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Enabling Advanced Vehicle Heat Protection Through the Digital Prototype
Frederick J. Ross Director, Ground Transportation
Agenda
STAR-CCM+ Designed for Vehicle Heat Protection Over 25 years of experience STAR-CCM+ Design Focus on VTM Benefit of Siemens
Automation tools to help reduce turn-around time
Vsim: Automating Front End Air Flow C2M: Automating Component Modeling
Case Studies
STAR-CCM+ For Vehicle Thermal Management v2.0 was first enabler using client-server with mesh generation
Solver Team
New Client Server
Cell Quality Remediation
Heat Exchanger Models
Fast S2S Radiation
Shell Conduction
Co-Simulation
Parts Based Profile
Mesh Development Team
Surface Wrapping: Clean Surface
Bring in CAD Tree
Imprint/Boolean Operations
Thin Mesher
Parts Based Meshing
Parallel Trimmer
Concurrent Meshing
STAR-CCM+V2:2006
STAR-CCM+V11:2016
Robustness Job needs to run with minimum user interaction.
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Reduce Turn Around Automation Ease-of-Use Quick Modifications
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Accuracy Need to simulate real world test conductions
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Goals 1
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Vehicle Thermal Management Maturity Roadmap
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FullVehicleThermalManagement• 4000+solids• Coolant/Oiletc• DriveCycleSimula?on
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PowerTrainCooling• EngineCHT• Coolant• Oil,Intake/ExhaustFlows
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BrakeCooling• Radia?on&CHT• Rota?ngParts/Fric?onHea?ng• Op?mizeCooling
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ExhaustSystemCHT• 100-400Solids• Radia?on&CHT• HeatShieldDesign/
Placement
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FrontEndAirFlow• TopTankTemperature
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Level 1 • Fully automatic • Single or Dual Stream • No Solid Modeling • Fast turn-around time
Level 2: Simulation of Systems • Automating Procedures • 40-400 Solids + Radiation
Level 3: Virtual Prototype • Working from CAD to Simulation • Simulating Systems: Solids/Fluid
• 4000 + Solids with Radiation & co-sim
Generation of a Digital Prototype Producing a digital twin CAD Data Freeze defines digital prototype
– As with a real prototype, design teams work together to meet a goal for the design freeze.
– Review board checks, to make sure all components are fitted together and data pool is complete.
Data Filter: Filters data for simulation – Data needed for simulation is filtered from the overall
data pool, and provided for the virtual simulation. • Key component for data transfer
– PLM (product lifecycle management) tools enable communication between different tools.
Analysis Response – Feeds back into the data pool for design improvement.
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Geometrical Data Functional Data
The clear leader amongst PLM solution providers in simulation and test software, and associated services.
Siemens PLM Software + CD-adapco: Market Leader in Systems Driven Product Development
§ Computational Fluid Dynamics (CFD), Computational Solid Mechanics (CSM), heat transfer, particle dynamics, reacting flow, electrochemistry, acoustics and rheology.
