Alpha Magazine July 2006 alpha - MSC Software...Fully integrated within the CAD process, SimDesigner...

Newman Haas Racing and Enterprise Simulation - The Winning Combination

MD Nastran and Marc Running on SGI Altix Achieves High Performance and Scalability Benchmarks

Hydroplaning Prediction Improved With Multidiscipline Simulation

MSC.SoftwareAlpha Magazine

alphaThe Journal of Virtual Product DevelopmentJuly 2006

[ On the Front Line ] Newman Haas Racing and Enterprise Simulation - The Winning Combination

Video of the 2005 NHR Lola Champ-Car performing constant-radius-corner maneuvers around circles marked on the vehicle dynamics area surface.

Six-time Champ Car World Series winner Newman/Haas Racing has refocused its simulation activities to include tire models and rough road surfaces in its vehicle dynamics simulations for predicting handling. Tires and rough road surfaces are crucial for damper setup and for predicting and understanding how a car will handle on a given track. Accurate tire models are difficult and costly to generate and the ability to run vehicle dynamics predictions and damper simulation over a rough surface can be cost prohibitive. Since its first season in 1983, Newman/Haas Racing has collected many wins, poles and track records with talented drivers such as Mario and Michael Andretti, Nigel Mansell, Cristiano da Matta and most recently, Sebastien Bourdais. These have resulted in one of the most successful racing teams in the history of Champ Car. Owners, Paul Newman, one of the most famous actors in the world, and Carl Haas, "One of the most powerful men in the history of auto racing - USA Today," have won six Champ Car Championships, and started their 24th season with a win in the 2006 Toyota Grand Prix of Long Beach.

Building cars to achieve and maintain such success requires continuous innovation and engineering excellence. Using a manufacturer's tire model that only predicts smooth surface

Detail of the MTS/Swift 20T wheel force transducer (magenta) for measuring forces and moments (torque) installed on the 2005 NRH Lola Champ-Car.

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7/27/2009http://www.mscsoftware.com/alpha/print_article.cfm?volume=9&articleId=76

performance instead of replicating the rough surface of a real track produces inherently inaccurate results. Obviously, the need is for accurate results leading to improved handling and the potential for more wins.

Tire Modeling and Simulation "The first thing to understand whenever generating a vehicle model is that the most important and the most difficult part of the car to characterize are its tires," said Brian Lisles, general manager, Newman Haas Racing. "Typically, racing teams rely on tire companies to provide tire data, but tire testing machines are expensive to operate and the tire companies don't necessarily generate the required data or in the manner required by the racing team." Newman/Haas Racing uses equipment that allows the tires to be tested on the car and measure the forces and moments produced by tires. In order to understand exactly how the tire is presented to the road, the team uses ADAMS/Motorsports to emulate the maneuvers performed during the test, thereby producing and defining the same conditions that existed when the tire data was measured. This involves running the vehicle in constant-radius circles on a skid-pad at gradually-increasing speeds, running at fixed speed with either stepped or gradual steering inputs or emulating an on-track corner-entry/mid-corner/exit maneuver to gather steady state and dynamic tire information. A skid-pad is a large flat area made of the same material as a race track. All of the data is measured and recorded and then regressed to produce a tire model. The model is input to ADAMS to make sure its behavior matches the observed behavior of the tire during the physical test. "Effectively, we do our own tire testing to create our own tire models, which is time and cost effective," said Lisles.

Rough Road Handling In the past, tire data measurements were made on a smooth surface, so when dynamic simulations were run, the user must assume a smooth surface. All the irregularities and bumps inherent in a real race track are absent - an idealization applied when performing pure handling analysis. "We use ADAMS as a virtual a 7-post rig, i.e. put the car on four hydraulic platforms, vibrate the platforms underneath the wheels, and observe the response of the car," said Lisles. "Consumer cars use four post test methods, but a racing car requires three more actuators to apply the downforce, which is the aerodynamic load applied to the body. We built an ADAMS model of the vehicle/rig system and then validated the virtual vehicle and test rig against the physical ones." This is a very straightforward thing to do. Having validated the results, the standard vehicle handling model can be run on a rough road instead of just a smooth road. This allows damper

The MTS Swift Transducer interface mounted to the right sidepod of the 2005 NHR Lola Champ-Car. Cable from left rear tire connects to computer mounted on right side of car for logging real time data acquisition.

