The Big Question
With engineering simulation becoming so widespread, the big question
now for manufacturers is not if to use the technology but how. And
their answers will determine who gains the competitive edge.
Companies are investing in
engineering simulation at unprecedented levels. According to the
latest statistics from market
research and technology assessment firm Daratech, sales revenue
for computer-aided engineering
(CAE) software and services grew
from $2.31 billion in 2005 to more
than $2.43 billion in 2006. Daratech
forecasts a compound annual
growth rate of 13 percent through
2010, when figures are expected to top $3.7 billion.
Driving this expansion is the tremendous need for
companies to shorten time to market, lower costs, improve
performance and develop steady streams of knock-out,
innovative products. With survival on the line in many
cases, manufacturers use simulation as a proven way of
addressing these issues.
According to Daratech statistics, the number-one player
in CAE is ANSYS, Inc. So a substantial portion of the broad
range of simulation applications worldwide is based on the
company’s suite of solutions. The breadth of applications is
evidenced by the articles in this current issue of ANSYS
Advantage on simulation projects involving the design of
products ranging from trucks and turbojet engines to consumer goods and healthcare equipment. The content also
demonstrates the vast range of company sizes, from the
one-man design firm Stein Design in the story “No-Hassle
Kitchen Appliance” to the $70 billion global consumer
product giant Procter & Gamble Company in the article “The
Democratization of Engineering Analysis.”
As these and other successful simulation users know,
gaining market advantage now takes more than just
utilizing analysis tools. Because of the ubiquitous use of
CAE technology, the competitive edge isn’t necessarily
determined by which companies use simulation — most
manufacturers now implement it in one way or another —
but rather how they uniquely apply the technology in their
organizations and integrate it into their product development processes.
To fully leverage a solution, many successful firms have
initiatives for performing more upfront simulation to refine
designs early instead of trying to hurriedly fix problems
near the end of development. In most cases, this means
deploying appropriate tools beyond the ranks of dedicated
analysts to more rank-and-file engineers and designers for
routine use throughout development.
There is no cookie-cutter way to best implement such
an approach. Rather, companies have found that they must
carefully evaluate their existing processes, skill sets,
organizational structures, product strategies and business
priorities to leverage simulation most effectively. Scheduling,
funding and performance reviews generally are adjusted to
allow for training; the approach also gives engineers
and designers the time they need to perform analysis,
what-if simulations and optimizations in the early stages of
development rather than the usual rush to finalize computeraided design (CAD) models.
These and other necessary organizational changes
require a significant investment in time and effort, of
course, but the level of commitment defines how
companies uniquely leverage simulation; it also determines
which firms will most likely lag behind while others
reap the greatest business value from Simulation Driven
Product Development. ■
John Krouse, Editorial Director
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Email: [email protected]
About the Cover
Racing yachts competed this
summer in the America’s Cup
competition in which all the
leading teams employed computer
simulation to gain an edge. See
page 3. Cover photograph ©ACM
2007/Photo: Carlo Borlenghi.
Simulation courtesy Christos
Pashias, Team Shosholoza.
About the Biomedical
The biomedical industry is
emerging as a strategic user
of engineering simulation.
One research team has found
that improvements in cochlear
implants might be possible
using shape memory alloys.
See page s4.
ANSYS Advantage is published for ANSYS, Inc. customers, partners and others interested in the field of design and analysis applications.
Neither ANSYS, Inc. nor the editorial director nor Miller Creative Group guarantees or warrants accuracy or completeness of the material contained in this publication.
ANSYS, ANSYS Workbench, CFX, AUTODYN, FLUENT, DesignModeler, ANSYS Mechanical, DesignSpace, ANSYS Structural, TGrid, GAMBIT and any and all ANSYS, Inc.
brand, product, service, and feature names, logos and slogans are registered trademarks or trademarks of ANSYS, Inc. or its subsidiaries located in the United States
or other countries. ICEM CFD is a trademark licensed by ANSYS, Inc. All other brand, product, service and feature names or trademarks are the property of their
respective owners.
ANSYS Advantage • Volume I, Issue 2, 2007
© 2007 ANSYS, Inc. All rights reserved.
The Simulation Race for America’s Cup
Yacht designers used engineering simulation in a variety of applications
to edge out the competition.
Plying the Composite Trade
ESAComp software overcomes challenges in designing with composites.
Hair Today
Product developers in the cosmetics industry can put simulation to use in
performing hierarchical analyses of hair care product performance.
Heavy-Duty Lightweight
An innovative aluminum design gives a truck-body manufacturer the
competitive edge in the worldwide construction industry.
Gassing Up with Coal
A two-fluid multiphase model allows for more accurate simulation of coal gasification.
Chopping Away at Solids
CFD simulation provides a pump company with a virtual test facility.
No-Hassle Kitchen Appliance
Finite element analysis helps redesign a countertop water filter.
Overcoming Big Challenges for
Small Turbojet Engines
Engineers used FEA to develop an impeller for a microjet turbine engine for
unmanned drone aircraft.
Keeping It Cool
Modeling fluid flow and heat transfer throughout a nuclear fuel assembly
helps prevent reactor burnout.
The Greening of Gas Burner Design
Simulation assists in developing efficient and environmentally friendly
recuperative burners used in heat-treating applications.
(Continued on next page)
ANSYS Advantage • Volume I, Issue 2, 2007
Managing Engineering Knowledge
Web-based solution is aimed at hosting and integrating simulation
data, processes and tools for more effective Simulation Driven Product
The Democratization of Engineering Analysis
To compete successfully in today’s business climate, Procter & Gamble
makes analysis tools available to rank-and-file engineers as well as to
analysts and advanced simulation experts.
Rotordynamic Capabilities in ANSYS Mechanical
Useful features are available to study vibration behavior in rotating parts.
Submodeling in ANSYS Workbench
To obtain accurate stress in a local region, submodeling separates local
analysis from the global model.
Spotlight on Engineering Simulation in the
Biomedical Industry
Making Life Longer and Better
The biomedical industry is emerging as a strategic user of
engineering simulation.
Turning Up the Volume
The use of shape memory alloys offers the promise of better
functioning in cochlear implants.
Hip to Simulation
Evaluation of designs for a hip replacement prosthesis
overcomes physical and scientific limitations.
Walking Pain Free
New insoles designed with the ANSYS mechanical suite
relieve pain from foot disease.
Engineering Solutions for
Infection Control
Simulation assists in designing a hospital ward to reduce
the airborne transmission of disease.
Standing Up Right
ANSYS Multiphysics sheds light on the wonders of the
human spine and how to fix it.
Designing with Heart
CFD-based design optimization for a pediatric implant can
shave years off the development cycle.
Going with the Flow
Functional biomedical imaging through CFD provides a new
way of looking at pathological lungs.
Battle of the Bulge
Rapid prototyping results in a new surgical tool to treat
back pain.
ANSYS Advantage • Volume I, Issue 2, 2007
Emirates Team New Zealand used CFD to predict the
effect of design alternatives on yacht performance.
The Simulation Race
for America’s Cup
Yacht designers used engineering simulation in a variety
of applications to edge out the competition.
The America’s Cup is the most famous sailing regatta in
the world and also the oldest active trophy in international
sport. The trophy, originally known as the Royal Yacht
Squadron Cup, was first awarded in 1851 when the New
York Yacht Club schooner America defeated 15 Royal Yacht
Squadron challengers in a race around the Isle of Wight in
England. In honor of America’s victory in the first competition, and the subsequent dominance of American boats for
over a century, the trophy officially became known as the
America’s Cup.
Despite its name, it is truly an international competition.
In 2003, the Swiss challenger Alinghi defeated Team New
Zealand to win sailing’s grand prize; Alinghi successfully
defended this summer at the 32nd America’s Cup in
Valencia, Spain. The boat sizes and designs have varied
through the years, ranging from the 130-foot J-class yachts
of the 1930s to a 60-foot catamaran in 1988. Since 1992
though, the teams have sailed an International America’s
Cup Class (IACC) sloop, a monohull boat that has an
average length of about 75 feet. To determine which
team would challenge Alinghi for the trophy in 2007, an
ambitious schedule of regattas was held, commencing in
2004 and culminating with the Louis Vuitton Cup this past
spring. The America’s Cup match series was held in late
June and early July, with Alinghi the winner in the closest
Cup in recent history.
The racing syndicates that compete for the cup
are composed of the best sailors, designers, sailmakers,
nautical engineers and boat builders in the world. The top
teams expend more than 150,000 labor hours to optimize
the designs of their boats. All of the leading teams employ
computer simulation to determine the power generated by
the sails, the drag produced by the boat’s hull and the air
resistance of the deck. Four of the top teams, including
BMW ORACLE Racing from the United States, South
Africa’s Team Shosholoza, Emirates Team New Zealand
(ETNZ) and defending champion Alinghi from Switzerland,
use computational fluid dynamics (CFD) software from
ANSYS, Inc. to predict the effect of design alternatives on
yacht performance down to the smallest details.
ANSYS Advantage • Volume I, Issue 2, 2007
CFD simulates the wind flowing over the deck and
cockpit of the Alinghi boat. Note the vortex that
formed in the bow where the wind wraps around
on the deck.
The two most critical aspects of yacht performance are
the sail aerodynamics and the hydrodynamics of the hull
and appendages. Picture this analogy: A racing yacht is like
a plane floating on its side with one wing sticking up in the
air and the other down into the water. The art of yacht
design is to extract drive force because the two fluids (air
and water) have different speeds and directions. The curvature of the sails generates lift in a manner similar to an
airplane wing, while the keel of the boat generates lift in the
opposite direction — like the opposite wing of the airplane
— to prevent the boat from moving sideways. The keel can
be proportionately much smaller than the sails because
it operates in a fluid 800 times denser than air. As in
aircraft design, improving performance of a racing yacht is
basically a question of maximizing lift and minimizing drag.
Small changes in geometry often make the difference
between a competitive boat and an also-ran.
BMW ORACLE Racing: It’s In the Details
In the 2003 competition, BMW ORACLE Racing used a
public-domain CFD code to simulate the performance of
their boat. However, they found that meshing and solution
times were so long that they were forced to simplify their
models to the extent that they could not distinguish
between small design changes. For the 2007 race, the team
used ANSYS CFX software. BMW ORACLE Racing ran
models with 10 to 15 million cells on large computer
clusters that can resolve the performance impact of the
smallest design changes. The team’s designers simulated
the performance of large numbers of different sail shapes
and trims to understand performance under a variety of
conditions. They evaluated the aerodynamic effects of the
deck, such as the shape of edges and corners and the
ANSYS Advantage • Volume I, Issue 2, 2007
position of the winches, and they also looked at the shape
of underwater components, such as the ballast bulb.
“Our new simulation methods make it possible to model
the most complex problems down to the finest details in a
day or two,” said Ian Burns, design team coordinator for
BMW ORACLE Racing. “We now can determine the effect
of the smallest changes, such as the shape of the deck or
small hardware components on the mast. Some of these
changes can have a significant impact on performance and
are helping us make significant performance improvements.
We have analyzed and improved nearly every detail of the
boat with ANSYS CFX software.”
An upwind aerodynamic simulation of the Team Shosholoza yacht clearly shows the tip
vortices. Induced drag reduction is important for sails operating near their maximum lift.
Team Shosholoza: Big Things from Small Packages
Team Shosholoza, South Africa’s first America’s Cup
entrant, was one of the smaller teams in this year’s competition. Unlike some of the larger teams, Shosholoza has only
one boat, so it can’t rely on running two boats against each
other to evaluate design changes. Therefore, CFD simulation is critical to the team, which has built a 42-node cluster
that places it near the top in terms of computing capabilities
among the smaller entrants. Shosholoza used computeraided design (CAD) tools to develop a parametric model of
the boat and then read the model into the ANSYS ICEM
CFD Hexa meshing tool, which quickly generates a series
of models by varying a key design variable over a defined
range. Shosholoza then solved the models with ANSYS
CFX software, and designers used the results for force and
drag to predict the velocity.
“To date, the area where we have made the greatest
improvements is in the shape of the sails,” said Christos
Pashias, fluid dynamicist for Shosholoza. “We are trying to
get as much power out of the sails as possible because the
winds in Valencia are so light. We set up a parametric model
to automatically generate sail models. This enabled us to
have a quick turnaround and study more shapes. Being a
new team, initially we made improvements of between
5 and 10 percent in driving force. A 1 percent improvement
in driving force typically increases the speed of the boat
by about 0.1 percent. We have tested boats with the
new designs and discovered that they actually do provide
the performance improvements that ANSYS CFX predicts.
Since we made those initial big gains, we have made
many other improvements that have provided smaller
gains, typically in the area of 1 percent, which is what most
teams are after. Testing already has shown that these
predictions are accurate, so we trust them to make
more improvements.”
Shosholoza also used FLUENT CFD software to better
understand the flow of water around the yacht. The ranking
of candidate hull shapes by FLUENT software agreed well
with experimental results.
Emirates Team New Zealand: Location, Location, Location
ETNZ has been focused on improving the ballast bulb
at the bottom of the boat. At about 21 tons, this torpedoshaped lead component makes up nearly 80 percent of the
boat’s mass and provides the craft with the stability to
balance a very large sail area. Choosing a bulb shape with a
lower center of gravity increases the boat’s righting moment
and enables the sail to provide a larger driving force. On the
other hand, moving to a lower drag force wastes less of the
available driving force and increases the speed of the yacht.
In preparing for the 2003 race, the New Zealand designers
were able to lower the center of gravity substantially without
any increase in drag. With these major improvements under
its belt, the team’s goal for 2007 was to make more subtle
and site-specific changes, such as optimizing the bulb
design for the expected conditions off Valencia.
“We developed a genetic algorithm that works by
defining the geometry of the bulb with control points whose
coordinates and weighting are considered to be genes,”
said Nick Holroyd, designer for ETNZ. “Then the population
was seeded with a range of candidates, and mutations
were introduced into each generation to adequately spread
the population across the design space. Each candidate
was simulated with ANSYS CFX software using the laminarto-turbulent transition model to provide a drag value.
This value is factored against the stability contribution of
the shape to provide a fitness score for the design. We
developed a family of new bulb shapes with a better
Simulations were conducted under a wide variety of conditions to determine
performance. Velocity magnitude contours around the hull and sails of the
BMW ORACLE Racing boat are shown (windward above and leeward below)
with plane cuts that are perpendicular to the boat track.
ANSYS Advantage • Volume I, Issue 2, 2007
BMW ORACLE Racing has analyzed and improved nearly every detail of the boat,
including the keel–ballast bulb juncture.
Team Shosholoza
drag/stability trade-off for the racing conditions expected at
Valencia. This approach made it possible to evaluate the
design space with much less time than would have been
required manually.”
calibrated its results,” said Jim Bungener, CFD engineer for
Alinghi. “The main areas where we have made performance
improvements have been in the winglets on the ballast
bulbs and the downwind sails or spinnakers. We also have
made smaller gains in areas such as winch placements and
pillar shapes. These improvements have significantly
increased the speed of the boat. When considered as a
whole, the results that we have achieved with CFD aided us
considerably in defending the America’s Cup.” Bungener
also used ANSYS Structural software to identify the composite laminar structure that withstands the loads on the
hull while minimizing weight.
Alinghi: Defending Its Honor
Winner and defending champion Alinghi used CFD to
evaluate every portion of the boat, including the sails, the
underwater portion of the hull and deck details. Alinghi
designers spent more than a year evaluating CFD results
compared to wind tunnel testing and scientific papers.
“We gained confidence in the ANSYS CFX software and
Steady Wins the Race
Computer simulation has played a crucial role in the
boat design process for many of the top racing syndicates.
With all entrants now using CFD to optimize the
performance of their boats, different design groups have
arrived at generally the same conclusions and made
substantial performance improvements. As a result, the
boats are closer together in terms of performance, making
tiny improvements that much more important. The teams
now are all creating finer and finer meshes using larger
clusters of computers so they can evaluate the effects
of smaller design changes on yacht performance.
The America’s Cup is thus becoming a showcase, not
only for the world’s fastest yachts but also for its most
powerful simulation tools. ■
This article was written through contributions from Alinghi, BMW
ORACLE Racing, Emirates Team New Zealand and Team Shosholoza.