§ Multidisciplinary optimization and design space exploration § Electric machine simulation and design
STAR-CCM+ HEEDS
Optimate SPEED
BDS
§ Behavioral simulation: 1D cross-discipline simulation, like mechanical and electrics, e.g. fuel economy & range simulation for hybrid vehicles
§ 3D mechanical simulation: e.g. stiffness, noise, vibration § Testing: Solutions for prototype testing (stationary & mobile)
Virtual.Lab Samtech
Imagine.Lab Test.Lab
§ Streamlines and accelerates the product development process in a collaborative environment
§ Includes a modern, multi-discipline CAE environment
NX CAD NX CAE Nastran
Teamcenter Tecnomatix
Generation of a Digital Prototype Producing a digital twin TeamCenter
Allows user to sort throw CAD, pick assemblies to be modelled Export PLMXML data with JtOpen
Coarse/Medium/Fine Tesselation Brep: Passing geometry Material Properties linked to parts
AmeSim 1D tool for modeling cooling circuit Helps predicting top tank temperature
STAR-CCM+ Read CAD and prepare mesh for simulation Simulate 3D flow field Post results
Geometrical Data
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Functional Data
CADImport
• ParasolidFiles• TeamCenterInterface• STLData
FrontEndAirFlow
• Setupairstreamthroughenginecompartment• Definezonesforheatexchangers/fans• Connectto1Dtoolsforcoolantcircuitifneeded
SolidCHT
• CADcleanup• BuildInterfacesbetweenparts• Concurrentmeshing
Co-simulaPon
• ParallelSurface-2-SurfaceRadiaPon• Solidsrunfullthermaltransient• Fluideithersteadyortransient
STAR-CCM+ Workflow
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Computational Process & Tools
radiation
conduction
convection
oil coolant exhaust
driving cycle 1D thermal network Source: M. Disch (upcoming Ph.D thesis, FKFS)
Import CAD Separate region for fan/heat exchangers Underhood Regions:
Group surfaces for underhood region Separate by mesh and physics size:
Set prevent contact for important gaps Close large holes? Use gap closure/anti seed point to prevent leakage into main cabin Wrap Region
Setup heat exchanger/fans: Create interfaces for sub-regions Wrap fan region, if needed. Just remesh heat exchangers
Create physics continua (including material properties) Create all reports, monitors, plots for monitoring convergence Use parallel trimmer to reduce mesh generation time.
Front End Air Flow Workflow
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Solid Conjugate Heat Transfer Model
Goal Predict local component temperature
Typical Applications Components Surrounding Exhaust Brake Cooling
Important Physics Convection Conduction Radiation
Solutions Convection: Vsim Conduction: Parts Based Meshing Framework
C2M: Cad to Mesh Tool
Radiation: Parallel Surface-to-Surface
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Import CAD Check CAD
Check fit and completeness multiple components per leaf-level part and split into separate parts Check for duplicate parts and tag / delete
Repair CAD problems Extrude parts without thickness Clean CAD surface errors (pierced faces, free edges, non-manifold) Replace or fix gross non-fitting CAD Wrap poor quality parts Boolean subtract all intersecting components Split part surfaces at special internal BC locations
Create physics continua Apply physics to regions Set material properties for each region Apply all radiative surface properties to boundaries
Create all reports, monitors, and plots for monitoring convergence Mesh using parts based meshing to allow multiple pipelines
Enable concurrent meshing to reduce meshing time
Solid Conjugate Heat Transfer Workflow
April 3, 2014
Agenda
STAR-CCM+ Designed for Vehicle Heat Protection Over 20 years of experience Focus of STAR-CCM+ since version 2.0 Benefit of Siemens
Automation tools to help reduce turn-around time
Vsim: Automating Front End Air Flow C2M: Automating Component Modeling
Case Studies Note:
TheautomaPontoolscanbeprovidedbyCD-adapcoasexamplesforclientstouse.Theyaremaintainedforeachrelease,andaslongastheyaremaintained,clientscangetupdated.
VSim: Aero/Thermal Automation STAR-CCM+ reading setup information directly from excel
Automated Process from CAD to Report Reads CAD from subdirectory Spreadsheet Contains Settings
• CAD Grouping to CFD Boundaries • Heat Exchanger/Fan Information • Thermal Boundary Conditions
Run: Mesh/Solve/Post Output: PowerPoint Input: Cad/Excel
Run: Mesh/Solve/Post
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VSim: Aero/Thermal Automation STAR-CCM+ reading setup information directly from excel 1
1• OperaPngCondiPons
2• GroupCADtoBoundaries
3• MeshSeYngs
4• Fan/HeatExchangerProperPes
5• MonitorsandPostProcessing
Automation: C2M Toolbox
Checks Surface for errors Repair parts with severe errors
Move into surface repair Alternatively wrap/replace part
Generate Volume mesh Sets up parts based meshing tree
Find and Generate Interfaces between components
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Agenda
STAR-CCM+ Designed for Vehicle Heat Protection Over 20 years of experience Focus of STAR-CCM+ since version 2.0 Benefit of Siemens
Automation tools to help reduce turn-around time
Vsim: Automating Front End Air Flow C2M: Automating Component Modeling
Case Studies
Case Study:
Challenge: Investigation of overall aerodynamic drag reduction impact on front end cooling is difficult to predict experimentally.
