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ALE3D: An Arbitrary
LagrangianEulerian
MultiPhysics Code
Charles Noble, Andrew Anderson, Nathan Barton, Jamie
Bramwell, Arlie Capps, Michael Chang, Jin Chou, David
Dawson, Emily Diana, Timothy Dunn, Douglas Faux, Aaron
Fisher, Patrick Greene, Ines Heinz, Yuliya Kanarska, Saad
Khairallah, Benjamin Liu, Jon Margraf, Albert Nichols, Robert
Nourgaliev, Michael Puso, James Reus, Peter Robinson, Alek
Shestakov, Jerome Solberg, Daniel Taller, Paul Tsuji,
Christopher White, Jeremy White
May 23, 2017
ALE3D: An Arbitrary LagrangianEulerian MultiPhysics Code
Lawrence Livermore National Laboratory ii
Disclaimer
This document was prepared as an account of work sponsored by an agency of the United States
government. Neither the United States government nor Lawrence Livermore National Security,
LLC, nor any of their employees makes any warranty, expressed or implied, or assumes any
legal liability or responsibility for the accuracy, completeness, or usefulness of any information,
apparatus, product, or process disclosed, or represents that its use would not infringe privately
owned rights. Reference herein to any specific commercial product, process, or service by trade
name, trademark, manufacturer, or otherwise does not necessarily constitute or imply its
endorsement, recommendation, or favoring by the United States government or Lawrence
Livermore National Security, LLC. The views and opinions of authors expressed herein do not
necessarily state or reflect those of the United States government or Lawrence Livermore
National Security, LLC, and shall not be used for advertising or product endorsement purposes.
Lawrence Livermore National Laboratory is operated by Lawrence Livermore National Security,
LLC, for the U.S. Department of Energy, National Nuclear Security Administration under
Contract DEAC5207NA27344.
LLNLTR732040
Introduction
ALE3D is a multiphysics numerical simulation software tool utilizing arbitraryLagrangian
Eulerian (ALE) techniques. The code is written to address both twodimensional (2D plane and
axisymmetric) and threedimensional (3D) physics and engineering problems using a hybrid
finite element and finite volume formulation to model fluid and elasticplastic response of
materials on an unstructured grid. As shown in Figure 1, ALE3D is a single code that integrates
many physical phenomena.
Figure 1. ALE3D supports a wide range of applications.
ALE3D supports a wide range of simulation needs. The ALE and mesh relaxation capabilities
broaden the scope of application in comparison to tools restricted to Lagrangianonly or
Eulerianonly approaches, while maintaining accuracy and efficiency for large, multiphysics
and complex geometry simulations. For some applications ALE can deliver accuracy similar to
Eulerian techniques using as few as 1/10th the number of mesh elements and a reduction in
memory requirements.
Figure 2 provides a chart showing that ALE3D has an integrated flexible and extendable
architecture. Beyond its foundation as a hydrodynamics and structures code, ALE3D has multi
physics capabilities that integrate various packages through an operator splitting approach.
Additional ALE3D features include heat conduction, chemical kinetics, species diffusion,
incompressible flow, a wide range of material models, chemistry models, multiphase flow, and
magnetohydrodynamics, which can be used in numerous combinations for long (implicit) to
short (explicit) timescale applications.
ALE3D: An Arbitrary LagrangianEulerian MultiPhysics Code
Lawrence Livermore National Laboratory 4
Figure 2. ALE3D has an integrated flexible and extendable architecture supporting a
variety of mesh generators, and material models can be pluggable components.
The discretized domain or mesh may consist of arbitrarily connected hexahedral, shell and beam
elements. In 2D simulations, the mesh can comprise of arbitrarily connected quadrilaterals. The
mesh can be constructed from disjointed blocks of elements that interact at the boundaries via
slide surfaces or other types of boundary conditions.