Alinghi simulation of typical downwind sail geometry illustrates the way air flows
over the sails. A large vortex is created behind the spinnaker, a billowing sail used
when the wind is behind the boat.
ANSYS Advantage • Volume I, Issue 2, 2007
Dialog boxes in the ESAComp ply
specification tool enable users to
readily enter various input data.
Plying the Composite Trade
Coupled with technology from ANSYS, Inc., ESAComp
software overcomes challenges in designing with composites,
enabling engineers to evaluate part designs and better use
these versatile materials to their full advantage.
Carbon-fiber reinforced plastics
and other composite materials are
used in a wide range of applications
because of their high strengthto-weight ratios. High-performance
composites made of continuous fibers
bound with thermoset resins can be
used in making extremely efficient
structures, and laminated composites
are well suited for lightweight parts
with complex surface contours.
Composites present some complex challenges in utilizing these
materials to their best advantage,
however. Material properties are
anisotropic — that is, they are directionally dependent on the orientation
of the reinforcing fibers. Differences in
thermal expansion of the matrix and
reinforcing materials cause residual
stresses, and asymmetric structures
especially can yield unexpected
responses to temperature variations.
Moreover, sandwich structures exhibit
complex behavior because of large
differences in strength and stiffness
between layers.
When designing with laminated
composites, engineers must take into
account these and many other considerations in establishing important
design variables, including selection
of material types, layer orientation
and thickness, number of layers, and
stacking sequence. Compounding the
difficulty, complete material property
data cannot always be found from the
supplier data sheets.
Composite Analysis and Design
High-performance composites are
used extensively in the aerospace
industry, where engineers rely on
in-house tools developed specifically
for composite analysis. These programs require considerable resources
to develop and maintain, however.
Engineers need extensive training to
understand the specialized commandbased interfaces and numerical
outputs. In addition, users often have
to transfer data manually between
multiple programs for modeling and
analyzing components.
By Harri Katajisto
Componeering Inc.
Helsinki, Finland
Concerned about the inefficiency
and lack of consistency between the
wide range of in-house codes used in
the aerospace industry, the European
Space Agency (ESA) initiated a project
in the early 1990s to standardize the
analysis approach with a single software platform combining various tools
under a unified user interface. ESA,
with headquarters in France and
consisting of 17 member states, is in
charge of shaping the development
of Europe’s space capability and
ensuring that investment in space continues to deliver benefits to the citizens
of Europe. By coordinating member
resources, the agency can undertake
programs and activities far beyond the
scope of any single European country.
ESA also works closely with space
organizations outside Europe.
Development work for the composite project was conducted by
Helsinki University of Technology in
Finland, and the first version of
ESAComp software was released in
1998. Development responsibility later
ANSYS Advantage • Volume I, Issue 2, 2007
Layer charts indicate the effect of layer orientations
on interlaminar shear stress distribution in a short
beam test sample.
was transferred to the spin-off Finlandbased company Componeering Inc.,
which now distributes and supports
the software. Although the software
originated in the aerospace industry, it
has been developed as a general tool
for engineers in other applications
designing with high-performance composites, including automotive, marine,
construction, machinery, rail transportation, sports and wind energy.
The software has analysis and
design capabilities for solid–sandwich
laminates and micromechanical
analyses. It further includes analysis
tools for structural elements: plates,
stiffened panels, beams and columns,
and bonded and mechanical joints.
ESAComp focuses on the conceptual
and preliminary design of composite
structures as well as detailed product
evaluation using ANSYS Mechanical
and other analysis software. Engineers
can study constitutive relations and
hygrothermal behavior of laminates, for
example, and compare laminate layups with respect to strength and other
design requirements. Input checks
help guarantee that analyses are not
performed with inadequate data.
Users can run preliminary design
checks to ensure that columns do not
buckle, plates withstand applied loads
without deflecting excessively, pressure vessels carry specified internal
pressures, joint configurations are
efficient for load transfer, holes in
plates do not cause severe stress
concentrations, and scatter in material
properties does not cause unexpected
problems. The initial solution obtained
gives a starting point and benchmark
when going to finite element analysis
(FEA) of the full structure, after which
post-processing of the results helps
survey the numerous failure mechanism possibilities.
ANSYS, Inc. software and ESAComp were instrumental in the design
of the 75-foot Wally-class racing yacht.
Image courtesy Johannes Schlieben, University of Applied Sciences of
Northwestern Switzerland.
ANSYS Advantage • Volume I, Issue 2, 2007
The software includes a material
database of fibers and matrix
materials, adhesives, sandwich core
materials, and reinforced material
systems from commercial suppliers.
A ply specification tool in ESAComp is particularly valuable in setting
up the input data for various material
configurations, such as a cured
fiber-matrix system or a honeycomb
core material. Since ply behavior is
typically between isotropic and fully
anisotropic, the ply specification tool
utilizes material symmetry rules to help
in defining the data. Ply data also can
be derived from fiber and matrix data
with micromechanics analyses.
With the laminate lay-up tool, laminates can be created and edited
efficiently. The user has a wide range of
options for performing analyses as well
as selecting and combining result data.
For example, several laminates,
laminate orientations or failure criteria
The esaplot viewing utility gives quick insight into the overall safety performance of the yacht
design. For each composite element, a safety factor determined by the most critical layer of the
section is given. Options provide detailed data on the laminate failure mode and the most critical
layer, with this information overlaid on each element. Here, for example, cs indicates core shear
failure, and w(n) denotes wrinkling of the face sheet. The second option characterizes the most
critical layer: the stacking number and the orientation.
Analysis determined criticality of the interlaminar shear
strength for the trailer tank structure during deceleration.
Margin to safety is indicated with contours, and results of
the failure analysis are overlaid on the elements.
A liquid-hauling tank and associated structures of the truck were analyzed. The truck’s
tank was made of filament-wound composites and sandwich structures.
can be selected for different types
of analyses. The results display
options include numeric tables, line
and bar charts, failure envelopes, and
contour plots.
Integration with Software from ANSYS, Inc.
ESAComp is fully integrated with
ANSYS Mechanical software. ESAComp FE export supports ANSYS
pre-processing. Also, the program can
be launched from the ANSYS interface
to perform detailed stress analysis and
post-processing. ANSYS Mechanical
software allows defining FE model
input files in text format using specific
commands, which is, in many cases,
the best way to set up models; the
ESAComp FE export capability fits in
this scheme. The ANSYS Workbench
platform supports these text format
laminate definitions as well. For each
part in the model tree, the user can
give ANSYS commands through
ANSYS Workbench command objects.
Laminates can be defined with
ESAComp FE export, and the definitions override the default material
Currently, the best way to simulate
complex composites structures is to
import computer-aided design (CAD)
geometry in ANSYS Workbench as
surface bodies and use enhanced
contact features, automated meshing
and environment commands. Then,
open the simulation model in ANSYS
Mechanical software and read in all
laminate definitions from an ESAComp
FE export file. When the geometry
is imported as surfaces, ANSYS
Workbench automatically uses shell
181 elements. After elements have
been updated to correspond to the
correct laminate definitions, the model
is solved and post-processed.
Integration of ESAComp postprocessing with ANSYS has been
realized with the versatile ANSYS
Parametric Design Language (APDL)
and is used through two commands:
esapost and esaplot. The most relevant data can be combined in a single
ANSYS contour plot showing safety
margins for the most critical failure
mode, including layer failure, interlaminar shear, or sandwich core shear
and wrinkling. Text labels on elements
provide additional information on
the failure modes or critical layers.
Through this procedure, the user
quickly identifies design-driving areas,
since all relevant failure modes are
considered automatically and clearly
ANSYS, Inc. technology and ESAComp are complementary tools used
routinely in developing products made
of high-performance composites. The
technologies were instrumental in the
design of the 75-foot Wally-class
racing yacht, for example, which
features a unique canting keel for
balancing the moments produced by
the sails. In this application, the weight
of the boat was a dominant design
driver; simulation tools were critical in
optimizing the lay-ups and certifying
the laminates of heavily loaded components, such as the chain plates and the
junction between the keel box floor and
the hull.
Another application involved a
design project for a truck with a liquidhauling tank made of filament-wound
composites and sandwich structures.
Advanced contact features and
automatic meshing capabilities in the
ANSYS Workbench environment were
used to transform the CAD geometry of
the tank support structure to the FE
model. ANSYS parametric modeling
features and interfacing capabilities
with ESAComp were further used to
optimize the design. Finally, ANSYS
Mechanical software was used for
validating the design against the certification authority’s requirements.
Processing indicated how interlaminar
shear (ILS) strength of the laminate
structure is a dominant design factor in
the discontinuity location while the
truck is decelerating.
The ANSYS ESAComp postprocessing utility indicates to designers
the weakest point of the structure,
the weakest ply in that location and
the most likely mechanism of ply
failure. This information gives users
valuable insight for making informed
decisions on refining the design of
the structure. ■
ANSYS Advantage • Volume I, Issue 2, 2007
Hair Today
Product developers in the cosmetics
industry can put simulation to use in
performing hierarchical analyses of hair
care product performance.
By Aniruddha Mukhopadhyay, ANSYS, Inc.
Simulation of water flow rinsing process using
head-scale modeling
In the consumer-driven world of
cosmetics, consumer experience and
expectations are anything but an exact
science. Qualitative performance
testing, to gather information such as
“Does this product increase hair’s
shine?” or “Does this product spread
through the hair well?” usually is
achieved through subjective testing.
As an alternative to such testing,
product developers and researchers
can use computational fluid dynamics
(CFD) coupled with appropriate
surface science and emulsion decomposition mechanisms for virtual testing
of hair care products.
Illustration of subjective test results representation for
two hair care systems
In order to mimic the subjective
test procedure, a standard (baseline)
hair with the standard (baseline)
product can be simulated at the outset
to establish quantitative correlations
between subjective characteristics and
chemical or fluid properties. Examples
include the measurement of tackiness
associated with surface tension,
greasiness with viscosity and resulting
glossiness with optical reflectance. As
simulation progresses and correlations
are developed, product developers
also need to understand how and what
to model on various scales.
Consistency in simulation is only
as reliable as the details of physics
and chemistry in the models. Within a
predefined scope, simulation provides
controlled test conditions. For example, a simulation-driven test procedure
could be set up to begin with a known
test subject, possibly developed within
a “hair library” in the simulation software, of specified morphology, age,
pore size, moisture absorption properties, temperature, and grease in and on
the hair. The researcher then could
define the environment around the test
material (a sample hair assembly or
tress) and apply the product making
various assumptions, such as the
choice to define application such that
it yields approximately a uniform layer
on the head. More detailed options
include an applicator or a fingertip for
studying the spreading and coating.
Varying size and scope of the
CFD model can provide insight for
behaviors that are best observed on
various scales. Product application
and spreading can be accurately
modeled on a relatively large “headscale,” while functions such as glosser
binding, which actually occur at the
hair surfaces, are best modeled at a
much smaller “hair-scale.” An effective
ANSYS Advantage • Volume I, Issue 2, 2007
Simulation of shampoo concentration contours
using head-scale modeling
Simulation of water velocity contours using
head-scale modeling
Spread of a complex oil droplet over a pair of cross-hairs: on the left, initial state in which ingredients suspended in the product’s emulsion are represented as sub-droplets in the
larger drop; on the right, the state after spreading has occurred
overall modeling approach involves
coupling external flow with microphenomena near the hair surface. With
this method, based on the large-scale
flow conditions, the model is used to
extract useful hydrodynamics data
down to microscopic fluid volumes
near a single hair and locally evaluate
performance of various agents. This
would enable gathering detailed
information about the effectiveness of
factors such as grease removal rate
or product decomposition, which is
relatively difficult, if not impossible, to
consistently observe through tressbased tests.
Hair care products usually are
packaged as emulsions, multi-liquid
dispersions with suspended ingredients that don’t segregate while stored.
They are designed to dilute and break
down when applied to the head with
either fingers or a stream of shower.
Variations in properties such as
density, rheology, surface energy,
Dynamic simulation of long hairs in a liquid stream
chemical potential, temperature and
phase-equilibrium of different immiscible and dissolving ingredients pose
the design challenges to product
developers. To understand the product
breakdown process that occurs during
application, a hair-scale simulation
is required.
To examine the emulsion decomposition process, a complex, multiphase simulation is performed. A drop
of the specified product is deposited at
a location at which two hairs cross.
The drop being modeled is about three
times the hair diameter and includes
suspended sub-droplets intended to
represent the elemental ingredients in
the emulsion. The simulation demonstrates the capillary effects of the
cross-hair assembly and provides the
product designer with information on
the state of decomposition and spread
of the product that will occur on such
cross-hair configurations. Due to a
variety of governing physics and the
dissolution kinetics, pretreated hairs as
well as conditioner ingredients greatly
affect surface forces on the product
drop that is being decomposed and
The embedded constituents can
be further defined to have their own
specific material properties. For example, they could be defined as wettable,
which means they stick to the hair,
thereby serving as active deposition
sites for various ingredients. In a
case involving ingredients that are
responsible for “hold” qualities, the
sub-droplets could be defined as
polymers that will undergo glass transition, leading to a firmer film at room
temperature. This film structure will
provide added elastic strength for the
hair strand and evolve as a hold
quality. One complexity for these films
is that they will neither be exactly
homogeneous in content nor have
isotropic properties for factors such as
elasticity, smoothness or thickness.
It is possible to set up a range of
simulations for different starting
compositions, sizes, temperatures and
environmental dilutions and then to
observe the final state for each distinct
model. Although each simulation
will predict a single resulting state,
as though the product is in fact
homogeneous and isotropic, a heuristic
compilation of multiple simulations
can together provide a more realistic
statistical representation and characterization of the relative performances
of various formulations. ■
ANSYS Advantage • Volume I, Issue 2, 2007
This Volvo hauler truck is equipped with a lightweight aluminum Alutip tipper
bed that tilts back to unload vehicle contents. The unique semicircular bed is
designed by Axis Developments Ltd.
Heavy-Duty Lightweight
An innovative aluminum design gives a truck-body manufacturer the
competitive edge in the worldwide construction industry.
By Mauritz Coetzee
Axis Developments Ltd.
Pretoria, South Africa
In developing hauler trucks, every
extra pound of vehicle weight increases
manufacturing costs, lowers fuel
efficiency and reduces vehicle payload
capacity. So Axis Developments Ltd.
had an idea for making one of the
largest parts of the vehicle out of lightweight aluminum: the tipper body bed
that tilts back to unload soil, rock,
debris or other contents.
A designer and manufacturer of
trailers and truck bodies for the worldwide highway transportation and
construction industries, South Africa–
based Axis is known for its Alutip series
of aluminum tipper beds, which weigh
considerably less than comparable
steel bodies. Developing these structures is an engineering challenge,
however, since body strength must be
maintained with aluminum material,
which has different properties than
steel; the amount of material must be
minimized as much as possible for
further reduction in weight and cost;
ANSYS Advantage • Volume I, Issue 2, 2007
and there is the additional desire to
get new designs released quickly
without numerous physical prototype
testing cycles.
In redesigning an existing tipper
body having a capacity of 15 cubic
meters, Axis addressed these issues
upfront in the design cycle with software
from ANSYS, Inc. by readily evaluating
stress levels for different configurations.
Geometry of the existing design was
imported from Autodesk Inventor, a
computer-aided design (CAD) package,
into ANSYS DesignModeler software,
which has functions for preparing design
models specifically for simulation. The
engineering team used a mid-surface
extraction tool in ANSYS DesignModeler
to convert the solid model of the tipper
body’s 10-mm-thick plates to a simpler
surface representation. This simplification enabled the software to model the
structure with a minimal number of shell
elements for greater solution speed
while still retaining information on plate
Using aluminum materials saves weight but presents a new set of challenges. The first step in redesigning the tipper
body was importing existing geometry into ANSYS DesignModeler software. Axis Developments’ engineers modeled
the truck body with shell elements and parameterized so models could be readily modified by changing a few key
parameters, instead of rebuilding the entire model from scratch.
thickness throughout the simulation.
Additionally, the model was parameterized so engineers could quickly modify
the geometry of the model by
changing only a few key parameters,
instead of having to rebuild the entire
model from scratch.
