrounding rock and therefore shed load deeper into
the rock away from the [excavation].) The microfailure mode within the shear band need not be of a
shearing type; many tensile microcracks may combine
in an en-echelon fashion to accommodate the
macroscopic shearing motion and thereby produce
the shear band.
4.3. Discussion of simulation results for the Mine-by
models
No significant damage forms as a result of excavation
in any of the BPM simulations of the Mine-by
Experiment; however, application of a strength-reduction factor of 0.6 to the material with Davg ¼ 8 mm
produces a stable breakout notch as seen in Fig. 14(b).
Activation of stress corrosion to the material with
Davg ¼ 8 mm after excavation produces a notch that
grows over time and does not fully stabilize before
reaching the PFC2D-FLAC boundary, which occurs at
a time of approximately 14 years. A notch of similar
extent (but different internal damage fabric) as that
produced by a uniform strength-reduction factor of 0.6
has formed after approximately 2 months of stress
corrosion.
The notch-formation process is sensitive to the
strength-reduction factor, as seen in Fig. 14. It is not
clear what procedure should be used to calibrate the
strength-reduction factor, other than comparing the
final extent of any notches that form in boundary-value
models of excavations. The use of a uniform strengthreduction procedure to predict excavation damage may
be limited to qualitative assessments of the nature of the
possible damage, and use of a properly calibrated stresscorrosion model may be required to make quantitative
assessments. The stress-corrosion model was calibrated
to match the static-fatigue behavior of the granite [76].
The fact that similar notches form for both strengthreduction procedures supports such use of a uniform
strength-reduction approach.
The notch-formation process is sensitive to the
particle size, as seen in Fig. 15. Notches form more
readily in material with smaller particles. One hypothesis to explain this behavior is that the material with
Fig. 15. Effect of particle size on damage patterns in the potential
damage region of the Mine-by model for PFC2D granite models with
strength-reduction factors of 0.6. (a) Davg=32 mm (75 cracks, tensile/
shear=59/16); (b) Davg=16 mm (412 cracks, tensile/shear=325/87);
(c) Davg=8 mm (3428 cracks, tensile/shear=2865/563).
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smaller particles has a lower fracture toughness
(as discussed below). The extent of the notch is
controlled by macroscopic fracture formation in the
form of the wing-cracks described above. Stress
concentrations occur at the tips of these wing-cracks,
giving rise to the conditions for which the principles of
fracture mechanics apply, such that the material
resistance to such macroscopic fracture formation is
measured by the fracture toughness rather than the
unconfined compressive strength.
5. Emergent properties of the BPM
Systems composed of many simple objects commonly
exhibit behavior that is much more complicated than
that of the constituents [77]. The particles and contacts
comprising the BPM are described by simple equations,
with few parameters, but an assembly of such particles
displays a rich spectrum of behaviors that closely
resemble those of rock.
The following behaviors are observed both in rock
samples and in synthetic samples composed of bonded
particles:
1. Continuously non-linear stress–strain response, with
ultimate yield, followed by softening or hardening.
2. Behavior that changes in character, according to
stress state; for example, crack patterns are quite
different in the tensile, unconfined- and confinedcompressive regimes.
3. Memory of previous stress or strain excursions, in
both magnitude and direction. This behavior is
commonly expressed in terms of moving yield
surfaces, or evolving anisotropic damage tensors.
4. Dilatancy that depends on history, mean stress and
initial state.
5. Hysteresis at all levels of cyclic loading/unloading;
cyclic energy dissipation is strongly dependent on
cyclic amplitude.
6. Transition from brittle to ductile shear response as
the mean stress is increased.
7. Dependence of incremental stiffness on mean stress
and history.
8. Induced anisotropy of stiffness and strength with
stress and strain path.
9. Non-linear envelope of strength.
10. Spontaneous appearance of microcracks and localized macrofractures.
11. Spontaneous emission of acoustic energy.
It may be noted that there is no existing continuum
constitutive model that reproduces all of these behaviors. Some models can reproduce selected items, but,
usually, many ad hoc parameters are needed. An
assembly of bonded particles exhibits all of the
1349
behaviors, using few microparameters (but at the
expense of often quite lengthy calibration procedures).
Further, continuum-based models (typically implemented via finite or boundary element techniques) have
difficulty reproducing the spontaneous development of
many microcracks and macrofractures. BPMs explicitly
represent the evolution of damage (in terms of the
density and orientation of microcracks), in contrast to
continuum models, which commonly contain evolution
laws that are phenomenological, and not mechanistically based.
Many of the noted behaviors arise from the existence
of many sites of non-linear response, each of which may
be activated at a different stress level. Thus, the memory
of a previous stress level, at which unloading occurred, is
encoded by a set of contacts that are either on the point
of sliding or opening/closing. In either case, a change in
response occurs at a particular stress level when a
contact starts to slide or it opens or closes. Each such
contact site contributes to the stress-dependent, nonlinear response of the entire assembly—not only in
magnitude but also in direction, because the contact
activation depends critically on its orientation in
relation to the direction of applied strain.
Similar arguments may be made for the micromechanical bases of the other phenomena noted above. The
following focus is on a single aspect of the emergent
behavior of the BPM—namely, the ability to reproduce
the fracturing behavior of a brittle material and its
application to explain the size effect observed in
Brazilian tests.
5.1. The reproduction of fracture mechanics behavior
BPMs produce patterns of bond-breaks that are
qualitatively similar to microcracks and extended cracks
seen in real rock samples. Although bond-breaks in a
particle assembly might appear conceptually different
from monolithic cracks that propagate in a brittle
continuum, it is possible to establish a formal equivalence between the mechanisms and parameters of the
BPM and the concepts and equations of LEFM.
Consider the bonded-disk assembly shown in Fig. 16,
in which a ‘‘crack’’ (an unbonded line of contacts) is
introduced into a cubic packing of unit-thickness (t ¼ 1)
disks of radius R joined by contact bonds with kn =ks ¼
2:5 and subjected to an extension strain normal to the
crack. Large tensile contact forces occur at contacts in
front of the crack tip, as shown by the red lines. The
force magnitudes conform well with those that would be
induced over finite line segments in front of a crack tip
in an isotropic linear elastic continuum; see Fig. 17, in
which the LEFM values are derived as follows.
For a through-thickness crack of half-width a in an
infinitely wide plate of isotropic linear elastic material
subjected to a remote tensile stress, sf ; acting normal to
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versus disk sequence number. The BPM values are from
a symmetric model containing 64.5 disks along the crack
width and model boundaries at a distance of 3a and 2a
above and in front of the crack, respectively.
Having established that forces in the BPM conform
well to those induced on line segments in a continuum,
the next step is to examine the maximum contact force
existing at m ¼ 1;
pffiffiffiffiffiffi
¼ 2sf t aR:
(29)
F max
n
Fig. 16. Force distribution and displacement field near the crack tip in
a cracked cubically packed contact-bonded disk assembly.
Noting that the mode-I stress
pffiffiffiffiffiffi intensity factor for the
system is defined as K I ¼ sf pa; Eq. (29) can be written
as
rffiffiffiffi
R
max
:
(30)
F n ¼ 2tK I
p
The true tensile strength of the BPM (i.e., the strength
from a test in which no force concentrations exist) is
denoted by s0t : For a cubically packed BPM loaded
parallel with the packing direction, s0t ¼ fn =2Rt; where
fn is the contact-bond tensile strength (in force units).
