<html><head><meta name="color-scheme" content="light dark"></head><body><pre style="word-wrap: break-word; white-space: pre-wrap;">\documentclass[granma]{svjour}
\usepackage{graphicx}
%\input{totalin.grm}
%\idline{Granular Matter 1, 1-6}{1}
%
\begin{document}
\title{A Fast Model for the Simulation of Non-round Particles}
\author{Alexander V. Potapov and Charles S. Campbell}
\institute{Department of Mechanical Engineering \\
University of Southern California \\
Los Angeles, Ca. 90089-1453, USA}
\date{}
\maketitle

\abstract{%
This paper describes a new, computationally efficient model for the discrete
element simulation of a certain class of non-round particles. The boundaries
of the particles in this model are constructed from the circular segments of
different radii in such a way that connections between these segments are
continuous. As such, the model does not permit the simulation of arbitrarily
shaped particles, but it does allow a wide enough variety of shapes to assess
the effects of non-round shapes (in particular, particle interlocking) in an
efficient maner. A direct test of the model's performance demonstrates that
the model is much more efficient than other models for non-round particles
currently available and is less than two times slower than models for the
same number of round particles.}

\section{Introduction}

In recent years, soft particle discrete element simulations have pro\-ven to be
a powerful tool for investigating the behavior of granular systems. All of
these simulations (see the reviews in \cite{camp86,camp97}) follow individual
particles as they move, rotate and interact with their neighbors. In a real
granular system the forces generated when particles are in contact result in
small changes in the particle shape, particularly around the points of
contact. However, in the simulation, it is generally assumed for simplicity's
sake, that individual particles do not change shape. Instead their surfaces
are allowed to overlap slightly and, in an approximation of the true elastic
response, generate a repulsive response which is a function of that overlap.
Virtually any imaginable dependence of the contact force on the overlap may
be incorporated into the model, e.g. simple linear elastic, Hertzian or some
other.

At present time, the majority of the soft particle discrete element
simulations have been performed using round particles for both
two-dimensional and three-dimensional systems \cite{camp86,camp97}. The
round
shape is very easy to simulate in the sense that every point on its surface
can be determined simply by knowing the position of the center and its
diameter; in particular, there is no dependence on the orientation of the
particle. As a result, it is easy to determine the overlap between two
particles simply as the distance between their centers minus the sum of their
radii. Also, it reduces memory requirements as only the center position need
be stored.

However the use of round particles has several limitations. Near\-ly all
natural particles are not round, a quality which is shared even by artificial
particles that are intended to be round (e.g. commercial glass beads).
Furthermore, non-round particle shape can create a vast difference in the
mechanical behavior because they do not roll easily. For example, bulk
materials composed of round particles have angles of repose that are much
smaller than natural materials (see, for example \cite{posch93}). One
solution to this problem is to not allow the particles to rotate at all, but
instead interact only frictionally. Realistic angles of repose may be
obtained using this technique, but it in no way clear that the resulting
material accurately simulates all the effects of non-round particles. In
particular, realistic particles may interlock with one another and produce
behavior that cannot be approximated by a simple friction at the surface of
round particles. Another technique is to introduce the special force term
\cite{cund79} to account for the \ Coulomb's law behavior commonly
associated with granular materials, but this moves the simulation even
farther from real situation.

The most natural solution for this problem is to use particles that are not
round. Several such model have been proposed. In general they can be divided
into two classes. In the first, an analytic representation of the shape of a
particle is used for which it is possible to simplify the contact and overlap
determinations. For example, algorithms have been developed for particles
with elliptic (e.g. \cite{roth91,roth92,ting92,kohr93}) or superquadric (e.g.
\cite{will89,must93}) shapes (the superquadric particle shape is described by the
same equation as elliptic one with the only difference is that the
degree is above two). Such particle can interlock like real materials,
but they
do not resemble natural materials. Also, aspect ratios for elliptical
particles must be significantly different from unity in order to obtain
realistic angles of repose, which may present other problems as the majority
of natural granular materials have aspect ratios that are close to unity. \ \
The second type of model assumes that the particles are in the shapes of
arbitrary convex polygons \cite{hogue93,hop92,kohr95,till95,posch95}. (Such a
model forms the basis
of the fracture simulations presented in \cite{pota95a,pota95b,pota96a,pota96b}.) More
realistic looking particles may be created in this manner, but at tremendous
computational costs. Polygonal simulations can take up to an order of
magnitude more computer time than their round counterparts. For analytically
represented particle shapes, (elliptic or superquadric cases) the majority
of the computer time is spent in iterative solutions of the non-linear
equations used to calculate the particle overlap. In the polygonal
simulations, the majority of the computer time is spent calculating
intersections of the sides of contacting polygons which is a necessary part
of the overlap determination.