Large mesh distortions can be addressed via mesh relaxation and/or the use of ALE techniques
where material is advected through the mesh. All components of the code participate in
advection and all the mature capabilities operate with slide surfaces. Advection is the process
whereby the mesh is modified to alleviate tangling or to preserve an Eulerian grid. Advection is
implemented in a Lagrange plus remap fashion. For each cycle, after a Lagrangian motion, the
state variables flow from the original mesh to the modified mesh. The mesh is allowed to cross
material boundaries and create multimaterial elements. The ALE and mesh relaxation capability
broadens the scope of applications in comparison to tools restricted to Lagrangian or Eulerian
(advection) only approaches, while maintaining accuracy and efficiency for large, multiphysics
and complex geometry simulations.
Slide surfaces are boundaries between disjoint sections of the grid that may or may not be in
contact. They represent either physical contact discontinuities or a discontinuity in the zoning.
The unstructured grid is composed of 3D hexagonal elements that can be arbitrarily connected.
Triangular or prismatic elements are not allowed, but shell and beam structural elements can
couple to 3D elements.
The 2D capability includes explicit and implicit hydrodynamics, thermal diffusion, chemistry,
deflagration, shape generation, advection, and most explicit slide surface features.
ALE3D: An Arbitrary LagrangianEulerian MultiPhysics Code
Lawrence Livermore National Laboratory 5
Thermal and chemistry packages are tightly coupled and have been successfully used for long
(implicit) to short (explicit) timescale applications. The incompressible flow module has been
used in simulations of turbulent thermal convection. A multiphase flow package (a continuum
representation of solid particulate transport in solids, liquids and gases and impulse load at
impact) is available for simulation of multiphase fluid, structure interaction. Another package
that solves the magnetohydrodynamics equations (MHD in 3D only) can simulate a variety of
high magnetic field, high velocity, thermal applications.
ALE3D operates on a wide variety of platforms, ranging from laptops to the world’s largest
supercomputers. ALE3D has native implementations for Windows™ and Mac workstations for
smaller scale problem sets, and it is portable to virtually any Unixbased machine with C++/C
and Fortran compilers available. The code will also run in parallel on multiprocessor
Windows™ and Mac machines. While most users will be interested in Linuxbased versions of
the code, it has also been ported to several other lightweight kernel operating systems.
Operation on massively parallel machines has always been a core requirement for the code.
Parallelization is implemented by decomposing the mesh into computational subdomains.
Message passing is the primary mode for communication between domains. The emphasis on
message passing means that it is possible to run parallel computations on a network of
workstations, as well as utilizing multicore processors available on most workstations.
Explicit Hydrodynamics
ALE3D’s hydrodynamics capability captures the behavior of solids and fluids and has been
successfully used for long (implicit) to short (explicit) timescale applications. The explicit
hydrodynamics module was developed to model the behavior of objects undergoing deformation
due to the application of shocks in the kilobar regime. For such problems, the natural time step is
consistent with the Courant time scale which governs the stability of the equations.
The code explicitly conserves mass and momentum. Following DYNA3D (Hallquist, 1982), the
stress gradients and strain rates for the Lagrange step are evaluated by a lowestorder finite
element method. A diagonal mass matrix is used. For secondorder accuracy a staggered space
and time grid is also used. The stress gradient calculation has been modified so that it is
represented by an integral of the shape function over the surface of an element rather than an
integral of the gradient of the shape function over the volume. (The stress in general is
discontinuous at the surface so that the stress gradient is a delta function.) This modification
corrects a problem in which distorted elements generated forces even though the stress field was
constant. Likewise, a more accurate volume calculation is done following J. Dukowicz (JCP)
(1984). Hourglass modes are damped using the method of Flanagan and Belytschko (1981).
The hydrodynamics is energy based rather than temperature based. Energy conservation is not
explicitly enforced but depends on the accuracy of the time integration. This averts the problem
of converting lost kinetic energy into internal energy and overheating materials. The pressure,
viscosity and strain work evaluations are fully time centered. To integrate –PdV for nonlinear
equationsofstate, a thirdorder RungeKutta method is used. Although the explicit
hydrodynamics module is isentropic except at shocks, a temperature variable exists for each
region, and the temperature Equation of State (EOS) can be evaluated either as part of a
constitutive model or from EOS tables.