At the condition of incipient failure, or crack extension,
F max
¼ fn and K I ¼ K Ic ; where K Ic is the mode-I
n
fracture toughness. Substituting into Eq. (30),
pffiffiffiffiffiffiffi
(31)
K Ic ¼ s0t pR:
Fig. 17. Normalized tensile force of LEFM and BPM at the five
contacts ahead of the crack.
the crack, the induced stress, sn ; acting on the crack
plane near the crack tip ðr
aÞ is [78]
rffiffiffiffiffi
a
sn ¼ sf
;
(26)
2r
where r is the distance from the tip. The force, F n ; acting
over a line segment equal to a disk diameter (2R) at a
mean distance r ¼ ð2m 1ÞR is given by
rffiffiffi Z rþR
Z rþR
a
Fn ¼
sn t dr ¼ sf t
r1=2 dr
2
rR
pffiffiffiffiffiffi pffiffiffiffi pffiffiffiffiffiffiffiffiffiffiffiffirR
¼ 2sf t aRð m m 1Þ;
ð27Þ
where m is a positive integer denoting the disk sequence
number. The tensile forces in the BPM are compared
with those of LEFM in Fig. 17 by plotting normalized
force
F~ n ¼
pffiffiffiffi pffiffiffiffiffiffiffiffiffiffiffiffi
Fn
pffiffiffiffiffiffi ¼ m m 1
2sf t aR
(28)
The fracture toughness is thus related to the properties of the BPM. Notably, because particle radius enters
into the expression, particle sizes cannot be chosen
arbitrarily if it is required to match fracture toughness.
This is not surprising, as the concept of fracture
toughness implies an internal length scale, whereby the
ratio of fracture toughness to material strength has the
dimension of square root of length. The particle size in
the BPM supplies this internal length scale.
The foregoing analysis is based on incipient failure
and does not address the condition for propagation of a
crack. Considering Eq. (29), the new induced force, F 0n ;
following breakage of the bond nearest the crack tip, is
found by substituting the new crack length for the
original crack length:
pffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi
pffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi
F 0n ¼ 2sf t ða þ 2RÞR ¼ F max
1 þ 2R=a:
(32)
n
Thus, the new maximum contact force is always
greater than the previous maximum and greater than the
bond strength. This condition ensures that the crack will
propagate in an unstable fashion. The analysis assumes
that the crack is remote from other boundaries and that
the far-field load remains constant, but proximate
boundaries or fixed-grip loading might cause F 0n to be
less than F max
if the breaking of the critical bond leads
n
to a force on the next bond that is less than the bond
strength. In such a case, the crack would not propagate;
thus, the condition for propagation is not necessarily a
local one, but depends on the influence of the complete
model on the contact forces near the crack tip.
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The derivation for fracture toughness in Eq. (31) is
based on the assumption of a cubically packed contactbonded assembly with perfectly brittle bonds. The
toughness for more general cases is obtained by testing
a set of self-similar Center Cracked Tension specimens,
as shown in the inset of Fig. 18. This system is
characterized by two length scales
f¼
a
1
¼ ;
W 3
c¼
a
;
2R
(33)
where W is the specimen half-width and c is the crack
resolution. A set of self-similar specimens is generated
by varying c while keeping f and particle size, R; fixed.
For LEFM conditions, the applied far-field tensile stress
at incipient failure, s0 ; is [78]
K Ic
pffiffiffi a1=2 ;
CðfÞ p
1=2
pf
½1 0:025f2 þ 0:06f4 :
CðfÞ ¼ sec
2
s0 ¼
ð34Þ
This equation is normalized by dividing by the true
tensile strength and setting a ¼ c2R to obtain
"
#
s0
K Ic
pffiffiffiffiffiffiffiffiffi c1=2 :
(35)
¼ 0
s0t
st CðfÞ 2pR
For each specimen, s0 is measured and normalized
strength versus crack resolution is plotted in log–log
space. If the slope equals minus one-half, then LEFM
conditions apply, and
pffiffiffi pffiffiffiffiffiffiffi
K Ic ¼ ½10b CðfÞ 2s0t pR;
(36)
where b is the y-intercept.
The results of a set of self-similar tests on the cubically
packed contact-bonded material with brittle bonds and
bonds that have softening slopes one-fifth and one-tenth
1351
of the loading slope are shown in Fig. 18. Results similar
to those for the softening slope of k=10 were obtained
for an arbitrarily packed contact-bonded assembly with
brittle bonds assigned both uniform and normally
distributed strengths. These results support the postulate
that
pffiffiffiffiffiffiffiffiffi
ðcontact-bonded materialÞ;
(37)
K Ic ¼ s0t paR
where aX1 is a non-dimensional factor that increases
with packing irregularity, strength heterogeneity and
bond ductility. The value of aR represents the apparent
internal length scale of the BPM. The a values are
obtained from the y-intercepts of the tests by comparing
Eqs. (36) and (37) to obtain
2
K Ic
pffiffiffiffiffiffiffi ¼ 2ð10b Cð1=3ÞÞ2 :
a¼
(38)
s0t pR
For the cubically packed contact-bonded material
with brittle bonds, softening slope k=5 and softening
slope k=10; using the last five data points, the slopes are
–0.47, and the y-intercepts are –0.1590, 0.0980 and
0.0034, giving a values of 1.11, 1.46 and 2.26,
respectively. Therefore, the effect of decreasing the
softening slope is to increase the apparent internal
length scale of the material, making it possible to match
a given K Ic for several different particle sizes. The
asymptotic slope of all curves (at large crack resolutions) approaches minus one-half, but they are shifted to
the right for increasing ductility. This is consistent with
an increase in apparent length scale.
The expression for fracture toughness in Eq. (37) only
applies to a contact-bonded material. The results of a set
of self-similar tests on the cubically packed paralleln
s
bonded material (with l̄ ¼ 1; k̄ =k̄ ¼ 2:5 and s0t ¼ l̄ s̄c )
are also shown in Fig. 18. The parallel-bonded material
Fig. 18. Normalized strength of self-similar numerical specimens.
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is weaker than the contact-bonded material for the same
true tensile strength, because a non-zero bending
s
moment, M̄ ; develops at the crack tip and increases
the maximum tensile stress acting on the bond periphery
(see Eq. (16)). This leads us to postulate that
pffiffiffiffiffiffiffiffiffi
K Ic ¼ bs0t paR
ðparallel-bonded materialÞ;
(39)
where aX1 is a non-dimensional factor that increases
with packing irregularity, strength heterogeneity and
bond ductility, and bo1 is a non-dimensional factor
that accounts for the weakening effect of the bending
moment. For the results shown in Fig. 18, a ¼ 1; and b
is obtained from the y-intercept of the tests (0.3623) by
comparing Eqs. (36) and (39) to obtain
pffiffiffi
K Ic
b ¼ 0 pffiffiffiffiffiffiffi ¼ 10b Cð1=3Þ 2
st pR
pffiffiffi
¼ 100:3623 Cð1=3Þ 2 ¼ 0:66:
ð40Þ
Fig. 18 also provides evidence for a size effect
whereby the behavior becomes plastic (strength independent of crack resolution) at small crack resolutions
and brittle (conforming to LEFM with a slope of minus
one-half) at large crack resolutions. This behavior, in
terms of specimen size, is reported extensively for
laboratory tests [79]. In the present analysis, increasing
crack resolution corresponds with increasing specimen
size.