The 2005 NHR Lola Champ-Car being prepared to perform objective handling maneuvers on a skidpad (vehicle dynamics area). Tire warming blankets shown preheat the tires to operating temperatures prior to testing on the semi-smooth surface. The dusty, imperfect surface approximates a race track surface. Computers mounted on left and right sides of car are connected to each axle for measurements.

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(shock absorber) development and setup to take place virtually, instead of requiring a four-post shake test.

Conclusion Newman/Haas Racing has been using ADAMS to process independently-gathered tire data that can be applied to a dynamic vehicle simulation on a rough surface. This enables their engineers to develop and tune damper settings for cornering over a rough road. "There are several ways of achieving our objectives including measuring real car data and working backwards to construct why the car responds the way it does. The surface determines how the car responds. The information can be regressed from the measurements to what the road surface would be to make the car respond in that manner." To achieve this, a high fidelity model is required, which is why Newman/Haas Racing validates the ADAMS/Motorsports handling model on a virtual seven-post shake rig. The virtual model provides the flexibility of applying any input to the vehicle to produce a simulated response. By making a virtual rig in ADAMS and correlating the results, the tire parameters can be adjusted until they match physical test results. According to Lisles, the engineers get the same response with the ADAMS model as measured on a test rig. "In an ideal world, we could measure the track on a Friday

afternoon, send it away and Saturday morning process the information, run the analysis and have suggestions for solving any problems," said Lisles. "We were trying to improve the vehicle dynamics simulation to answer more and more questions. We kept finding the tire information was out of date and wasn't what we wanted. With ADAMS, we found a way of overcoming the inaccurate data problem using the current tires and eventually we'll be able to do this very quickly."

"Instead of using expensive rig test time to test tires, we can just go and run a series of standard tests and get the information," said Lisles. "The nice thing is you are running on a real surface with a real car at real speeds. It's the real thing compared to just doing it on a tire testing machine."

One or more optical slip sensors are used to measure the vehicle side-slip angle as the car moves through a curve. It captures how the grains are moving in the road in relation to fore and aft and side to side. Together with the wheel-force transducers the slip sensors calculate the longitudinal and lateral slip of each tire. This enables Newman-Haas Racing to regress their own tire models for use in ADAMS simulations.

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[ Company & Industry News ] Current News & Events MSC.Software and Pacific Northwest National Laboratory Collaborate to Develop Systems for Energy Independence

Joint effort supports the development of alternative energy systems for the government and private sector

MSC.Software and Pacific Northwest National Laboratory (PNNL), one of nine U.S. Department of Energy (DOE) multi-program national laboratories, are collaborating to develop computational technologies for next-generation energy systems. The two organizations will demonstrate cutting-edge techniques for the design of fuel cell and alternative energy conversion technologies. The focus is to contribute systems and solutions to help the United States achieve independence from foreign sources of oil.

PNNL and MSC.Software will work jointly to develop a range of solutions that are needed for efficient and effective alternative energy design and development, including modeling and simulation, stochastics, simulation data and process management.

"Industry has been trying to develop cost-effective fuel cells for some time now and our work allows the private sector to gain access to new and more efficient methods of multidisciplinary design and development that makes affordable fuel cells more possible," said Reza Sadeghi, vice president enterprise computing, MSC.Software.

ADVICS Selects SimDesigner Enterprise to Accelerate Early Design Validation inside Native CAD Environment

MSC.Software's enterprise solution enables leading brake system supplier to speed product development and reduce time-to-market on a global scale The ADVICS Co., LTD., a leading supplier of automotive brake systems and components, purchased MSC.Software's SimDesigner Enterprise for deployment in its CATIA® V5 CAD environment to accelerate the product development cycle. SimDesigner Enterprise is part of ADVICS' highly-efficient product development program to promote digital engineering.

