CFD Applications in the Automotive Industry -...

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CFD Applications in the Automotive Industry

By:

Sandeep SovaniSenior Consulting EngineerFluent Inc., Ann Arbor, MI

June 12th (Shanghai) and June 15th (Beijing) 2006

FLUENT Roadshow

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Presenter

The presenter of this presentation, Dr. Sandeep Sovani, is a Senior Consulting Engineer at Fluent. He specializes in automotive applications of Computational Fluid Dynamics with a focus on aero-acoustics and aerodynamics. Dr. Sovani has over 11 years of experience in conducting research and executing projects on a wide variety of topics in automotive thermo-fluid sciences. He has worked with Fluent for the past five years. During the five years preceding his employment at Fluent, he conducted doctoral research at the Thermal Sciences and Propulsion Center of Purdue University. Prior to that, he worked as a Senior Engineer in the Engineering Research Center of Tata Motors. Dr. Sovani holds three degrees in Mechanical Engineering: a Ph.D. from Purdue University, an M.Techfrom the Indian Institute of Technology, Chennai, and a B.Eng. from the University of Pune, India. He has authored more than 40 papers, articles, and technical reports in his field. He has been invited to deliver numerous lectures on his research at conferences as well as in industry and academia. He is a member of SAE, ASME, Sigma Xi, and MENSA. Dr. Sovani serves as a chair for technical sessions on Aerodynamics and Computational Fluid Dynamics at the annual SAE World Congress. He serves as an e-mentor in ASME. He has frequently been invited to review papers by several prominent journals and conferences. Dr. Sovani has received the prestigious National Talent Search Scholarship awarded by India’s National Council for Educational Research and Training. He is a three-time recipient of the Excellence in Oral Presentation Award from SAE International. He has also received the Lloyd L. Withrow Distinguished Speaker Award from SAE International.

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Outline

OVERVIEW

● Introduction

● CFD for Non-Powertrain Applications

● CFD for Powertrain Applications

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Introduction: CFD

● Computational Fluid Dynamics (CFD) the science of predicting fluid flow, heat transfer, etc.by solving the mathematical equations which govern these processes using a numerical process (that is, on a computer).

● CFD analysis is useful for:conceptual studies of new designsdetailed product developmenttroubleshootingredesign

● CFD analysis complements testing and experimentation.Reduces the total effort required in the laboratory.

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Introduction: Advantages of CFD

● Low CostComputational simulations are relatively inexpensive when compared to testing

● SpeedCFD simulations can be executed in a short period of timeQuick turnaround means engineering data can be obtained early in the design process

● Ability to simulate conditions hard to achieve in testinge.g. A car traveling at 200 mphExtremely low temperatures

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● Comprehensive InformationExperiments yield data at a limited number of locations (e.g. pressure and temperature probes, heat flux gauges, etc.)

CFD provides data over the entire region of interest, i.e. a “complete picture”

Introduction: Advantages of CFD

Contour plot ofvelocities in a plane.

Temperature contours show the thermal distribution felt by the passengers.

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Introduction: Automotive Applications

● In Automotive Engineering, CFD analysis can be used for all components and systems that closely interact with fluids

Air, water, fuel, exhaust gases, coolants, lubricants, hydraulicfluids, etc.

● There are hundreds of such components and systems in automobiles

● Automotive CFD applications are generally classified into two categories:

Non-Powertrain (NPT)Powertrain (PT)

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● Non-Powertrain (NPT) Applications of CFD

External Aerodynamics

Deicing, Defogging

Fans

and more….

Passenger ComfortWind Noise

Fuel Fillingand Supply HVAC Ducts,

Vents, Jets

HeatExchangers

Front-End Flow

LightingUnderhood Thermal Modeling

Brake Cooling

Hydraulics

Airbags

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● Powertrain (PT) Applications of CFD

Exhaust After-Treatment

and more….