The BPM has been shown to be equivalent to a
material described by LEFM in terms of observable
behavior and mathematical description. However, the
results cast fracture mechanics in a new light. The
singularities discussed extensively in the literature of
fracture mechanics simply do not arise in a discontinuous medium. Therefore, there is no need to propose
devices, such as a process zone or tip plasticity, to
eliminate the crack-tip singularity. The analysis of the
initiation and stability of a crack in a BPM may be done
in terms of forces, not global energy balance, as
commonly done for fractures in a continuum [80,81].
Finally, the BPM shows naturally how size effect arises,
in terms of the ratio between specimen size and particle
size. A discontinuum interpretation of fracture mechanics has been given previously, notably by Eringen
[82], who derives an equation almost identical to
Eq. (31) and remarks: ‘‘No poorly known constant such
as surface energy appears. . .’’ (in reference to the
existence of surface energy in the Griffith criterion). An
extensive comparison between BPMs and the results of
fracture mechanics is given in Ref. [83].
single macrofracture that travels across the specimen
parallel with the direction of loading. The macrofracture
is comprised of tensile microcracks and is driven by
extensile deformation across the crack path similar to an
LEFM mode-I crack as shown in Fig. 19. The
conditions at peak load can be idealized as shown in
Fig. 20, where the wedge-shaped damage regions are
replaced by edge cracks of length a: If the two cracks are
not interacting ðD 2a4aÞ; then the mode-I stressintensity factor at each crack tip is
pffiffiffi
K I / s a;
(41)
where s is the tensile stress acting across the uncracked
ligament. At peak load, K I ¼ K Ic ; s ¼ st and a ffi 0:2D
(observed for all particle sizes of the granite models),
Fig. 19. Damage in Brazilian specimen just past peak load (148 cracks,
tensile/shear=125/23).
5.2. Relating Brazilian strength to fracture toughness
During Brazilian tests on BPMs, a wedge-shaped
region of cracks forms inside of the specimen below each
platen. Then, at peak load, one of the wedges initiates a
Fig. 20. Idealized conditions in Brazilian specimen at peak load
showing two cracks subjected to tensile loading across the uncracked
ligament.
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which can be substituted into Eq. (41) to give
K Ic
st / pffiffiffiffi ;
D
(42)
where D is the diameter of the Brazilian disk. The form
of Eq. (42) is the same as the empirical relation between
fracture toughness and tensile strength of st ¼ 6:88K Ic
suggested by Zhang [84]. Eq. (42) suggests that the
Brazilian strength should increase as specimen size
decreases, and this trend is exhibited by Lac du Bonnet
granite, for which the Brazilian strength is about
10 MPa for specimens greater than 50-mm diameter
and increases to about 15 MPa for specimens smaller
than 50-mm diameter [55].
The analysis leading to Eq. (39) supports the postulate
that
pffiffiffiffi
K Ic / s̄c R;
(43)
where s̄c ¼ t̄c is the mean parallel-bond strength with
l̄ ¼ 1; and R is the mean particle radius. Combining
Eqs. (42) and (43) yields
rffiffiffiffi
R
st / s̄c
(44)
D
which suggests that the Brazilian strength is affected by
the ratio of particle size to Brazilian disk diameter. If
model resolution, C; is defined as the average number of
particles across the Brazilian disk ðC ¼ D=2RÞ; then
models with constant C will have the same Brazilian
strength. For example, if all other microproperties are
kept fixed, then the same Brazilian strength will be
measured by either doubling the size of the Brazilian
disk for a fixed particle size, or halving the particle size
for a fixed Brazilian disk size. The BPM for granite
exhibits such dual-model similarity as shown in Fig. 21.
Fig. 21. Dual-model similarity: If all microproperties are kept fixed,
then the exact same six short-term macroproperties in Table 3 are
measured for both models B and C.
1353
The test results in Table 3 indicate that the Brazilian
strength decreases as particle size decreases. The same
trend is suggested by Eq. (44). The test results are
compared with Eq. (44) by plotting ðst =s̄c Þ versus ðR=DÞ
on a log–log scale. The test data are well fit by a straight
line with slope of approximately 0.3, whereas Eq. (44)
suggests a slope of one-half. The slope will only be onehalf if LEFM conditions apply, but such conditions do
not apply here because (1) the microcracks at peak load
do not form sharp macrofractures, and (2) the crack
resolution ðc ¼ a=2R ffi 0:2D=2RÞ is relatively small
ranging from 2.2 to 17.6. Eq. (44) can be expressed as
st
/ c1=2
(45)
s̄c
and the test data compared with Fig. 18 to see that the
test data lies in the range of c for which the slope is less
than minus one-half (indicating a size effect whereby the
behavior is more plastic than brittle) for the two reasons
cited above.
6. Conclusions
The BPM approximates the mechanical behavior of
rock by representing it as a cemented granular material.
The model has been used to predict damage formation
adjacent to excavations in Lac du Bonnet granite. The
damage-producing mechanisms activated in rock loaded
in compression are complex and not understood fully.
There is a complex interplay occurring between the
macroscale compression and the induced microscale
tensions, which drives the damage processes. This
interplay produces non-linear, anisotropic elastic behavior under low loads before any significant damage
forms, and it subsequently controls the damage that
results under higher loads. In addition, it contributes to
the long-term strength degradation processes, such as
stress corrosion, that are activated by the increased
stresses adjacent to an excavation but which appear to
be inactive (at least on engineering time scales) under in
situ conditions.
Particle size controls model resolution but is not a free
parameter; instead, particle size is related directly to
the material fracture toughness. When modeling damage
processes for which macroscopic fractures form, the
particle size and model properties should be chosen
to match the material fracture toughness as well as
the unconfined compressive strength. Such processes
occur at the boundary of an excavation and contribute
to the formation of breakout notches. This poses a
severe limitation on the size of a region that can be
represented with a BPM, because the present microproperty characterization is such that the particle
size must be chosen to be of the same order as the
grain size.
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The BPM for Lac du Bonnet granite, as presented
here, has the following limitations. The material
strength matches that of Lac du Bonnet granite only
for stresses near the uniaxial state—i.e., the tensile
strength is too high, and the slope of the strength
envelope as a function of confining stress is too low.
However, there is evidence to support the postulate that
including complex-shaped, breakable grains of a size
comparable to that of the rock will remove this
limitation. Also, computations are time-consuming
and are limited to small volumes of rock, unless the
BPM is embedded within a larger continuum model.
Despite the limitations noted above, BPMs have a
number of advantages when compared with conventional continuum approaches. Damage and its evolution
are represented explicitly in the BPM as broken bonds;
no empirical relations are needed to define damage or to
quantify its effect on material behavior. Localized
microcracks form and coalesce into macroscopic fractures without the need for re-meshing or grid reformulation. Complex non-linear behaviors arise as emergent
features, given simple behavior at the particle level; thus,
there is no need to develop constitutive laws to represent
these effects. BPMs provide a rational means of
incorporating additional physical processes that occur
at the grain scale, such as fluid flow [85], stress corrosion
[53] and thermal loading [86]. In addition, secondary
phenomena, such as AE, occur in the BPM without
additional assumptions.