A number of designer-friendly tools in SimDesigner Enterprise enable earlier design validation, such as multidiscipline simulation workbenches in a single package. These integrated workbenches now include an embedded Nonlinear workbench, Linear workbench, Thermal workbench and Enterprise Gateways for MSC Nastran and MSC Marc.

With its global implementation of SimDesigner Enterprise, ADVICS will be able to execute simulations at the earliest stages of design, improving the efficiency of each project and speeding time-to-market.

"Our company's goal is to contribute to the creation of safer and more comfortable automobiles," said Hirohiko Yoshida, manager of the design administration section, technical administration department at ADVICS Co. "This goal requires us to continuously advance the power of brake-system development-on a global scale. MSC.Software's products will allow us to accelerate our development while continuously improving the quality and functionality of MSC's products."

SimDesigner Enterprise is a CAD-embedded simulation suite, featuring enterprise collaboration and centralized data management. With an intuitive and CAD embedded environment, design engineers and engineering teams can perform repeatable, fully documented simulation studies earlier in the design process. SimDesigner Enterprise delivers the ability for product teams across the extended enterprise to create and collaborate on designs and performance simulations in one powerful application.

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Fully integrated within the CAD process, SimDesigner Enterprise speeds innovation, reduces development costs, improves product quality, enables better collaboration, and improves both productivity as well as consistency. With SimDesigner Enterprise for CATIA V5, designers and teams can easily use MSC.Software's industry-leading solver products in a CATIA V5 environment, delivering a feature-rich suite of powerful tools for accurate analysis and the ability to manage, control and reuse simulation data on an enterprise-wide, global scale.

"We are very pleased that ADVICS has implemented MSC.Software's SimDesigner Enterprise for CATIA V5 in their development of brake systems, one of the most important points for automotive safety," said Christopher St.John, president, MSC.Software Ltd. Japan. "SimDesigner Enterprise enables companies to facilitate true simulation-driven design early in the engineering process, bringing faster, more competitive innovation to the marketplace."

MD Nastran Achieved New Leading Performance Benchmark, Demonstrating Speed and Processing Power for Real-World Engine Analysis

MD Nastran Proves Speed and Performance Advantage on Linear and Nonlinear Benchmarks from the German Association for Research on Automobile-Technique

MD Nastran achieved two new leading performance benchmarks for engine analysis issued by the German Association for Research on Automobile-Technique (FAT).

"Engine models have many millions of degrees of freedom (DOF) making them very large and requiring as much as several days processing time, that MD Nastran reduces to hours," said Reza Sadeghi, vice president, product development, Enterprise Computing, MSC.Software Corporation.

The following results from the FAT benchmark models demonstrate the fast processing and performance results achieved with MD Nastran.

Engine Block Linear Simulation with MD Nastran Model size: 25-Million DOF Compute resources: Itanium2, 1.4 GHz, 8GB RAM Elapsed time for 2-static load cases: 3-hours, 20-minutes Elapsed time for 20-eigenmodes: 24-hours (1 CPU); 8-hours (4 CPU's)

Engine Block, Head and Gasket Nonlinear Simulation with MD Nastran

Model size: 10.5-Million DOF Compute resources: Itanium2, 1.6 GHz and 2x2 CPU's DMP (distributed memory parallel), 9GB RAM Elapsed time for 2-load cases (pretension and pressure): 50,200-seconds (13.9-hours)

"Processing speed and performance are crucial for cutting costs and enabling innovation," said Glenn Wienkoop, president and chief operating officer, MSC.Software Corporation. "The automotive industry understands these crucial issues and runs standard benchmarks used by its members for comparison of competing products. In this study MD Nastran was evaluated against other solvers and continued to highlight superior capability and performance time enabling more "what-if" scenarios that can increase innovation, reduce errors and accelerate time to market."