Next, design geometry passed
from ANSYS DesignModeler to ANSYS
Professional software for structural
analysis. Since the two modules both
operate on the ANSYS Workbench
platform, transfer of data occurred
with a menu pick, allowing switching
between design and analysis without
having to open and close different
applications. In this way, Axis Developments’ engineers quickly developed a
mesh and performed stress analysis in
ANSYS Professional software; they
then were able to appropriately modify
the geometry in ANSYS DesignModeler
and immediately perform another
analysis to ensure that stress concentrations were eliminated.
Using this approach, engineers
quickly arrived at an optimal design
by performing three iterations, with a
total solution time of only five minutes
per iteration. By experimenting with
different types of designs, Axis
Developments determined that the
traditional support beam configuration
could be replaced with a more effective semicircular design having a
reinforced rib structure and end plate
for additional stiffness. As the only
manufacturer employing this unique
design shape, the Axis bodies are
easily recognizable on the road and
quickly are becoming the company’s
trademark. Body weight was reduced
25 percent yet provided the additional
strength needed for higher payload
capacities — a benefit for customers
and, thus, a definite competitive
advantage for Alutip in the hauler truck
market. The material cost savings paid
for the company’s software investment
within only 10 truck bodies.
Axis Developments’ engineers
had no previous experience with finite
element analysis, yet they were productive after only two hours of training.
The tipper body design was completed
in less than two days, which would
have been unfeasible using conventional hand calculations. Moreover,
the design was refined with fewer
hardware prototypes. Reduction in
prototype testing was a huge benefit,
since these large structures are
extremely time-consuming and expensive to build and test. With the success
of this tipper body redesign, Axis
Developments now uses a simulationbased product development approach
in which all new design concepts are
evaluated, “what-if” scenarios are
studied, problems are fixed and
designs are refined before detailed
CAD work is started. ■
The authors would like to acknowledge the
efforts of SolidCad (, a
South Africa reseller of ANSYS, Inc. products
that provides software and training.
Stress distribution contours (from ANSYS Professional software) plotted on the Axis tipper body structure
ANSYS Advantage • Volume I, Issue 2, 2007
Gassing Up with Coal
A two-fluid multiphase model allows for more
accurate simulation of coal gasification.
By Christopher Guenther, U.S. Department of
Energy, National Energy Technology Laboratory
West Virginia, U.S.A., and Shaoping Shi and
Stefano Orsino, ANSYS, Inc.
The technology of coal gasification
has existed since the early 19th century.
Prior to the discovery of natural gas,
coal was used to produce so-called
“town gas” for lighting and heat in cities
across the United States and Europe.
Specifically, the gasification process is
used to convert any carbon-containing
material into a synthesis gas, or syngas.
Syngas contains mostly carbon
monoxide (CO), carbon dioxide (CO2)
and hydrogen (H2) and can be used as a
fuel to generate electricity or as a basic
chemical building block for a large number of applications in the petrochemical
and refining industries. Gasification
thus adds value to low-rank coal
feedstocks by converting them into
marketable fuels and products. Due to
more recent technological advances,
gasification offers one of the most efficient and cleanest ways to convert the
energy content of coal into electricity,
hydrogen, methanol and other usable
Based on the mode of conveyance
of the coal and the gasifying medium,
gasifiers can be classified into fixedor moving-bed, fluidized-bed, and
entrained-flow reactors. Entrained-flow
gasifiers are normally dilute-flow with
small particle sizes and have been successfully modeled with computational
Mixing zone
PSDF gasifier schematics (left) and an exploded view of the mixing zone (right) colored by contours of CO fraction
fluid dynamics (CFD) using the
Euler–Lagrange, or discrete phase,
model approach [1]. For fluidized-bed
gasifiers however, Eulerian–Eulerian
(E-E), or two-fluid multiphase, model is
the most appropriate approach. The
E-E model treats the solid phase as
a distinct interpenetrating granular
“fluid” and is the most generalpurpose multi-fluid model.
Transport gasifiers are based on
circulating fluidized–bed (CFB) reactor
technology and have the ability to
achieve higher throughput, better
mixing, and increased heat and
mass transfer rates compared to
other conventional technologies. CFB
reactors have been an established
technology in the chemical and power
Visualizations of the flow in the mixing zone of the PSDF gasifier for a case with air-blown and steam-enhanced lignite
fuel. Included are flow pathlines colored by CO fraction (left); velocity vectors on isosurfaces of solid fraction of 0.2 and
0.3, in which the formation of particle clusters can be seen (center); and contours of carbon reaction rate (right).
Recycling solids
ANSYS Advantage • Volume I, Issue 2, 2007
generation industries for years. However,
new reactor designs to improve performance, reliability and safety have
been slow to emerge due primarily to the
lack of understanding of the complex
hydrodynamics of the gas and solid
The idea of describing fluidized beds
and CFBs with two-fluid hydrodynamic
models has existed since the early
1960s [2]. Even with today’s powerful
computers, numerical solutions of largescale CFBs are rarely found in the
literature, and even fewer that consider
3-D solutions [3]. Fortunately, the E-E
modeling approach is one that can help
researchers understand the complex
interactions between the gas and solid
phases and aid engineers in the design
of new reactors. This approach can provide detailed 3-D transient information
inside the reactor that otherwise could
not be obtained through experiments
due to the large scale, high pressures
and high temperatures involved.
To gain more insight into the process
phenomena, ANSYS teamed with the
U.S. Department of Energy’s National
Energy Technology Laboratory (NETL) to
develop different CFD models for simulating coal gasification applications.
Mass flux at outlet (kg/s)
t (s)
Fluctuations of the mass flux (including both solid and gas) at the gasifier outlet. The negative
value represents the outgoing flow at the outlet. The magnitude of these fluctuations can deviate
by as much as 70 percent around the mean of – 47.12 kg/s.
Temperature (F)
Time-averaged temperature distribution along the PSDF center line as compared to experiment
Their objective was to illustrate how CFD
can be used for complex large-scale
geometry with detailed physics and
chemistry. Using FLUENT software, the
team developed a 3-D transient model of
KBR, Inc.’s Power Systems Development
Facility (PSDF) transport gasifier. KBR is a
global engineering, construction and
services company that has partnered
with other companies to build a commercial transport gasification unit, based
on the technology developed from the
PSDF, at a 285-MW power generation
facility in Florida that promises to be the
cleanest coal-fueled plant in the world.
Outlet gas composition for the PSDF transport gasifier
as compared to experiment
In the FLUENT simulation of the
PSDF, 11 species were included in the
gas phase while four species were
assumed to be in the solid phase.
A total of 16 reactions, both homogeneous (involving only gas phase
species) and heterogeneous (involving
species in both gas and solid phases),
were used to model the coal gasification chemistry. The gas combustion
reactions were simulated with a finiterate combustion model. The coal
reactions, including moisture releasing,
devolatilization, char combustion, char
gasification, tar cracking and water–
gas shift reactions, were modeled with
a heterogeneous reaction scheme and
a set of user-defined functions. The
geometry was meshed with 70,000
cells, and each simulation case was
run in parallel on an eight-processor
machine. Post-processing the data
was done once the solution reached a
pseudo-steady state, which required
running the simulation until it generated physical data representing about
40 seconds of time.
The basic design of the PSDF
transport gasifier included a mixing zone,
which kept the recycling solids present
long enough for the carbon left in the
particles to react with the incoming gas
(O2, steam or CO2). Visualizations of the
system interior showed that the flow was
recirculating and mixing in the mixing zone
before it moved up into the riser section,
and also that local conditions were very
chaotic and turbulent. At the bottom of the
mixing zone, combustion of the carbon
present in the recycle material depleted
the available O2. Further combustion
occurred as the solids moved up higher
into the mixing zone. At the same time,
other reactions such as CO and H2
combustion were competing for the O2.
These exothermic reactions generated the
necessary heat for the endothermic
reactions, including steam gasification and
CO2 gasification of carbon.
The research team validated the overall computational results against PSDF
experimental data for both bituminous
and sub-bituminous coals under both
air-blown and oxygen-blown conditions.
The computational difference between the
mass flux at the inlet and average mass
flux at the outlet was only 0.1 percent,
which meant that the mass was balanced
well from the simulation standpoint. The
team drew the same conclusion for the
heat balance. For the temperature profile,
the difference between the simulation and
measurement was due mainly to the
location of the probes relative to the center
line. Despite the finding of very uneven
temperature distributions at any given
cross section, the overall trends of
the temperature profiles were in good
agreement with the measured data. ■
[1] Shi, S.; Zitney, S.; Shahnam, M.; Syamlal, M.;
Rogers, W., Modeling Coal Gasification with CFD
and the Discrete Phase Method, 4th International
Conference on Computational Heat and Mass
Transfer, May 2005, Paris.
[2] Davidson, J., Symposium on Fluidization —
Discussion, Trans. Inst. Chem. Eng., 1961, 39,
pp. 230-232.
[3] Guenther, C.; Syamlal, M.; Shadle, L.;
Ludlow, C., A Numerical Investigation of an
Industrial Scale Gas–Solids CFB, Circulating
Fluidized Bed Technology VII; Grace, J.; Zhu, J.;
de Lasa, H., Eds.; CSCHE, Ottawa, 2002, pp.
ANSYS Advantage • Volume I, Issue 2, 2007
Chopping Away
at Solids
CFD simulation provides a pump
company with a virtual test facility.
By Glenn Dorsch and Kent Keeran
Vaughan Company Inc., Washington, U.S.A.
Geometry of a typical casing, impeller and cutter bar assembly
Chopper pumps utilize a
chopping action between
the impeller and the suction
plate to break down solids
that pass through the pump
into smaller pieces. Vaughan
Company, an established
pump manufacturer in
Washington, U.S.A., designs
and manufactures a line of
In a Vaughan chopper pump, the main
impeller vanes extend all the way to the
centrifugal chopper pumps.
center hub of the impeller, and the suction
These pumps originally were
plate includes two stationary fingers that
protrude to the center of the suction
designed in the 1960s for use
opening. As the main vanes pass by the
in the local dairy industry to
stationary fingers, a chopping action
results, which macerates any solids
transport manure to and from
entering the pump.
storage tanks. Since then,
Vaughan chopper pumps have been refined continually and
awarded a number of patents; the company has earned wide
acceptance for many applications that require solids
handling. Today, Vaughan chopper pumps are used in
various phases of municipal and industrial sewage treatment,
food processing, and pulp and paper industries, in which the
pumped liquid contains solids that need to pass through the
pump without clogging or plugging.
The benefit of a Vaughan chopper pump over a typical
non-clog or slurry pump is that it reduces the solids size of
material passing through the pump. The unique chopping
requirements and suction arrangement of these pumps
make it difficult to apply standard impeller design practices
in order to evaluate hydraulic performance. As energy costs
continue to rise, developing more efficient pumps becomes
increasingly critical for all pump manufacturers. Vaughan
Company found that simulation was an effective and
efficient way to approach the optimization of pump design.
Vaughan Company’s simulation process begins by
importing computer-aided design (CAD) models from
Pro/ENGINEER® into ANSYS DesignModeler software. The
impeller domain and casing domain are meshed separately
and assembled within the CFX pre-processor in which
boundary conditions are applied. The ANSYS CFX solver
performs the required calculations; then, results are
viewed and pump performance is calculated in the computational fluid dynamics (CFD) post-processor. The ANSYS
Workbench platform facilitates the entire simulation process,
from geometry import through visualization.
Performance curve for a recently redesigned 6-inch pump. The simulation slightly
underpredicts TDH because the geometry for the impeller and casing had to be
reverse-engineered, and there were likely some differences between the model
and the actual parts.
ANSYS Advantage • Volume I, Issue 2, 2007
Comparison between the simulated existing impeller and the simulated redesigned
impeller ensured that the redesigned impeller had TDH characteristics that were as
good as the original impeller. The new design achieved an approximately 8-point
increase in efficiency over most of the flow range.
Spotlight on Engineering Simulation in the
Biomedical Industry
Making Life Longer and Better
s10 Standing Up Right
Turning Up the Volume
s12 Designing with Heart
Hip to Simulation
s14 Going with the Flow
Walking Pain Free
s15 Battle of the Bulge
Engineering Solutions for
Infection Control
Simulation Driven
Product Development:
Making Life Longer
and Better
The biomedical industry is emerging as a
strategic user of engineering simulation.
By Thierry Marchal and Kumar Dhanasekharan, ANSYS, Inc.
Recent analyses show that leading biomedical companies around the world are continuously growing their
investment into research and development (R&D), with an
increase of 12.5 percent in 2006 that reached total R&D
expenses exceeding $9 billion [1]. This is no surprise, given
the need for advanced medical treatments and care due to a
large and growing population of aging individuals, the need
to find minimally invasive treatments for conditions such as
diabetes and heart disease, and the increasing demand for
artificial organs. As medical product innovation continues to
become more complex, there is a strong emerging need for
Simulation Driven Product Development, which has been
seen and is broadly accepted in the semiconductor,
aerospace and automotive industries.
Simulation is becoming an integral part of the product
design cycle in biomedical applications ranging from
prosthetics and artificial organs to endovascular techniques
to surgical devices, medical equipment and diagnostic
products. There are a number of reasons for such simulation
to continue its entrenchment in biomedical product development. First, the advancement in technologies such as
high-performance computing (HPC) is able to meet the
demands of biomedical product development, allowing
healthcare institutions, life science researchers and the
industry to conduct large-scale simulation studies. The
increasing ability to import computed tomography (CT)
scans and magnetic resonance imaging (MRI) into simulation
software — a process now becoming routine — makes it
feasible to address in vivo device design needs (such as with
respiratory drug delivery and endovascular devices), essentially enabling virtual prototyping. In addition, the integration
of simulation techniques across multiphysics, from structural
analysis to flow modeling to thermal analysis, is enhancing
the virtual prototyping needs of the biomedical industry. For
example, in studying aneurysms, ANSYS simulation tools
have been used to import CT scans into the simulation
Arterial wall
Simulation Driven Product Development is being applied regularly in the biomedical industry. This aneurysm study was performed within an integrated environment to
analyze coupled fluid flow and structural simulation. The steps are: 1) CT scan; 2) segmentation from scans to extract branches; 3) cuts are written in form of splines;
4) creation of solid geometry composed of arterial wall/thrombus and automatic creation of fluid volume from the solid geometry; 5) independent mesh for each simulation
technique (flow modeling and structural modeling); and 6) coupled fluid and structural model with model setup, analysis and post-processing in a single environment.
ANSYS Advantage • Volume I, Issue 2, 2007
environment, allowing researchers to study a structural
analysis of the weakened arteries along with the flow patterns
in a single virtual environment, truly creating a virtual prototype model with multiphysics, all in an integrated manner.
Another growing area is drug delivery, particularly with
medicines that are released into the bloodstream or respiratory system. There is a need to better understand the
process and how adjustments can be made to accelerate
drug delivery to the point of highest efficacy, which then will
allow healthcare companies to design better devices that
administer appropriate dosages.
Similarly, orthopedic departments are paying more
attention to the virtual prototyping approach brought by
computed-aided engineering (CAE). Bones are critical
pieces of the body, having complex, specific geometries;
they are made of different materials exhibiting strongly
nonlinear behavior. Until now, scientists have lacked proper,
robust models that can be used to bring together, into a
single simulation, characteristics as complex as poroelasticity, nonlinear viscoelasticity and linear elasticity, which
are needed for an accurate description of an intervertebral
disc (ID), for example. The improved robustness of existing
models together with the availability of reliable material
properties now provides evidence that these numerical
results can bring new, invaluable information to doctors. As a
result, healthcare institutions now are studying how a hip
prosthesis will perform related to a comfortable walk over a
long period of time as well as investigating — prior to planning spinal surgery or even designing an ID implant —
whether the remodeling procedure leading to the unification
of the pedicle screw and the vertebra is likely to progress
smoothly. [See Standing Up Right on page s10.]
To illustrate recent concrete progress in addressing reallife problems and pain relief via CAE, this biomedical
spotlight describes applications in which simulation technology has made a major difference. Both fluid flows and
solid mechanics, or the combination of the two, appear in
surprising applications. Some are critical to patient life or
function, such as lung air flow and spine implant; others
simply make life more comfortable through better ear
implants and insole design.