In principle, the BPM is capable of representing all of
the significant physical behavior mechanisms in rock.
The BPM is complete in the sense of Linkov [87], who
describes a hypothetical model that encompasses all
aspects in a causal chain of events that occur in a
geomechanical medium. The links in his chain of
processes are elastic distortion, creep deformation,
dynamic instability, bifurcation and localization and
transient equilibrium. Linkov emphasizes that a model
embracing all of these features would be able to produce
synthetic seismograms during a simulation [88], for
example, of underground construction. The BPM
provides such a complete model and reproduces
qualitatively all of the mechanical mechanisms and
phenomena that occur in rock, although adjustments
and modifications may be necessary to obtain quantitative matches in particular cases.
Ongoing work [64] is addressing three-dimensional
modeling of excavation damage. There are two thrusts
to this work. The first addresses computational limitations inherent in performing such simulations. A scheme
called AC/DC (adaptive continuum/discontinuum) is
being developed that replaces elastic regions (remote
from cracks) by a continuum formulation, represented
by a linear matrix, thus achieving economies in
computation time. The switch between continuum and
discontinuum is done automatically, such that a BPM is
in place in time for cracking to occur. The second thrust
focuses on rock physics and aims to develop a
quantitative link between passive monitoring (of AE/
MS events and velocity surveys) and rock mass damage
by developing a BPM that can reproduce the evolution
of the stress- and damage-induced modulus anisotropy
in the rock. If it can be shown that such a BPM exhibits
the same modulus anisotropy as the rock, then it is likely
that the damage in such a BPM is similar to the damage
in the rock. Also, the relations between BPM properties
and fracture toughness are being explored to determine
if one can develop a BPM material with a fracture
toughness that is independent of particle size.
Acknowledgements
Much of the development of the bonded-particle
model has been funded by Atomic Energy of Canada
Limited and Ontario Power Generation during the years
1995–2001 as part of its Thermal-Mechanical Stability
Study, with a goal of producing a mechanistically based
numerical model that can predict excavation-induced
rock-mass damage and long-term strength of Lac du
Bonnet granite. We also thank Fabian Dedecker (Itasca
Consultants S.A.) for performing the triaxial and
Brazilian tests on the PFC3D material as part of a
project co-funded by the European Commission and
performed as part of the fifth EURATOM framework
program, Nuclear Fission (1998–2002).
Appendix A
All vector and tensor quantities are expressed using
indicial notation with respect to a fixed right-handed
rectangular Cartesian coordinate system: the position
vector is denoted by xi and the stress tensor is denoted
by sij : The Einstein summation convention is employed;
thus, the repetition of an index in a term denotes a
summation with respect to that index over its range. For
example, the traction vector ti ; acting in the direction ni ;
is given by ti ¼ sij nj ¼ si1 n1 þ si2 n2 þ si3 n3 : Vertical
braces denote the magnitude of a vector or the absolute
value of a scalar. The notation ½;i denotes differentiation
with respect to the coordinate xi and a dot over a
variable indicates a derivative with respect to time (e.g.,
x_ i ¼ @xi =@t). The Kronecker delta, dij ; and the permutation symbol, eijk ; are employed.
A.1. Stress-measurement procedure
The average stress, s̄ij ; in a volume, V ; of material is
defined by
Z
1
sij dV
(46)
s̄ij ¼
V V
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where sij is the stress acting throughout the volume. For
a particulate material, stresses exist only in the particles;
thus, the integral can be replaced by a sum over the N p
particles contained within V as
1 X ðpÞ ðpÞ
s̄ij V ;
s̄ij ¼
V N
(47)
p
where s̄ðpÞ
ij is the average stress in particle ðpÞ: In the
same way, the average stress in a particle ðpÞ can be
written using Eq. (46) as
Z
1
ðpÞ
ðpÞ
s̄ij ¼ ðpÞ
sðpÞ
(48)
ij dV :
ðpÞ
V
V
The identity
S ij ¼ dik S kj ¼ xi;k Skj ¼ ðxi Skj Þ;k xi Skj;k
(49)
holds for any tensor S ij : Applying this identity to the
stress in a particle, one can write
Z
1
ðpÞ
ðpÞ
ðpÞ
s̄ij ¼ ðpÞ
(50)
xi skj
xi skj;k dV ðpÞ :
;k
V
V ðpÞ
The stress in each particle is assumed to be continuous
and in equilibrium. In the absence of body forces, the
equilibrium condition is sij;i ¼ 0: The volume integral in
Eq. (50) is re-written as a surface integral by applying
the Gauss divergence theorem to the first term and
noting that the second term vanishes in the absence of
body forces such that
Z
1
ðpÞ
xi sðpÞ
nk dSðpÞ
s̄ij ¼ ðpÞ
kj
V
S ðpÞ
Z
1
ðpÞ
xi tðpÞ
ð51Þ
¼ ðpÞ
j dS ;
ðpÞ
V
S
where S ðpÞ is the particle surface, nk is the unit outward
normal to the surface and tjðpÞ is the traction vector. If
the moment carried by each parallel bond is neglected,
then each particle is loaded by point forces acting at
discrete contact locations, and the above integral can be
replaced by a sum over the N c contacts as
s̄ðpÞ
ij
1 X ðcÞ ðcÞ
¼ ðpÞ
xi F j ;
V Nc
(52)
ðcÞ
where xðcÞ
i is the location and F j is the force acting at
ðcÞ
contact ðcÞ: F j includes both F i and F̄ i from Eqs. (4)
and (13), and the negative sign is introduced to ensure
that compressive/tensile forces produce negative/positive stresses.
The contact location can be expressed as
ðcÞ
ðpÞ
ðpÞ ðc;pÞ
xðcÞ
;
(53)
i ¼ xi þ xi xi ni
is the location of the particle centroid and
where xðpÞ
i
nðc;pÞ
is
the
unit-normal
vector directed from the particle
i
1355
centroid to the contact location. By substituting
Eqs. (53) into (52) and noting that
X ðcÞ
Fj ¼ 0
(54)
Nc
for a particle in equilibrium, one obtains
1 X ðcÞ
ðpÞ ðc;pÞ ðcÞ
s̄ðpÞ
xi xi ni F j :
ij ¼ ðpÞ
V Nc
(55)
An expression for the average stress in a volume, V ; is
obtained by substituting Eq. (55) into (47); however,
definition of the volume in the resulting expression is
problematic because of the particles that intersect the
measurement region. The problem is overcome by
noting that, in a statistically uniform assembly, the
volume associated with each particle is V ðpÞ =ð1 nÞ;
such that
V ðpÞ
;
(56)
1n
where n is the porosity of the region. The average
stress in a measurement region is found by combining
Eqs. (47), (55) and (56) to yield
0
1
B 1 n C X X ðcÞ
ðpÞ ðc;pÞ ðcÞ
(57)
s̄ij ¼ @P ðpÞ A
xi xi ni F j ;
V
Np Nc
V¼
Np
where the summations are taken over the N p particles
with centroids contained within the measurement region
and the N c contacts of these particles, n is the porosity
within the measurement region, V ðpÞ is the volume of
particle ðpÞ; xðpÞ
and xðcÞ
i
i are the locations of a particle
centroid and its contact, respectively, nðc;pÞ
is the uniti
normal vector directed from a particle centroid to its
contact location, and F ðcÞ
j is the force acting at contact
ðcÞ; which includes both F i and F̄ i from Eqs. (4) and (13)
but neglects the parallel-bond moment.