ALE3D: An Arbitrary LagrangianEulerian MultiPhysics Code
Lawrence Livermore National Laboratory 6
Shocks are treated with a scalar artificial viscosity. The default version simply uses
d
v/v for
compressing elements. Both linear and quadratic terms are available. R. Christensen’s monotonic
artificial viscosity (Christensen, 1990) has also been implemented. This scalar viscosity is
constructed using velocity gradients from which the linear component of the gradient has been
subtracted. The form can be derived from the linearized Riemann problem.
The most commonly used equationsofstate and constitutive models are analytic models using
the MieGrüneisen and SteinbergGuinan forms, respectively (Steinberg, 1980 and 1996).
Several engineering constitutive models are available to facilitate modeling of structures.
Tabular equationofstate models can be accessed through the Livermore equationofstate
(LEOS) tables. The majority of the available material models are for isotropic materials and a
von Mises yield condition is applied. The deviatoric part of the stress tensor is integrated through
time, and the Jaumann stress rate is used to satisfy objectivity. A number of microstructurally
based models have also been added to provide a more accurate representation of damage
evolution mechanisms leading to fracture and to capture anisotropy at both the single crystal and
polycrystal size scales. A few of these latter models do not have timecentered energy
evaluations or use highorder integration for the EOS. For all material models, a NavierStokes
viscosity is available to augment the stress tensor.
For most problems, high explosive (HE) detonation is simulated by using a programmed burn
model with a beta burn override. Several options are available for computing HE lighting times.
Reactive flow models for HE detonation are also available. These models use pressure and
volume dependent rate laws to describe the detonation process. The reactive flow models are
zoning dependent, need high resolution, and may have limited usefulness in 3D.
Implicit Mechanics
The implicit mechanics module was developed to model problems that evolve at time scales that
are orders of magnitude greater than the Courant time scale that determines the stability of the
explicit equations. The implicit hydrodynamics is a finite element displacement formulation with
single or eightpoint integration. Singlepoint integration requires the addition of hourglass
stabilization forces. The formulation solves the nonlinear equilibrium equations using a
NewtonRaphson iteration surrounding a linearization of the equations. This linearization is
based on estimates for material properties, etc., at the end of the time step. Convergence of the
nonlinear iterations is achieved when corrections to the displacements and the nodal forces are
sufficiently small. Slide surface constraints are supported. The implicit time integration can be
run using a quasistatic approximation, or the inertial terms can be included via a HilberHughes
Taylor stabilization of the standard Newmark time integration. The code can convert
automatically from implicit to explicit hydrodynamics when the time step is sufficiently small
that the explicit integration is more computationally efficient. The reverse transfer from explicit
to implicit hydrodynamics is also possible.
Slide Surfaces
The interaction between multiple material surfaces is captured with a numerical technique called
slide surfaces. As mentioned above, slide surfaces model contact discontinuities or mesh
discontinuities. Slide surfaces may be either twosided (master / slave) or singlesided. In two
ALE3D: An Arbitrary LagrangianEulerian MultiPhysics Code
Lawrence Livermore National Laboratory 7
sided surfaces, the nodes of each side interact with the faces of the other side to conserve
momentum and enforce impenetrability. With singlesided surfaces, any node may interact with
any face, barring nearest neighbors. Singlesided slides are useful for surfaces that fold upon
themselves and surfaces consisting of many discrete segments.
There are several options for contact enforcement: the pointonplane method for explicit or
implicit hydrodynamics, the commonplane method (available only for singlesided surfaces) for
explicit hydrodynamics, and a mortar method for implicit hydrodynamics. In addition, ALE3D
provides an automatic slide surface capability with either the pointonplane or commonplane
approach.
For the pointonplane method, slide surface velocities are computed with a momentum
conserving algorithm. Each side of a slide surface is independently accelerated using interpolated
physics quantities from the opposing side. First a node is accelerated as if it were on a free
surface or a surface with a pressure boundary condition. The boundary pressure is the average of
the normal stresses on each side of the surface. The acceleration of the node is decomposed into
normal and tangential components. The normal component for each side is combined with the
interpolated normal component from the opposite side to form a centerofmass acceleration.