Shanghai Automotive Engineering Academy Chooses MSC.Software as Simulation Solutions Provider

The Leading Technology Center for Major Chinese Automotive Manufacturers Selects MSC.Software's Integrated Simulation Solutions to Improve Virtual Product Development

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Shanghai Automotive Engineering Academy (SAEA), the leading technology center for the major Chinese automotive manufacturers, has selected MSC.Software's integrated enterprise software solutions to enable product lifecycle management (PLM).

MSC.Software's simulation solution suite was chosen, in a very competitive environment, as the strategic partner to enable SAEA to achieve their ambitious VPD goals within durability, safety and NVH modeling and analysis methods. Through MSC's software solutions, SAEA will have access to the most comprehensive simulation portfolio in the world, featuring best-in-class integrated simulation solutions.

"We chose MSC.Software because they provide best-in-class enterprise simulation solutions, rather than providing single tools," said Dr. Dai Yi, CAE Director of SAEA. "MSC's industry-leading enterprise software and services will enable our engineers to truly leverage the advantages of VPD."

"The People's Republic of China is one of the most important growth markets and we recognize that manufacturing companies must deal with intense global competition and continue to improve the product development processes," said Dr. Christopher St. John, senior vice president, Asia Pacific operations, MSC.Software. "MSC's solutions provide the engineering teams at SAEA with the industry's best and most well integrated suite of solutions to exceed their VPD goals."

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[ Technical Matters ] MD Nastran and Marc Running on SGI Altix Achieves High Performance and Scalability Benchmarks

To drive down costs, customers are reducing the number of expensive and time consuming physical tests by increasing the use of simulation. This is increasing the level of detail in finite element (FE) models, making them more and more complex. In turn, this is driven by customer demand for higher accuracy results and an expanding number of regulatory test requirements. However, the use of high fidelity FE models in the growing number of more complex simulations leads to longer simulation times. To reduce simulation time, organizations are accelerating the use of High Performance Computing (HPC). Benchmarks of such platforms as MSC.Software's MD Nastran and MSC.Marc with advanced Grid Computing technologies and the new SGI® Altix® 4000 HPC platform with dual-core Intel® Itanium® 2 processors demonstrate a crucial and beneficial impact on cost cutting, innovation and speed to market, leading to reduced warranty and field failure costs.

Less Cost - More Innovation

Computer simulations cost far less and require much less time than physical tests. Additionally, simulations provide data not always available or practical with physical tests. For example, design of experiments (DOE), what-if studies and sensitivity studies are not always practical or affordable using physical tests. However, the use of simulation to reduce the number of physical tests before

running a physical test for final validation allows a substantial reduction of time and costs. Furthermore, the time saved can be used for more "what-if" simulations, providing a better understanding of product performance issues, leading to greater innovation and even better products.

Benchmarking HPC Performance and Scalability

Today, HPC systems commonly consist of large SMP and blade systems; and computer clusters, with each computer considered a node and connected by LAN or a more specialized high speed system interconnect. Ideally, the more nodes (processors) the shorter the solution time. In exceptional situations, super linear scalability occurs - that is for double the number of processors the rate of solve time reduction is greater than double. In uncommon situations, scalability is linear - for double the number of processors the rate of solve time reduction is double. However, the most common scaling follows the law of diminishing returns - for double the number of processors the rate of solve time

reduction is less than double and eventually additional processors provide little if any reduction in the solve time reduction rate.

Various components of the simulation environment influence solution time, including the operating system, simulation software, processor and hardware architecture, and run time resource usage management tools. The result is a need for performance and scalability benchmarks providing a better understanding of various combinations of software and hardware platforms. In conjunction with MSC.Software, SGI has run a series of benchmarks achieved by using the powerful combination of MD Nastran and a SGI Altix 4700 Server built using dual-core Intel® Itanium® 2 processors.