A.2. Strain-rate measurement procedure
The procedure employed to measure local strain rate
within a particle assembly differs from that used to
measure local stress. In determining local stress, the
average stress within a volume of material is expressed
directly in terms of the discrete contact forces, as the
forces in the voids are zero. It is not correct, however, to
use the velocities in a similar way to express the average
strain rate, as the velocities in the voids are non-zero.
Instead of assuming a form for the velocity field in the
voids, a velocity-gradient tensor, based on a best-fit
procedure that minimizes the error between the predicted and measured velocities of all particles with
centroids contained within the measurement region, is
computed. The strain-rate tensor is the symmetric
portion of the velocity-gradient tensor.
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Before describing the least-squares procedure, the
relation between the strain and strain rate will be
reviewed, and the corresponding terms defined. The
relation between the displacements ui at two neighboring points is given by the displacement gradient tensor,
aij : Let points P and P0 be located instantaneously at xi
and xi þ dxi ; respectively. The difference in displacement between these two points is
dui ¼ ui;j dxj ¼ aij dxj :
(58)
The displacement-gradient tensor can be decomposed
into a symmetric and an anti-symmetric tensor as
aij ¼ eij oij
where eij ¼ 12ðui;j þ uj;i Þ;
infinitesimal-strain tensor
and
oij ¼ 12 ðuj;i ui;j Þ; rotation tensor:
(59)
In a similar fashion, the relation between velocities vi
at two neighboring points is given by the velocitygradient tensor, a_ ij : (The velocity field is related to the
displacement field by ui ¼ vi dt; in which vi is the velocity
and dt is an infinitesimal interval of time.) Let points P
and P0 be located instantaneously at xi and xi þ dxi ;
respectively. The difference in velocity between these
two points is
dvi ¼ vi;j dxj ¼ a_ ij dxj :
(60)
The velocity-gradient tensor can be decomposed into
a symmetric and an anti-symmetric tensor as
_ ij
a_ ij ¼ e_ij o
where
e_ij ¼ 12 ðvi;j þ vj;i Þ; strain-rate tensor
and
_ ij ¼ 12 vj;i vi;j ;
o
spin tensor:
(61)
a_ ij is computed using the following least-squares
procedure. The velocity-gradient tensor computed over
a measurement region represents the best fit to the N p ðpÞ
measured relative velocity values V~ i of the particles
with centroids contained within the measurement
region. The mean velocity and position of the N p
particles is given by
P ðpÞ
P ðpÞ
Vi
xi
V̄ i ¼
Np
and
Np
x̄i ¼
Np
Np
;
(62)
where V iðpÞ and xðpÞ
are the translational velocity and
i
centroid location, respectively, of particle ðpÞ: The
measured relative velocity values are given by
ðpÞ
V~ i
¼
V ðpÞ
i
V̄ i :
(63)
For a given a_ ij ; the predicted relative velocity values v~ðpÞ
i
can be written, using Eq. (60), as
_ ij x~ ðpÞ
_ ij ðxðpÞ
v~ðpÞ
i ¼a
j ¼a
j x̄j Þ:
(64)
A measure of the error in these predicted values is
given by
X ðpÞ
X ðpÞ
ðpÞ 2
ðpÞ
~ ðpÞ ;
V
v~ðpÞ
v~i V~ i
z¼
v~i V~ i ¼
i
i
Np
Np
(65)
where z is the sum of the squares of the deviations
between predicted and measured velocities. The condition for minimum z is that
@z
¼0 :
@_aij
(66)
Substituting Eq. (64) into Eq. (65) and differentiating,
the following set of nine equations is obtained:
2 P ðpÞ ðpÞ P ðpÞ ðpÞ P ðpÞ ðpÞ 3
x~ 3 x~ 1
x~ 2 x~ 1
x~ 1 x~ 1
Np
Np
78 _ 9
6 Np
7> ai1 >
6
=
< >
6 P ðpÞ ðpÞ P ðpÞ ðpÞ P ðpÞ ðpÞ 7>
7
6 x~ 1 x~ 2
~
~
~
~
x
x
x
x
2
2
3
2
a_ i2
7
6N
Np
Np
>
7>
6 p
;
: >
7>
6
4 P ðpÞ ðpÞ P ðpÞ ðpÞ P ðpÞ ðpÞ 5 a_ i3
x~ 1 x~ 3
x~ 2 x~ 3
x~ 3 x~ 3
Np
Np
Np
9
8 P ðpÞ
>
V~ i x~ 1ðpÞ >
>
>
>
>
>
>
Np
>
>
>
>
>
>
>
=
< P ðpÞ ðpÞ >
~
V i x~ 2
:
¼
Np
>
>
>
>
>
>
>
>
>
>
>
>
> P V~ ðpÞ x~ ðpÞ >
>
;
:
i
3 >
ð67Þ
Np
These nine equations are solved by performing a
single LU decomposition upon the 3 3 coefficient
matrix and performing three back substitutions for
the three different right-hand sides obtained by setting
i ¼ 1; 2 and then 3. In this way, all nine components of
the velocity-gradient tensor are obtained. (For the
PFC2D model, four equations are used to obtain the
four non-zero values of the velocity-gradient tensor.)
A.3. Stress-installation procedure
The stress-installation procedure installs a general
state of uniform stress (i.e., stress that does not vary with
position) within an arbitrarily shaped particle ensemble.
The intended use is to initialize internal stresses—not to
apply stress boundary conditions. The procedure is
based upon the following relations. The displacementgradient tensor, aij ; can be decomposed into a symmetric
and an anti-symmetric tensor [89] as
@ui
¼ ui;j ¼ eij oij
@xj
¼ 12 ui;j þ uj;i 12 uj;i ui;j ;
aij ¼
ð68Þ
where eij is the infinitesimal-strain tensor and oij is the
rotation tensor. The velocity-gradient tensor, a_ ij ; relates
the velocities vi ¼ u_ i at two neighboring points. Let the
ARTICLE IN PRESS
D.O. Potyondy, P.A. Cundall / International Journal of Rock Mechanics & Mining Sciences 41 (2004) 1329–1364
points P and P0 be located instantaneously at xi and
xi þ dxi ; respectively. The difference in velocity between
these two points is
dvi ¼
@vi
dxj ¼ vi;j dxj ¼ a_ ij dxj :
@xj
(69)
The velocity at an arbitrary point xj (expressed as
vi ðxj Þ) is found by integrating Eq. (69) with respect to
position. Let x̄j be a fixed reference position, then
Z xj
Z xj
Z xj
@
_
ðeij oij Þ dxj ;
dvi ¼
aij dxj ¼
@t
x̄j
x̄j
x̄j
Z xj
vi ðxj Þ v̄i ¼
ð70Þ
e_ij dxj ;
x̄j
where a condition of no rotation has been enforced by
setting oij ¼ 0 in Eq. (68). If the time derivative of the
strain tensor is approximated by
Deij
;
(71)
NDt
where Deij is a strain increment applied over N time
steps, each of size Dt; then the velocity field can be
written as
Deij
(72)
vi ðxj Þ ¼ v̄i þ
ðxj x̄j Þ
NDt
e_ij ffi
by assuming that the strain field does not vary with
position. (If the strain field did vary with position, one
could express the variation explicitly before performing
the integration and thus obtain a final expression for the
velocity that would depend upon the parameters used to
characterize the strain-field variation.)
