Simulation Software

Multimedia communications for the simultaneous transmission of voice, data, and video or still images need a number of communications systems and network servers at transmitting stations. To reduce equipment size yet maintain capabilities, these systems are increasingly designed with their printed circuit boards situated in very close proximity, increasing the critical need for an effective means of cooling.

Generally, several fan trays with multiple 4.69 in. sq. fans cool the printed circuit boards that are mounted in standard 19-in. rack enclosures. However, over stuffing an equipment cabinet with fans can create other problems for installation, wiring, noise, and power consumption.

The engineers at Oriental Motor, Calif., thought they had a solution. Through the use of their proprietary computational fluid dynamics (CFD) simulation program, they demonstrated that one low-noise ORIX MRS20 7.87 in. sq. x 3.54 in. thick fan would produce cooling equivalent to multiple fan trays. Plus, use of one fan rather than many solved problems in wiring, noise, and power consumption.

Internal system cooling


The following procedure was used to select the appropriate type of fan:

• Specify the required conditions for fan selection.

• Calculate the amount of heat dissipation required in the system.

• Calculate the amount of heat released through the surfaces of the system.

• Calculate the amount of heat released by the fans.

• Calculate the amount of airflow required by the fans.

• Select the appropriate fans

• Check the temperatures present within the system.

Heat in a system is either dissipated through the cabinet walls and mounting surfaces by means of convection and radiation, or through ventilation provided by one or more fans (Fig. 1).

Fig.1-Heat in a system cabinet must be dissipated through the cabinet walls and mounting surfaces or through ventilation provided by fans.

Using computational fluid dynamics calculations


Computational fluid dynamics software was used to analyze airflow, static pressure and temperature within a system to compare the cooling effects of the MRS20 and fan trays with respect to the printed circuit boards contained in the system (see Fig. 2).

Fig.2- Layout models for fan trays indicate the potential to place up to 24 fan units. But, before selecting the maximum number, it is always wise to try other configurations.

The CFD method took a model and divided it into meshed areas where heat and flow equations could solve for each area. This simulation approach permits the modeling and analysis of individual electronic components. Therefore, it helps in the creation of general designs in applications where internal layouts must accommodate a variety of factors regarding the printed circuit boards and fan trays, heat-dissipating conditions, and others.

Fig.3- This photo shows a system that incorporates four fan trays and how air moves through them.

 

Temperature-contour comparisons


For the simulations to test temperature contours within the system, four models were assumed. One or more fan trays, each carrying a row of six MU1238 units, were inserted between the shelves in the mounting test fixture, starting from below the bottom shelf.

One tray:

Six units inserted below the bottom shelf only.
Two trays:

A total of 12 units inserted below the bottom and second shelves.

Three trays:

A total of 18 units inserted below the bottom through third shelves.

Four trays:

A total of 24 units inserted below the bottom through fourth shelves.

Layout model for the MRS20: One MRS20 unit was placed on top of the mounting test fixture.

The mounting test fixture consisted of twenty printed circuit boards W18.9 x D14.2 x H9.4 in., each dissipating 40 watts of heat, and placed in a shelf at 0.24 in. intervals. The shelf was then stacked within a system to a height of four levels, with the adjacent shelves separated by 3.8 in. (total heat dissipation 3.2 kW). Outside the system the ambient temperature was maintained at a constant 68°F.

Fig.4- A curve of airflow/static pressure characteristic was created for each simulation model.

With one and two fan trays installed, temperatures in the upper section rose to 125.6°F and 111.2°F, respectively, and the interior of the system was not cooled uniformly. Temperatures in the upper section were 102.2°F with three fan trays and 89.6°F with four fan trays. Only when four fan trays were installed, did the system’s interior cool uniformly.

 

Fig.5 – Noise levels can be a key factor in any design. This graph shows calculated noise levels for each simulation model.

When one MRS20 fan was used for cooling, the temperature in the upper section was only 96.8°F, indicating that it produced a cooling effect roughly equivalent to that achieved with four fan trays. Also, analyzing the temperature contours at the center of the shelves in the horizontal direction showed that each shelf was cooled in a relatively uniform manner (see Fig. 3).

 

Simulation models


Generally speaking, the static pressure of a fan decreases as the airflow it generates increases. Ventilation resistance is created in such a direction as to prevent that airflow. This ventilation resistance, which increases as airflow increases, is given as the internal pressure present in the system.