\begin{figure}
\includegraphics[width=\hsize]{p1.ps}
\caption{The picture of a typical oval. The
boundary of this oval consists
of four arches drawn around points $O_1$, $O_2$, $O_3$ and $O_4$, arches
drawn around points $O_1$ and $O_3$ have the same radius and angles
$\alpha_1$ and $\alpha_3$ are the same. The same is true about the arches
drawn around points $O_2$ and $O_4$ and angles $\alpha_2$ and $\alpha_4$.
Points $O_1$ and $O_3$ are situated in such a way that line connecting these
points pass through the center of an oval, the same is true about the line
connecting the points $O_2$ and $O_4$.}\label{fig1}
\end{figure}


\section{The Description of the Model}


Here we propose a soft particle discrete element model for the simulation of
non-round particles which exhibits a performance that is comparable to the
performance of round particle models and is able to accommodate a much wider
variety of shapes (and more realistic shapes) than the elliptic or
superquadric models. The idea for this model was born from the way the
ellipses are sometimes approximated in technical drawings; when appropriate
elliptical templates are not available, an oval with the same aspect ratio is
often used to approximate the ellipse. An oval is geometric figure whose
boundary is determined by four circular arches of two different radii which
are joined together in a continuous way (i.e. the first derivative is
continuous between the arches) and thus can be drawn with compasses and other
standard tools used to draw circles. However, it is possible to generate more
complex shapes, many nearly polygonal in shape, from circular arches. At the
same time, the determination of contact and overlap between two circular
arches segments is nearly identical to the same procedures for circles. Thus
a simulation of particles generated from circular arches will allow a variety
of shapes to be studied at only a small computational cost beyond that of
round particles.


To illustrate this technique, consider the typical oval presented in
Fig. \ref{fig1}.
The boundary consists of four arches drawn around points $O_1$, $O_2$,
$O_3$ and $O_4$. In a classical oval, the arches drawn around points $O_1$
and $O_3$ have the same radius (we shall call this radius ``large'') and the
angles $\alpha_1$ and $\alpha_3$ are identical. The same is true about the
arches drawn around points $O_2$ and $O_4$ (we shall call this radius
``small'') and the angles $\alpha_2$ and $\alpha_4$. Points $O_1$ and $O_3$
are situated in such a way that line connecting these points passes through
the center of an oval, as does the line connecting the points $O_2$ and $O_4$.

\begin{figure}
\includegraphics[width=\hsize]{p2.ps}
\caption{This picture illustrates the procedure of the calculation of the
contact parameters between a pair of ovals. After the contacting arches are
determined (arches corresponding to angles $\alpha_1$ and $\alpha_2$), the
calculation of the contact parameters can be carried out in the same way as
it is done for the round particles.}\label{fig2}
\end{figure}

Now suppose that we have a granular medium consisting of oval shaped
particles which will be simulated using an otherwise standard soft-particle
discrete element model. To do this, we must at every time step find the
particles which are overlapping, calculate the distance of this overlap and
determine the center of this overlap in order to know the point at which
contact forces are to be applied to the contacting particles. Let us suppose
that we have a contact between two ovals as is shown in Fig. \ref{fig2}.
Any possible
contact must occur between the arch of one oval and the arch of the other
oval. This type of contact can be treated in the same way as the contact of
the two circular particles. Thus the overlap distance is simply the sum of
the two radii of the contacting arches minus distance between the points
around which these arches are drawn (i.e. distance between the points $O_1$
and $O_2$ in Figure \ref{fig2}). The center of the overlap lies in the
line connecting
$O_1$ and $O_2$ \ midway between the points of intersection of this line and
the two arches (point $C$ in the Figure \ref{fig2}).