The stress-installation procedure utilizes an iterative
approach whereby a set of boundary (and possibly also
interior) particles is moved, then the boundary particles
are fixed, the interior particles are freed and staticequilibrium conditions are allowed to develop. During
each iteration, the applied particle displacements are
computed from the strain increment that is related by
linear elasticity to the stress increment needed to reach
the target stress. The iterations continue until the target
stress is obtained. The stress field is measured by
averaging the stresses within a set of measurement
regions that cover the ensemble. The stress increment is
defined as the difference between the target stress and
the current stress
Dsij ¼ stij sij
(73)
and the corresponding strain increment is found by
assuming isotropic, elastic behavior:
1þn
n
(74)
Dsij Dsaa dij :
Deij ¼
E
E
The applied particle velocities are given by Eq. (72),
where x̄j and v̄i are chosen as the initial position and
velocity of the ensemble centroid, respectively. Good
1357
performance is achieved by setting n ¼ 0; N ¼ 10 and
E ¼ 2E 0 ; where E 0 is an estimate of the ensemble
modulus. (Note that when E is greater than the true
ensemble modulus, the strain required to reach the
target stress will be underestimated; thus, the stresses
will converge to the target stress from below in a smooth
fashion. If E is too small, the stresses at the end of each
iteration will overshoot the target stress; the stresses will
then oscillate about the target stress and not converge.)
A stress field can also be installed within an ensemble
containing holes by including the hole boundaries in the
set of boundary particles. For such a system, the installed
stress field will not sense the presence of the holes. Such a
scheme has been used to model a tunnel excavation
without having to include particles within the tunnel
itself. After installing the desired stress field, the tunnel
boundary particles are freed to allow stress redistribution
to occur as the tunnel is now sensed by the system.
During the procedure, displacements can be applied to
designated boundary particles or to all particles. For cases
in which the material remains primarily elastic, applying
displacements to all particles will: (1) speed convergence
(as it will not be necessary to allow the entire system to
respond to boundary displacements in order to reach final
equilibrium; instead, the entire system is made to
correspond with the required strain field instantaneously
during each iteration); and (2) produce a stress field that is
nearly uniform throughout the ensemble. Such would not
be the case if either the boundary particles alone or a set
of confining walls were moved, because then non-uniform
force chains would develop throughout the ensemble,
producing a locally non-uniform stress field—for compressive conditions, a compressive cage that shields the
internal region from the full compressive stresses often
forms. Note, however, that for cases in which localized
failure occurs, the strain field is locally non-uniform.
Thus, for such cases, it may be more appropriate to move
only the boundary particles.
A.4. Ball-generation procedure
A procedure is described to generate a collection of
particles of a given uniform size distribution with radii
in the range ½Rmin ; Rmax that fill a given area, A; or
volume, V ; at a given porosity, n: The basic algorithm is
presented first. It makes use of two relations that are
derived at the end of this section.
The number of particles, N; that satisfies the above
constraints is given by
8
Að1 nÞ
>
>
;
PFC2D
<
2
Rmin þ Rmax
pR̄
with R̄ ¼
:
N¼
>
3V
ð1
nÞ
2
>
:
; PFC3D
3
4pR̄
(75)
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These particles are chosen from a uniform size
distribution with radii in the range 12 ½Rmin ; Rmax and
placed randomly within the specified region such that
they do not overlap one another or the region boundary.
The particles are generated at half their target sizes to
ensure that the no-overlap criterion can be satisfied.
Next, the porosity of the generated assembly, n0 ; is
computed, and the radii of all particles are multiplied by
the factor
1 n 1=l
m¼
where
1 n0
(
2; PFC2D;
ð76Þ
l¼
3; PFC3D:
The radius multiplier must be computed (i.e., it will
not equal 2) because Eq. (75) is an approximation.
Eq. (76) is derived as follows. The porosity, n; of a
collection of particles contained within an area, A; or
volume, V ; is defined as
8
A Ap
>
<
; PFC2D;
A
n¼
(77)
>
: V V p ; PFC3D;
V
where Ap and V p are the total area and volume,
respectively, of all particles given by
X
Ap ¼
pR2 ;
X4
Vp ¼
pR3 ;
ð78Þ
3
P
where
is over all particle radii, R: By combining Eqs.
(77) and (78), one can write
X
Að1 nÞ
;
R2 ¼
p
X
3V ð1 nÞ
R3 ¼
:
ð79Þ
4p
Denoting the old porosity and radii by n0 and R0 ; the
new porosity and radii by n and R; and using Eq. (79),
one can write
P l
R
1n
(80)
¼P l:
1 n0
R0
If the same radius multiplier, m; is used for all
particles, then R ¼ mR0 ; which can be substituted into
Eq. (80) to obtain Eq. (76). Thus, given a collection of
particles of porosity, n0 ; within an area, A; or volume,
V ; Eq. (76) is an exact expression of the radius multiplier
for all particles necessary to obtain a porosity,Pn:
Eq. (75) arises from the approximation
that Rl of a
P l
uniform distribution is equal to
R̄ of a collection of
same-size particles of size R̄: This approximation can be
expressed as
X
X l
l
Rl ¼
(81)
R̄ ¼ N R̄ ;
which can be substituted into Eq. (79) to obtain
Eq. (75).
A.5. Isotropic stress installation procedure
The isotropic stress, s0 ; of a particle assembly is
defined as the average of the direct stresses
s0 ¼
s̄kk
l
where l ¼
2;
PFC2D;
3;
PFC3D:
(82)
In the scheme described here, the radii of all particles
are scaled iteratively to modify the isotropic stress of the
assembly. Combining Eqs. (55) and (47), an expression
is obtained for the average stress, s̄ij ; in a volume, V ; of
material
1 X X ~ ðc;pÞ ðc;pÞ ðcÞ
R ni F j ;
(83)
s̄ij ¼
V N N
p
c
ðc;pÞ
ðpÞ
where R~
¼ xðcÞ
x
i
i : The isotropic stress can then
be evaluated by
1 X X ~ ðc;pÞ nðcÞ
s̄kk
s0 ¼
¼
R F
(84)
lV N N
l
p
c
nðcÞ
is the normal component of the force acting
where F
at contact ðcÞ: If the radii of all particles is scaled by the
same factor, a; such that the change in radius is
DRðpÞ ¼ aRðpÞ
(85)
and it is assumed that all particles remain fixed, then the
change in the normal component of force acting at each
contact will be
DF nðcÞ ¼ aK nðcÞ fðcÞ ;
( ðAÞ
R þ RðBÞ ;
fðcÞ ¼
RðpÞ ;
particle2particle contact;
particle2wall contact;
ð86Þ
where K nðcÞ and fðcÞ are the normal stiffness and particle
radii, respectively, at contact ðcÞ: Substituting in the
incremental form of Eq. (84) gives
a X X ~ ðc;pÞ nðcÞ ðcÞ
Ds0 ¼
R K f :
(87)
lV N N
p
c
Rearranging this expression gives
a ¼ PP
lV Ds0
:
ðc;pÞ
R~ K nðcÞ fðcÞ
(88)
Np Nc
Ideally, this formula enables one to determine the
change in radii that will produce a given change in
isotropic stress. However, some particle rearrangement
occurs when the radii are changed, so formula (88) is
applied several times, until the measured isotropic
stress is within some tolerance of the target isotropic
stress.