This acceleration is used to integrate the velocity. Unless friction is called for, the tangential
acceleration remains that of the free surface. A distinction is then made between master and slave
surfaces for the final application of continuity boundary conditions. This last step corrects for
any lack of perfect continuity in the normal direction due to truncation errors.
Techniques for ordering nodes on one side of the slide surface with respect to nodes on the other
side and for making projections normal to the slide surface are borrowed from DYNA3D. These
techniques have been modified, however, to make them more robust. The ordering algorithm has
been improved so that nodes are not prone to penetrating the slide surface and getting lost. The
normal projection algorithm uses normals that vary across a slide surface element and capture the
effects of curvature of the surface.
The opposing sides of a slide surface may be separated and come into contact during the course
of a calculation. This is called a void. When voids close, the momenta from the opposing sides
are combined to form the centerofmass momentum. The collision is inelastic for the first layer
of nodes on each side of the slide surface. Void closing is always calculated from the perspective
of the master side. This is done to avoid miscounting momentum transferred from one side to the
other if nodes on each side of the surface close in different cycles.
By default, the tangential velocities on each side of a slide surface are decoupled. However,
coulomb friction can be applied. In this case, a tangential force is applied that opposes any
relative velocity. This force is proportional to the normal force that is inferred from the
acceleration required to change the normal velocity from its free surface value to its centerof
mass value. For socalled tied sliding both the normal and tangential accelerations are combined
into centerofmass accelerations. This enables one to use slide surfaces to affect a zoning
change in the middle of a region.
Special provision is made for intersecting or overlapping slide surfaces. Intersections are
assumed to be orthogonal and errors grow to the extent that this condition is violated.
The commonplane method of contact enforcement checks for contact between each pair of
faces, defined as penetration of a plane constructed midway between the two faces. If both faces
ALE3D: An Arbitrary LagrangianEulerian MultiPhysics Code
Lawrence Livermore National Laboratory 8
penetrate the plane, then the intersection of their penetrations projected onto the common plane
is the area of contact, and an opposing force (penalty method) is applied to resist and reverse
penetration. This force is distributed to the nodes of the faces in contact.
The mortar method of contact is a faceonface type of method and is implemented for use with
implicit hydrodynamics. This method considers the faces on one side of a surface that are
connected to a node, and the faces on the other side that overlap these faces, and enforces that a
weighted sum of the gap volumes of the overlap be zero.
At most one slide surface may be designated as an autocontact surface. The faces of the
autocontact surface are not explicitly specified, but typically consist of all external faces (faces
with a zone on only one side) which are not included in any other slide surface.
FEusion Embedded Mesh Coupling
The FEusion library provides an embedded mesh method that allows the coupling of two
separate, spatially overlapping meshes. The embedded mesh approach can greatly simplify the
preprocessing requirements while potentially avoiding many runtime issues related to tangling
of an ALE mesh conforming around Lagrange objects.
The approach used here, which was developed by Puso et al., uses Lagrange multipliers from a
piecewise constant space on the cut background elements to constrain the jump between
background and foreground velocities. A stabilization scheme penalizes the difference in face
adjacent Lagrange multipliers tractions. These multipliers are solved for implicitly using a
conjugate gradient (CG) iterative method on the subset of the mesh where they are active, i.e.,
only on the cut background cells.
Advection
ALE3D uses an arbitrary LagrangianEulerian (ALE) algorithm. The algorithm consists of two
distinct steps: (i) a Lagrangian step that updates nodal positions, nodal velocities, and zonal
quantities, and (ii) a remap/advection step that remaps the results of the Lagrangian step onto a
mesh determined by the relaxation method specified by the user.