Compared to the case of round particles, the only additional operation which
is required here is to determine which of the arches may be involved in the
contact. This can be carried out in very simple and effective way. Note that
two ovals can have the contact along a pair of arches if and only if the line
connecting the points around which these arches are drawn lies within the
limits of the angle of both arches (in Figure \ref{fig2} this requires
determining
that the \ line $O_1O_2$ lies between angles $\alpha_1$ and $\alpha_2$). This
is easy to check by calculating the dot products of the unit vector
connecting the points around which the arches are drawn with unit vectors of
the bisectors of the angles of the arches. Plus, the dot product of the
vector connecting the centers of gravity of the ovals and the vector
connecting the points around which the arches are drawn should be calculated
to ensure, by its sign, that the potential contacting arches are oriented
towards rather than away from each other. The calculation of these three dot
products is an additional computational step with respect to the case of the
round particles. However, it is not necessary to perform all three
calculations at each time step. Since the particles do not drastically change
their orientation during a single time step, in the vast majority of cases,
it will only be necessary to check at each time step whether the same two
arches remain in contact. This means the calculation of only the first two
dot products, which is rather fast and straightforward procedure. Also, it is
quite likely that any two arches that are in contact, were in contact during
the previous time step. Consequently, much computer time can be saved by
simply verifying that the contact continues on subsequent time steps. The
calculation of the contacts of the ovals with the straight boundary walls is
performed in much the same way.  \enlargethispage{3pt}

\begin{figure}
\includegraphics[width=\hsize]{p3.ps}
\caption{Examples of the construction of the particles out of the
arches continuously joined to each other (the first derivative is the
same on the both sides of the arch to arch transition point): (a)
approximation of a triangle, (b) approximation of a square, (c)
approximation of a pentagon and (d) approximation of a heptagon.}\label{fig3}
\end{figure}

The model described above is easily extended beyond the case of ovals. Ovals,
like ellipses, have the disadvantage of requiring relatively large aspect
ratios to obtain realistic values of the angles of repose. Much more
complex particles may be constructed in the same way the ovals are
constructed. If the boundary of a particle consists of any number of arches
which are continuously connected together, one can see that the algorithm for
determining contact as described above still holds true. Some examples of
this sort of particles are presented in Fig. \ref{fig3}. For these
particles, a large
radius is used to construct the ``sides'' of the particles and a smaller
radius is used to connected them smoothly together at the ``vertices.''
Clearly, one can easily construct an approximation to a triangle, square,
pentagon and so on, and one can get very close to an actual polygonal shape
as one wishes by making the corresponding radius of curvature of the arches
that form the sides very large and those that form the corners, very small.
(This process is limited only by roundoff errors in the determination of the
overlap. I.e. as the overlap is computed by taking differences, high accuracy
requires that its magnitude be large enough relative to the radius to be
represented by several number significant digits in its floating point
representation within the computer.) If these particles are constructed of
the arches with only two values of radii as it was done for the oval and all
of the shapes in Fig. \ref{fig3}, no additional memory (beyond that
required for an
oval) need be used for the storage of the information about position and
orientation of the particles.

One additional advantage and one additional disadvantage of the model
proposed here should be mentioned. The advantage is that this model has a
fixed value of the radius of curvature at every point of the surface of the
particles that is bounded by continuously joined arches. This makes it
possible to use the Hertzian contact model (which describes the contact
between particles with arbitrary, but finite and non-zero, radii of
curvature) without any additional assumptions - which would be a questionable
for the case of the angular particles. The disadvantage of the model is that
for the moment we can not see its simple three-dimensional implementation.


\section{Demonstration of the Performance of the Mo\-del}

It is clear from the material presented above that the performance of the
proposed model should be only marginally worse than a round particle model as
only a few additional calculations are required. A direct test of this fact
is described in the following.

For the test, we have chosen the problem of settling the particles into a
rectangular box under the influence of the gravity. In the first case, the
particles are round, in the second case, the particles are the same number of
quasi-triangles (Figure 3a), in the third case the particles are
quasi-squares (Figure 3b), in the forth case, particles are of superquadric
shape with superquadric degree 3.0 which are simulated by the technique
described in \cite{must93} and finally, in the fifth case
particles are
square and simulated by the algorithm described in \cite{hop92}.
Linear spring contact laws are assumed for all cases except for the case of
square particles for which the normal contact force was based on the area of
overlap (see \cite{hop92}). The geometry of the boundary walls,
the
particle masses, particle densities, the time step and the coefficient of the
restitution of the particles were the same in all cases. The models were run
on the same Sparcstation 20 computer (75 MHZ processor), for the same period
of simulation time (4.69$\cdot 10^4$ time steps), and the amount of CPU time
expended was determined and compared. The same contact search routine for
near neighbors \cite{hop92} was used in all simulations.