ARTICLE IN PRESS
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A.6. Floater-elimination procedure
When a particle assembly is compacted, even under
the condition of zero friction, typically 10% to 15% of
the particles are found to have no contacts. These
particles are termed ‘‘floaters’’, because they are
detached from the material matrix and appear to be
floating in space. In physical specimens of an unbonded,
granular material, such as sand, floaters are believed to
exist, and it is reasonable, therefore, to accept their
presence in a numerical specimen. However, if a particle
model is used to represent a solid material, such as rock,
each floater is equivalent to a void in the material. The
effect of such voids on material response can be
minimized by adjusting microproperties to obtain
correct ensemble properties—nevertheless, the voids
introduce a pattern of inhomogeneity that has no
physical counterpart. The effect of this inhomogeneity
is unknown and may be small. To be safe, steps can be
taken to eliminate its source; an algorithm to eliminate
floaters is described here. It may be argued that a
‘‘solid’’ consisting of bonded circular or spherical
particles, even with no floaters, contains many voids.
However, in a dense assembly, these voids are inaccessible during deformation, because they are too small to
allow particles to move into them. In this sense, they are
invisible as far as potential mechanisms are concerned.
The starting point for the algorithm is a stable,
compacted assembly with no bonds in which all contacts
carry similar levels of force (i.e., the force distribution is
fairly uniform). Further, the average stress level is low
compared to the final stress level to be carried by the
material. The algorithm expands and moves floaters
until every particle has the specified minimum number
of contacts. The key to success (i.e., elimination of all
floaters) is the recognition that it is not necessary to
enforce local equilibrium. If the assembly were destined
to become an unbonded granular medium, then
equilibrium of the final state would be required (and
floater elimination made more difficult). However, a
bonded material always carries locked-in forces of
magnitudes that are related to the levels of contact
forces existing at the instant of bonding. These locked-in
forces typically are made low compared to the forces
carried by the material in its operating range. Extra
forces of low magnitude (e.g., one-tenth of pre-bonding
contact forces) introduced by the floater-elimination
algorithm add little to the existing ‘‘noise’’ of locked-in
forces, even though the forces are not in local
equilibrium. After bonding, equilibrium is again established, with final forces at levels comparable to their prebonding levels.
In summary, the algorithm is described as follows. All
particles except floaters are fixed and given zero
velocities. Floaters are then expanded by a large amount
(30%), sufficient to ensure contact with all of their
1359
immediate neighbors. After being cycled to local
equilibrium, the floaters are contracted by an amount
(see Eq. (94)) that is calculated to reduce their mean
contact normal force below a target force (one-tenth of
the mean contact normal force for the assembly). If the
mean contact normal force for a particle is below the
target force, then it is declared ‘‘inactive’’ and is not
contracted further at this stage. The contraction step is
applied repeatedly until all floaters become inactive.
After executing this iteration, the number of active
floaters is reduced considerably. The complete procedure is repeated several times until all floaters have
been removed. The algorithm works well, because
the adjustments to floater radii (and positions, through
the law of motion) are done for small groups within
a ‘‘cage’’ of fixed particles. As mentioned, it is
only necessary to establish equilibrium within this
trapped group. Then, as floaters themselves become
part of the cage, the scheme becomes increasingly
more efficient as the number of particles in each floater
group decreases.
The following parameters control the algorithm: N f
(minimum number of contacts to be a non-floater, set to
3 in our granite models); M r (initial radius multiplier, set
to 1.3); f m (target fraction of F̄ a ; set to 0.1); F r
(relaxation factor, set to 1.5); and H (hysteresis factor,
set to 0.9). The following variables are used in the
algorithm: F̄ a (mean contact normal force for entire
assembly); F̄ p (mean contact normal force for single
particle); R (particle radius); and kn (particle normal
stiffness). The algorithm is defined by the following
pseudo-code.
Perform this outer loop up to 10 times.
Get current mean contact normal force for
the assembly, F̄ a :
Scan all particles to identify floaters: a
floater is
a particle with less than N f contacts.
If no floaters, then EXIT outer loop.
Fix all non-floaters.
For all floaters:
–expand by M r ,
–set friction to zero.
Cycle 200 steps to get floater groups to
equilibrium.
Perform this inner loop up to 100 times.
Define ‘‘active’’ floaters. An active
floater is a particle with more than one
contact and mean contact normal force
greater than f m F̄ a :
If no active floaters, then EXIT inner
loop.
Shrink each active floater according to
the formula:
R :¼ R F r ðF̄ p H F̄ a f m Þ=kn :
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Cycle 100 steps to obtain approximate
equilibrium.
End of inner loop.
End of outer loop.
In order to speed up the algorithm, contact calculations are inhibited whenever the two particles comprising any contact are fixed. The inhibit flags are removed
upon exit from the algorithm. For a large assembly, it is
found that one or two floaters may be positioned almost
exactly between two non-floaters such that the two
contact directions are nearly coaxial. The algorithm
cannot establish more than two contacts in this case. To
allow convergence, the parameter N f is reduced by one
if the same number of overall floaters is observed
between iterations of the outer loop.
The objective of the shrinkage procedure is to reduce
the mean contact normal force on a particle below some
target force, F target ¼ F̄ a f m ; by setting
R
R F r ðF̄ p H F̄ a f m Þ=kn :
(89)
This expression is now derived. The mean normal
force on a single particle is given by
1 X nðcÞ
F̄ p ¼
F
(90)
Nc N
c
nðcÞ
is the normal component of the force acting
where F
at contact ðcÞ: The normal force at each contact is
changed by the following amount, if the radius is
changed by DR; assuming that particles remain fixed
during the radius change:
DF n ¼ 12 kn DR;
(91)
where kn is the particle normal stiffness. Thus, the new
0
mean normal force, F̄ p ; is
1 X nðcÞ
0
(92)
F̄ p ¼
F
þ DF n :
Nc N
c
Then, for the new mean normal force to be below the
0
target normal force, set F̄ p ¼ HF target ; where H is a
factor less than unity. Thus,
kn DR
1 X nðcÞ
1 X nðcÞ
þ
F
þ DF n ¼
F
HF target ¼
Nc N
2
Nc N
c
c
(93)
and
DR ¼ 2ðF̄ p H F̄ a f m Þ=kn :
(94)
This expression is identical to Eq. (89), except that F r
replaces the factor of two. It is found that setting F r
equal to 1.5 gives smoother convergence, because the
radii of several neighboring particles are likely to be
adjusted simultaneously. A value of F r less than 2
provides some damping in the algorithm, preventing
excessive oscillation and possibly instability. A value of
H ¼ 0:9 also prevents ‘‘noise’’, caused when particles
satisfy the force criterion by only a small margin
(thus possibly requiring multiple adjustments).