In the ALE3D implementation of the ALE algorithm, the Lagrangian step is executed, a new
representation of the mesh is created, and then material variables such as mass, momentum, and
energy are advected from the old mesh to the new mesh. The advection of the material variables
is done by computing fluxes of the state variables between the Lagrangian mesh and the new
mesh. The pressure is recalculated after the remap with a call to the EOS routines. If the
materials have strength, the stress deviators, plastic strain, and other constitutive model variables
are also advected.
The advection step comprises a relaxation phase and an advection phase. An “ideal” grid is first
created using an equipotential or condition number grid relaxation algorithm. (A pure Eulerian
option is also available.) The state variables are then remapped onto the new grid by constructing
fluxes between the old grid and the new grid. The fluxes for extensive variables (mass, internal
energy, and momentum) are conservative. For pure zones, a secondorder, monotonic algorithm
is used to calculate the fluxes. This technique was pioneered by van Leer (1977). Velocities are
updated by applying the results of momentum conservation. This leads to a loss of kinetic energy
ALE3D: An Arbitrary LagrangianEulerian MultiPhysics Code
Lawrence Livermore National Laboratory 9
(which is quadratic rather than linear in the velocity), and highorder advection is required to
limit the loss. As a rule, lost kinetic energy is not added to internal energy to explicitly force total
energy conservation. However, kinetic energy lost in the vicinity of a shock can be put back into
the internal energy field. This is useful for the purpose of propagating shocks over long distances
without degradation.
For problems with several material regions, the process of advection can create mixed elements
in which more than one material region resides in an element. While material region interfaces
are currently not tracked explicitly during the advection step, they are inferred from the volume
fractions of each region in neighboring zones. This is done to determine the order in which
regions are moved from one element to another. The ordering process preserves the integrity of
region objects as they move through the mesh. When volume fractions provide no guidance,
regions are moved from one element to another in the order in which they are numbered, so it
can be very important to order regions in such a way that “more important” (i.e., non
background) materials have lower region numbers. Separate values of the thermodynamic state
variables are maintained for each region in a mixed element, and advection is done using a first
order upwind method. Regions in mixed elements are allowed to relax towards pressure
equilibrium. The relaxation algorithm is based on a linearized solution to the Riemann problem.
Free surfaces are not relaxed unless tangential relaxation is explicitly set up for a free surface
nodeset. Advection can take place up to, but not across, a slide surface. Ordinarily only the slave
nodes of a twosided slide surface are relaxed, but masterside relaxation is available (similar to
tangential relaxation). If necessary, and if slide surface nodes are forced to line up across the
slide surface, the slide surface can be deleted during the course of the calculation and thereby
allow for advection after that time.
Thermal Diffusion
Thermal diffusion is the conduction of heat from a hot to a cold temperature location in a solid or
fluid. The thermal diffusion module was originally incorporated to model manufacturing
processes such as casting, forging, rolling, and extrusion. It is implemented in a manner that
allows for application to most engineering heat transfer problems. The thermal diffusion module
has also been coupled to a chemical kinetics module for the purpose of modeling thermal
ignition of high explosives. The existing capabilities include conduction with orthotropic and
temperature dependent properties, phase changes, enclosure thermal radiation, thermal contact
resistance across interfaces, and temperature, flux, thermal radiation, and convection boundary
conditions.
Two modes of coupling between the hydrodynamics and the heat transfer are supported. The first
solves the hydrodynamics and heat transfer consecutively at each step by operator splitting. The
heat transfer step changes energy without changing volume and the hydrodynamics step changes
volume without transferring heat. Cellcentered energy is made consistent with nodal
temperatures by including an adiabatic expansion source term, g (dV/V), and strain heating.
Chemical reactions also contribute a source term. The second mode solves the hydrodynamics
and heat transfer iteratively using the intermediate results of the package until they both
converge.
ALE3D: An Arbitrary LagrangianEulerian MultiPhysics Code
Lawrence Livermore National Laboratory 10
The heat conduction equations are solved using a finite element approach. The solution includes
implicit time integration, direct or iterative matrix solution, hexahedral elements with second
order Gaussian quadrature integration, nonlinear convergence by successive substitution or
NewtonRaphson methods, and variable time step control with subcycling of the thermal
diffusion and hydrodynamics.