In-cylinder Flow andCombustion

PumpsMufflers

Torque ConverterFilters

Air Intake System

Exhaust Manifold

Engine CoolingJacket

Valve Flow

Transmission

Clutches

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Outline

OVERVIEW

● Introduction



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Example 1: Heavy Vehicle Aerodynamics

● Drag reduction for a tractor/trailer is examined

● A discontinuity in the height of the tractor and trailer is imposed for the analysis

● A viscous hybrid mesh of 1.5 million cells is used (prismatic layers near the walls, tetcells elsewhere)

● Parallel processing is used to accelerate convergence and reduce turnaround time: 48 hours on a 2 GByte, 4 processor HP-K series computer.

Courtesy of Freightliner Corp.

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● Surface pressure and flow ribbons show disadvantage of mismatched tractor / trailer heights

● Complicated geometrical intricacies captured in the model; boundary layer effects near walls efficiently resolved.

● Study shows the ability of CFD to help reduce drag and improve fuel economy through proper external design

Courtesy of Freightliner Corp.

Example 1: Heavy Vehicle Aerodynamics

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Example 2:Car Aerodynamics

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8Highly detailed surface including wheel-houses and underbody

8Upper parts used to grow 5 prismatic near-wall layers

8Transition to underbody using non-conformal interfaces

8Final hybrid mesh with a total of 4.6 million cells


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15October 2000

46.8 million final adapted mesh(3x)

4Compute Resources:

42 CPU HPJ6000 (PA8600)

46GByte RAM

41600 iterations to converge

430 hours

Drag coefficient from wind-tunnel: cD = 0.286

Computed drag coefficient: cD = 0.296 ( 3.5%)


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● Aim: predict the frequency spectrum of sound heard by the driver when the side window is open

● Mesh: 2.2 million tets● Runtime: 5 days on 6 processors of HP J6000

for complete steady state and transient solutions

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0 5 10 15 20 25 30 35 40 45 50

SPL @ Driver'sLeft Ear

Frequency (Hz)

PT Cruiser, 60 mph, 5o yaw

Fluentx+3 dB @ 17.8 HzExperimentx dB @ 17 Hz

Sou

nd P

ress

ure

Leve

l (dB

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Example 3:Transient Aerodynamics

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Example 4:Underhood Thermal Management

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Bottom View Top View

• Geometry


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Surface Mesh: 330,358 Triangular Elements

Volume Mesh: 1.98 Million Tetrahedrals

Shell Elements 195,587

• Mesh


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● Steady state flow.● Radiator and Condenser were modeled via macro-

based heat exchanger user-defined function.● Heat transfer due to radiation modeled (DOM).● Temperature was imposed on exhaust system, engine

block, and transmission box.● Fluent’s built-in lumped parameter fan model used.● Constant density was assumed.

• Models

• Compute resourcesNetwork of 2 HP J6000’s2 CPU’s Each (440 MHz)2.5 GB RAM required

49 Hrs to Compute Flow Field41.8 Hours to Compute Thermal Field


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• Results

Contour plot showing temperaturedistribution on UH surfaces.


Planar cut showing contour plot offluid temperature downstream of the heat exchanger

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Example 5:Passenger Comfort

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● Ventilation system in a Ford hatchback with four adult occupants:

Summer conditions, AC turned on

● Volume mesh of 850,000 tetrahedral elements.

Courtesy Ford-Werke AG

Cabin interior geometry, showing the distribution of air inlets and passengers.

Surface grid on the compartment interiorand passengers.


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Courtesy Ford-Werke AGPathlines colored by velocity illustrate the flow through the compartment.

Contour plot ofvelocities in a plane.

Temperature contours show the thermal distribution felt by the passengers.


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Defroster / Demister performanceFootwell flow


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● Fluent used to successfully predict ice melt patern observed experimentally.

● De-icing simulation uses steady-state flow with a time-increasing temperature along the inside of the windshield that is representative of the defroster output.

● Finite layer of solid ice present at the start of transient calculation.

● Glass modeled as a conducting wall.● Phase change model used to track

the meltingboth thinning ice as well as melted region.

Courtesy of Visteon

Comparison of defrost patterns from test and CFD analysis after5 minutes.