\begin{figure}
\includegraphics[width=\hsize]{p4.ps}
\caption{Results of the simulation of gravity settling round particles.
This simulation has been performed in order to compare the efficiencies of
the models. (a) Initial positions of the particles; (b) positions of the
particles at the end of the simulation.}\label{fig4}
\end{figure}

\begin{figure}[!t]
\includegraphics[width=\hsize]{p5.ps}
\caption{Results of the simulation of the gravity settling of the
quasi-triangular particles in a rectangular box. It was performed for the
same particle mass, same time stepand same time elapsed in the system (same
number of time steps) as the simulation for round particles presented on
Figure 4. (a) Initial positions of the particles; (b) positions of the
particles at the end of the simulation.}\label{fig5}
\end{figure}

\begin{figure}[!t]
\includegraphics*[height=7.3cm,bb=118 219 494 572,angle=-90]{p6.ps}
\caption{Same as Figure 5, but for quasi-square particles}\label{fig6}
\end{figure}

\begin{figure}[!t]
\includegraphics[width=\hsize]{p7.ps}
\caption{Results of the simulation of gravity settling of the same number of
superquadric particles \cite{will89} as on Figure 4. It was
performed
for the same particle mass, same time step and same time elapsed in the
system (same number of time steps) as the simulation for round particles
presented on Figure 4. \ (a) Initial positions of the particles; (b)
positions of the particles at the end of the simulation}\label{fig7}
\end{figure}

\begin{figure}[!t]
\includegraphics*[height=7.1cm,bb=118 219 494 572,angle=-90]{p8.ps}
\caption{Results of the simulation of gravity settling of the same number of
square particles as on Figure 4. It was performed for the same particle mass,
same time step and same time elapsed in the system (same number of time
steps) as the simulation for non-round particles presented on Figure 4. (a)
Initial positions of the particles; (b) positions of the particles at the end
of the simulation.
}\label{fig8}
\end{figure}

The initial positions of the particles are presented in Figure
\ref{fig4}a for the
case of round particles, in Figure \ref{fig5}a for the case of
quasi-triangular
particles, in Figure \ref{fig6}a for quasi-square particles, in Figure
\ref{fig7}a for the
superquadric particles and in Figure \ref{fig8}a for square particles.
Figures
\ref{fig4}b,
\ref{fig5}b and \ref{fig6}b, \ref{fig7}b and \ref{fig8}b depict the
final positions of the particles for these five cases.

\begin{table}
\caption{CPU time spent on SPARC-20 for performimg of $4.69
\cdot
10^4$ time steps}\label{tab1}
\begin{tabular}[t]{|l|l|}
\hline
Particle shape&amp;CPU$\,$time (seconds)\\
\hline
Round &amp;29\\
\hline
Quasi-triangle&amp;48\\
\hline
Quasi-square&amp;51\\
\hline
Superquadric&amp;347\\
\hline
Square&amp;114\\
\hline
\end{tabular}%
\end{table}

The results of the simulation of these cases on a SPARC-20 workstation are
presented in Table \ref{tab1}. These results show the CPU difference of
about
66\%
between the case of round particles and case of the quasi-triangular
particles composed of arches. The case of quasi-square particles is just 4\%
slower than the case of quasi-triangular particles, this time difference is
due to slightly longer procedure of the determination of contacting arches
for quasi-square particles than for quasi-triangular particles due to larger
number of arches. The case of superquadric particles was more than one
order of magnitude slower than the case of round particles. (It is hard to do
exact performance comparisons for this case since the procedure is
iterational and ``exact'' solution is never reached. We used four iterations
per time step here, different number of iterations may produce different
results.) Finally, the model with square particles was almost four times
slower than the model for round particles and thus more than two times slower
that the model proposed in this paper. Thus, the model presented here easily
outperforms every other model for non-round particles available at the
present time.


\section{Conclusions}

In this paper, a model has been proposed for a soft-particle discrete element
simulation of the motion of non-round particles. This model is based on the
construction of a particle boundary out of a set of arches which are
connected to each other so that the first derivative at the point of
transition from one arch to another is the same from both sides. The model
allows us to vary considerably the degree of roughness of a particle surface,
and it performs approximately 60\% slower than a model for the round
particles, thus easily outperforming any other model currently available for
non-round particles.

The model is capable of efficiently simulating nearly polygonal particles.
The main use of this type of simulation is not necessarily to simulate the
actual shapes of the particles in naturally occurring materials, but to
provide a way of adding the effects of non-round shapes (in particular,
particle interlocking) into existing simulations.


\begin{thebibliography}{19}
\bibitem{camp86} Campbell, C.S., Computer simulation of rapid granular
flows, Proc. 10$^{th}$ US National Congress of Applied Mechanics, Austin
Texas, June 1986, ASME, New York, p.327-338.