Figure 4 shows a curve indicating airflow and static pressure characteristics, which demonstrated the relationship between fans and the system’s internal pressure. The intersection between these two curves is referred to as the “operating point,” which represents airflow in a system and the pressure loss that occurs at that particular airflow. To cool a system internally, it is important to select fans offering greater capacity than the operating point would otherwise indicate.

The noise level inherent with each simulation model was predicted by means of a calculation. The noise level of one MRS20 unit was 61 dB, being roughly equivalent to the degree of noise produced by four fan trays (a total of 24 fan units).

A curve of airflow/static-pressure characteristic was created for each simulation model (Figure 4). The airflow/static pressure characteristic curves of the respective models, along with a sample characteristic curve of system pressure loss proved that one MRS20 fan unit is capable of producing airflow at 10.1 m3/min—roughly equal to the 10.5m3/min airflow obtained with four fan trays (a total of 24 fan-units).

The results of the computational fluid dynamics simulation showed that, with a system whose printed circuit boards are mounted close together, thereby generating a large amount of heat, the cooling effect and noise level of one MRS20 fan unit are roughly equal to those of four fan trays (with 6 fan units, each 4.69 in. square).

Oriental Motor

www.orientalmotor.com

: Design World :

SANTA ANA, Calif. – MSC.Software (NASDAQ: MSCS) announced that the automotive manufacturer AUDI AG has further extended their existing simulation management environment, going into full-scale production with MSC.Software’s SimManager Enterprise offering. The system of Audi represents the largest global installation of SimManager Enterprise to date, helping multiple engineering groups within Audi as well as their supplier community to accelerate the vehicle development process of Audi and improve their insight into system level functional performance.

The Audi SimManager system highlights the scalability of SimManager to support the simulation requirements of global engineering enterprises. SimManager Enterprise manages currently more than 180,000 simulations, with up to 850 new simulations created per day and enables collaboration amongst 400 internal and external users on all new vehicle multi-discipline programs, for Crash, Pedestrian Safety, Occupant Safety, Head Impact and NVH engineering disciplines. The system provides secure, managed access to currently over 20 million simulation content objects and provides an audit trail for each one that documents how they were created. Manually intensive tasks such as model assembly, post-processing and report generation are automated in SimManager, allowing Audi to run more simulations per vehicle and effectively use CAE to improve vehicle performance and innovate. To validate the production readiness of SimManager, the Audi system was exhaustively tested against the unique performance and scalability demands of simulation.

SimManager Enterprise allows automotive and other manufacturing organizations to harness and fully exploit both the large quantities of simulation content for their inherent knowledge. This is crucial in high value product development. SimManager Enterprise is designed to complement existing PDM and PLM systems, saving time and cost with easy integration of simulation content within the existing IT infrastructure. Additionally, SimManager goes beyond traditional data management approaches in additionally enabling process-based automation of the required simulation tasks.

An effectively managed simulation environment supports the engineering in two ways. Firstly the standardization, automation and robust execution of simulation processes using repeatable and reliable simulation processes effectively enables more simulation throughput with guaranteed best-practice quality. Secondly, content management capabilities enable the analyst to easily find, re-use and share simulation information within collaborating workgroups as well as across remote departments, production sites or the extended supply chain. This is evident in the new Audi deployment with the production scale SimManager environment.

www.mscsoftware.com

::Design World::

Brecksville, Ohio – Comsol Corp. presented a seminar Dec. 6 on use of Multiphysics software for FEA-like analysis of engineering models. This was one of a series of local seminars offered by this supplier.  

Comsol’s Applications VP Bjorn Sjodin led the discussion, giving an overview of modeling and the concepts of Multiphysics in the 2-way coupling of heat transport and conduction currents.  The model was inspired by simulations within the area of MEMS and electronics, but the concepts apply to all types of Comsol Multiphysics models, whether from chemical engineering, structural mechanics, electromagnetics, or any other field.

Following the discussion, attendees had the opportunity for a 90-minute hands-on session with computer and software.  Each attendee received the latest version of Multiphysics software with a 14-day trial license.  The useful and informative seminar was so well attended that latecomers had to scramble to get access to a computer.  If you plan on attending, it’s a good idea to get there early.

www.comsol.com

.: Design World :.