Example 6:Windshield De-icing

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● Good agreement is obtained after 5, 10 and 15 minute intervals.

Courtesy of VisteonComparison of defrost patterns from test and CFD analysis after10 minutes.

Example 6:Windshield De-icing

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Example 7:HVAC Flow Controls

● The time-dependent flow inside an automotive HVAC coolant control valve is analyzed.

insight gained through the CFD analysis is used to improve its design and performance.

● The valve controls the amount of hot engine coolant entering the heater core of an automotive HVAC system, regulating the temperature of air entering the passenger compartment.

Transient analysis provides more realistic solution than a steady-state analysis of individual static position.

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● The valve has dual control so that driver and passenger can control temperatures individually.

The valve spools operate independently for this purpose.

● Moving spools give rise to a time-dependent flow field.

motion of the valve spools prescribed through time-varying profiles.

● To capture this behavior correctly, the moving mesh model is used


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● The valve geometryconsists of inlet port and three outlet ports

Inlet flow splits and goes to outlets A, B, or C

● Valve spools control flow to outlets A and B

● Excess exits through outlet C

● Unstructured tetrahedral mesh has 170,000 cells.

Courtesy Robert Bosch Corporation

Outlet C

Outlet AOutlet B

Inlet


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● Pathlines showing the coolant flow field at different times during the valve cycle: flow is diverted and distributed between various outlets by the spools.

Side B – open, Side A – closed Sides A and B both half open Side A - open, Side B - closed

• Results


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● Fluent used to study the flow and static pressure rise through a 6-bladed automotive axial fan for the AMCA chamber test conditions

upstream and downstream plenum chambers included in the model.

● The model consists of an inlet, fan and outlet

● Modeling approach:Due to cyclic repetitions in the geometry and flow, only one-sixth of the fan modeled: passage to passage volume analyzed.Flow equations solved in the reference frame of the rotating fan, allowing for steady-state treatment of the problem.Standard k-epsilon turbulence model used.

Courtesy of Siemens VDO Automotive

The fan geometry and mesh .

Example 8:Engine Cooling Fan

Inlet

Fan

Outlet

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● A close-up view of the shroud shows that it is L-shaped.● It overlaps a flat plate (aqua and blue) that is part of the

fan housing.● The plate separates the high and low pressure sides of

the fan.● A small gap separates the shroud and plate.● Results obtained:

Static pressure rise across the fan.Tip leakage of the flow.Flow separation and wash at the trailing edge.Fan efficiency.Distribution of turbulent kinetic energy (~ noise). Courtesy of Siemens VDO Automotive

Mesh detail.


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● Static pressure contours on the hub, blades, and shroud show:

low pressure (blue) on the suction sidehigh pressure on the edge of the pressure side and inside surface of the shroud

Courtesy of Siemens VDO Automotive

● Path lines colored by pressure show the flow in the rotating frame

Numerous results were compared to data for AMCA chamber test conditions and good agreement was obtained.


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● Fluent can be used to predict the flow field and the mass flow rate in the automotive squirrel cage blower.

● The geometry consists of:axial flow inletvolute casingrotating wheeldiffuserflow outlet.

inlet

exit

Example 9:HVAC Blower

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● The mesh consists of ~ 145,000 tetrahedral cells.

Generating hexahedral mesh time consuming.

● Multiple reference frame model (MRF) used:

A rotating reference frame to solve for the flow in the region of wheel, and a stationary frame to solve for flow in the region of the volute.Two regions interact through a pre-defined interface.

● Standard k-epsilon turbulence model used.

Surface mesh.


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● Stream ribbons colored by velocity magnitudeshow

radially outward turn of the flow due to wheel rotationflow acceleration induced by blower wheel.

● Contours of static pressure show highest values on casing walls, lowest at the wheel with recovery near the exit.


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● Full contact brake rotor (i.e. pad and rotor in contact for the full 360 degrees of rotation): frictional heat transfer of paramount importance.

● To reduce testing costs, transient CFD fade test runs on different rotor designs performed.