For the future, imagine the impact of simulation to drive
the development of patient-specific medicine and medical
care. For example, tomorrow’s surgeons may be able to take
CT scans of patient physiology and use simulation to
conduct virtual surgery as well as study the procedure’s
effectiveness as part of the overall process. This is enabled
through automation of simulation along with rapid design
comparisons through automated parametric studies — and
it is rapidly becoming reality. The era of simulation in the
biomedical world is rising. ■
[1] The R&D Scoreboard 2006, Volume 2, Department of Trade and
Industry (DTI), U.K.
Proper design of a medical insole required to develop an accurate modeling of the foot
at different stance phases during required ambulation: 1) the initial contact state; 2) the
mid-stance state; and 3) the toe-off state. The resulting data was used to calculate the
pressure and stress induced on the plantar surface as well as inside deep tissues.
ANSYS Advantage • Volume I, Issue 2, 2007
Cochlear implant diagram: implant components (left) and insertion in the cochlea (right)
Image from Hals-Nasen-Ohren-Heilkunde, Boenninghaus, Hans-Georg, Lenarz, Thomas, 2005, Kapitel 5
“Klinik des Innenohres,” p 116. Published by Springer Berlin Heidelberg, ISBN 3-540-21969. With kind
permission of Springer Science and Business Media.
Turning Up the Volume
The use of shape memory alloys offers the promise of
better functioning in cochlear implants.
By Dieter Kardas, Institut für Baumechanik und Numerische Mechanik (IBNM), Leibniz Universität Hannover, Germany
Wilhelm Rust, Fachhochschule Hannover, Germany
Ansgar Polley, CADFEM GmbH, Burgdorf, Germany
Tilman Fabian, Hannover Medical School, Germany
Cochlear implants (CIs) are electronic hearing devices designed to
restore partial hearing to those who are
deaf or severely hearing-impaired. The
devices consist of three external and
two internal components. The external
device comprises a microphone that
picks up sounds from the environment,
a speech processor and a transmitter.
The internal components include two
surgically implanted devices: a receiver
that works with the transmitter to
convert speech processor signals into
electronic impulses and an electrode
array that uses those signals to stimulate the auditory nerves within the ear.
One of the traditional limitations of
the electrode array is the inability to
achieve optimal depth of insertion into
the cochlea, the auditory portion of the
inner ear. A German team including
Heat up
Cool down
Demonstration of one-way shape memory effect, from left
to right: initial shape of a component, deformed shape,
shape on warming, shape on cooling after warming
CADFEM GmbH, the Hannover
University of Applied Sciences and
Arts, and the Leibniz University of
Hannover has found that an improvement might be possible using shape
memory alloys (SMA).
Shape memory materials display
distinct thermo-mechanical behavior.
In the case of shape memory effect
(SME), a body that has undergone
plastic deformation will return to the
original shape or form that it had prior
to deformation by heating it above a
critical temperature. After being heated
and returning to its original form, a
shape memory material will not change
back to its deformed shape if cooled.
This phenomenon can be observed in
many shape memory alloys, specifically nickel-titanium (Nitinol), which has
a wide range of applications in the
automotive and aerospace industries.
In addition, due to its high biocompatibility, high resistance to corrosion and,
above all, the thermal-induced SME,
Nitinol is very useful in the field of
medical engineering.
In the case of the CI, the research
team thought that by taking advantage
of the thermally induced shape
memory behavior of Nitinol, greater
implantation depth for the electrode
ANSYS Advantage • Volume I, Issue 2, 2007
array could be achieved. The concept
was to design an SMA component
whose shape matched that of the
cochlea. Prior to the insertion process,
the component would be deformed
pseudo-plastically, and then, relying
on heating from the body itself, it
would return to its original form during
implantation. To pursue this idea,
implant simulations that accounted for
the pseudo-plastic deformation and
shape memory behavior were carried
out using ANSYS Multiphysics tools.
For these simulations, the team
created a material model for SMA and
implemented it in ANSYS Multiphysics
via user-interface USERMAT for threedimensional finite elements. The
phenomenological material model
was developed using stress–strain–
temperature data for SMA and was
based on a linear kinematic hardening
model. The stress–strain behavior of
shape memory materials, which is
highly nonlinear in nature and varies
with temperature, was incorporated into
the simulation with the addition of
parameter: the middle stress σm.
The shape memory stress–strain
curve differs from the standard linear
kinematic model in that the shape of
Pseudo-plasticity σm = 0 (left) and pseudo-elasticity σm > σy* (right). The middle stress (σm) rips the
shape memory alloy stress–strain hysteresis as temperature increases.
Final state superimposed
(Scale: 20˚C to 37˚C)
Time: 53 Seconds
Time: 35 Seconds
Time: 17 Seconds
Time: 0 Seconds
Superposed Cochlea-model
(Scale: 20˚C to 37˚C)
Time: 65 Seconds
the stress–strain hysteresis — which
one gets by periodically changing force
direction — is ripped in a manner
that varies with temperature. Shape
memory alloys exhibit pseudoplasticity at a low temperature range
and pseudo-elasticity at a high temperature range. These temperature ranges
depend on the percentage composition
of nickel and titanium; generally
both are equiatomic, which means that
the rip of the curves increases with
increasing temperature.
The degree to which the curve is
ripped is determined by the mentioned
middle stress, σm. If σm is set to zero,
then the hysteresis experiences no rip,
and pseudo-plasticity can be represented. If σm is set to a higher value
than the so-called amplitude stress σy*
(half value of the distance from upper
flow curve to lower flow curve), pseudo-elasticity can be represented. The
actual value of the middle stress was
determined using experimental data
taken at various temperatures. In order
to obtain a smooth, nondiscontinuous
representation of the flow curve, a
tanh-function was included in the
equations that describe the offset/rip
behavior as a function of σm.
By incorporating this offsetfunction σoff (tensor-function of order
two) into the material model, the shape
memory behavior was effectively
captured with only two sets of material
constants: one set for pseudo-plasticity
and another for pseudo-elasticity.
ANSYS Multiphysics software itself
interpolates between these parameter
sets to provide the material constants
for the actual temperature. With this
technique, it was possible to reproduce
any intermediary state between
pseudo-plastic and pseudo-elastic
stress–strain behavior.
By including this shape memory
behavior, the CI development team was
able to simulate implantation of a shape
memory cochlear implant (SM-CI) into
the cochlea. The results of a 65-second
simulation of the implantation process
supported the idea that the temperature
of the human body could have enough
of a thermal effect on the array that,
when implanted, it could return to the
original shape: that of the cochlea.
These findings support the possibility
of a solution that can provide
deeper implantation and, thus, better
functionality for the CI. ■
Time-spaced results of the implant simulation for a shape memory cochlear implant. The red color
indicates that body temperature has been reached by the implant.
Cochlear geometry data courtesy Hannover Medical School, Dr. Omid Majdani.
ANSYS Advantage • Volume I, Issue 2, 2007
Hip to Simulation
Evaluation of designs for a hip replacement
prosthesis overcomes physical and
scientific limitations.
By Joel Thakker, Integrated Design and Analysis Consultants, U.K.
Hip replacement surgery involves to model the force required to remove
replacing the damaged or diseased the socket axially. A three-dimensional
ball-and-socket joint configuration model was used to analyze rotational
with artificial parts. During surgery, a removal of the joint, since a twocup or hip socket — a dome-shaped dimensional case would not represent
shell/liner — is implanted into the the behavior fully. The ANSYS
acetabulum portion of the pelvic girdle Mechanical simulation used nonlinear
after the bone has been hollowed out contact elements in the prosthetic hip
using a grater. The thigh, or femoral, socket and accounted for friction
portion of the hip replacement pros- between the cup and bone. In all
thesis is composed of a
analyses, the implant
ball, which acts like a
cup was modeled in
bearing where it fits into
titanium while the bone
the cup and is attached
was treated as an anisoto a stem that further
tropic material.
attaches to the femur.
For both analyses,
The Duraloc® unceIDAC created parametric
models in order to evalumented acetabular hip
The Duraloc® uncemented acetabular
socket, a replacement hip socket is made from titanium and ate different bone and
implant cup geometries,
cup developed by has a porous coated shell.
material properties and
DePuy Orthopaedics,
Inc., in the U.K., uses an interference fit boundary conditions. The assembly
to hold the socket in place in the hip conditions involved inserting the cup
bone. To assist DePuy in the design of into the bone to overcome interthe Duraloc product, Integrated Design ference, allowing the frictional effects
and Analysis Consultants (IDAC) to hold the cup in place, and subseused ANSYS Mechanical software to quently removing, either axially or
develop parametric models that are rotationally, the cup from the bone to
used to establish both the necessary establish disassembly loads.
This form of modeling allows
implantation and disassembly forces
DePuy to evaluate different configurafor variations of the replacement joint.
IDAC performed a two-dimensional tions of implant design numerically
analysis on the cup assembly in order rather than by physical testing, which
Contour plot of stresses induced by the interference fit between the prosthesis and the bone;
the areas colored in grey illustrate the region
of the bone that could be expected to yield
during the assembly process.
ANSYS Advantage • Volume I, Issue 2, 2007
Three-dimension finite element model mesh
of bone and prosthesis
X-ray of a hip showing a prosthesis, including the socket,
ball and stem. Image courtesy DePuy Orthopaedics, Inc.
is time-consuming and expensive in
comparison. Physical testing is limited
as real bone materials are not highly
available. Some synthetic and naturally
occurring materials can be used, but
their material properties do not precisely match that of human bone
materials. Numerical modeling allows
DePuy to view detailed stress and
deflection distribution plots and load
versus time history plots that cannot
be created easily from physical tests.
Comparisons between the results
obtained through simulation and those
obtained from previous testing reveal
a close correlation.
As a result of this study, DePuy has
used this type of design evaluation in
other orthopedic implant products,
including artificial knee joints. ■
Illustration of stress distribution in the hip
joint assembly after the prosthesis has been
pressed into place
Walking Pain Free
New insoles designed with the ANSYS mechanical
suite relieve pain from foot disease.
By Bum Seok Namgung, Dohyung Lim, Chang Soo Chon and Han Sung Kim
Yonsei University, Seoul, Korea
The human foot does more than
simply enable mobility. Feet are an
important part of the body because they
bear weight, absorb shock and stabilize
body structure, but they usually get little
of our attention. When foot disease
appears and pressure and stress
exceed a given limit, pain occurs —
making a person suddenly aware of just
how critical a function the feet provide.
For people with diabetes, subject to
poor circulation and neuropathy, even
ordinary foot problems can get worse
and lead to serious complications.
One research project designed
to benefit such patients involves
developing insoles that will prevent pressure sores on the deep tissues inside the
plantar surface of the foot. A team at the
Institute of Medical Engineering at
Yonsei University in Korea is finding new
ways to gather information on the
mechanical response of the foot to various insole designs. They are utilizing
finite element analysis (FEA) software
from ANSYS, Inc. to design new patientspecific insoles that reduce both
pressure during ambulation and stress
within the feet, ultimately relieving
pain. The team selected the ANSYS
mechanical suite because of its reliability
and flexibility for handling complex and
irregular geometries. Furthermore, its
nonlinear, hyper-elastic models and
advanced contact conditions provide a
realistic alternative to experimental
approaches for gait analysis.
Using the ANSYS technology, the
researchers first created a threedimensional model using computerized
tomography (CT) images obtained from
the right foot of a subject with hallus
valgus, commonly called a bunion.
Commercial software, CANTIBio™
(CANTIBio, Inc., Korea) and meshing
software were used to fine tune the
contours of the foot.
Three geometries representing three
primary states (initial contact, mid-stance
and toe-off) during ambulation then were
created. The simulation models incorporated two insole designs: one flat and
one contoured to contact the entire
bottom of the foot. Each design was
analyzed at various values of elastic
modulus (0.3 MPa, 1.0 MPa and 1 GPa) in
order to represent a variation in insole
firmness and identify which more effectively redistributed von Mises stresses on
the plantar, or bottom, surface of the foot
during standing.
During ambulation, ANSYS software
showed that high pressures first appear
on the plantar surface region overlying
the heel bone for the initial contact state,
progresses through the middle of the foot
for the mid-stance state, and finally, for
the final toe-off state, is concentrated in
the vicinity of the metatarsal head bone at
the front of the foot. These results are in
agreement with those obtained from a
foot scan system used in experimental
gait analysis.
The results found that stresses on the
plantar surface are significantly lower with
the total contact insole compared with
those of the flat insole; stresses also are
dependent on the insole elastic modulus.
This confirms that customized design of
an insole for patients with foot disease
may be necessary, and the solution
should include biomechanical and clinical
points of view. ■
During ambulation (top to bottom), the highest
pressure progressively shifts from the plantar
region under the heel bone forward to the
metatarsal head bone.
Von Mises stress distributions on the plantar
surface of the foot using the flat (top) and
total contact insoles (bottom)
Two insoles, one flat (left) and one shaped to contact the entire sole of the foot (right), were compared in this analysis
to understand the impact of the geometry on foot pain.
ANSYS Advantage • Volume I, Issue 2, 2007
Engineering Solutions
for Infection Control
Simulation assists in designing a hospital ward to reduce the airborne
transmission of diseases such as tuberculosis and influenza.
By Cath Noakes and Andrew Sleigh
University of Leeds, U.K.
Hospital Nacional Dos de Mayo in Lima, Peru, was the
site of a TB ward ventilation system redesign.
Hospital-acquired infection poses a
major problem in healthcare facilities
around the world. Although many
infections are transmitted through handto-hand contact, airborne transmission
also may play an important role; this is
the primary mechanism for a number of
infections, including tuberculosis (TB)
and influenza. Airborne routes also have
been implicated in the transmission of
hospital-acquired infections such as
methicillin-resistant Staphylococcus
aureus, Acinetobacter spp and norovirus. Successful control of infection
involves breaking the chain of transmission. To do so, it is necessary
to understand both the mode of transmission as well as the nature of the
pathogen and its behavior in the
The role played by airborne
transport of pathogens has been
the driving force behind the research
carried out by the Pathogen Control
Engineering Group at the University of
Leeds in the U.K. for the past 10 years.
The multi-disciplinary team of engineers, mathematical modelers and
microbiologists is based in the School
of Civil Engineering, with strong links
to clinicians at the Leeds Teaching
Hospitals and to academics and
scientists around the world. Originally
set up to investigate ultraviolet (UV) air
disinfection devices to combat TB, the
group now focuses on understanding
airborne transmission routes with a
strong emphasis on the hospital
environment. This knowledge is used
to aid the development of new
infection control technologies and to
optimize engineering strategies to
reduce the risk of disease.
The suitability of a ward ventilation
system design was the subject of a
recent study carried out using ANSYS
CFX computational fluid dynamics
(CFD) software [3]. The two-bed ward in
Hospital Nacional Dos de Mayo,
located in Lima, Peru, is one of a
number of similar rooms housing
patients with TB. Unusual to a hospital
in this part of the world, the wards are
mechanically ventilated. Any airborne
transmission of TB within the hospital
will be strongly influenced by the
imposed ventilation flow. As part of a
wider project researching TB transmission, led by Dr. Rod Escombe of
Imperial College in London, U.K., the
CFD study was carried out to examine
whether changes to the ward layout and
ventilation system could reduce the risk
of cross-transmission between patients,
staff and visitors in the hospital.
A simplified geometry represented
the key features in the ward, including
ANSYS Advantage • Volume I, Issue 2, 2007
the basic furniture, the ventilation
supply and extract vents. Isothermal
airflow was modeled on an unstructured tetrahedral grid using a standard
k–ε turbulence model. Supply air
velocities were defined to ensure a
room ventilation rate of 6 AC/h for all
simulations, and a pressure of –10 Pa
was imposed on the extracts to
Bed 1
Bed 2
Extract (low, wall)
Extracts (high, wall)
Bed 1
Bed 2
Original room layout and ventilation system (top) and
proposed new layout (bottom) showing the location of the
partition between the two beds, the additional ventilation
supply diffuser and the modified extract locations
simulate the negative pressure that is
maintained in the real facility. As
the study focused on the risks of
cross-infection, it was important to
include a model to represent the
release of infectious material from TB
patients. To relate the CFD study to
published outbreak data, a scalar
infectious particle production variable
was defined in terms of units of infectious dose, known as “quanta.”
To represent a patient’s production
of TB bacteria, a small inlet condition
was located close to the head of
each bed. Scalars, representing the
infectious particles produced by each
patient, were introduced into the room
at a constant rate of 14 quanta/hour
in order to represent the typical production rate of a pulmonary TB patient.