When Hamler Test and Analysis (HTA), a consulting firm in Cookeville, Tenn., needed to fatigue test a compressor blade from a gas turbine engine, they used linear dynamic finite element analysis (FEA) software from ALGOR, Inc., Pittsburgh, to simulate the test and determine the optimal setup.

“This program lets me do ‘virtual’ testing,” said Jesse Hamler, President and Chief Technical Officer of HTA. “I can simulate different ideas and hardware configurations without spending time or money to physically make the hardware for each setup, which saves weeks if not months of trial-and-error testing.”

HTA offers testing, design and FEA consulting services. “We specialize in vibration measurement and experimental vibration analysis tools,” said Hamler, “such as tap testing, modal analysis, operating deflection shapes analysis and rotating machinery analysis – particularly for engine vibration. With Algor FEA software, I purchased only the analysis capabilities I really needed – that is, linear static stress and linear dynamics.”

Linear Dynamic Analysis of a Shaker Fatigue Test

HTA was contracted to physically fatigue test a compressor blade from a stationary gas turbine engine used for power generation. “Electro-dynamic shaker testing was required to verify the client’s analytical vibratory high-cycle fatigue life prediction methodology,” said Hamler. “The first phase of this testing involved vibrating several blades to failure at the first bending mode, and the second phase to failure at the first torsion mode.”

Hamler Test and Analysis (HTA) used ALGOR FEA software to analyze the compressor blades of a gas turbine engine like the one shown here. (Image courtesy of The National Energy Technology Laboratory.)

The graph shows the blade tip displacement versus frequency for a shaker sine sweep. Notice the difference in resonance response between the bending and torsion modes.

The left photograph shows the weighted compressor blade test setup for the second phase of shaker testing, where the blade was vibrated at the first torsion mode until it broke (at right).

The primary challenge involved finding an acceptable displacement response of the blade tip at the first bending mode frequency of 2900 Hz. Because displacement is directly proportional to acceleration but inversely proportional to the square of frequency, the target displacement would be difficult to achieve at 2900 Hz, even with the gain in response at resonance. Mass loading the end of the blade with a special investment cast clamp lowered the first bending mode frequency to approximately 850 Hz. Experimental trail and error determined the correct amount of mass.

It was more challenging to find a way to fail a blade at the first torsion mode for the phase two testing. A trial-and-error approach was not feasible due to time constraints, so the FEA program was used to direct the testing in the right direction.
“It is difficult to excite an angular mode shape with linear movement,” said Hamler.  “Initial sine sweeps of the phase one mass-loaded test setup indicated that the first torsion mode had dropped from 8400 Hz to 1450 Hz with the addition of the tip mass.  It did not appear as though the shaker would enable a good response from the new ‘mass-loaded’ torsion mode.”

The gain in response obtained at a torsion mode is minimal when the excitation is linear motion. A commercially available linear or rotary shaker system would not provide enough excitation to achieve the desired torsion mode response with the phase one test setup. However, the FEA program showed that a sufficient torsion mode response could be attained by substantially increasing the mass moment of inertia about the nodal axis or nodal line of the first torsion mode (axis of rotation with zero displacement).

“An initial analysis predicted that, by making such modifications, the first torsion mode would occur at a lower frequency than the first bending mode, and that the shaker could reach the appropriate acceleration to meet the desired blade stress levels,” continued Hamler.  The results also predicted that if the total mass increase was too large, the torsion and bending modes would become coupled. Thus, increasing the mass moment of inertia about the torsion mode nodal axis would require concentrated masses to be applied at a significant radial distance from the nodal axis, while reducing the mass increase near the nodal axis. Designing hardware that could meet these requirements and physically attach to the blade would be challenging. Furthermore, such hardware would have to be manufacturable.”

Using Alibre Design software, Hamler created a CAD model of a clamp that could attach to the
compressor blade and support a weight on each side of the torsion mode nodal axis. The assembly measured 3.5 in. wide by 1.14 in. deep by 0.86 in. high.

Hamler opened the CAD model in the Algor program to set up for linear dynamic analysis. In the FEA model, the surface at the base of the compressor blade was fully constrained. Loads were applied as 17g acceleration in the Z direction with excitation at the first torsion mode and first bending mode natural frequencies of 420 Hz and 622 Hz, respectively. The proper damping amount was determined experimentally and included in the FEA model. Modal and frequency response analyses predicted the proper size and location of each weight, which reduced the number of experiments.