● Compared flow-rate and heat transfer characteristics of multiple fin configurations.

● CFD advantage over FEA thermal analysis package: no need to assume heat transfer coefficients; the actual heat transfer at solid-fluid interface is computed.

● Periodic slice of single fin in rotor modeled.

• Design Study

Example 10:Brake Cooling

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● Zonal hybrid mesh generated:hex cells for simple portions of geometry (pads, parts of rotor, rotor-pad gap)other regions of high geometric complexity meshed with tetrahedral cells.

● In the contact region, high-aspect ratio hex cells were used to accurately capture the large heat flux normal to the friction surface.

● Mesh sizes typically in the 250,000 - 500,000 element range.

• Mesh

Turnaround time of full transient analysis (CAD-> Solution) in less than 1 week


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● Results

Contours of temperature showing the areas of increased heat on the rotor and pad surfaces.

Pathlines colored by temperatureshowing the air flow patterns in thevicinity of the rotor


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● Data export of wall loads on selected solid-wall zones can be exported:

forcestemperatureheat flux

Heat Transfer Coefficients exported as Boundary Conditions for Thermal Stress Analysis


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● A generator set consists of an electric motor mounted on a gasoline engine.

● Cooling the motor is a challenging task, since heat released from both the coils and the attached IC engine.

Most heat comes from the engine, through the housing and shaft adapters.Additional heat is generated by friction in the bearings.

● Motor cooling is achieved by water circulating through coils and the air separating the rotor and stationary parts.

● Designers need to know if cooling coils can adequately protect the motor components given these heat sources.

Example 11:Electric Motor Cooling

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● CFD is used to assess the cooling potential of a motor design.

The fluid and energy equations are solved in the air gap; the energy equation is solved throughout the solid material.

● Boundary conditions:stator surfaces modeled as walls with radially varying temperaturetemperature prescribed on adapter surfacesconvection heat transfer specified on housinggasket-covered surfaces incorporated thermal resistancetemperature prescribed on surfaces where the bolts attach

● 30 degree periodic sector analyzed.● Hybrid mesh consisted of 1.5 million cells.● Rotor motion simulated with the Moving Reference Frame

(MRF) model.


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Temperature contours on the shaft and motor housing. High temperatures near the shaft are mostly due to the engine mounts and partly due to friction in the bearings.

Temperature contours on the rotor show the uneven heating and cooling on this component.

• Results


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● The magnets, which rotate with the rotor, also show uneven temperatures.

● Those on the engine side (right) are not adequately cooled.

● Results indicate that additional heat protection is necessary

Different cooling coilsHigher flow through engine side coil Courtesy of Lynx Motion Technology, Inc.

Temperature contours on the magnets.

• Results


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Example 12:Fog Lamp Heat Dissipation

● Automotive fog lamp generate significant amount of heat: it is important for designers to select materials that can handle these high thermal loads.

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● CFD can help predict the radiation and convection flows in the lamps’interiors.

Heat transfer between the air inside the lamp and solid components of the bulb, lens and reflector modeled. Temperature profile over the components predicted.

● From the CFD-computed temperature profiles, the proposed headlamp designs are analyzed and validated quickly, saving time and cost associated with building prototypes.

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● Lamp interior meshed with tetrahedral grid. Lens thickness modeled extruding prisms from the lens’ interior surface definition.

● Temperature contours confirm that the temperatures are within the acceptable range for the materials. (Lamp viewed from the underside).


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Example 13:Fuel Tank Sloshing

● CFD is used to study the free surface movement of liquid in an automotive fuel tank undergoing acceleration, followed by motion at constant velocity.

Fuel location, shape and velocity of free interface of interest.

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● Two tank configuration studied: fuel tanks equipped with or without baffles.

The goal is to see whether baffles keep the fuel pick-up pipe submerged in liquid at all times.

● By comparing the sloshing patterns, design engineers can gain insight into the importance of the baffles for ensuring problem-free operation, especially when the tank is low on fuel.


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● Simulating the car acceleration of 1g in horizontal direction for 1.15 seconds, followed by const velocity for another second.