MD Nastran and Marc

MD Nastran, arguably the most powerful simulation software commercially available today, combines such best-in-class technology platforms as Nastran, Marc, Dytran and LS-Dyna into one fully integrated (coupled)

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multidiscipline simulation solution for the enterprise. Through such industry-specific disciplines as implicit (long duration, small deformation) and explicit (crash or drop - short duration, large deformation) nonlinear, MD Nastran is able to support all the disciplines necessary to meet the needs of all manufacturers, i.e. results that very closely represent real world behavior. The parallel processing algorithm of MD Nastran implicit nonlinear technology utilizes the Domain Decomposition Method (DDM), delivering dramatic performance scalability. DDM is a methodology for dividing large simulations into smaller simulations. These usually artificial subdivisions of a large simulation allow the introduction of parallelism. For example, simulations intractable on a single computer may be solved using parallel computers. In addition to the DDM technology, MD Nastran has the most advanced Distributed Memory Parallel (DMP) technology for explicit nonlinear, NVH and multi-disciplinary applications.

SGI® Altix® 4700 Platform

The distinctive modular blade design of the SGI® Altix® 4700 platform is made of interchangeable compute, memory, I/O and special purpose blades for plug and solve configuration flexibility. SGI's novel blade-to-NUMAlink™ architecture enables mixing and matching eight standardized blade choices, allowing right-sizing the system for a given application. The compact Altix 4700 rack packages the blades for industry-leading performance density. Additionally, the Altix 4700 server with dual-core Intel® Itanium® 2 processors offers leading floating-point performance per watt of power consumption compared to other high-end platforms.

Designed for future upgrade, expansion and integration of next-generation HPC technologies, the Altix 4700 platform is designed to be socket-compatible with upcoming single and dual-core Intel® Itanium® 2 processors, offering an easy upgrade or expansion of memory, I/O or visualization capabilities. With this flexible growth path, customers can tune system configurations for current and changing requirements easily and cost-effectively. Through peer I/O, the SGI Altix 4700 is the first SGI platform designed to support new computing paradigms, such as reconfigurable computing with field programmable gate arrays (FPGAs), which take over where Moore's Law ends.

SGI's shared-memory NUMAflex™ architecture provides scalable system size for simplified programming, administration, workload management and very high sustained performance. With NUMAlink™ interconnect, up to 512 processors (1,024 cores) under one instance of Linux and as much as 60TB of globally addressable memory can be supported. NUMAlink leads the industry in interconnect bandwidth as well as latency for superior performance on cluster applications.

Dual-Core Intel® Itanium® 2 Processors

The SGI® Altix® 4700 platform used for the benchmarks that follow feature 1.6GHz dual-core Intel® Itanium® 2 processors with 24MB L3 caches (24MB cache is shared by two cores). These processors were designed for such data-intensive applications as HPC computing. The processors provide excellent properties for parallelism and scalability, which it so happens is exactly what high fidelity FEA models need when being solved for NVH, crash, nonlinear and multidiscipline simulations.

Three-Car Crash Benchmark

When a van crashes into the rear end of a compact car, which in turn, crashes into a midsize car, the simulation is very complex. A high fidelity model is necessary for real life results and because it is a very complex simulation, it will be a very compute expensive simulation. This makes it a good example for simulation using

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HPC. The vehicle models were created by the National Crash Analysis Center (NCAC) and assembled into an input file by Mike Berger, consultant, Livermore Software Technology Corp (LSTC). The MD Nastran model was prepared by Casey Heydari, (Sr. Manager), MSC.Software Corporation. The model consists of 827,627 grid points and approximately 795,160 elements.

Program Sizing and Requested Options

Scalability Linear

Solid Cube Benchmark

Application MD Nastran Sol 700 (explicit nonlinear)

Hardware SGI Altix 4700 Server

Processor1.6GHz dual-core Intel® Itanium® 2 processors with 24MB L3 cache (24MB cache is shared by two cores)

Operating System Propack 4 SP3

Number of Nodes: 827627 Number of Solid Elements: 9,642Number of materials or property sets: 1,051Number of beam elements: 116 Number of shell elements: 785,021 Number of rigid body constraint sets: 2,278Number of rigid body merge cards: 10,639Number of rigid wall definitions: 3Number of joint constraints: 52Number of extra node blocks: 117Number of spring-damper material types: 10Number of discrete springs and dampers: 16Number of lumped masses: 365Number of load curves: 46Number of accelerometers: 22