Alibre Design was used to create this CAD model of the weighted compressor blade assembly. The compressor blade is highlighted in orange and the weights and clamps are highlighted in green.

Natural Frequency (Modal) and Frequency Response analyses were performed to simulate a shaker fatigue test. On the left, color-coded contours show the displacement magnitude in the compressor blade. A wireframe of the undisplaced shape illustrates the torsion mode movement. On the right, a display of stress contours indicated the area where a crack would likely initiate. A close-up view (inset) shows that the finite element mesh was made finer in the area of highest stress.

The initial test setup design used a 1.25 oz trailing edge weight and a 0.8 oz leading edge weight. “FEA results indicated that this design produced an acceptable response on the shaker, but each weight was initially made to 1 oz, with the assumption that the resulting experimental response would still be in the vicinity of the FEA prediction,” said Hamler. “If needed, the shaker
excitation level could be adjusted to compensate for any difference. However, the first run with the 1 oz weights indicated that the response was significantly lower than the FEA prediction of the initial weight setup, even at the maximum excitation level capable from the shaker. The next logical step was to tune the test setup to replicate the FEA model. Two pieces of steel flat stock were bolted to the top of the trailing edge weight, giving it a total weight of 1.25 oz. Then the leading edge weight was milled down to 0.8 oz. This small weight adjustment provided a night-and-day difference in shaker response, as predicted by FEA analysis.”

Experimental results closely matched FEA predictions. “Testing was a success, and the blades failed as predicted,” said Hamler. “I was surprised that the FEA model was able to predict the real-world response of a structure so accurately.”

Hamler concluded, “This was a valuable exercise in how FEA can drastically reduce experimentation and troubleshooting involved with non-standard testing objectives. I would say that using FEA cut the testing time in half at the very least.”

Algor Inc.
www.algor.com

 :: Design World ::

Ionut Ghionea, Lecturer, Faculty of Engineering, University Politehnica of Bucharest

The finite element method (FEM) has become  a widely used and  indispensable engineering tool  for critically analyzing new component and product designs.  Since its introduction, continuous updates by most suppliers have made the FEM technique even more accurate and easier to apply. To appreciate just how much FEM has improved recently, its capabilities are illustrated in an example of a fixture design for attaching a wedge to two principal bolts on planar surfaces.   The fixture contains a circular eccentric gear (cam) and a two-arm bridle which clearly shows that the  cam’s working profile is a circular arc.

The scope of the finite-element analysis for this device is to identify the zones with high stresses and their values. This does not consider the stresses that result from the technological processes when the piece is machined, or the rigidity of supports and tightening elements.
The assembly consists of a bedplate, abutment bolts, a holder with a spherical head, a cam, an attachment flange for gripping cams, and associated hardware, Fig.1.

Fig. 1. The fixture device in isometric view.

The holder actuates the cam and fixes the piece on the device while friction forces hold the  eccentric gear in place.  To simplify the FEM calculus and explanations, the coiled spring is not represented. Bending, tension or compression stresses are applied to the components as the device is actuated.

Setting constraints
This analysis uses the Generative Structural Analysis module from the CATIA software package. Also, the 3D modeling of the device and its assembly require two other modules: Part Design and Assembly Design. A very important step in the FEM analysis process addresses how the device’s components are assembled using numerous constraints of the following types: coincidence, surface contact, linear contact, offset and fix, Fig. 2.

Fig. 2. Fragment of the assembly constraints list.

 

In this example, these constraints apply:
Coincidence constraints between the axes of the swell pin and of the cam hole.

Coincidence constraints between the axes of the dowel screw and its corresponding nuts.

Linear-contact constraints between the active surface of the cam and the guide’s planar surface, and between the tightening curved surface from the bridle’s end and the piece’s planar surface.

Surface-contact constraint between the supporting surface of abutment bolts and the bedplate.

Each component is made of steel, with appropriate material properties applied: Young modulus (2 X 1011 N/m2), Poisson ratio (0.266), density (7860 kg/m3), thermal expansion (1.17 X 10-5 K) and yield strength (2.5 X 108 N/m2).

Using the module Generative Structural Analysis, a node network discretization is done for each component, establishing the dimension, the type of each finite element and the tolerance
between the real model and the discretized one, Fig. 3. The finite element type is chosen as Linear because a Parabolic element type could extend calculation time excessively.  (Later, the effect of this choice will be examined.)