● The liquid fuel initially at rest with its surface 10 cm from the bottom (25% capacity of the tank).

● Tetrahedral mesh elements in the region of pick-up pipe, hexahedral elements elsewhere.

● The same mesh used to simulate both tank configuration (w/ and w/o baffles), by changing boundary types from walls into interiors.


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The liquid surface shows large amplitude sloshing in the tank after about 1 sec. Velocity vectors on the surface help illustrate the complex flow at the interface.

• Results: without baffles

Without baffles, the pick-up pipe orificeis exposed after 2 sec.


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● With baffles, there is less sloshing.● Small circulation patterns between the baffles keep

the amplitude low.● The fuel pick-up pipe orifice is submerged at all times

during the simulation.

• Results: with baffles

After 1 second After 2 seconds


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● A volume integral of kinetic energy during sloshing shows

large scale sloshing without baffles (red)small scale sloshing with baffles (black)

● Results can be used to help engineers design problem-free fuel tanks, even when operating near empty


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Outline

OVERVIEW

● Introduction



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● Performance of an internal combustion engine studied.

● Cold flow simulations give insight into flow characteristics such as

Volume efficiencySwirl

as functions of port and chamber design and valve lift timing.

● The moving and deforming mesh (MDM) model in FLUENT was used.

Example 14:I.C. Engine In-Cylinder Flow

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● When the MDM model is used, the geometry changes with time.

● The CFD user supplies the initial mesh and a function to describe the motion of the components.

● At each new time step during the simulation, a new grid is constructed automatically.

● With the piston at bottom dead center (right), the cell layers grown during the motion are shown in gray.


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● Layers of cells (pink) are built on the intake runner as the valve moves down into the cylinder

● Three remeshing techniques are available:

Dynamic layeringSpring smoothingLocal remeshing

● These can be used alone or in combination, as needed.


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● Pressure boundary conditions are used for the intake and exhaust ports

● Compressible air is the working fluid

● Contours of velocity magnitude at 9 times during the cycle are shown

● MDM model for complex IC engine simulations - with or without combustion – help to better understand the flow field and aid in design modification.


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● Flow pattern inside a clutch needs to be understood in order to optimize the cooling of friction parts.

● Amount of fluid passing through the holes of clutch cover is of interest.

● Results can be used to indicate whether the air flow is enough to cool the clutch during operation.

● The clutch geometry consists of:Pressure plate (blue)Diaphragm spring (magenta)Cover (red and green)

Example 14:Automotive Clutch

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● The moving reference frame model (MRF) is used to simulate the rotating clutch in a stationary bell housing.

Clutch rotation is 2000rpm.Time averaged flow is of primary importance.

● A zonal hybrid mesh of 700,000 cells used.

– Models

● Only isothermal flow is studied, since the purpose of the calculation is to maximize airflow inside the cover.

● The RNG k-e turbulence model for swirl dominated flow is used.

Mesh


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● Pressure contours are uniform on the cover, but uneven in the flow passages.

This result suggests that air is passing through these regions.

● Pathlines under the cover (left) and inside the housing (right) illustrate the flow. Good circulation in all regions suggest good cooling potential.


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● Water is drawn in through three inlet channels (violet).

● An impeller operates in the center section.

● Outflow is through two exit channels (gold) with 90o bends at each end.

● The impeller has 10 blades that are tapered and curved to draw water in axially and expel it radially.

● The multiple reference frames (MRF) model in FLUENT is used for the rotating impeller region.

Impeller speed is 6000 rpm.

● Turbulent flow is modeled using the standard k-ε model.

Courtesy of Tesma Engine Company

• Geometry

Impeller

Example 15:Automotive Water Pump

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● Due to complexity of geometry, a hybrid mesh was generated

1.6 million cells used this cell count is at the high end for water pump applications

● Hexahedral elements are used for the intake channels.

● Tetrahedral elements are used elsewhere.

• Mesh


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● Overall predictions for pressure rise agree with experiment to within 7%

Velocity vectors in the impeller and outflow plane show swirling and radial flow.Pressure contours on the pump housing show a large loss at a constriction in the outflow channel.