Solution: Simulation can be used to look at cooling drag at both 55mph and 120mph to ensure aerodynamic drag reduction still meet cooling requirement.
Impact: Digital prototype can aid engineer to reduce overall energy used by vehicle, including aerodynamics drag to front end cooling.
Full Vehicle Aero-Thermal Cooling Drag Sensitivity Analysis
Cranfield Univ., Jaguar Land Rover SAE 2016-01-1578
CustomerSuccess:MulPobjecPvedesignexploraPon} Challenge:
} OpPmizeacrossmulPplecompePngobjecPves} Minimizevehicledrag} Minimizeradiatorinlettemperature
} Whilevaryingthesedesignvariables:} Geometryofgrillandbumpervents} Radiatorfangeometryandspeed
} Subjecttoconstraints
} OpPmate+Results:} Dragreduced5.4%} Radiatortemperaturedecreased11.3%} Evaluated120designs;135hourson128cores
18 | Copyright 2014 - Red Cedar Technology: All Rights Reserved
A U T O M O T I V E
Baseline Optimized
Optimization process
Vehicle Drag Load Case Radiator Temp Load Case
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Case Study:
Challenge: Use computational methods for prototype development Reduce turnaround time for prediction of thermal behaviour in driving cycles
Solution: Transient Vehicle Thermal Management approach in STAR-CCM+ Co-Simulation of a transient solid model with steady state fluid model Comparison with measurements
Impact: Turnaround time of two weeks for full vehicle transient VTM Good prediction of temperature Optimization of thermal management through computational methods Reduction of testing/prototypes
Thermal Management of Dynamic Driving Cycles Daimler AG 3
Steady-State Full VTM Simulation Airflow + Solids using Co-Simulation
• Airflow model is 50+ million cells. • Solid Model is 40+ million cells. • Over 5000 solid components modeled in the simulation
Case Study:
Challenge: Use simulation to replace endurance testing for source of component temperature failure.
Solution: Use 3D simulation of solids and air to run repeat real world test conditions.
Impact: Digital prototype helps reduce costs and design time from physical testing.
Simulating the Idle: A New Load Case for Vehicle Thermal Management Daimler AG SGC 2016 3
Virtual Powertrain Development Combines work done by individual analysis to accurately predict metal temperature
Concept: Bring models from different simulations to the same detailed engine CHT model to accurately predict metal temperature
Engine Thermal Prediction
In-Cylinder Simulation Coolant Circuit Oil Circuit Crankcase Breathing Piston Cooling
FEA model
Exhaust/Intake Ports
Exhaust/Intake Manifold
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Challenge Engines that pass the dynamometer still fail when installed into the vehicle. Once vehicle design has been finalized, it can be costly to adjust cooling to the engine. At early design stages, it is important to determine possible thermal issues.
Solution
Use existing geometry of the engine in dynamometer and place engine in vehicle.
Impact Reduce prototype of engine/vehicle construction. Reduce time to find out thermal failures. Reduce cost Reduce time to production. Improve information on failure cause.
In-Vehicle Engine Testing Simulation General Motors
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Maturity of VTM Easy to automate front end air flow CAD improving making solid conduction easier and improving component prediction.
STAR-CCM+ Key Features Java based interface, easy to automate steps CAD structure to match material properties Parts based meshing to enable easy part replacement Fast surface-to-surface radiation Co-simulation to enable drive cycles
Vehicle Heat Protection Toolbox Vsim: Automate aerodynamics/front end cooling C2M: Helps automate modeling solid assemblies
Summary
Case Study:
Thank You!