Heat transfer can occur across a slide surface by perfect thermal contact or by heat conduction
using ‘virtual elements’. Virtual elements are conduction and thermal radiation resistive elements
that are inserted between the slide surfaces. The virtual elements can have zero thickness or their
resistance can be scaled with gap distance. The perfect thermal contact algorithm is formulated
as a penalty method. It maintains symmetry at boundary edges through geometrical and mass
weighting, and scales the penalty function with the magnitude of the diagonal term of the
coefficient matrix.
Chemistry and Chemical Diffusion
ALE3D’s chemistry model is capable of capturing the composition, structure and properties of
chemically reacting materials. The chemical kinetics module was developed to model
decomposition of high explosive materials in thermal environments. A chemical material is a set
of materials that can transform among each other. These materials (or species) define all the
properties of the chemical material. Several models for combining the properties of the
individual species are provided. In principle, any material model that supplies a temperature and
pressure can be used as a species in a chemical material. It is even possible to combine several
models by including a chemical material as a species in another chemical material.
The composition of a chemical material can be modified through a set of user defined chemical
reactions. ALE3D organizes the reactions into groups that act on the same set of species. Only
reactions that involve all of the species present in a chemical material are included in that
material’s full reaction scheme. The change in composition is calculated implicitly with a self
correcting NewtonRaphson technique. The temperature derivative of the change is also
calculated for use by the thermal module.
The chemical kinetics package is normally run tightly coupled to the thermal module. However,
it can also be run during the hydrodynamics phase. When run during the hydrodynamics phase,
the chemical kinetics package can be used to emulate a variety of reactive flow detonation
propagation models. This emulation is accomplished by including the appropriate set of reaction
mechanisms with the appropriate material models for the reacting species. Both the standard
LeeTarver (Lee and Tarver, 1980) and PERMS (Propellant Energetic Response to Mechanical
Stimuli) (Maienschein et al., 1997) models can be implemented this way.
A chemical diffusion model is also available in ALE3D. It allows for diffusion within a chemical
material (not between chemical materials). The species diffusion equations are solved using a
finitevolume approach. The operator is explicit in time and computes fluxes of chemical species
across faces between elements based on the locally determined chemical potential gradient. Both
tracer, where the diffusing species is assumed to be only a small fraction of the total mass of the
system, and nontracer models are available.
ALE3D: An Arbitrary LagrangianEulerian MultiPhysics Code
Lawrence Livermore National Laboratory 11
Incompressible Flow
The incompressible flow package solves the incompressible NavierStokes equations and is
useful for simulations involving a fluid that can be approximated with a constant density, such as
lowspeed aerodynamics or internal fluid mechanics. As a rule of thumb, flows with a Mach
number less than 0.3 are candidates to be considered incompressible. An obvious exception to
this rule is any flow where the density variations drive the flow, no matter how fast it is going.
The package can be coupled to the thermal package for simulations of natural convection of a
fluid with temperature gradients. The incompressible flow model may also be run simultaneously
with the standard ALE hydro package for coupled fluidstructure problems. The fluid and solid
components are coupled through their boundary conditions. The incompressible flow module
includes explicit, semiimplicit (either the advection or viscous terms implicit) and fully implicit
time integration options. An advectiondiffusion solver is also available to model species
concentrations within an incompressible material.
Multiphase Flow
The ALE3D multiphase flow model was developed for simulating mixed materials with separate
velocity fields. This model reuses the species framework developed for the chemical materials.
In principle, any ALE3D material model that supplies a temperature and pressure can be used as
a species in the chemistry and multiphase packages. Often, it is desirable to create a hierarchical
chemical material for use in the multiphase model. An example of this is a multiphase flow of
particles in a fluid flow, each composed of multiple constituents that can react amongst
themselves. This hierarchy of material models enables chemical reactions to be modeled in a
unified manner with multiphase flow.
