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Explore Abaqus/Explicit
Techniques
Yogesh Parkhi
Technical Specialist, SIMULIA India
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Presentation content
Abaqus/Explicit – What? When? Why?
Applications of Abaqus/Explicit
Defining Abaqus/Explicit procedure
Quasi-Static Simulations using Explicit Dynamics
Advanced Capabilities in Abaqus/Explicit
Arbitrary Lagrangian-Eulerian (ALE) Method
SIMULIA Multiphysics – FSI capabilities
Managing large models
Simplifying the Model
Techniques for Reducing CPU Time
Tips
Summary
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Abaqus/Explicit
What? When? Why?
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What is Explicit Dynamics?
Explicit dynamics is a mathematical technique for integrating the equations of
motion through time.
The dynamic equilibrium equations are written for convenience with the inertial forces
isolated from the other forces.
These equilibrium equations are completely general.
They apply to the behavior of any mechanical system and contain all nonlinearities (large
deformations, nonlinear material response, contact).
When the first term—the inertial or dynamic force—is small enough, the equations reduce to the
static form of equilibrium.
I
P
u
M 



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What is Explicit Dynamics?
1
( )
( )
( )
t
t

   ,
u M P I
The explicit dynamic integration method is also known as the forward Euler or central
difference algorithm.
Unknown values are obtained from information already known.
The lumped mass matrix, M, allows the program to calculate the nodal accelerations easily at
any given time, t, using the following expression:
where P is the external load vector and I is the internal load vector.
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When should Abaqus/Explicit be used?
The deciding factor when choosing between Abaqus/Standard and Abaqus/Explicit
is often the smoothness of the solution.
It may not be possible to obtain an efficient solution with Abaqus/Standard if there are
significant discontinuities in the solution.
Possible sources of discontinuity in a solution:
Impact
Buckling or local wrinkling of the material
Material degradation or failure, such as cracking of concrete
A large three-dimensional model that contains one or more of the discontinuities
listed above is a good candidate for Abaqus/Explicit.
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Why use Abaqus/Explicit?
It expands the range of problems you can address
Abaqus/Explicit contains many modeling capabilities that do not exist in
Abaqus/Standard.
For example, Coupled Eulerian-Lagrangian (CEL) analysis, Smoothed Particle
Hydrodynamics (SPH), Discrete Element Method (DEM)
It is easy to learn
The basic input structure and options for an Abaqus/Explicit model are the same as those for
an Abaqus/Standard model.
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Applications of Abaqus/Explicit
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Applications of Abaqus/Explicit
Abaqus/Explicit provides the capability to
analyze the following types of problems:
High-speed (short duration) dynamics
Drop tests and crash analyses of structural
members
Large, nonlinear, quasi-static analyses
Deep drawing, blow molding, and assembly
simulations
Extreme deformations,
Bulk metal forming, impact and crushing, and fluid
flow
Courtesy Mechanical Design and Analysis Corporation, 2010 SCC
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Defining Abaqus/Explicit
Procedure
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Defining Abaqus/Explicit Procedure
An Abaqus/Explicit analysis is performed when the model contains any of the
following procedure options:
*DYNAMIC, EXPLICIT
an explicit dynamics step
*DYNAMIC TEMPERATURE-DISPLACEMENT, EXPLICIT
a coupled thermo-mechanical explicit dynamics step
*ANNEAL
annealing procedure
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Defining Abaqus/Explicit Procedure
For the majority of Abaqus/Explicit analyses only the total step time needs to be
specified.
Time increment size is chosen automatically so that it always satisfies the stability
limit.
*STEP
*DYNAMIC, EXPLICIT
, ttotal
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Stable Time Increment
Defining Abaqus/Explicit Procedure
The explicit procedure integrates through time by using many small time
increments.
The stability limit can be defined in terms of the highest eigenvalue in the model
(max) and the fraction of critical damping () in the highest mode
A bounded solution is obtained only when the time increment (Dt) is less than the
stable time increment (Dtmin).
If Dt  Dtmin, the solution will be unstable and oscillations will occur in the model’s
response.
2
min
max
2
( 1 )
t  

    .
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Stable Time Increment
Defining Abaqus/Explicit Procedure
The stable time increment can be expressed as
Decreasing Le and/or increasing cd will reduce the size of the stable time increment.
Decreasing element dimensions reduces Le.
Decreasing material density increases cd.
Increasing material stiffness increases cd.
e
d
L
t
c
  . d
E
c

 ,
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Stable Time Increment
Defining Abaqus/Explicit Procedure
Example: Compression of a jounce bumper
Abaqus/Explicit writes a report to the status (.sta) file during the
datacheck phase of the analysis.