SGI Altix 4700 Series Results

Number of Dual-Core CPUs

Elapsed Time (Seconds)

Elapsed Time (Hours)

4 57,698 16 hours 1 minutes 38 seconds




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The model is a square cube consisting of 300,763 eight-node isoperimetric brick elements and 314,432-grid points. A 10-increment non-linear analysis with the MARC solver2 or MD Nastran Sol 600, which employs an iterative method with an incomplete Cholesky pre-conditioner, is done. The solver is sensitive to the amount of aggregated memory bandwidth the computer system can provide. This is where the bandwidth compute blade of the A4700 really shines.

Program Sizing and Requested Options

Application MSC.Marc or MD Nastran Sol 600


Processor1.6GHz dual-core Intel® Itanium® 2 processors with 24MB L3 cache (24MB cache is shared by two cores)


Element type requested 7Number of elements in mesh 300,763Number of nodes in mesh 314,432Max number of elements in any dist load list 0Maximum number of point loads 0Load correction flagged or set Number of lists of distributed loads 3Option for debug print out 13Values stored at all integration points Tape no. for input of coordinates + connectivity 5No. of different materials 1 max no of slopes 5Number of points on shell section 11New style input format will be used Number of processors used 1Extended precision input is used Marc input version 11Suppress echo of list itemsSuppress echo of bc summarySuppress echo of NURBS data



Wall Time CPU Time

1 4144.63 4088.99

4 CPU bandwidth compute blade performance

1229.84 1215.65

4 CPU density compute blade performance

1329.24 1310.17

8 CPU density 770.58 753.48

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Bioengineering Bone Segment Simulation Benchmark

The model is a bone joint segment consists of 68,401 grid points and 61,038 eight-node isoperimetric brick elements. A 10-increment non-linear static analysis with contact was run with the MSC.Marc parallel sparse direct solver. The parallel sparse direct solver is an openmp application, which is sensitive to the remote memory latency on a NUMA computer system. Therefore, the density compute blade of the SGI Altix4700, with its larger node and lower latency, is better suited for the task.

Model Sizing and Requested Options:

compute blade performance

Application MSC.Marc (implicit nonlinear)


Processor1.6GHz dual-core Intel® Itanium® 2 processors with 24MB L3 caches (24MB cache is shared by two cores)


Element type requested 7Number of elements in mesh 61,038Number of nodes in mesh 68,401Max number of elements in any dist load list Maximum number of point loads 3Large displacement analysis flaggedLad correction flagged or set Number of lists of distributed loads 3Values stored at all integration pointsTape no. for input of coordinates + connectivity 5No. of different materials 2 max no of slopes 5Number of points on shell section 11Geometry updated after each load stepFormulation for large strain plasticityNew style input format will be usedNumber of processors usedAssumed strain formulation is usedExtended precision input is usedMarc input version 11



Wall Time CPU Time

1 9224.66 9200.24

4 CPU bandwidth compute blade

2800.69 N/A

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MD Nastran Linear Scalability with HPC SGI Altix 4700 and Dual-Core Intel® Itanium2® Processors

Running MD Nastran with such advanced Grid Computing technologies as DDM and DDP on the SGI Altix 4700 platform with dual-core Intel® Itanium® 2 processor provides linear scalability in many applications and super linear scalability in others. The resulting reduction of FEA solution times with parallel processing is very cost efficient. Because the law of diminishing returns does not impact processing speed even up to 128 processors used in the benchmarks, customers can reduce capital investment costs by replacing slower, more expensive proprietary RISC-based mainframe platforms with the SGI Altix 4700 Server. The end result is to reduce solution time, hardware costs and allow the time saved to be invested in additional simulations, sensitivity studies and what-if studies to further improving products.

performance


2694.10 N/A


1708.97 N/A

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[ Case Studies ] Hydroplaning Prediction Improved With Multidiscipline Simulation Multidiscipline Simulation Results with Marc and FINE™/Hexa More Closely Represent Real Life Improving the Safety of Tire and Tread Designs by Professor Dr. Ir. Charles Hirsch - President Numeca Int. Arie Platschorre consulting services engineer - MSC.Software Corporation