A.7. Biaxial, triaxial and Brazilian testing procedures
The macroscopic properties of the model material
are obtained by performing biaxial, triaxial and
Brazilian tests, in which each specimen is confined and
loaded by pairs of opposing frictionless walls. These
are the walls of the material vessel used during material
genesis. For the biaxial and triaxial tests, the top
and bottom walls act as loading platens, and the
velocities of the lateral walls are controlled by a servomechanism that maintains a specified confining stress.
Strictly speaking, the biaxial and triaxial tests simulate
a polyaxial loading test—not a triaxial test, in which a
specimen is encased in a membrane and confined
by fluid pressure. Such a triaxial test could be simulated
by replacing the side walls with a sheet of particles
joined by parallel bonds to mimic the elastic membrane.
The current biaxial and triaxial tests inhibit specimen
bulging, whereby the specimen sides deform into
a barrel shape, because the side walls remain straight.
Such bulging should be minimal for granite, but may be
important for softer rocks or cohesive soils.
The lateral wall normal stiffnesses are set equal to a
fraction (0.001–0.02 in PFC2D and 0.001–0.10 in
PFC3D for confinements of 0.1–70 MPa) of the average
particle normal stiffness to simulate a soft confinement.
For the Brazilian test, the specimen is trimmed into a
circular (in PFC2D) and cylindrical (in PFC3D) shape
that is in contact with the lateral walls, and the lateral
walls act as loading platens. For all tests, the loadingplaten normal stiffnesses are set equal to the average
particle normal stiffness. The tests are run under
displacement control such that the platens move toward
one another at a constant rate. Hazzard et al. [49] ran
similar tests with a servo-control to move the platens, so
as to maintain a constant cracking rate, and observed a
snap-back in the stress–strain response. Platen velocities
of 0.05 m/s are chosen to ensure quasi-static test
conditions, which are confirmed by demonstrating that
reducing the platen velocities does not alter the
measured macroproperties.
The advantage of using the material-vessel walls to
perform these tests is that the boundary particle
alignment produces a rather uniform force transmission
from the walls to the specimen—i.e., there are no
particles protruding from the specimen and producing
localized loading. However, the boundary particles tend
to be aligned with these walls (see Fig. 5(d)) and, thus,
are not fully representative of the internal microstructure. The model material mimics a sandstone created by
first filling a vessel with sand, compacting the sand, and
then cementing the sand at grain-grain contacts. A rock
specimen that has been cored and polished is also not
ARTICLE IN PRESS
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fully representative of the internal microstructure, but
for a different reason—namely, there is grain-scale
damage at the specimen boundaries. Both of these
specimen-creation processes will affect measured properties, but if the grains in the real rock and the particles
in the modeled rock are small relative to the specimen
dimensions, then these effects should be minimal. A
more representative measure of the internal microstructural properties of the model material can be obtained
by removing all particles outside of a nominal core
region, identifying a set of boundary particles and
specifying their motion while monitoring stress and
strain within the core using a stress-installation procedure. Such measures are used to measure the evolving
properties within selected regions of the model surrounding an excavation.
Stresses and strains are computed using the specimen
dimensions at the start of the test. Stresses are computed
by dividing the average of the total force acting on
opposing walls by the area of the corresponding
specimen cross section. Stresses in the PFC2D models
are computed assuming that each particle is a disk of
unit thickness. Strains are computed by monitoring the
motion of pairs of gauge particles that lie along the
global coordinate axes at the centers of the specimen
faces. (For both PFC2D and PFC3D models, the
specimen axis is parallel with the global y-axis.)
Computing strains via gauge particles removes the error
introduced by particle–wall overlap when using the
distances between opposing walls to compute strain.
The elastic constants are computed using the stress
and strain increments occurring between the start of the
test and the point at which one-half of the peak stress
has been obtained. For the PFC3D material, the
Young’s modulus is computed by
E¼
Dsy
Dy
ðPFC3D materialÞ
(95)
and the Poisson’s ratio is computed by
1
ðDx þ Dz Þ
Dx
¼ 2
u¼
Dy
Dy
1
Dv
1
¼
ðPFC3D materialÞ;
2
Dy
ð96Þ
where the average of the two lateral strains is used to
approximate the lateral strain, and volumetric strain
Dv ¼ Dx þ Dy þ Dz : These relations are valid for
constant lateral stress during the test. For the PFC2D
material, first the Poisson’s ratio and Young’s modulus
corresponding with a state of plane stress are computed as
Dx
Dy
Ds
y
E0 ¼
:
Dy
n0 ¼
ðPFC2D material; plane stressÞ;
ð97Þ
1361
Eq. (97) is valid for the case of plane stress ðsz ¼ 0Þ
and constant lateral stress ðDsx ¼ 0Þ during the stress
and strain increments. Then, the elastic constants
corresponding with a state of plane strain are obtained
via
n0
ðPFC2D material; plane strainÞ;
1 þ n0
E ¼ E 0 ð1 n2 Þ:
n¼
ð98Þ
Eq. (98) is the general relation between plane-stress and
plane-strain conditions [90].
When calibrating the PFC2D model, E and n (not E 0
and n0 ) are compared with the elastic constants
measured during triaxial tests on real rock specimens.
Recall that the PFC2D model behaves as an assembly of
unit-thickness disks. The conditions are neither plane
strain nor plane stress, because the corresponding
stress–strain constitutive relations are not employed—
i.e., the out-of-plane forces and displacements do not
enter into the force–displacement law. Therefore, the
elastic constants of the PFC2D model are measured
by interpreting the force–displacement response. For
the same PFC2D model, one force–displacement response is measured, but two sets of elastic constants,
corresponding with plane-stress and plane-strain conditions, are computed. If a region of a 2D isotropic elastic
continuum were extracted and replaced with this
model material, and the corresponding set of elastic
constants were assigned to the remaining continuum,
then the deformation state of the model material
would match that of the continuum—i.e., there would
be full displacement compatibility along the extraction
boundary. This procedure is used in the construction
of boundary-value models of excavation damage in
which the model material is inserted into a pre-defined
region within a larger continuum model. For a tunnel
simulation, the continuum model is run in planestrain mode and assigned the plane-strain elastic
constants E and n:
The initiation of cracking in the PFC models is
controlled by the ratio of standard deviation to mean
material strength. Increasing this ratio lowers the stress
at which the first crack initiates. However, the axial
stress at the time of the initiation of the first crack in a
synthetic specimen will underestimate the crack-initiation stress, sci ; measured in typical laboratory experiments. Therefore, sci measured during a biaxial or
triaxial test of a PFC model is defined as the axial stress
at which there exists a specified fraction (chosen as 1%
in the present simulations) of the total number of cracks
existing at peak stress. The choice of 1% is rather
arbitrary, and sci serves as a qualitative calibration
property providing a means to match the onset of
significant internal cracking before ultimate failure.
(For Lac du Bonnet granite, sci ¼ 0:45qu :)
ARTICLE IN PRESS
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