There are several models for drag and compaction in the multiphase flow package. These
include semianalytic models where the drag terms can be integrated analytically to those which
are evaluated using backward Euler. For cases where the compaction viscosity is unknown, the
pressure relaxation module defaults to an infinite relaxation rate or pressure equilibration.
Magnetohydrodynamics
ALE3D’s magnetohydrodynamics model is capable of capturing the dynamics of electrically
conducting solids and fluids. The magnetohydrodynamics (MHD) module was developed
primarily for the modeling of coupled electrothermalmechanical (ETM) systems that are
inherently 3D in nature. Example applications for this capability include explosively driven
magnetic flux compression generators, induction heating / metal forming and electromagnetic
rail gun systems. The ALE3D MHD module solves the resistive magnetic induction equation
given a collection of specified current and voltage sources. The equation is solved in the
Lagrangian frame using a mixed finite element method employing H(Curl) and H(Div) finite
element basis functions which preserves the solenoidal nature of the magnetic field to machine
precision. Electromagnetic force and resistive Joule heating terms are coupled to the equations of
motion and thermal diffusion in an operator split manner. For problems that require mesh
relaxation, magnetic advection is performed using the method of algebraic constrained transport
that is valid for unstructured hexahedral grids with arbitrary mesh velocities. The advection
method maintains the divergence free nature of the magnetic field and is secondorder accurate
ALE3D: An Arbitrary LagrangianEulerian MultiPhysics Code
Lawrence Livermore National Laboratory 12
in regions where the solution is sufficiently smooth. For regions in which the magnetic field is
discontinuous (e.g., MHD shocks), the advection step is limited using the method of algebraic
flux correction, which is local extremum diminishing and divergence preserving.
Parallelization and Scaling
ALE3D is parallelized across the problem space using domain decomposition to associate
separate pieces of physical space to individual processors. The implementation uses MPI to
communicate across processor boundaries. Several of the key characteristics of the ALE3D
software infrastructure contribute to the code’s scalability. Field data are contained in simple C
arrays, giving the compiler canonical loop iteration patterns to optimize. Ghost boundary data is
always stored contiguously, removing the need for gather / scatter operations during MPI
communication. Nearly all MPI communication is pointtopoint, with only two global
reductions per time step: the duration of the next time step, and a global error status check.
The amount of pointtopoint communication required is dependent on the type of calculation
being run. Problems running explicit hydrodynamics require a single communication to collect
the sum of the forces at nodes along domain boundaries, although some optional algorithms (e.g.
monotonic Q) require more communication. Problems running advection require a 20x – 30x
greater amount of communication, both in terms of the number of communication points, and the
amount of data typically sent. A rough breakdown of the steps performed in the advection are:
nodal relaxation; calculation of volume fluxes; identification of mixed elements and interface
reconstruction; advection of element centered variables; and momentum (node centered)
advection. If there are slide surfaces, additional communications are required. The approach
taken in ALE3D is to use a separate decomposition for slide surfaces. Nodes on one side of a
surface (the “master” side) are assigned statically to the various processors in a loadbalanced
manner, and then nodes on the other (“slave”) side of the surface that are currently “close” to the
masters on a processor are assigned to the same processor.
The daunting task of fully characterizing the performance of ALE3D’s many packages has never
been done in a systematic way, but we present an overview of the scaling of the Lagrangian
hydrodynamics package that forms the core of ALE3D. Figure 3 shows the weak scaling
behavior of a 5695 Element / process Sedov problem from 256 to 96,000 processes.
ALE3D: An Arbitrary LagrangianEulerian MultiPhysics Code
Lawrence Livermore National Laboratory 13
Figure 3. Weak scaling results for ALE3D’s Lagrangian mechanics package.
Conclusion
The ALE3D code continues be under active development at LLNL. In addition to new physics
and methodology improvements, the underlying computer science framework is being modified
to ensure excellent performance on the latest generation of High Performance Computing
machines. This Export Controlled and Official Use Only code is available to analysts in the
Department of Defense and associated contractors for work related to national defense. Contact
the authors for additional information.
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