The initial stable time increments listed do not include damping
(bulk viscosity) or mass scaling effects.
Initial time increment = 5.09466E-04
Statistics for all elements:
Mean = 1.53743E-03
Standard deviation = 3.20027E-04
Most critical elements :
Element number Rank Time increment Increment ratio
(Instance name)
----------------------------------------------------------
485 1 5.094664E-04 1.000000E+00
230 2 5.213121E-04 9.772771E-01
224 3 5.219781E-04 9.760302E-01
.
.
.
185 10 5.687587E-04 8.957514E-01 jounce bumper critical elements
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Contact in Abaqus/Explicit
Defining Abaqus/Explicit Procedure
The explicit integration method
efficiently solves extremely
discontinuous events.
Contact is an extremely discontinuous
form of nonlinearity.
Possible to solve complicated, very
general, three-dimensional contact
problems with deformable bodies in
Abaqus/Explicit. * Gholami, T., J. Lescheticky, and R. Paßmann, “Crashworthiness
Simulation of Automobiles with ABAQUS/Explicit,” ABAQUS Users'
Conference, Munich, 2003.
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Contact in Abaqus/Explicit
Defining Abaqus/Explicit Procedure
The general contact algorithm
is usually faster than the contact pair algorithm and
is geared toward models with multiple components and
complex topology.
invoked by using the keywords:
*CONTACT
*CONTACT INCLUSIONS, ALL EXTERIOR
Other features unique to the general contact algorithm
include:
Contact domains span multiple bodies, including both rigid
and deformable bodies
Edge-to-edge contact for perimeter edges, geometric
feature edges, beams, and trusses Wire crimping
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Quasi-Static Simulations using
Explicit Dynamics
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Quasi-Static Simulations using Explicit Dynamics
Challenging nonlinear quasi-static problems often
involve:
Very complex contact conditions
Very large deformations
Mesh distortion possible
Applications:
Metal forming simulations:
Bulk forming (drawing, rolling, extrusion, upsetting,
etc.)
Sheet metal forming (stretching, drawing)
Rolling of a symmetric I-section
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Quasi-Static Simulations using Explicit Dynamics
Two approaches to obtain an economical quasi-static solutions with an explicit
dynamics solver
Increased load rates
Artificially reduce the time scale of the process by increasing the loading rate.
Material strain rates calculated in the simulation are artificially high by the same factor applied to
increase the loading rate.
Mass scaling
Mass scaling allows you to model processes in their natural time scale when considering rate-
sensitive materials.
How much can I increase the load rate or scale the mass?
Increased load rates and mass scaling achieve the same effect
Increased load rates reduce the time scale of the simulation.
Mass scaling increases the size of the stable time increment.
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Check for Quasi-Static Analyses
Quasi-Static Simulations using Explicit Dynamics
Examination of the energy content provides measure to evaluate whether the
results from an Abaqus/Explicit simulation reflect a quasi-static solution.
The kinetic energy of the deforming material should not exceed a small fraction of its
internal energy throughout the majority of a quasi-static analysis.
A small fraction typically means 1–5%.
Not interested in kinetic energy of rigid bodies.
Subtract their contribution from global model kinetic energy or restrict energy output to deforming
components.
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Example: Deep drawing of a square box
Quasi-Static Simulations using Explicit Dynamics
We examine three different punch speeds:
3 m/s
30 m/s
150 m/s
The computation cost of each deep drawing
simulation is summarized in the following table:
Punch speed
(m/s)
Time increments Normalized CPU time
3 (1) 27929 1.0
30 (10) 2704 0.097
150 (50) 529 0.019
Initial configuration for square box deep drawing
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Vpunch = 3 m/s Vpunch = 30 m/s
Vpunch = 150 m/s
Example: Deep drawing of a square box
Quasi-Static Simulations using Explicit Dynamics
Contours of blank thickness in final
formed configuration
Excessive punch speeds lead to results
that do not correspond to the physics. At
150 m/s unrealistic thinning
of the blank is predicted.
Results obtained at 30 m/s and 3 m/s are
very similar, even though the difference in
computation cost is a factor of 10.
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Example: Deep drawing of a square box
Quasi-Static Simulations using Explicit Dynamics
Comparison of internal and kinetic
energies
At a punch speed of 150 m/s the
kinetic energy of the blank is a
significant fraction of its internal
energy.
At punch speeds of 3 m/s and 30 m/s
the kinetic energy is only a small
fraction of the internal energy over the
majority of the forming process history.
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Advanced Capabilities in
Abaqus/Explicit
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Arbitrary Lagrangian-Eulerian (ALE) Method
Motivation
In many nonlinear simulations, the material in
the structure undergoes very large
deformations.