Hydroplaning is a phenomenon characterized by complete loss of directional control when a car moves fast enough that the tire rides on a thin film of water that causes it to lose contact with the road surface. Although hydroplaning is a very complex phenomenon, it is known to be associated with several such factors as water depth, tread design, road-surface texture, tread wear, tire load to inflation pressure ratio and vehicle type. For results that accurately represent real life, analysis of these issues requires closely coupled (multidiscipline) simulations with such software as MSC.Software's explicit nonlinear Marc and Numeca's FINE™/Hexa fluid (CFD) software.

In the not-too distant past, the time and cost of designing tires to minimize the effects of hydroplaning was prohibitive because a mold had to be made, a prototype manufactured on the same machines used in production and finally the prototype tire had to be physically tested - a very costly and time-consuming process. The use of uncoupled explicit nonlinear simulation allows analysis of the tire's material characteristics, rolling of the tire on the road surface, the exact tread and contact between the tire and road surface. CFD simulation allows analysis of the flow of water around the tire and inside the road surface grooves. These simulations relied on assumptions concerning the interactions between the two disciplines, which reduced the accuracy of results.

Multidiscipline Nonlinear FEA and CFD Simulation To eliminate assumptions and deliver results that approach real life scenarios, multidiscipline nonlinear and CFD simulation was required. The nonlinear and CFD software programs had to work together, providing the correct engineering and mechanical feedback to each other at exactly the right time.

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Through the use of MpCCI(Mesh-based parallel Code Coupling Interface) developed by the Fraunhofer Institute, Marc and FINE™/Hexa benefit with an inter-communication backbone that couples their FEA and CFD analysis capabilities.

Since Marc and FINE™/Hexa can run iteratively, interactions between the two disciplines can be considered. This provides a far more life-like simulation with higher accuracy results with which to base design changes for improving tire safety when encountering conditions conducive to hydroplaning.

Simulating Hydroplaning Effects The increase of speed generates a wedge of water that propagates along the leading edge and underneath the tire footprint, increasing the lift force on the tire and resulting in a reduction of the contact area. Then free-stream friction in and around the tire as well as free-stream turbulence come into play. Each stream becomes turbulent above a certain speed and increases deformation of the tire. Consequently, the free stream no longer moves in smooth and regular layers, but in turbulent, irregular swirls. Finally, such multiphase flow factors as air entrainment, bubble flow in the water flowing around the tire and detachment of liquid fragments and droplets from the liquid surface increase the effects of hydroplaning. The rate of air entrainment and the rate of liquid and bubble detachment determines the air content in the bow wave. Simulation of these factors is crucial for accurate and real life prediction of the behavior of a given tire design in conditions conducive to hydroplaning.

Combining Simulations MSC.Marc transmits the calculated values and the deformed shape to CFD via MpCCI. On the basis of this data, CFD calculates the forces on the tire, friction and turbulence. Subsequently, the pressure of the water on the tire is transmitted from CFD to FEA as a precondition, again via MPCCI. This is an ongoing, iterative process. FEA and CFD analyze different meshes, the results are evaluated on different points. However, MpCCI translates the results of both meshes, so are become comparable. Multidiscipline simulation makes the measurement of such linear and non-linear factors as the interaction between non-linear elements such as the tire and the water, and also the influence of these on a linear element such as the road. Furthermore, multidiscipline simulation can provide an accurate analysis of when a tire loses contact with the road.

Future of Tire Simulation With multidiscipline simulations, many more opportunities exist for improving the value of simulation with higher accuracy results. The more lifelike these results the better information is generated through running design of experiments (DOE) and What-If scenarios. Additionally, the time and cost of innovation and testing can be driven down. All of these factors contribute

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to innovating competitive advantages and improving designs for the real world.

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Alpha Magazine July 2006 alpha - MSC Software...Fully integrated within the CAD process, SimDesigner...

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