The CFD study made it quick and
easy to compare the impact of a
number of proposed modifications to
the ward. The original room layout with
its single ceiling-mounted supply
diffuser and wall-mounted extract
resulted in significant mixing of TB
contamination throughout the room,
demonstrating the high risk of crossinfection between patients. The simple
addition of a partition between the two
beds yielded an immediate benefit,
providing a physical barrier that limited
the transfer of infection between the
two areas. As a low-cost intervention,
this could prove beneficial in resourcepoor countries, although it may not
be suitable for naturally ventilated
environments. Combining the partition
with a new ventilation system layout,
comprising ceiling supply diffusers
above the foot of each bed with wallmounted extracts at the head of each
bed, yielded the best results. Despite
the ventilation rate remaining constant,
the transfer of infectious material
between the two beds was reduced by
over 75 percent, representing a
Streamlines originating from patients 1 (red) and 2 (blue) show how
a partitioned room with modified ventilation system (bottom) more
efficiently extracts contaminated air than the original room (top) does.
significantly reduced risk of crossinfection between patients. These
findings were of immediate benefit to
the architects redesigning the ward,
who based the new ventilation system
and ward layout directly on the study
results. ■
[1] Noakes, C.J.; Sleigh, P.A.; Fletcher, L.A.;
Beggs, C.B., Use of CFD Modeling in
Optimising the Design of Upper-Room UVGI
Disinfection Systems for Ventilated Rooms.
Indoor and Built Environment, 2006 15(1),
pp. 347-356.
[2] Noakes, C.J.; Fletcher, L.A.; Beggs, C.B.;
Sleigh, P.A.; Kerr, K.G., Development of a
Numerical Model to Simulate the Biological
Inactivation of Airborne Microorganisms in
the Presence of UV Light. Journal of Aerosol
Science, 2004, Vol. 35(4), pp. 489-507.
[3] Noakes, C.J.; Sleigh, P.A.; Escombe, A.R.;
Beggs, C.B., Use of CFD Analysis in
Modifying a TB Ward in Lima, Peru. Indoor
and Built Environment, 2004, 15(1),
pp. 41-47.
Contaminant concentration contours, at an elevation of 1.4 m
above the floor originating from patient 1. The figure on the top
has no partition, while the figure on the bottom uses a partition
and ventilation systems local to each patient.
ANSYS Advantage • Volume I, Issue 2, 2007
Standing Up Right
ANSYS Multiphysics sheds light on the wonders of the
human spine and how to fix it.
By Stavros Kourkoulis, Satraki Margarita and Chatzistergos Panagiotis, National Technical University of Athens, Greece
The human spine is a wonder of
engineering work, one that is heavily
used in daily activities. An important
part of it, the intervertebral disc (IVD), is
one of the most sophisticated suspension and shock absorption systems
ever found. When disorders arise, back
pain quickly can become a nightmare.
The National Technical University of
Athens (NTUA) in Greece conducted
a study using ANSYS Multiphysics
software that revealed some secrets of
how this precious structure works, as
well as ways to fix it efficiently when it
The spine’s intervertebral disc
is exposed to a combination of
compression, bending and torsion
Simulating the Intervertebral Disc
The IVD is located between the vertebrae in the spine. In performing daily
activities, it acts as a cushion and
therefore is exposed to a combination
of compression, bending and torsion
stresses. Each disc consists of the
nucleus pulposus, a gel-like inner portion of the disc; the annulus fibrosus,
the outer portion made of about 20
lamellae of coarse collagen fibers; and
the two cartilaginous endplates, composed of hyaline cartilage, located on
either side of the nucleus and annulus.
The IVD simulation model comprised
four distinct volumes corresponding to
the disc’s regions: The nucleus was
modeled as a nonlinear viscoelastic
material in a kidney-like cross section;
the two cartilaginous vertebral endplates
were considered linear elastic bodies;
and the annulus surrounding the nucleus
was simulated as dual laminated shell
elements whose outer surfaces were
viscoelastic in nature. The study
analyzed various scenarios in order to
determine the contribution of each
section of the IVD to the viscous character of the entire structure.
The numerical model revealed that
the maximum stresses appeared in the
fibers of the intermediate volumes of the
annulus, in the vicinities of the endplates.
The nucleus was almost stress-free, as
expected due to its gel-like nature.
The NTUA study also investigated the
behavior of the IVD during daily activities;
the results found that the reduction of
disc height related to a person’s 24-hour
daily cycle was in very good agreement
with the respective experimental data by
Tyrell et al (L3–L4 discs) [1].
The numerical model of the intervertebral disc: a) nucleus pulposus, b) annulus fibrosus and c) cartilaginous vertebral endplates
ANSYS Advantage • Volume I, Issue 2, 2007
The von Mises stress distribution through the center of the disc horizontally (left) and at the point of minimum
vertical cross-sectional area (right)
Studying the Surgical Remedy
Spinal stabilization using pedicle
screws and rods (or plates) is one of the
most common invasive treatments for
spinal disorders and injuries. In this
procedure, the surgical team implants
screws posteriorly into a number of
vertebrae and bolts them to a rod or
plate. This assembly actively fixes the
vertebra in place, with respect to each
other, and thus stabilizes that section of
the spine. After such a procedure, some
serious problems can still exist. Pain in
the IVD adjacent to the fixed vertebrae
can occur due to failure of the spinal
instrumentation, from either a fracture in
structural elements or a loosening of
the screws. Experimental and clinical
studies alone cannot provide a complete view of the mechanical behavior
of such complex structures. Numerical
simulations introduce a unique tool for
the thorough and parametric study of
such systems.
From the moment a pedicle screw
is implanted into the vertebra, the bone
begins to regrow around the screw.
This regrowth leads to the eventual
complete unification of the bone and
the implant, which occurs about two
years postoperatively. A fundamental
requirement for the success of this
procedure is the stability of the screw’s
fit into the bone. NTUA used mechanical simulation to investigate the
influence of the vertebra structure and
screw specifications — such as depth
of implantation, pitch and inclination
of the thread — on the value of the
force required to loosen the screw from
the spine.
The distribution of the Mises equivalent stress in a typical
vertebra for a pull-out displacement of 0.02 mm
The parametric study assumed
that the vertebra consisted of cortical,
subcortical and cancellous bone as
suggested by measurements of bone
mineral density of typical human
lumbar vertebrae. The simulations
estimated the force required to produce a pull-out displacement of 0.02
mm, the stress distribution onto the
bone, and the contact pressure on the
bone–screw interface. The results indicated that the pull-out resistance could
be amplified significantly by ensuring
that the screw was anchored into the
regions of stronger materials located
near the cortical shell. Furthermore, the
parameter found to have the strongest
influence on the pull-out force was the
screw pitch. For pitch values varying
from 2 to 5 mm, the pull-out force
increased linearly by approximately
30 percent. The variation of the screw
depth and the thread inclination had
limited impact on the pull-out force.
A comparison of the numerical results
with the experimental results found
them to be in very good agreement,
within the tolerance of experimental
The main advantage of the
numerical models lies in the accurate
simulation of both the structure and the
shape of the various portions of the
biological disc or vertebra as well
as of the constitutive behavior of
the different materials. In order to
further improve the accuracy of these
numerical analyses, researchers must
develop studies using models of
increasing sophistication adapted to
specific groups of people with morphology and properties varying with
age, sex, type of activities, degenerations and other factors. ■
[1] Tyrell, A; Reilly, T; Troup, J., Circadian
Variation in Stature and the Effects of Spinal
Loading, Spine, 1985, 10(2), pp. 161-164.
The two phases of model construction: (left) the screw and surrounding bone implanted
into the vertebra and (right) the regions of the vertebra (yellow: cancellous bone; red:
subcortical bone; blue: cortical shell)
ANSYS Advantage • Volume I, Issue 2, 2007
with Heart
The PediaFlow ventricular
assist device provides
long-term cardiac support
for infants.
CFD-based design optimization
for a miniature ventricular assist
implant can shave years off the
medical device development cycle.
By Jingchun Wu, LaunchPoint Technologies, Inc., California, U.S.A.
and Harvey Borovetz, McGowan Institute for Regenerative Medicine
Pennsylvania, U.S.A.
An important challenge facing the
design of turbodynamic ventricular
assist devices (VADs) intended for
long-term cardiac support is the optimization of the flow geometry to
maximize hydraulic efficiency while
minimizing the peak shear stress in the
blood flow. High efficiency reduces the
required battery size while low shear
reduces the number of red blood cells
that are ruptured by the pump. A pediatric heart-assist pump is particularly
challenging. Due to its small size
(about 28 mm diameter by 51 mm
length), the design laws for adult-sized
pumps do not apply, and they cannot
be scaled. Therefore, the design of
pediatric blood pumps must rely on
modern design approaches to optimize the flow path. Computational fluid
dynamics (CFD) has been widely used
in the field of artificial heart pumps for
the analysis of internal flow because it
offers an inexpensive and rapid means
of acquiring detailed flow field information that is expensive and painstaking
through in vitro testing. LaunchPoint
Technologies, Inc., in the United
States, which developed the first magnetically levitated (maglev) heart pump
(the Streamliner ventricular assist
device that reached animal trials in
1998), finds that CFD is a powerful tool
in the performance assessment and
optimization of artificial heart pumps.
LaunchPoint has developed a CFDbased design optimization approach
that integrates internally developed
3-D inverse blade design methods,
parameterized geometry models,
automatic mesh generators and mathematical models of blood damage with
the commercial ANSYS CFX solver.
The system provides rapid optimization for various types of centrifugal,
mixed-flow and axial-flow blood
pumps. The ANSYS CFX solver was
chosen because of its robustness for
computations with multiple frames of
reference (MFR) (the coupling between
rotating and stationary components).
A new LaunchPoint VAD, PediaFlow™ is intended to deliver a flow rate
of 0.3 to 1.5 l/min against 100 mmHg
pressure rise to neonates and infants
weighing 3 to 15 kg. The PediaFlow
was designed with a magnetically suspended, mixed-flow style impeller with
a single annular flow gap between the
rotor and housing to avoid unfavorable
retrograde flow and separation. The
shear stress transport (SST) model, a
low Reynolds number turbulence
model, was selected for the turbulent
flow simulation, which was justified
by the representative Reynolds
number of ~30,000 based on the
impeller outlet diameter and the pump
tip speed. Although blood exhibits
non-Newtonian behavior at very low
shear rates, many studies have shown
that blood can be modeled as a
Newtonian flow at a shear rate larger
than the threshold of a 100 s -1. The
ANSYS Advantage • Volume I, Issue 2, 2007
shear rate in the computational model
of the PediaFlow is much larger than
this threshold, so Newtonian blood with
a constant viscosity of 0.0035 Pa-s and
a density of 1040 kg/s3 was assumed
for the simulations.
The CFD-predicted velocity vectors
at both the mid-span blade-to-blade
region of the impeller and the vane-tovane region of the stay-vanes show a
very smooth distribution without any
vortices at the nominal flow condition
for the optimized PediaFlow model. As
literature is replete with anecdotal evidence that recirculating flows lead to
attachment of platelets to biomaterial
surfaces — which in the clinical VAD
setting can promote blood clot formation — reverse flows and vortices are
undesirable. The CFD results found
that a smooth and gradual transition in
the secondary flow velocity was
present at the curvature of one inflow
and outflow cannula geometry. This
graduation helps to prevent separation
and reversal flow for the primary flow
velocity. In addition, the predicted
pathlines of representative particles
through the entire flow region did not
exhibit any vortices.
The exposure of blood elements to
shear stress above a certain threshold
as a function of exposure time can
cause hemolysis, which actively breaks
open the red blood cells; activate
platelets, which can cause clotting
problems; and denature proteins, which
alters the proteins so they can no longer carry
out their cellular functions. Thus, it is desirable
to minimize the shear stress that blood
passing through the pump may experience.
Using the results of the CFD simulation, a plot
of shear stress versus exposure time for
particles passing through the pump demonstrates relative uniformity within the annular
flow gap region, but it is less uniform within
both the impeller and stay-vane regions.
The overall mean blood damage through
the entire domain of the model is divided
according to the three main regions of the
flow path: impeller, annular gap and the stayvane. The analysis reveals that the hemolysis
level in the annular gap region is highest,
accounting for more than 50 percent of the
total, while the level of hemolysis in the
impeller region and stay-vane region is almost
the same, each causing approximately 20 to
25 percent of the total blood damage.
CFD-based design optimization with the
integration of the ANSYS CFX solver can
significantly reduce the design optimization
cycle from years, compared to the traditional
trial-and-error methods, to just several
months. It provides detailed and useful flow
field information from which blood damage
may be computed, and it also predicts the
hydrodynamic characteristics such as the
relationship of developed pressure and
efficiency to flow rate. ■
Predicted smooth velocity vectors at mid-span blade-to-blade region of the impeller (left) and
mid-span vane-to-vane region of stay-vanes (right)
Secondary flow streamlines at sections of inflow cannula (left) and sections of outflow
cannula (right)
This research was supported in part by NIH Contract
No. HHSN268200448192C (N01-HV-48192).
Pathlines of particles at inflow cannula and impeller side (left) and stay-vanes side and
outflow cannula (right)
PediaFlow is a trademark of WorldHeart, Inc.
Shear Stress (Pa)
0.002337 0.002341
0.00 0.02
Shear stress history from impeller inlet to stay-vane outlet
Annular Gap
Stay Vane
Proportion of total blood damage at different pump components under
nominal flow condition
ANSYS Advantage • Volume I, Issue 2, 2007
Going with the Flow
Functional biomedical imaging through CFD provides
a new way of looking at pathological lungs.
Reconstructed airway of a patient with cystic fibrosis:
The red arrows indicate regions in which inflammation
has restricted the airways.
By Jan De Backer and Wim Vos
FluidDA nv, Antwerp, Belgium
Contour plots show the effect that the use of a bronchodilator has on the local values for airway volume (left) and
resistance (right); red indicates high values and blue indicates low values.
simulate and examine the air flow. Flow
Diseases such as asthma, chronic
using CFD. The fluid and structural
patterns, relative pressure drops and
obstructive pulmonary disease (COPD)
dynamics company combines clinical
drug delivery profiles are readily
and cystic fibrosis can have a signifiexperience and capabilities with
extracted from the simulation results.
cant adverse impact on the structure
numerical simulations to offer a variety
The resistance distribution — defined
and integrity of the lungs’ airways.
of services to the healthcare industry.
as the total pressure drop over various
While functional magnetic resonance
The workflow process begins with
lung segments — also is available.
imaging (MRI) allows for measurethe conversion of CT scan data into a
The pharmaceutical and medical
ment of air flow, computational fluid
3-D computer model of the airway,
device sectors also can benefit from
dynamics (CFD) provides highly
performed with the Materialise product
patient-specific flow analysis as a way
detailed information of local flow
Mimics. FluidDA then uses TGrid
to evaluate performance and efficacy in
characteristics and resistances. The
software to create surface and volume
a virtual patient population. In clinical
first requirement of a patientmeshes and FLUENT technology to
studies, it is possible to analyze
specific analysis is knowledge
For patients with deformation of the spinal column (kyphoscoliosis),
the effect of bronchodilating
of the bounding walls of the
simulation can be used to determine the site of obstruction and/or
respiratory function.
medication, which widens lung air
patient’s flow domain — their lung
passages and relaxes bronchial
geometry. This type of information
Stent location
smooth muscle to ease breathing,
usually comes from computed
on airway volume and flow resisttomography (CT), a scan that indiance. A researcher then can begin
cates detailed information about
to establish correlations between
lung geometry because of the
drug deposition patterns and clininatural contrast between air and
cal outcomes, thereby providing
the lung walls. The main drawan indication as to why the drug
back of CT is that the resulting
does or does not work. Functional
scan is a static image. Coupling
Obstruction site (and subsequent location) of an intrabronchial stent,
which re-inflated the blocked lower right lung lobe. Pressure contours
imaging also can be used to
computational analyses of air flow
are plotted in the airway.
assess the placement of intrawith the lung scan has the potenbronchial devices such as stents
tial to provide significant added
and valves.
value to the clinical evaluation of
Coupled with CFD, such
lung function.
imaging can dramatically increase
FluidDA, a spin-off of the
insight into medical assessment
Antwerp and Ghent universities in
and improve the accuracy of
Belgium, has successfully develLower lobe
medical interventions. ■
oped a workflow for predicting air
An increase in the volume of the lower lobe is clear in time following
flow in healthy and diseased lungs
insertion of a stent.