Fig. 3. Node network discretization.

Using the assembly constraints, the next step involves setting the physical constraints, necessary in the simulation of the tensile stresses, generated by the application of a force on the holder. Thus, the physical constraints are chosen after the assembly constraints and they are of these following types: Fastened Connection Property, Pressure Fitting Connection Property and Contact Connection Property.  A small section of these physical constraints is shown, Fig 4, along with some of their symbols positioned on the respective components.

As an example, the coincidence assembly constraints between the swell pin axis and the axis of the cam hole become physical constraints of type Fastened Connection Property. The coincidence assembly constraints between the abutment bolt axes and the corresponding axes drilled in the bedplate become physical constraints of type Pressure Fitting Connection Property. Also, the surface contact assembly constraint between the guide and the bedplate become a physical constraint of type Contact Connection Property.

Fig. 4. Fragment of the physical constraints list and symbols.

The next step in this application consists of adding a fixing restraint (Clamp), positioned on the base surface of the bedplate. In this step we establish the applied load on the holder, a Distributed Force of 600 N value. This force has the device’s working direction (holder-cam-bridle), tightening the piece. The specification tree, positioned on the left side of the CATIA interface, will show the sub-elements “Clamp.1” and “Distributed Force.1”, Fig. 5.

 

Fig. 5. Application of the fixing restraint and the loading force.

 

Begin analysis
Launching of the finite-element analysis process can begin after these preliminary stages (choosing the discretization values and imposing constraints and loads)  The procedure is very specific to the CATIA software. Finally, the specification tree is completed with the sub-element Static Case Solution, which may contain different solutions depending on the instruments used: Deformation, Von Mises Stress, Displacement, Principal Stress and Precision.

To determine the tensions caused by the applied loading force, use the Von Mises Stress results. Use of the Image Extrema instrument allows highlighting (locating) the minimum and maximum tension values, at a global or local level. The specification tree, Fig. 6, presents the sub-elements “Von Mises Stress” and “Extrema” which shows on the device’s 3D assembly model some indicators of the extreme values. This figure also shows the node network discretization.

Fig. 6. Representation of the Von Mises results and the localization of the extreme tensions.

From the colors and values palette, which correspond to the Von Mises model representation, you can see the maximum tension in the assembly is 2.63 X 107 N/m2, located on the holder, in the joint area between its end and the cam. The first analysis shows an error of 45.81%, but this result is too inaccurate, so an assembly-node network-discretization refinement is necessary, followed by another analysis process, applying the instrument New Adaptivity Entity.

Fig. 7. Tension representation and values for cam.

In this analysis, the user imposed a 20% error after three iterations, but in the second step of analysis, the error is decreased only to 26.57%. That eror reduction is accompanied by a maximum tension increase on the holder, in the same area of joint: 5.18 X 107 N/m2.  If these values (error percent and tension) are not acecptable, another node-network discretization refinement will be required, using the finite element type Parabolic, which will further decrease the percentage of error.

Results of analysis
The CATIA facility shows tension for each component (Figs.  7, 8 and 9) indicating tensions in colors-and-values palettes for these three components.

Fig. 8. Tension representation and values for bridle.

 

Fig. 9. Tension representation and values for dowel screw.

• For the cam, the most stressed areas are: the assembly hole with the holder (3.11 X 107 N/m2), the assembly hole with the swell pin (1.1 _ 107 N/m2) and the contact surface with the guide.

• For the bridle, the most stressed areas are: the surfaces of the assembly hole with the swell pin (2.25 _ 107 N/m2) and the planar contact surface with the conical pocket washer (3.35 _ 106 N/m2). On the contact area with the piece, the bridle presents tensions of 1.1 _ 105 N/m2.

• For the dowel screw, the most stressed areas are at the upper end, in the proximity of the assembling zone with the nuts (6.66 _ 106 N/m2).

• The assembly zone with the bedplate is stressed to a tension of 6.17 _ 106 N/m2. Thus, the tension distribution along the dowel screw indicates that it is loaded and bent.

 

: Design World :

Vector Fields offers new capabilities for its design software for rotating electrical machinery. The software combines finite-element analysis (FEA) modeling with a design entry system that lets you create models of electric motors or generators in minutes.