These deformations distort the finite element
mesh, often to the point where
the mesh is unable to provide accurate results
or the analysis terminates for numerical reasons.
In such simulations it is necessary to use adaptive
meshing tools to periodically minimize the
distortion in the mesh.
without adaptive meshing
with adaptive meshing
Forming of a steel part
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Arbitrary Lagrangian-Eulerian (ALE) Method
The primary characteristics of the ALE adaptive meshing capability are:
A smoother mesh is generated at regular intervals to reduce element distortion and to
maintain good element aspect ratios.
The same mesh topology is maintained—the number of elements and nodes and
their connectivity do not change.
The ALE adaptive meshing algorithm in Abaqus/Explicit is not designed to correct
discretization errors in finite element meshes.
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Arbitrary Lagrangian-Eulerian (ALE) Method
Example: Axisymmetric forging problem with adaptive meshing
Interior nodes adaptively adjust in all
directions
Nodes along the free boundary move with the material in the
direction normal to the material’s surface. They are allowed to
adapt (adjust their position) tangent to the free surface.
ALE Simulation
Deformed meshes at 70% of die travel
Lagrangian Simulation
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Smoothed Particle Hydrodynamics (SPH) analyses
Smoothed Particle Hydrodynamics is a very general
approach to the simulation of bulk matter in motion.
SPH addresses modeling needs in cases where
traditional methods (FEM, FDM) fail or are
inefficient:
Extremely violent fluid flows where mesh or grid-based
CFD cannot cope (free surface)
Extremely high deformations/obliteration where CEL is
inefficient and Lagrangian FEM is difficult
Its use can be extended to the simulation of:
Fracture of brittle solids
Metal forming
High (or hyper) velocity impact (HVI)
Liquid spraying through a hose
Water fall under gravity
Turbofan blade bird strike
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Coupled Eulerian-Lagrangian (CEL) analyses
An Eulerian solution is another option for problems involving significant material
flow.
Coupled Eulerian-Lagrangian (CEL) Approach:
An Eulerian mesh and a Lagrangian mesh are assembled in the same model
Interactions between Lagrangian bodies and materials in the Eulerian mesh are
enforced with a general contact definition
Water Drop Simulation
Tank Sloshing
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Discrete Element Method (DEM)
DEM is intended for modeling events in which large numbers of discrete
particles contact each other
New method for analysis of non-continuous media
Granular material, material handling, shot peening, etc.
Agriculture, pharmaceutical, oil and gas, mining
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Managing Large Models
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Introduction
What is a Large Model?
Difficult to define
Absolute size changes as computers become more powerful.
Rough measures for large models based on number of variables:
1980: Models with >100,000 variables
1990: Models with >1,000,000 variables
2000: Models with >5,000,000 variables
Turn-around time is a universal measure
This measure includes jobs with relatively few variables and a huge number of increments.
Models that take at least 12 hours (overnight) to run are generally considered “large”.
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Introduction
Large models often require:
Simplification of the model
geometry, physics, element formulation, etc.
Intelligent use of system resources:
disk space, available processors, memory
Minimization of CPU time, number of increments, etc.
Several techniques are available to assist in the management of large models:
Submodeling
Restart
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Simplifying the Model
Geometry simplification
When building a complex model, start simple (and
small), then add complexity gradually.
Making careful choices regarding your geometry and
mesh:
Take advantage of symmetry
axial, planar, quarter, half, cyclic,…
Defeature the geometry
Avoid small features
They result in small elements which in turn reduce the stable
time increment. Defeaturing a mechanical component
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Simplifying the Model
Modeling fewer details
Consider what you want from the analysis and reduce the level of modeling detail in
regions that are less critical to the analysis goals.
For example:
If you have two parts connected to each other and if you are not interested in detailed
stresses of the connection, use connector elements.
Use beams or shells instead of solids when appropriate.
Focus mesh in regions of interest and use a coarser mesh elsewhere.
Simplify the physics.
Can a stiff portion of an assembly be replaced with a rigid body or a boundary condition?
Do you need all interactions?
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Simplifying the Model
Prototype with rigid bodies
Make deformable parts rigid with a rigid body constraint for faster initial runs of the analysis.
Once you have verified the model definition, remove the rigid body constraints.
Mouse type
Portion of mouse
that is
deformable
Relative
CPU time
rigid prototype 23% 0.35
fully
deformable
100% 1
Final deformed shapes
Deformable regions in color
fully deformable mouse
rigid prototype mouse
Drop Test Simulation of a Cordless Mouse
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Techniques for Reducing CPU Time
Initial conditions can be used to reduce the length of some analyses
You can define initial conditions (stress fields, hardening conditions, velocities,…)
rather than modeling the history that lead to the initial conditions.