ANSYS Advantage • Volume I, Issue 2, 2007
Battle of the Bulge
Rapid prototyping results in a new surgical tool
to treat back pain.
By Joe Richard, HydroCision, Massachusetts, U.S.A.
Brenda Melius, consulting firm, New Hampshire, U.S.A.
In the United States, back pain is one of the most common reasons for healthcare visits and missed work. Four
out of five adults have at least one bout of back pain at
some point in their lives.
A common source of pain is from a bulging intervertebral disc impinging on spinal nerves, which can cause back
pain or sciatica (pain down the leg) — a condition known
as herniated disc. The intervertebral disc is sandwiched
between the vertebrae of the back and acts as a shock
absorber during spinal movement. The disc is made of two
parts: a tough outer wall called the annulus and a gelatinous
inner core called the nucleus. Trauma or aging of the disc
can cause the annulus to bulge.
Most occurrences of lower back pain resolve with rest
and medication. For many people, though, the pain can be
debilitating and last for several months to years. Such
patients typically require surgery.
Minimally invasive surgical techniques offer many benefits, since traditional back surgery can cause further pain
and complications. HydroCision, which develops and manufactures fluidjet-based surgical tools in the United States,
used computational fluid dynamics (CFD) to improve a
novel minimally invasive surgical treatment called
The goal of HydroDiscectomy is to decompress the
herniated disc. When performing the procedure, a physician uses a tool called the SpineJet® to remove a portion of
nucleus, which debulks the disc and retracts the bulge.
The device uses a high-pressure jet of sterile water
directed into an evacuation tube. The jet is attuned to cut
the softer nucleus but protect harder surrounding tissues
such as the vertebrae and the annulus. The water jet naturally provides cutting and a low-pressure Venturi to draw
the nucleus to the jet, cut it and aspirate it through an
evacuation tube.
Supply and evacuation tube of the original SpineJet
The SpineJet repairs a herniated intervertebral disc by removing a portion of the
nucleus. The tool uses the Venturi effect created by high-velocity saline jets to
cut and then aspirate targeted tissue. Image courtesy T.G. Communications.
As physicians adopt new technologies, their product
demands increase. HydroCision saw CFD as a technology
that could reduce development time and improve product
performance. Manufacturing limitations with the existing
SpineJet nozzle affected the flow divergence, directionality
and alignment with the evacuation tube. By redesigning the
SpineJet nozzle for better flow characteristics and greater
ease of manufacture, the surgical device could be made
more consistent and cost-effective. HydroCision’s product
development team used FLUENT software in analyzing the
performance of the existing nozzle geometry. CFD simulations allowed new geometries to be designed and analyzed
for performance in a matter of hours to days. Optimization
of the device was faster and less expensive than the traditional method of making and testing prototypes.
The CFD model included flow simulations through the
supply tube, nozzle orifice and evacuation region. CFD
results helped the HydroCision team visualize critical flow
characteristics such as the velocity profile, pressure distribution and flow divergence (cone angle).
The team modeled six alternate SpineJet designs that
incorporated significant changes to the nozzle and/or the
supply tube. Engineers selected velocity magnitude and
general jet shape as the primary means for comparing the
different designs, since these two parameters are considered the most accurate predictors of overall SpineJet
Image courtesy T.G. Communications.
ANSYS Advantage • Volume I, Issue 2, 2007
CFD results for the existing SpineJet showed the influence of a sharp-edge orifice and its location on the flow
characteristic. As expected, the orifice creates a flow separation at the corner, and a vena contracta is formed. In
addition, the proximity of the orifice to the 90-degree-bend in
the supply tube and the additional supply tube length past
the orifice create a non-uniform flow condition at the
orifice entrance. As a result, the region of highest flow
velocity is concentrated in the lower portion of the orifice;
therefore, the flow is neither symmetrical nor well developed.
CFD results for the alternate SpineJet designs showed
substantial improvement compared to the existing design.
Three of the alternate configurations had 20 percent higher
mass flow rates than the existing design as well as a 40
percent reduction in cone angle (flow divergence). These
designs had general jet shapes that were symmetrical and
well developed. They also retained higher flow velocities
over longer distances from the orifice exit.
Historically, HydroCision manufactured prototypes of
new geometries for testing to examine the feasibility of
producing a new and improved design. Although fairly
effective, this method was costly (more than $15,000 for
each design tested) and time-consuming (taking approximately six months). Furthermore, testing did not always
lead to a full understanding of the fluid flow characteristics
that occur.
Computer modeling utilizing FLUENT software provides a different approach to the problem. The only
expenses are computing and software costs; creating a
CFD model and running it takes just a few days. This allows
HydroCision to model and refine many designs in a fraction
of the time it would take to manufacture and test a single
prototype. In addition, computer simulation can yield better
insights into the interactions between the geometry and the
fluid flow. Finally, the graphics generated by FLUENT software help stakeholders better understand the operation of
the surgical tool. ■
Supply tube volume
Supply tube 90°
bend volume
Cross-sectional view of all fluid volumes for original SpineJet design
(top) with close-up section indicated by the red box at orifice (bottom)
Cross-sectional view of SpineJet alternative design colored by
velocity magnitude
About the Industry Spotlight
Cover image: Simulation demonstrates shape memory for a cochlear implant.
Photo courtesy Cochlear GmbH. Simulation courtesy Fachhochschule Hannover
– University of Applied Sciences and Arts, CADFEM GmbH and Dr. Omid
Majdani – Hannover Medical School.
For ANSYS, Inc. sales information, call 1.866.267.9724, or visit
To subscribe to ANSYS Advantage, go to
Supply tube
Orifice volume
Cross-sectional view of all fluid volumes
Evacuation tube volume
ANSYS Advantage • Volume I, Issue 2, 2007
ANSYS Advantage is published for ANSYS, Inc. customers, partners and others
interested in the field of design and analysis applications. Neither ANSYS, Inc.
nor the editorial director nor Miller Creative Group guarantees or warrants
accuracy or completeness of the material contained in this publication. ANSYS,
ANSYS Workbench, CFX, AUTODYN, FLUENT, DesignModeler, ANSYS
Mechanical, DesignSpace, ANSYS Structural, TGrid, GAMBIT, and any and all
ANSYS, Inc. brand, product, service and feature names, logos and slogans are
registered trademarks or trademarks of ANSYS, Inc. or its subisdiaries located in
the United States or other countries. ICEM CFD is a trademark licensed by
ANSYS, Inc. All other brand, product, service and feature names or trademarks
are the property of their respective owners.
© 2007 ANSYS, Inc. All rights reserved.
Managing Engineering
Web-based solution is aimed at hosting and integrating
simulation data, processes and tools for more effective
Simulation Driven Product Development.
By Michael Engelman, ANSYS, Inc.
Managing simulation processes
and data is a specialized subset of the
larger product lifecycle management
(PLM) vision. But it is often overlooked
or poorly addressed, since managing
simulation processes and data is more
demanding than the file/documentcentric approach of PLM and related
product data management (PDM)
systems. Simulation data is both richer
and typically many orders of magnitude larger than other types of product
data: It can be many gigabytes in size
and can require sophisticated data
reduction techniques. In addition, to
extract the true value and knowledge
represented by simulation data, a user
must capture both the content and the
context associated with the product
being simulated.
The complexity of the task notwithstanding, the need to manage
simulation data and processes is now
more important than ever. Robust data
management systems have the potential to provide significant benefits to
companies by enabling users to
access and reuse historical design
information and expertise for speeding
creation of new designs, providing
ways to capture and leverage
existing engineering knowledge, and
addressing the problems of loss of
engineering expertise and protection
of intellectual property.
Process management in the
context of product engineering
essentially means optimizing the
design workflow through more effective
use of computer-aided engineering
(CAE) simulation tools. This can result
in a wide range of improvements,
including enterprise standards for work
procedures, consolidation and automation of best practices, and increased
quality and reduction in errors.
Data or knowledge management
applies an archiving system to allow
for searches based on relevant and
descriptive tags that help identify files
and their contents. Thus, what is
involved is knowledge management —
capturing both data content and
context — rather than just file or data
management. This information can
later be mined for insight into the
how and why of a design or simulation.
A managed simulation environment
can address this issue by automating
much of the uploading and data
entry steps.
The ANSYS Engineering Knowledge Manager (EKM), scheduled for
initial release this year, is aimed
at meeting these challenges with
capabilities for backup and archival,
traceability and audit trail, process
automation, collaboration, and capture
of engineering expertise and IP protection. It is a Web-based design and
simulation framework aimed at hosting
all simulation data, processes and tools
(whether in-house or commercial) while
maintaining a tight connection between
them. It provides three services: access
management to address deployment
and collaboration, process management to address integration and
process automation, and knowledge
management to address the issues
associated with simulation data. Adding
ANSYS EKM to the capabilities of the
ANSYS, Inc. family of simulation
products empowers organizations to
create enterprise systems and achieve
the goal of Simulation Driven Product
Development. ■
Executes simulations
and extracts data
using a batch system
Web browser
Application server
Stores meta data
Compute cluster
Content management
Desktop application
File server
Repository of all files
and applications
ANSYS Advantage • Volume I, Issue 2, 2007
Kitchen Appliance
Finite element analysis helps redesign a countertop water filter that is
easier to maintain, can be injection-molded in half the time and costs a
third less to manufacture than previous models.
By Matthew Stein, Stein Design, California, U.S.A.
Even with degrees from top
technical schools and considerable
design experience, engineers find
complex parts — especially ones with
modern ergonomic curves — difficult
to analyze with traditional handbook
thermal and stress analysis. As a small
one-man design shop, Stein Design
completes several such projects each
year that benefit from the application of
finite element analysis (FEA).
The firm has used the technology
to develop a wide range of plastic and
cast parts, including water filtration
systems, drinking fountains, medical
bacteriological filters, emergency chemical drench systems and computer disk
drives. Clients include Hewlett-Packard,
Seagate, Plantronics and Duraflame —
companies that value Stein Design for
providing fast-turnaround designs that
meet their unique engineering and business requirements. In the development
of consumer products in particular, the
firm recognizes that product aesthetics
and visual impact often are critical elements in the commercial success of a A countertop drinking water filter was redesigned to cut costs while making it easy for consumers to change
the carbon filter cartridge and flow meter battery.
In one recent project, Water Safety
Corporation of America in the United production time and cost while making a mark recognized for its value in
States commissioned Stein Design to it easier for consumers to change the international trade and respected by
complete a major redesign of their carbon filter cartridge and flow meter regulatory agencies at the local, state
Essence™ countertop drinking water battery annually. The previous housing and federal levels. These thick walls
filter, an appliance intended to be had incorporated thick walls to accom- resulted in slow injection molding cycle
attractive as well as effective in turning modate the hydrostatic pressure of times, excessive material usage and
ordinary tap water into better-tasting, 150 psi required for certification by the an undesirably expensive housing.
healthier water. The goal was to cut National Sanitation Foundation (NSF), However, arbitrarily reducing material
ANSYS Advantage • Volume I, Issue 2, 2007
Left: In spite of the device’s 0.27 inch-thick bottom wall
and three internal ribs, stress-levels in the original design
were excessive.This showed up as red areas on the ribs,
as displayed in this color-coded stress plot.
Right: After the iterative process of testing various
combinations using ANSYS DesignSpace software, the
final design included 12 radial ribs with a thickness of
0.125 inch.
from the overall design could potentially
cause part failures leading to water
damage of consumers’ homes and high
warranty costs. To account for these
issues, Stein Design used FEA in
developing a lightweight, reliable design
for an appliance that would be easier for
consumers to maintain.
The redesign was started by
performing an FE analysis of Water
Safety’s existing product. When the
housing was subjected to an internal
hydrostatic pressure of 150 psi,
analysis with software from ANSYS,
Inc. showed that, in spite of its 0.27inch-thick bottom wall and three
internal ribs, stress levels of 5,360 psi
were unacceptably close to the yield
strength of the ABS thermoplastic
material. In redesigning the housing,
one of the primary concerns was
reducing this maximum stress to
half the material yield strength — thus
providing a safety factor around 2.0 —
while reducing wall thickness and
injection molding cycle time for
the parts.
To arrive at an optimal design satisfying these complex requirements,
Stein Design performed an iterative
process of evaluating different wall
thickness and rib combinations. Threedimensional models were designed
in SolidWorks® software and then
imported into ANSYS DesignSpace.
Once the initial pressure loads and
boundary conditions were set for the
first model, the project geometry was
updated with each new model iteration, making quick work of the analysis
of “what if” scenarios. Since this was a
highly cosmetic part, the maximum rib
thickness was kept to a maximum of
70 percent of the wall thickness to
ensure that the part would not display
excessive marks where the ribs joined
the outer cosmetic surface. Such
indentations occur when the plastic
cools and shrinks, and they are considered problematic on products that
must be highly attractive in nature.
The iterative process of analyzing
various rib and wall thickness combinations using FEA yielded a domed
surface having a wall thickness of
0.175 inch and 12 radial ribs with a
Three-dimensional models of the water filter were
designed in SolidWorks and then imported into ANSYS
DesignSpace software for analysis of various ribbing
configurations and wall thicknesses.
thickness of 0.125 inch minus 1/2
degree of rib draft. Rib height was 7/8
inch at the outside wall and sloped
down to 1/2 inch at the inside of the rib
hub. The maximum rib stress on the
new design was reduced to 2,240 psi,
giving a safety factor of 2.3 and
exceeding the 2.0 target. At the same
time, by reducing the nominal bottom
housing wall thickness from 0.27 inch
to 0.17 inch, injection molding cycle
time was cut by a factor of two
and part cost was lowered by more
than a third.
ANSYS DesignSpace software is
an integral part of many Stein Design
projects — and part of the reason the
company has succeeded in the highly
competitive engineering consulting
business. Small consulting firms with
no full-time analysts on staff can’t
afford to spend a lot of time and money
on training to run a complicated FEA
program. Engineers who use ANSYS
DesignSpace need little training to be
highly productive, and the tool
interfaces seamlessly with SolidWorks
mechanical design software. Stein
Design finds it very easy to make quick
changes to the part geometry and to
regenerate the ANSYS DesignSpace
FEA solutions to investigate “what-if”
scenarios early in the design process,
when design changes have little
impact on project schedules and
tooling. Even though several months
may pass between FEA applications,
the software is designed so users can
get up to speed quickly in producing
meaningful results. ■
ANSYS Advantage • Volume I, Issue 2, 2007
Overcoming Big Challenges for
Small Turbojet Engines
In developing an impeller for a microjet turbine engine for unmanned drone
aircraft, engineers used FEA to reduce stresses by 20 percent, prevent
fatigue in high-speed rotating parts and study resonances in the assembly.
By Bulent Acar, Tusas Engine Industries (TEI), Inc., Eskisehir, Turkey
Finite element analysis was used in developing Tusas
Engine Industries’ turbojet engine as well as the
advanced turboprop engine shown here. These small
turbine engines are designed to power unmanned air
vehicles for applications such as military target drones.
The concept of the unmanned air vehicle (UAV) is
thought to have been envisioned first by Leonardo Da Vinci
in 1488. The idea was not put into action until World War I,
however, when radio control and gyro-stabilization technology were available to make such an aircraft feasible.
UAVs became more advanced during the Second World
War, when they were used to train anti-aircraft gunners and
fly attack missions. Most of these early machines were
remote-controlled, full-sized aircraft, but more recent technology advancements have led to the development of
miniaturized UAVs, providing opportunities for cheaper,
highly functional military aircraft that can be used without
risk to aircrews.
One of the most challenging aspects in the development
of these small aircraft is designing compact, lightweight
propulsion systems for delivering the required performance.
In one recent project, Tusas Engine Industries, Inc. (TEI),
based in Turkey, used finite element analysis (FEA) in
developing the high-speed, precision radial compressor
impeller for a microjet turbine engine to be used in UAV
applications such as target drones for testing the accuracy
of surface-to-air and air-to-air weapon systems.