The software is an application-specific version of the Opera package, providing a front-end to the electromagnetic simulator that speeds design entry by means of ‘fill in the blanks’ dialog boxes. You select the form of motor or generator you want to design from a list of common types including induction, brushless permanent magnet, switched reluctance motors, and synchronous motors or generators.  Then, you enter a list of parameters to define mechanical geometry, material properties and electrical data, and the model is automatically created. Parameters can include diameters of rotor, stator; and shaft, stator tooth width, and the number of stator slots.

New modeling features with this release include an extended range of cage geometries for induction motors. You can choose from six starting points including circular, bullet and square, plus variations and combinations of these shape elements. You can also define notch shapes on stator teeth as well as wedge geometries.  The choice of geometries for wound rotor synchronous motors has been expanded in a similar way.  These options give you the means to quickly arrive at a model, even for proprietary design techniques.

If you need to incorporate unusual features in a design, you have open access to scripting codes that generate models, and can modify them at will to create a proprietary automated design process. A library of material properties is also included and is selected by means of a drop-down menu. 

Using the scripts provided, you can generate motor or generator models in minutes. You can then simulate electromagnetic performance and view results such as the torque produced as a function of position, or the static analysis of flux linkage in the phases of the machine as a function of position and excitation. You can try design ideas easily by varying the values of model parameters.

An automatic optimization tool is optionally available.  It automatically selects and manages multiple goal-seeking algorithms to find the best design to a problem, even if you specify several or competing objectives.

Facilities include modeling the external circuit feed to the machine, as well as the mechanical load. ‘Multi-physics’ capabilities available in the package show you the effects of temperature rise, or the mechanical stresses that torque produced by the electric field will have on the machine’s component parts.

Vector Fields Inc.
www.vectorfields.com

:: Design World ::

FIELDVIEW 11.1, from Intelligent Light, delivers scalable post-processing to users of multi-core workstations, large shared memory systems, and cluster computing environments. As the size of data needing analysis has grown by 25 times, programs have increased the speeds of their processors. Fieldview offers a five times speed increase on 8 CPUs, necessary when post-processing realistic, multigrid CFD simulations on systems using AMD Opteron processors.

www.ilight.com

::DW::

One hundred years ago, Alberto Santos-Dumont flew one of the first heavier-than-air
machines in Europe. Recently, a team of Brazilian students used the ANSYS ICEM CFD
and CFX software to analyze and understand airflow around that plane’s surface.

For the CAD model of the 14-Bis students meshed surfaces using hexahedral elements
and represented volumes with a tetra/prism mesh. ANSYS ICEM CFD software created
both high-quality surface and volumetric meshes.

Santos-Dumont was an aircraft pioneer. On October 23, 1906, he flew his aircraft, named
the 14-Bis, almost 200 feet at Bagatelli Field in Paris, France, witnessed by officials from
what would become the Federation Aeronautique Internationale. The 14-Bis consisted of
a long neck at the front of the craft with wings in the rear. The pilot maneuvered the
plane from a standing position.

The students used modern engineering simulation to demonstrate the 14-Bis’ ability to
fly. By analyzing drag and lift as well as engine thrust, the team simulated the flight
speed of the aircraft, nearly matching the recorded values.

Qualitative analysis of the pressure field was provided through the ANSYS CFX
computational fluid dynamics software.

The plane model was developed using historic pictures, plans and discussion. Due to
complex geometry, the team used ICEM CFD software to create both high-quality
surface and volumetric meshes. CFX computational fluid dynamics tools simulated the
airflow around the aircraft.

The students also studied the influence of engine power on flight performance.

Santos-Dumont first flight attempt failed, but in his second attempt, he increased nominal
power to 50 hp. With simulated drag, lift, and engine thrust data, the students estimated
possible angle-of-attack of around 5 degrees and flight speed ranging from 12 to 14 mps.
The value of 11 mps is generally quoted as the ground-related speed. The discrepancy
could be due to the presence of wind or ground effects during the centennial flight, which
were not taken into account in the simulation.

“The CFD 14-Bis project was very much a forensic analysis for ANSYS, arming
engineers and designers with a better understanding of cause and effect of equipment
performance,” said Chris Reid, vice president, marketing at ANSYS, Inc. “It is
fascinating to see the validation of flight designs from 100 years ago with the cutting
edge simulation and modeling tools of today.”