• Results

The obtained CFD information helps with design modificationsthat improve pump performance.


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● Fluent can be used to predict Flow and Heat Transfer in an IC Engine water jacket

● Surface mesh: 132,000 triangular elements● Volume mesh: 577,000 tetrahedral cells● Computer Resources:

HP J6000 dual CPU (440MHz)512 GB RAM required

● Simulation Time:500 Iterations in 2 hours for both flow and thermal solutions

Pressure profile

Example 16:Engine Water Jacket

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Velocity Vectors on various cross-sectional cuts

Use CFD to predict mass flow rate of coolant based on

specified pressure loss


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Heat Transfer Coefficients on the surface of a 4 cylinder cooling jacket.

Detailed analysis included a water pump

CFD allows engineers to explore how design

changes of the jacket affect its performance


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● Catalytic converters are used to purify automotive exhaust gases.

● In the converter, gases pass through a substrate coated with a metal catalyst.

● The catalyst converts CO to CO2and NOx compounds to nitrogen and oxygen.

● Volatile organic compounds (VOCs) are converted to CO2 and H2O.

● Key design criteria, such as uniform flow distribution across the substrate, can be quickly analyzed by CFD.

Geometry of the converter and nearby components. Heated exhaust gas enters through 4 inlets of an exhaust manifold, and enters the substrate inside converter.

Example 17:Catalytic Converters

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● Due to varying complexity of the geometry and to minimize preprocessing time, a hybrid mesh is used.

120,000 cells.

● The substrate is treated as a porous media:

Losses in the cross-stream direction are three times larger than in the stream-wise direction

● The flow is laminar in the substrate, but fully turbulent elsewhere

The k-ε model is used for turbulence● Boundary conditions:

mass flow at the inlets constant pressure at outlet

Mesh


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● Pathlines colored by velocity magnitude show uniform axial flow throughout the converter. The speed increases as the flow cross section area reduces in the tail pipe.

● Pressure contours illustrate significant pressure drop in substrate region.

• Results


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● Several specific parameters were computed to evaluate catalytic converters

Pressure lossEccentricity of velocity profile (right)Gamma uniformity index

● Such metrics can indicate whether or not certain design is acceptable.


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● Seals are used to prevent leakage from centrifugal pumps, mixers, etc.

Courtesy of A.W. Chesterton Co.

• Pressurized fluid circulates through the seal

•forming a barrier to prevent leakage•removing frictional heat generated between rotating and non-rotating elements.

Centrifugal Pump Mechanical Seal

Example 18:Fluid Seals

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● Understand the effects of flow behavior within the seal on its design and operation.

● Validate CFD results with experimental data.● Examine several parametric design changes

that improves heat removal efficiency of cooling system.

• Objectives


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• Mesh


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• Boundary Conditions


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• Temperature Rise


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• Untapered Design

Velocity vectors colored by temperature:a circulation pattern forms midway between inlet and outlet


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• Tapered Design

Velocity vectors colored by temperature:tapered-surface design contributes an axialcomponent to the flow, propelling the fluid away and increasing heat removal by 50%.


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● Flow inside automotive torque converters and thereby their performance can be studied with Fluent

Example 19:Torque Converters

Pump

Stator

Turbine

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● The MRF model is used, and complete 360°geometry is considered

● A single blade passage is shown here to provide a clos-up view of the mesh


Pump

Stator

Turbine

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● Turbo Post-processing tools in Fluent allow the flow structure inside the torque converter to be investigated in detail

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● Performance characteristics are plotted. Results show excellent agreement with corresponding experimental data

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Summary

● Automotive CFD applications are broadly classified into two types

Non-Powertrain ApplicationsPowertrain Applications

● FLUENT is a widely used CFD software for dozens of applications in both these areas

● CFD analysis provides several benefitsLow CostFast Turn Around TimeComprehensive Insights ….

…. Ultimately Leading to Better Engineering Designs

CFD Applications in the Automotive Industry -...

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