ANSYS Advantage • Volume I, Issue 2, 2007
Recognized as a leader in developing and producing a
range of high-quality aircraft engine parts for the worldwide
aerospace industry, TEI was established in 1985 for aircraft
engine assembly primarily in the Turkish region and later
expanded into design, testing and manufacturing of components for gas turbine engines and other precision
systems. The firm began advanced research and development activities in 1996; since then, it has participated in
major international projects such as the Joint Strike Fighter
(JSF) and the A400M Airbus military transport aircraft with
the advanced TP400 turboprop engine.
One of the most critical parts of the Tusas TEI-TJ-1X
microjet engine, the impeller compresses air entering the
engine inlet to a high pressure and delivers it to the combustion chamber. Rotational speeds in the order of 100,000
rpm are necessary to achieve high compression, resulting in
design challenges related to vibration, resonance, transonic
flow, shock waves in diffusers and high stress levels.
Studies performed for the TEI-TJ-1X using FEA
included structural analysis to determine stresses and
deformation of the impeller, modal analysis of the impeller
and rotor, and rotordynamics analysis of the entire assembly
to study the response of the components to rotational
effects. TEI used ANSYS Mechanical software to minimize
stress and deformation in their impeller designs. Various
combinations of mechanical, fluid and thermal loads were
considered. By using this approach, stresses in the critical
regions of the impeller were reduced by 20 percent.
TEI engineers also used ANSYS Mechanical technology
to examine the centrifugal and aerodynamic loads that
can affect vibration of the blade and potential deformation
of its geometry. Such deformation is a major concern in
maintaining proper tip clearance — the spacing between
the outer edge of the impeller blade and the inlet housing —
under the range of operating conditions. If not carefully
accounted for, excessive deformation could create the risk
of contact between the blades and their housing.
Following the initial structural analyses that minimized
stress and deformation, Tusas engineers performed modal
analyses to determine dynamic characteristics of the
impeller. Analyses indicated that none of the impeller
frequencies coincide with any of the resonance frequencies
for the engine in the operational range of impeller speeds of
100,000 to 120,000 rpm. Since rotational speed is very high,
rotating parts (such as impeller and turbine) can undergo
millions of cycles in a relatively very short time. Vibration
characteristics of the impeller were investigated in detail to
prevent high cycle fatigue (HCF) as well as contact between
the impeller blade tips and the stationary inlet as a result of
excessive vibration.
TEI performed full rotordynamics modal analysis on the
complete assembly, including the impeller, shaft and
turbine, to determine the resonant frequencies of each
individual component. The most challenging aspect of the
full modal analyses was defining realistic boundary conditions for the rotor’s bearings and bearing housings, whose
stiffnesses substantially affect modal response. In order to
calculate the bearing housing stiffness values correctly and
precisely, the engineering team created a whole engine
model. ANSYS contact elements were used to blend the
different mesh patterns of the impeller, shaft and turbine for
dynamic analysis of the assembly.
As a result of the analyses, three critical frequencies
were determined. The first and second frequencies affect
the impeller and turbine respectively, while the last
frequency has impact on the shaft. The impeller and turbine
critical frequencies are especially important since they may
exist in operational range and/or during startup or shutdown cycles of the engine. This led the TEI team to make
design modifications, including incorporation of integrated
blades. Subsequent tests validated that critical frequencies
for the impeller and turbine were within approximately
10 percent of the FEA simulated values, which was acceptable. The shaft-related critical speed occurred 25 percent
above the maximum operation speed. Critical shaft
speeds could not be validated due to the requirement that
rotational speeds were higher than operational speeds. The
Tusas engineers noted that, while the test apparatus was
The radial compressor impeller is one of the most critical
parts of the engine. In designing the microjet turbine
impeller, TEI engineers used ANSYS Mechanical technology
for structural analysis to determine stresses and deformation (top) and for modal analysis in showing displacement
at various harmonic frequencies (bottom).
Rotordynamic analysis of the complete assembly was performed
to determine resonant frequencies of each individual component,
including the impeller, shaft and turbine.
operated at its maximum speed, there were no indications of
vibration-induced problems related to the shaft.
Simulation in the early stages of the development cycle
provided valuable insight for quickly identifying potential
problems and evaluating alternative solutions. This prevented
large numbers of costly and time-consuming late-stage
design changes, and it enabled TEI engineers to verify the
design with the minimum number of physical tests. Simulation was a critical tool in TEI’s successful development of the
TEI-TJ-1X microjet engine, which has successfully undergone initial performance tests and is being used as a basis
for the design of an advanced turboprop engine TEI-TP-1X,
now under development. ■
ANSYS Advantage • Volume I, Issue 2, 2007
Keeping It Cool
Modeling fluid flow and heat transfer
throughout a nuclear fuel assembly
helps prevent reactor burnout.
Temperature distribution
on the nuclear reactor’s
fuel plates
By Fahri Aglar, Turkish Atomic Energy Authority
Ankara, Turkey
Mustafa Ozer Gelisli and Emre Ozturk
ANOVA Ltd., Istanbul, Turkey
Adequate cooling of fuel in nuclear reactors has
always been an important safety concern. The bulk of the
radioactive inventory of a nuclear reactor is contained in
the fuel elements, and, normally, their integrity can be
destroyed only by excessive temperature. Insufficient
cooling of the fuel leads to burnout that can cause structural damage, and subsequent leaching of radioactive
fission products. Therefore, the main goal of nuclear safety
strategy is to avoid an imbalance between the heat generation and heat removal in all operational states. Such
imbalance could result from transients in which either the
heat generation exceeds the nominal values or heat
removal falls below these values. Another cause of imbalance could be the loss of coolant from accidents that
result in the partial or total depletion of coolant required for
the heat removal. In past investigations of the problems
encountered in cooling the fuel used in nuclear reactors,
thermal hydraulic studies have been carried out both
experimentally and theoretically [1, 2].
As part of its work studying reactor safety, the Turkish
Atomic Energy Authority (TAEK) needed to evaluate the
flow and heat transfer characteristics of a material test
reactor (MTR)-type fuel assembly. As a provider of
advanced engineering fluid mechanics solutions in Turkey,
ANOVA Ltd. performed this study to assist TAEK in
its evaluation.
The fuel assembly consisted of plate-type fuel
elements, with light water serving as both the coolant
and the moderator. Based on geometry and boundary
conditions provided by TAEK, ANOVA generated a mesh
of the assembly using GAMBIT software. By assuming
symmetrical flow and geometry, only one-quarter of the fuel
assembly needed to be modeled. When the cross section of
the fuel assembly was examined, distinctive geometries
with variable cross-sectional area — such as narrow cooling
channels, slender fuel elements, and sudden enlargements
and contractions — could be seen. Therefore, during the
GAMBIT modeling, the fuel assembly was divided into three
regions: the diffuser, the fuel plates and cooling channels
between them, and the outlet region. A generally hexagonal
mesh was developed, and the three regions were
connected through non-conformal interfaces. Accurate
evaluation of wall shear stress and local heat transfer
coefficients at narrow cooling channels was required, which
necessitated a boundary-layer meshing scheme. Under
these circumstances, and following a sensitivity analysis,
ANOVA analysts created a grid containing 2 million cells.
0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0
In an evaluation of the safety of a nuclear reactor, ANOVA simulated the rotating and
separating flow through the cooling channel and also modeled the wall shear stress
and local heat transfer coefficients. Geometry created in GAMBIT 2.3 software of a
material test reactor-type fuel assembly shows the diffuser and fuel plates (left) and
outlet region (right).
ANSYS Advantage • Volume I, Issue 2, 2007
Comparison of velocity profile in channel 1 [1]
∆p= 167 kPa
∆p= 119 kPa
∆T= 15.26K
Pressure drop along the fuel assembly
The realizable k–ε turbulence model with standard wall
functions was used throughout the computations to exploit
its advantage for simulating flow possessing rotation and
separation. The ANOVA team performed pressure and
velocity coupling with FLUENT software using the semiimplicit method for pressure-linked equations, or SIMPLE.
The convection and diffusion terms of the equations of
motion were obtained by cell-based discretization. One of
the main input variables for the FLUENT simulation was the
volumetric heat generation, which TAEK extracted from the
neutronic calculations using the WIMS-D/4 and CITATION
codes. The power peaking factors, which describe the local
power density at the hottest part of a fuel rod, also
were estimated and used to correct the volumetric heat
generation term.
One of the main concerns of the simulation was the
comparison of the velocities at peripheral and central
cooling channels. Engineers observed that the magnitude of
the velocities at the peripheral cooling channels was slightly
lower than the channels located at the center of the assembly. The reason for this became apparent when the influence
of the vortex observed in a region between the diffuser and
the fuel plates was taken into account. The vortex and its
influence are extremely important from the reactor safety
point of view, and estimations revealed that this velocity
reduction seemed to be negligible. The outcomes related to
velocity reduction also matched those obtained from experiment [1]. Further channel-to-channel flow distribution
analysis showed that the relative flow rate, evaluated as a
ratio of the flow rate in the individual channel to that of the
assembly, decreased from the central channel to the outermost channel. The plate-to-plate temperatures showed the
opposite behavior; that is, the temperature increased
toward the outer channels.
A final point of interest was that the pressure difference
between the inlet and the outlet of the fuel assembly was in
the acceptable range and did not cause flow instability and
phase change during normal operation. The pressure drop
along the fuel region was 70 percent of the total pressure
drop, which was in accord with experimental data [1].
The FLUENT results thus have been instrumental in
understanding the complex 3-D flow in an MTR-type
fuel assembly. Such CFD simulations have contributed
significantly to the design and licensing of nuclear
power systems. ■
Computational meshes in GAMBIT software for the cooling channel (left) and
diffuser section (right)
Pathlines colored by velocity showing a vortex observed in the space between the
diffuser and plate region (left) and corresponding velocity vectors (right)
[1] Ha, T.; Garland, W. J., Hydraulic Study of Turbulent Flow in
MTR-Type Nuclear Fuel Assembly, Nuclear Engineering and Design,
2006, 236, pp. 975-984.
[2] Franzen, F. L., Nuclear Power Plant Operational Safety — Safety
Strategy and its Technical Realization, IAEA Interregional Training
Course, Karlsruhe Nuclear Research Center, 1981.
ANSYS Advantage • Volume I, Issue 2, 2007
The Greening of
Gas Burner Design
Simulation assists in developing efficient and
environmentally friendly recuperative burners
used in heat-treating applications.
Gas inlet
By Örjan Danielsson and Marcus Andersson
Kanthal AB, Hallstahammar, Sweden
Companies that depend on gas
burners for heat-treating materials are
challenged with adapting to tougher
nitrous oxides (NOx) and carbon
dioxide (CO2) emissions rules and
legislation, along with maintaining
high efficiency. To address this, Kanthal
AB uses a simulation-driven design
process to develop innovative products
such as the ECOTHAL® single-ended
recuperative (SER) burner, the latest
addition to the Kanthal family of heating
The key to success in delivering
a low-emission, high-efficiency gas
burner lies in well-defined combustion.
Delivering too much air reduces heat
output and increases the amount of
harmful NOx produced, whereas too
Contours of velocity and streamlines predicted by ANSYS
CFX, viewed looking into the inner tube from its inlet area
Streamlines indicate exhaust gases that are exiting the
inner tube and recovered back through the outer tube
of Kanthal’s SER burner.
Air inlet
little air results in incomplete combustion that causes unburned residue in
the form of carbon monoxide (CO)
and hydrocarbons. In the ECOTHAL
SER burner, fresh air and fuel are combusted in an inner tube within a burner
assembly while exiting exhaust gases
are recovered, passed back through an
outer tube that surrounds the inner
tube and used to heat the incoming
fresh air in a recuperator region
upstream of the combustion area.
Kanthal used computational fluid
dynamics (CFD) to model and optimize
flow behavior, gas mixture control and
combustion efficiency. CFD simulations using software from ANSYS, Inc.,
together with physical testing, resulted
in an SER burner that had an efficiency
of approximately 80 percent — 10 to
20 percent higher than conventional
SER burners — while still keeping NOx
levels below 50 ppm (or 20 mg/MJ).
To help ensure that Kanthal
provides accurate recommendations
regarding procedures for maintaining
proper performance, the company
uses ANSYS Mechanical software to
model creep. Kanthal’s burner systems
often are mounted horizontally, and
creep, or deflection, of the tubes can
affect flow characteristics and operation within the burner. The deflection
rate typically is measured through
physical testing in which a sample tube
is placed in a furnace and the deflection is measured at specified intervals.
This is a very time-consuming test that
can take up to 3,000 hours, or
125 days. On the other hand, when
modeling creep, existing test data is
used to provide the coefficients for
the creep equation that is used in the
simulation inputs, and the testing
process is simulated in less than a day.
ANSYS Advantage • Volume I, Issue 2, 2007
Furnace wall
Flue gas
Inner tube
Outer tube
Geometry of a single-ended recuperative burner, in which
fresh air and fuel are combusted in an inner tube within
a burner assembly while exiting exhaust gases are
recovered, passed back through an outer tube that
surrounds the inner tube and used to heat the incoming
fresh air in a recuperator region
The SER burner from ECOTHAL is
the first in a family of five burners.
The second burner in the series was
designed entirely using CFD in
combination with traditional computeraided design (CAD) software. The
ability to go directly from a 3-D CAD
model to meshing and simulation
within the ANSYS Workbench platform,
and then to pass design changes back
to the CAD program, greatly improved
the speed of product development for
Kanthal. By using simulation in
conjunction with CAD tools, expensive
and time-consuming laboratory testing
was kept at a minimum, and development time was reduce by several
months. ■
ANSYS Advantage • Volume I, Issue 2, 2007
The Democratization
of Engineering Analysis
To compete successfully in today’s business climate, Procter & Gamble
makes analysis tools available to rank-and-file engineers as well as to
analysts and advanced simulation experts.
By Fred Murrell and Tom Lange, Procter & Gamble Company, Ohio, U.S.A.
Fred Murrell
Tom Lange
Early practitioners of techniques such as finite element analysis (FEA) and
computational fluid dynamics (CFD) typically were confined to industries in
which the risks to human life or mission success were such that the expense
could be justified. It is, therefore, no surprise that the first commercial FEA packages came from and were used by industries that could afford access to
expensive computational resources — and for which a failed component could
have catastrophic results.
As these techniques spread to other industries, computer-aided engineering
(CAE) remained the bailiwick of the expert analyst, requiring advanced degrees
and long apprenticeships to cope with the difficulties of the technique and to
ensure accurate results.
The rapid and unrelenting improvements in hardware, the personal computer and low-cost cluster computing — and technology such as the ANSYS
Workbench platform — has truly democratized CAE analysis. A common
desktop PC has more than 10 times more computing horsepower than a highend workstation from just 10 years ago costing 10 times that price. No longer is
engineering analysis a luxury that costs many thousands of dollars requiring the
services of highly trained experts.
ANSYS Advantage • Volume I, Issue 2, 2007
Simulation on the ANSYS Workbench platform was used to determine stresses (left) and thermal distribution (right) in these components of high-speed equipment used in
Procter & Gamble Company production operations.
The Procter & Gamble Company (P&G) is best known
for its brands. Three billion times a day, P&G brands touch
the lives of people around the world. The company has one
of the strongest portfolios of trusted, quality leadership
brands, including Pampers, Tide, Ariel, Always, Whisper,
Pantene, Mach, Bounty, Dawn, Pringles, Folgers, Charmin,
Downy, Lenor, Iams, Crest, Oral-B, Actonel, Duracell, Olay,
Head & Shoulders, Wella, Gillette and Braun. Chances are
that you have used one of these brands recently, if not today.
P&G also is well known for advertising these brands.
According to Advertising Age magazine, P&G was the
largest advertiser in the United States in 2005, spending
more than $4.6 billion. Advertising, packaging, display and
name recognition are aimed at what P&G refers to as the first
“moment of truth,” when a customer decides to purchase a
product they have never used before. But, as any manufacturer knows, you won’t have a customer for long if your
product doesn’t deliver as promised. If you fail the consumer
the first time, you will not be rewarded with repeat business.
P&G calls this the second moment of truth, when a customer
uses the product and judges whether you have delivered on
your advertised promise. This is where the science behind
the brands comes into play.