\bibitem{camp97} Campbell, C.S., Computer simulation of powder flows, to
appear in Powder Techology Handbook, Second Edition. (Gotoh et al. eds)
Dekker, New York, 1997, 777-793.

\bibitem{posch93} Poschel, T. \&amp; Buchholtz, V., Static
Friction Phenomena in
Granular Materials: Coulomb Law versus Particle Geometry, Physical Review
Letters 71 (1993), p. 3963-3966.

\bibitem{cund79} Cundall, P.A. \&amp; Strack, O.D.L., A discrete numerical model
for granular assemblies, Geotechnique 29 (1979), p.47-65.

\bibitem{roth91} Rothenberg, L. \&amp; Bathurst, R.J., Numerical Simulation of
Idealized Granular Assemblies with Plane Elliptical Particles, Computers and
Geotechnics 11 (1991), p.315-329.

\bibitem{roth92} Rothenburg, L. \&amp; Bathurst, R.J., Micromechanical features
of granular assemblies with plane elliptical particles, Geotechnique 1
(1992), p.79-95.

\bibitem{ting92} Ting, J.M., A robust algorithm for ellipse-based discrete
element modeling of granular materials, Computers and Geotechnics 13 (1992),
p.175-186.

\bibitem{kohr93} Kohring, G.A., Computer simulations of
sintering via granular dynamics, Physica A 195 (1993), p.1-11.

\bibitem{will89} Williams, J.R. \&amp; Pentland, A.P., Superquadric and Modal
Dynamics for Discrete Elements in Concurrent Design, Proc. $1^{st}$ US
Conference on Discrete Element Methods, Golden Colorado, October 1989, (Eds.
Mustoe, G.G.W., Henriksen, M. \&amp; Huttelmaier, H.P.)

\bibitem{must93} Mustoe, G.G.W. \&amp; DePooter, G., A numerical model for the
mechanical behavior of particulate media containing non-circular shaped
particles, Powders and Grains 93, 1993, (Ed. Thornton, C.) Balkena,
Rotterdam, p.421-427.

\bibitem{hogue93} Hogue, C. \&amp; Newland, D.E., Efficient
computer modeling of
the motion of arbitrary grains, Powders and Grains 93, 1993, (Ed. Thornton,
C.) Balkena, Rotterdam, p.413-419.

\bibitem{hop92} Hopkins, M.A., The Numerical Simulation of Systems of
Multitudinous Polygonal Blocks, US Army Cold Regions Research and Engineering
Laboratory, USACRREL Report CR 99-22, 1992.

\bibitem{kohr95}  Kohring, G.A., Melin, S., Puhl, H.,
Tillemans, H.J.,
Vermohlen, W., Computer simulations of critical, non-stationary granular flow
through a hopper, Computer Methods in Applied Mechanics and Engineering 124
(1995), p.273-281.

\bibitem{till95} Tillemans, H.J. \&amp; Herrmann, H.J., Simulating deformations
of granular solids under shear, Physica A 217 (1995), p.261-288.
\newpage

\bibitem{posch95} Poschel, T. \&amp; Buchholtz, V., Molecular Dynamics of
Arbitrarily Shaped Granular Particles, Journal de Physique I 5 (1995),
p.1431-1455.

\bibitem{pota95a} Potapov, A.V., Hopkins, M.A. \&amp; Campbell, C.S., A
Two-dimensional Dynamic Simulation of Solid Fracture.
Part I: Description of the Model, International Journal of Modern
Physics C 6 (1995), p.371-398.

\bibitem{pota95b} Potapov, A.V., Campbell, C.S. \&amp; Hopkins, M.A., A
Two-dimensional Dynamic Simulation of Solid Fracture. Part II: Examples,
International Journal of Modern Physics C 6 (1995), p.399-425.

\bibitem{pota96a} Potapov, A.V. \&amp; Campbell, C.S., A Hybrid
Finite-element
simulation of Solid Fracture, International Journal of Modern Phy\-sics C 7
(1996), p.155-180.

\bibitem{pota96b} Potapov, A.V. \&amp; Campbell, C.S., A Three-dimensional
Dynamic Simulation of Solid Fracture, International Journal of Modern Physics
C 7 (1996), p.717-730.

\end{thebibliography}
\end{document}
</pre></body></html>