Ansys, Inc.­
www.ansys.com

 

A normal active childhood can elude small children and infants with defective heart valves. Soon, however, that may change thanks to LaunchPoint Technologies, a venture-engineering firm specializing in incubating startups and developing new technology. This company is researching a Pediatric Ventricular Assist Device (Pediatric VAD) that, if successful, will aid infants and small children with congenital or acquired cardiac disease. Children receiving this device will be able to run and play like other children, yet obtain the ventricular assist they need. This device would be the first designed specifically to provide long-term cardiac support to these special patients.

 
This prototype of the Pediatric Ventricular Assist Device was developed using CFD software from Ansys Corp.

Thorough computational fluid analysis plays a critical role in the design of the PediaFlow. The researchers must analyze the complex blood flow field and find the right blood flow path through the pump that will maximize hydrodynamic performance while minimizing any induced damage to the blood.  

Each component was modeled to ensure maximum blood flow through the tiny heart valves with as little damage as possible.

The CFD program the researchers chose is ANSYS CFX. They have integrated it with their own internally developed design tools — geometric models, automatic mesh generators, and mathematical blood damage models.

When
implanted, this device, which is a little larger than a 25-cent coin
will help infants and small children lead more normal lives.

The CFX program is intuitive to set up and delivers quick and accurate results, which are a few of the reasons why LaunchPoint chose the software for its Pediatric VAD.   

Ansys Corp.
www.ansys.com

:: Design World ::

SANTA ANA, Calif. – MSC.Software Corp., a leading global provider of enterprise simulation solutions and services announced that Brunel GmbH, a Germany-based provider of technology and management consulting, has selected SimXpert to deliver faster, more accurate, cost-efficient results to customers within the automotive and aerospace industry. With SimXpert, Brunel can leverage a fully integrated, multidisciplinary mechanical simulation environment for its automotive and aerospace customers.

Auto manufacturing is one of the most significant industries to the German economy, and German automakers face fierce global competition, making technical innovation and cost efficiency critical. To reduce development time and enable its engineers to test multiple variables simultaneously in a collaborative environment, Brunel selected SimXpert.

“Brunel has a long history of providing the most innovative technical consulting in the industry. We selected SimXpert because we want to bring our customers the greatest value and most advanced technology on the market,” said Carsten Siebeneich, general manager of Brunel in Germany. “MSC. Software is the leader in the multidiscipline simulation space, so choosing them made perfect sense for our growing practice.”

“The partnership between Brunel’s world-class domain expertise and MSC.Software’s multidiscipline simulation technology is the ultimate win for customers,” said Amir Mobayen, Senior Vice President, EMEA for MSC.Software. “We are proud to work with Brunel to deliver the best-of-breed solutions to customers within the German automotive industry.”

About SimXpert accelerates the speed and accuracy of simulation; automates simulation processes and tasks; captures knowledge; and radically improves the analysis process.  SimXpert provides the tools needed to extend global engineering processes to the enterprise and supply chain level through SimXpert’s Template Studio, SimTemplate.  Once created, SimTemplate can be managed by SimManager and be shared with a variety of role-based users.

About Brunel
Brunel specializes in the support of development and innovation projects for the industry, with an interdisciplinary team of engineering and management experts. One of the focal points of the globally active company is the processing of technology and management issues as a project. Depending on the customer’s requirements, the corresponding Brunel specialists become active and supplement the existing project team within the customer’s company with their expertise.

In Germany, Brunel offers engineering and management expertise of 1,650 experienced engineers from 50 locations. In so doing, the company is primarily active in the automotive, IT, electronics, telecommunications, aerospace, mechanical engineering and plant constructions, railway technology and shipbuilding sectors.

For more information, visit www.brunel.de/english.

About MSC.Software Corporation
MSC.Software is the global leader of enterprise simulation solutions, that help companies make money, save time and reduce costs associated with designing and testing manufactured products.  MSC.Software works with thousands of companies in hundreds of industries to develop better products faster by utilizing information technology, software, services and systems.  MSC.Software employs more than 1200 people in 23 countries.  

MSC Software Corporation
2 MacArthur Place
Santa Ana, CA 92707
USA Tel: (714) 540-8900
Fax: (714) 784-4056
For more information, visit www.mscsoftware.com.

:: Design World ::