All manufacturers face similar tensions — rapid innovation, keeping down costs and improved time to market. P&G
is a leading proponent of CAE technologies in its drive for
improved innovation. In fact, in a 2003 conference call with
Wall Street analysts, P&G Chief Executive Officer A.G. Lafley
stated, “We are significantly expanding capabilities in
computational modeling and computer-aided engineering,
so we can do an increasing percentage of product and
process design through virtual simulation.”
In the consumer packaged goods business, this would
not have been realistic or feasible just 10 years ago. Highend CAE analysis was then the domain of experts, most
likely employed in the defense, aerospace or automotive
business. The expert also was armed with complicated,
high-end analysis software and an expensive UNIX®
workstation. Today, the ubiquity of inexpensive, fast and
powerful desktop PC workstations has made the use of
CAE analysis available to the rank-and-file engineer in ways
unimaginable in the past.
When P&G creates new products, there are three
goals — it has to fit, do what it is supposed to do and, most
important, make financial sense. The company wants to
make the first prototypes virtually and make the physical
item only when confident it will work. In the consumer
packaged goods business, companies make billions of
items and sell them for a relatively small amount. Analysis
allows P&G to optimize those products and processes to
save a penny or two here and there. The focus is in making
lots of high-quality products very quickly.
Just as the needs of individual projects vary, so do
schemes for utilizing CAE. P&G has developed a three-tier
approach for CAE. Tier 1 consists of a small cadre of
experts. They face new-to-the-world kinds of problems that
require a great deal of preparation and development. Here a
highly trained, advanced-degree individual will stretch the
bounds of a high-end commercial code or require specialized codes from national laboratories to solve the problem.
The second-tier analysts use very high-end analysis
tools, but the problems are such that the tools can be automated to some extent. A common example at P&G is the
analysis of bottles. P&G sells billions of packages each year.
Design optimization is critical to maintaining competitiveness and profitability. The sheer numbers of projects
annually require a different level of expertise to achieve effective results. P&G has chosen to automate a number of these
analyses in a product called the Virtual Packaging System
(VPS). VPS is a collection of common analysis tasks that
ANSYS Advantage • Volume I, Issue 2, 2007
have been developed over the years and automated to
a large degree by internally written code. This allows a
journeyman analyst to feed various geometries to the system
and view the results in short order. The time to complete
an analysis is reduced substantially. “This system frees
analysts to focus on the physical parameters of the design
problem rather than on setting up analytical solutions,” said
David Henning, manager of packaging analysis at P&G.
Typically, there are three times as many analysts in this
category as there are experts.
A third tier is that of the rank-and-file engineer engaged
in project work. Occasionally, this individual is faced with
the need for an analysis to determine the suitability of a
structure for a particular load or other such question. In the
past, a call would go to the expert practitioner who may
(or may not) have the time or resources to assist. For these
types of analyses, P&G uses the ANSYS DesignSpace
product as the software of choice. ANSYS DesignSpace
was selected after a careful investigation of solutions
available in the marketplace.
In making the decision on which software to use, the
comparison requirements were ease of use, accuracy, full
associativity with a number of 3-D computer-aided design
(CAD) systems, and widespread training and support.
In the end, ANSYS DesignSpace software was selected.
The solution allows for escalation of the problem to ANSYS
Mechanical or ANSYS Multiphysics software if a particular
analysis requires nonlinear materials, large deformation or
advanced contact. The ANSYS Workbench platform also
contains tools for convergence studies that serve to ensure
an accurate solution.
The ANSYS Workbench environment is available to
thousands of engineers and scientists within the P&G
organization. Training is available to those who wish to
utilize the tools. P&G also finds that more and more new
hires are already trained in CAE tools. These software
products allow the engineer to rapidly screen numerous
designs before having to commit to a physical prototype.
The overarching goal is to make sure the first physical
prototype has the best chance for success that the engineer
can provide.
This translates to fewer, more meaningful tests,
decreased innovation cycle times, and, most important,
reduced time to market. This is where analysis makes
money: in improving the decisions that are made every day
and getting a better product to the market faster. ■
Pampers, Tide, Ariel, Always, Whisper, Pantene, Mach3, Bounty, Dawn, Pringles,
Folgers, Charmin, Downy, Lenor, Iams, Crest, Oral-B, Actonel, Duracell, Olay, Head &
Shoulders, Wella, Gillette and Braun are registered trademarks of the Procter & Gamble
Company, all rights reserved.
Proctor & Gamble rank-and-file engineers routinely use ANSYS DesignSpace software in product development projects. Sample plots here show loads on the slotted
concentric shafts of a converting machine assembly, enabling engineers to quickly evaluate the design early in development.
ANSYS Advantage • Volume I, Issue 2, 2007
in ANSYS Mechanical
Useful features are available to study vibration
behavior in rotating shafts, bearings, seals, out of
balance systems, instability and condition monitoring.
Rotordynamics is a collective term for the study of
vibration of rotating parts found in a wide range of equipment including turbines, power stations, machine tools,
automobiles, home appliances, aircraft, marine propulsion
systems, medical equipment and more. In these applications, resonant vibration — in which mechanical systems
can oscillate excessively when excited by harmonic loads
at their natural frequencies — is of particular concern.
These large-amplitude vibrations can bend and twist
rotating shafts, leading to premature fatigue failure in these
components as well as bearings and support structures.
Also, deformation of shafts and other components can
cause rotating systems to impact adjacent parts in which
clearances are tight, causing potentially catastrophic
damage in high-speed equipment.
Analysis of rotating systems typically involves the study
of many different variables related to vibration including the
critical rotational speeds that set up natural-frequency resonances, the response of the entire system to unbalanced
loads and instabilities, deflection of the shaft during vibration, torsional vibration in which shafts also twist around
their axes, and flow-induced oscillations produced by fluids
moving through the system. Calculation of these and other
vibration-related variables can be performed in ANSYS
Mechanical software using some of the most advanced
rotordynamics simulation capabilities available in commercial finite element analysis (FEA) codes.
Rotordynamics usually is best studied in the rotating
frame of reference, in which Coriolis terms are used in the
equations of motion to describe rotational velocities and
accelerations. Introducing these Coriolis terms for static,
modal, harmonic and transient analysis provides a modified
equation of motion:
By Achuth Rao, ANSYS, Inc.
[M], [C] and [K] are the structural mass, damping and
stiffness matrices, respectively. [Kc] is the spin softening
matrix, and [G] is a “damping” matrix contribution due to the
rotation of the structure or the Coriolis term.
This modified equation of motion is at the foundation
of performing the most common types of rotordynamics
Modal analysis: When components are spinning, the
Coriolis term adds nonsymmetric terms that introduce
forces to the system, causing natural frequencies to split
and shift up and down. These natural frequencies must be
determined, therefore, to avoid excitations at the critical
speeds. Modal analysis predicts how speed affects
frequency by running at speeds from zero rpm up to the
maximum rotational velocity of the system.
Harmonic analysis: A harmonic analysis sweeps through
a range of frequencies to determine how the system
responds to various rotating speeds and excitation forces.
Again, the Coriolis terms shift the frequencies, and damping
plays a greater role. If the excitation is different from the
rotating frequency, ANSYS Mechanical technology offers
options to scale it up or down.
Static and transient analysis: Static and transient analyses
determine loads exerted on structures, joints and bearings
of rotating structures. This can be done as a static analysis
(by applying initial conditions to specify velocities) or
transient dynamic simulation in which the Coriolis effects
are included.
ANSYS Advantage • Volume I, Issue 2, 2007
Case in Point: Beam Model Analysis of a Multi-Spool Rotor
The following is an example of a harmonic analysis of a two-spool rotor on symmetric bearings with unbalance
force. An unbalance is located on the second disk of the inner spool, and harmonic response is calculated.
The example uses an excitation frequency that is synchronous with the rotational velocity of the structure. ANSYS
Mechanical software calculates the rotational velocity Ω of the structure from the excitation frequency and an
unbalance excitation force (F = Ω2 * Unbalance) is applied on the nodes.
Beam model of a two-spool rotor with symmetric bearings (left) and displacement plot (right)
In a typical rotordynamics harmonic analysis, quantities of interest such as nodal amplitude as a function of
frequency, orbit plots at a given frequency and displacements plots at a given frequency are often output as part of
the analysis.
Amplitude versus frequency (left) and orbit plots (right) for harmonic analysis of a beam model
Capabilities for Rotordynamics Analysis
ANSYS software offers a complete set of capabilities for
studying the dynamics of rotating machinery.
model rotating machinery starting from computer-aided
design (CAD) geometry.
Solids, shell and beam elements: For decades, rotordynamics has been performed with in-house and
commercial codes using beams and masses. For most
rotor assemblies, this still is the most efficient and the most
accurate method. However, sometimes a system does not
lend itself to this type of approximation. ANSYS Mechanical
software provides a unique solution to address such issues
using 2-D and 3-D solid and shell elements to accurately
Bearings and damping: In real-world rotating systems,
bearings are not infinitely stiff, and the friction and lubricant in
them introduce damping. Also, springs in these systems often
have stiffness that varies with speed and direction.
The same goes for damping. ANSYS Mechanical offers springdamper elements like COMBI14, or the newer COMBI214 for
modeling bearings in rotor dynamics, allowing users to
specify stiffness and damping ratios for their particular systems.
ANSYS Advantage • Volume I, Issue 2, 2007
Stationary and rotating frames: ANSYS Mechanical software provides both rotating and stationary reference frames
for rotor-dynamics analysis. The primary application for a
stationary frame of reference is a case in which a rotating
structure (rotor) is modeled along with a stationary support
structure. The primary application for a rotating frame of reference is in the field of flexible body dynamics in which,
generally, the structure has no stationary parts and the
entire structure is rotating.
Unbalance response: ANSYS Mechanical allows users to
specify whether the excitation frequency is synchronous or
asynchronous with the rotational velocity of a structure.
New capabilities in the software such as the SYNCHRO
command update the amplitude of the rotational velocity
vector with the frequency of excitation at each frequency
step of the harmonic analysis.
Campbell diagram: The primary post-processing tool for
rotordynamics work is the Campbell diagram showing how
vibration modes split because of whirling. The Campbell
diagram assists users in finding the critical speed for a
rotating synchronous or asynchronous force as a function
of rotation speed.
Whirl orbit plot: When a structure is rotating about an
axis and undergoes vibration motion, the trajectory of a
node around the axis generally is an ellipse designated as a
whirl orbit. ANSYS Mechanical software provides plotting
tools of the whirl for beam/mass and solid rotordynamic
models. The orbit (ANHARM macro) can be animated for
further examination. ■
The author would like to thank the development and technical support
team at ANSYS, Inc. and Eric Miller from Phoenix Analysis & Design
Technologies (PADT) for their efforts and contribution to this article.
Case in Point: Solid Model Analysis of a Hard Disk Assembly
In a hard disk assembly, modal analysis is run to predict how speed affects frequency by running at zero rpm
and then several speeds up to the maximum rotational velocity the system is expected to see. The primary postprocessing tool for modal analysis is the Campbell diagram.
Frequency (Hz)
Spin velocity(rd/s)
Hard drive assembly modeling using 3-D solid, beam and spring elements
Campbell diagram (top) and mode shapes (bottom) from modal analysis with
Coriolis effects
ANSYS Advantage • Volume I, Issue 2, 2007
Submodeling in ANSYS Workbench
By Dave Looman, ANSYS, Inc.
Figure 1. Full CAD model of a curved tubular assembly
Application courtesy Klaus-Dieter Schoenborn, CADFEM.
Figure 2. Full global model
ANSYS Advantage • Volume I, Issue 2, 2007
Submodeling utilizes two separate
models. A full or global model representing the entire structure is used to
transform global loads to local deformation. The submodel includes the local
geometric details with an appropriate
mesh density. The submodeling algorithm then interpolates the deformation
from the global model to the submodel
“cut boundaries” and solves for the local
stress state.
This method typically requires extensive planning and documentation of the
workflow, especially if many submodels
and numerous load cases are involved.
In addition, setup of a submodel may
take considerable time. However, the
ANSYS Workbench tree and efficient
computer-aided design (CAD) interaction
make the procedure easier. With small
ANSYS Parametric Design Language
(APDL) enhancements applied to the
model tree, the submodeling technique
may be combined with the ANSYS
Workbench Geometry handling and
process documentation. Thus, a workflow can be presented that covers the
whole process from CAD to fatigue
analysis in five steps.
Step 1. Build/import the model from
CAD. To illustrate this process, a sample
analysis is performed to determine
stresses on a tubular welded assembly
with a regular pattern of joints. It represents a small sample section of a
repetitive structure that forms the track
of a roller coaster. The model shown in
Figure 1 has been created using ANSYS
DesignModeler software.
The loading on this structure is
caused by a trolley rolling along the two
upside tubes. This loading is transferred
to the larger tube via the joint elements
and passed to the supporting structure.
Loading is generated by gravity and
centrifugal forces.
To obtain accurate stress in a local region, submodeling separates local
analysis from the global model. This allows mesh refinement in a region
that might not be possible on the full model without exceeding size limits.
Step 2. Mesh and solve the global
model. Each part was meshed
independently and connected with
surface-to-surface contact. Contact
pairs may be part of the interpolated
region in the full model, as long as
they are completely enclosed by the
submodel cut boundary. Figure 2
shows a sample mesh with surface-tosurface contact.
Step 3. Analyze the global model
to identify critical spots. The full
model gives a general impression of
the structural deflection and is used to
find the location of critical spots of
interest. The structural result is saved
and maintained in database and
results files in the parent directory.
The global solution is needed for interpolation of the submodel boundary
Step 4. Generate the submodel
from CAD data and mesh. Once
critical spots are known, submodels
such as the one shown in Figure 3
may be created from the original CAD
geometry. This is done by cutting the
model and suppressing the remaining
solids. This process automatically
achieves geometrical consistency since
the remaining solid does not change its
location with respect to the global
coordinate system. In order to interpolate displacements from the global
model to the submodel, a Named
Selection should be created on the cut
boundaries, which will be referenced
in the macro described next.
Step 5. Interpolate boundary
conditions from the global model to
the submodel and solve. The interpolation is done by inserting a small
macro into the environment branch of
Figure 3. Submodel geometry of a critical structural detail
!!! ANSYS 11.0 Procedure !!!
!!! Copy results to parent directory !!!
!!! Copy results from parent directory !!!
!!! Submodeling Commands !!!
Figure 4. Simulation tree showing
the submodeling procedure
ANSYS Advantage • Volume I, Issue 2, 2007
Figure 5. Submodel mesh detail using the sphere of influence feature
the submodel tree as shown in Figure 4.
This macro resumes the full model
database and results file, and it
performs the displacement interpolation (CBDOF command). After that, the
submodel is restored, the interpolated
boundary conditions are read and the
submodel is solved. Note that any
external loads present in the submodel
(including gravity effects or temperature loading) also should be applied.
ANSYS Workbench Simulation solves
the model and performs post-processing just as on any regular model. From
the interpretation of the resulting local
stress state in the submodel, the critical
locations now may be reviewed with
greater fidelity.
For this example, the initial submodel mesh is found to be still too
coarse to accurately predict fatigue life
from the resulting stress, so a locally
refined mesh is needed. The “sphere of
influence” method of the ANSYS
Workbench platform is ideally suited to
obtain the type of mesh needed.
Figure 5 shows the refined mesh on
the submodel.
This step is then repeated simply
by creating the “sphere of influence”
tab on the mesh branch and solving.
The interpolation now is performed on
the new FE mesh since the macro
overwrites any files that were created
on a previous run. The interpolation is
done from the original results file,
which still resides in the parent directory. Equivalent stress in the submodel
then can be solved.
In the submodeling process,
model consistency is maintained by
using ANSYS DesignModeler software
to create both full models and submodels. Capturing the process in the
tree clearly archives the analysis and
allows a user who later opens the
ANSYS Advantage • Volume I, Issue 2, 2007
database to understand immediately
what was done. Note that an arbitrary
number of submodels may be created
and solved by interpolation from a
single run of the global structure. All
of these submodels may be included
in the model tree, and variants may be
studied without having to repeat the
whole process. Users should remember to review and compare stresses at
the cut boundaries between the global
model and submodel to verify that the
cut boundary is far enough from the
region of interest. Submodels may be
altered using the bidirectional CAD
interface to ANSYS DesignModeler
software or other CAD programs. ■
For more information, refer to chapter 9 on
submodeling in the ANSYS Advanced Analysis
Techniques Guide.
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