Integrating multi Integrating multi - - body simulation and CFD: body simulation and CFD: toward complex multidisciplinary design optimisation toward complex multidisciplinary design optimisation Federico Urban ESTECO Italy Martin Mühlmeier AUDI Germany Stefano Pieri Department of Energetics University of Trieste Italy Courtesy of
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Integrating multiIntegrating multi--body simulation and CFD: body simulation and CFD: toward complex multidisciplinary design optimisationtoward complex multidisciplinary design optimisation
Federico UrbanESTECO
Italy
Martin MühlmeierAUDIGermany
Stefano PieriDepartment of EnergeticsUniversity of TriesteItaly
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This work show-cases how to carry out a multi-disciplinary design process couplingall the tools generally involved in a complete multi-body analysis.The integration will be managed by modeFRONTIER MDO package
The track: Le MansThe race-car:
Audi R8
PresentationPresentation OutlineOutline
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PresentationPresentation OutlineOutline
Optimisation Goals;The physics behind the problem: Aerodynamics Multi-bodyDynamics;The numerical analyses for simulating the real-life complexity: Tools;How to put together the numerical tools for achieving the result: Methods;Optimisation Results.
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GoalsGoals
INCREASE VEHICLE PERFOMANCES
Objective: Minimization of Lap-timeInput Variables: Geometrical Entities
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AerodynamicsAerodynamics
Aerodynamics is a crucial issue in the design of a high-speed vehicle.
Porsche911-GTO (McNish) Le Mans '98
It is useful and “safer” to simulate in advance the Aerodynamics at different race scenarios
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NumericalNumerical AnalysesAnalyses
For achieving a complete and reliable numerical simulation we shouldconsider the impact of the aerodynamic forces on the mechanicalbehaviour of the vehicleIn practice, carry out the coupled numerical solution with CFD tool(CFX) and Multi-Body tool (Adams) using a three-dimensional model.
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ToolsTools
The Numerical Tools SCENARIO:• 3-D Analysis• CAE Tools:
In order to achieve the most reliable map of aerodynamic forces to be used as boundary conditions along the multi-body analyses, eachdesign is evaluated in 12 different vehicle body positions
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MethodsMethods: The Design : The Design FlowFlow
Parmacro.CATScript
H2, Alfa, Xpar, Zpar
H1, BetaBody
n < 12AUDI_box.model
Matrix 3x4 Matrix 6x8
ICEM CFD CFX ifCATIA ADAMS LAP time
D.A.C.E. (Design and analysisof computer experiment), external Response SurfaceModeller
DACE
With 12 simulations, it is possible to extrapolate the complete 6x8 matrix of the aerodynamic forces required by ADAMS.
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MethodsMethods: The Design : The Design FlowFlow
Parmacro.CATScript
H2, Alfa, Xpar, Zpar
H1, BetaBody
n < 12AUDI_box.model
Matrix 3x4 Matrix 6x8
ICEM CFD CFX ifCATIA ADAMS LAP timeDACE
modeFRONTIERCourtesy of
MethodsMethods: : ProcessProcess ItegrationItegration with with modeFRONTIERmodeFRONTIER
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MethodsMethods: : ProcessProcess ItegrationItegration with with modeFRONTIERmodeFRONTIER
ResultsResults: : HistoryHistory ChartChart –– Lap Time vs. Design Lap Time vs. Design IDID
Simplex Algorithm
RESULTDesign 17 improves2,36 sec. the lap time
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Minimum height Maximum inclination
ResultsResults: CFD : CFD PlotsPlots –– Original vs OptimalOriginal vs Optimal
Cd coefficient: -15 %Cl coefficient: +6.0 %
Cd coefficient: -11 %Cl coefficient: -12 %
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VELOCITY
FUEL CONSUMPTION
ResultsResults: : DynamicsDynamics DiagramsDiagrams –– Original vs Original vs OptimalOptimal
OptimalOriginal
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Conclusive Conclusive remarksremarks
• modeFRONTIER managed a real-life multi-disciplinary optimization problem in a easy-to-use environment. CATIA, ICEM, CFX, ADAMS have been integrated in a process integration framework.
• The design chain worked successfully achieving virtually 2 seconds reduction of the lap time.
• Each the Process Integration issue and the Design Optimization problem have been reliably solved