Example: Drop test of a cordless mouse
Apply initial velocity conditions consistent with a 1m free fall.
V3
Mouse initial velocity
*INITIAL CONDITIONS,TYPE=VELOCITY
ALL_NODES, 3, 4500
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Techniques for Reducing CPU Time
Static initialization and import
Abaqus provides a capability to transfer the
deformed mesh and associated material state
between an Abaqus/Standard analysis and an
Abaqus/Explicit analysis (and vice-versa).
Reduce the analysis run time by solving portions of
an analysis with Abaqus/Standard.
Examples:
Simulate a transient event in Abaqus/Explicit after
steady-state conditions have been simulated in
Abaqus/Standard
Simulate springback in Abaqus/Standard after forming
analysis in Abaqus/Explicit
Steady-state spinning solution in Abaqus/Standard
Dynamic blade release analysis in Abaqus/Explicit
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Techniques for Reducing CPU Time
Mass scaling speeds up an analysis
by increasing the stable time
increment size.
Artificially increasing the material
density by a factor of f 2 increases the
stable time increment by a factor of f.
*VARIABLE MASS SCALING, FREQUENCY=1,
DT=0.0005, TYPE=BELOW MIN
Scale density of elements whose stable time
increment is less than .0005 s
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Techniques for Reducing CPU Time
Selective subcycling can reduce the run
time for an analysis when a small region
of elements in the model controls the
stable time increment
Subcycling allows for different time
increments to be used for different groups
of elements
Example – Rod impact analysis with
selective subcycling
With an appropriately chosen subcycling
zone, the rod impact analysis runs 2.3x
faster than the equivalent analysis without
subcycling
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Tips
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Postprocessing calculator
Tips
Review results during a long Abaqus/Explicit analysis to avoid wasting
resources running an incorrect model.
When reviewing an output database before an analysis is complete, you will need to
run the postprocessing calculator to:
extrapolate integration point quantities to the nodes or interpolate integration point quantities
to the centroid of an element.
Execution procedure (at the command line):
abaqus oldjob=job-name job=converted-odb-name convert=odb
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Double-precision execution
Tips
Analyses that require a large number of increments should be solved with the
double-precision executable.
Single precision provides accurate results in most cases.
Exceptions for which double precision is recommended:
analyses of more than 300,000 increments
models with hyperelastic materials
analyses with multiple revolutions of deformable parts
Double-precision execution procedure (at the command line):
abaqus job=job-name double
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No distortion control With distortion control
Element Distortion Control
Tips
Abaqus/Explicit offers distortion control to
prevent solid elements from inverting or
distorting excessively.
Distortion control is designed to prevent
negative element volumes or other excessive
distortion from occurring during an analysis.
In contrast to the adaptive meshing technique,
distortion control does not attempt to maintain a
high-quality mesh throughout an analysis.
Elements with distortion control can not be
included in an adaptive mesh domain.
crushable foam indentation
*SOLID SECTION, ELSET=BLANK,
MATERIAL=FOAM,CONTROLS=DistortionControl
*SECTION CONTROLS, NAME=DistortionControl, HOURGLASS=ENHANCED,
DISTORTION CONTROL
Constraint activates when a rectangular element
under uniaxial compression undergoes 90%
nominal strain (default).
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Summary
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Summary of Abaqus/Explicit
Designed to solve highly discontinuous, high-speed dynamic problems efficiently.
Very robust contact algorithm that does not add additional degrees of freedom to
the model.
Does not require as much disk space as Abaqus/Standard for large problems, and it
often provides a more efficient solution for very large problems.
Contains many capabilities that make it easy to simulate quasi-static problems.
Has the capability to effectively solve Fluid-Structure interaction (FSI) problems.
48
3DS.COM
©
Dassault
Systèmes
|
Confidential
Information
|
10/8/2014
|
ref.:
3DS_Document_2013
Next steps …
• Register for a Training Class
3ds.com/simulia-training
• eSeminar replay: Would be uploaded on SIMULIA
Resource Center and SIMULIA Learning Community (SLC),
watch out for the email announcement
• Join SIMULIA Learning Community
3ds.com/slc
• Follow us on social media: @3DS_SIMULIA
• Join our SIMULIA Regional User Meeting around globe in 24 locations. For more information visit
http://www.3ds.com/events/simulia-regional-user-meetings/
49
3DS.COM
©
Dassault
Systèmes
|
Confidential
Information
|
10/8/2014
|
ref.:
3DS_Document_2012

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