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Class 8 Truck External AerodynamicsChoice of Numerical Methods
1Security Classification Line
PVE Vehicle Analysis
Portland, March, 19th 2013
Dinesh Madugundi, Anna Garrison
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Product Validation Engineering
Vehicle Analysis
Agenda
� Motivation
� Review of existing literature
� Understanding Truck aerodynamics
� Choice of numerical methods for Truck aerodynamics
Daimler Trucks North AmericaPVE Vehicle Analysis 2
Source:
� Numerical methods comparison study
� References
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Product Validation Engineering
Vehicle Analysis
MotivationClass-8 Truck with Standard 53‘ Trailer
� Accurately predicting complex flow phenomenon in Truck aerodynamics using
numerical methods can be challenging.
Daimler Trucks North America
Wake interaction between the drive tires and trailer bogies
PVE Vehicle Analysis 3
Source:
Tractor trailer gap
Trailer back face
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Product Validation Engineering
Vehicle Analysis
MotivationWhy CFD to Evaluate Class 8 Truck Aerodynamics?
� Standard Class 8 trucks are ~2.8m wide and ~22m long including the trailer.
� Very few full scale wind tunnels can accommodate full tractor trailer
configuration, while simulating real road wind conditions.
� Advantages in using CFD
Daimler Trucks North AmericaPVE Vehicle Analysis 4
Source:
— Full tractor trailer configuration
— Simulating real road conditions
— Predicting performance of an aero component before modifying or installing
— Wide range of design validations
— Detailed flow visualization
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Product Validation Engineering
Vehicle Analysis
CFD ModellingStandard Numerical Methods
� Reynolds Averaged Navier Stokes (RANS)
� Unsteady RANS
� Large Eddy Simulation (LES)
� Detached Eddy Simulation (DES)
Daimler Trucks North AmericaPVE Vehicle Analysis 5
Source:
� Detached Eddy Simulation (DES)
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Product Validation Engineering
Vehicle Analysis
� Bruce L. Storms AerospaceComputing Inc. “A Summary of the Experimental Results for a Generic
Tractor-Trailer in the Ames Research Center 7- by 10-Foot and 12-Foot Wind Tunnels”.
� Generic Conventional model (GCM) of class-8 tractor-trailer 1/8th scale results available for
validation study.
Experimental Setup (Reference)NASA/TM – 2006-213489
� Simplified model of standard class-8 tractor-trailer,
no grille opening, no underhood components.
� Experiments were performed at Re* = 1.1e6 –
Daimler Trucks North America 6PVE Vehicle Analysis 09.04.2013
� Experiments were performed at Re* = 1.1e6 –
6.2e6.
� For this study, results from Re = 6.0e6 are
compared, no T-T gap aero treatment, no trailer
aero treatment.
*Re was calculated based on Truck width.
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Product Validation Engineering
Vehicle Analysis
CFD SetupGeometry and CFD Mesh Overview� GCM 1:1 scale, closed grille, flat underbody.
� No T-T gap aero treatment, no trailer aero devices
� Computational domain with far field domain, moving ground, and
spinning tires.
� Mesh settings
— Base size = 40mm
Daimler Trucks North America 7PVE Vehicle Analysis 09.04.2013
— Base size = 40mm
— Trim mesh, surface size 5mm – 40mm
— Wake refinement
— Low Re prism mesh
— Total number of volume cells ~15M
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Product Validation Engineering
Vehicle Analysis
CFD Results of GCMTransient vs Steady� Flow conditions, constant density, Re = 6.0e6, 0yaw
and 6yaw. No side extenders.
� Solvers RANS, URANS and DES with Spalart-Allmaras
turbulence model, are compared.
� The three solvers predicted Cd that matched relatively
close to the measurements.
Daimler Trucks North America 8PVE Vehicle Analysis 09.04.2013
� RANS and URANS results matched well with each
other.
� DES results are closer to the measurements at yaw,
compared to RANS. More accurate wake predictions?
80mph @0yaw: DES
80mph @6yaw: DES
80mph @0yaw: URANS
80mph @6yaw: URANS
Plane View
Time Avg Ptotal Plots Time Avg Ptotal Plots
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Product Validation Engineering
Vehicle Analysis
CFD ResultsUnderstanding Truck Aerodynamics 1/2� Production Cascadia sleeper, 45” T-T gap, and 53’
standard trailer.
� CFD Methods: Current DTNA best practices.
� About 50% of total drag is from tractor.
� Yaw effects are predominant on trailer bogies and
trailer back face.
∑=
−−
=
l
i
xxx iil
CdCdCumulative
1
1
Tracto
r d
rag
~5
0%
Traile
r d
rag
~5
0%
Daimler Trucks North America 9PVE Vehicle Analysis 09.04.2013
� Sections of drag effects
— A-surface
� Stagnation pressure on the grille
� Flow around the bumper and hood
� Stagnation pressure on wind shield
� Flow over the roof cap
� Effectiveness of roof deflector
� Effectiveness of side extenders and chassis fairings
Cumulative Cd[-] plot over the length of the Truck, normalized by
total vehicle Cd0yaw.
Tracto
r d
rag
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Product Validation Engineering
Vehicle Analysis
CFD ResultsUnderstanding Truck Aerodynamics 2/2� Sections of drag effects, cntd…
— Underhood pressure: flow below the bumper determines
underhood pressure.
— Underbody flow: chassis components and drive tires are
exposed to high speed flow.
— T-T gap: Pressure in T-T gap influences effectiveness of
side-extenders and roof deflector.
∑=
−−
=
l
i
xxx iil
CdCdCumulative
1
1
T-T gap Pressure
Daimler Trucks North America
Cumulative Cd[-] plot over the length of the Truck, normalized by
total vehicle Cd0yaw.
10PVE Vehicle Analysis 09.04.2013
side-extenders and roof deflector.
— Trailer bottom and trailer back face.
Plan view: Z-section along tire center: 55mph, 0yaw
Plan view: Z-section along tire center: 55mph, 6yaw
55mph, 0yaw 55mph, 6yaw
Time Avg Velocity Magnitudes
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Product Validation Engineering
Vehicle Analysis
CFD ModelingChoice of Numerical Methods for Truck Aero� Choice of numerical methods is critical to capture complex flow phenomenon of Truck
aerodynamics.
— Surface bounded flow (Current industry standards, RANS, k-e, or SA).
— Under the cab wake interaction (accurate prediction of vortex shedding).
— Tractor trailer wake interaction.
� RANS methodology with Low-Re mesh can achieve accurate boundary flow.
Daimler Trucks North AmericaPVE Vehicle Analysis 11
Source:
� LES methodology to capture vortex shedding.
— Highly mesh dependant in BL.
— Can be computationally expensive.
� For Truck aero applications, hybrid model DES (Detached Eddy Simulation) can deliver best aspects
of RANS and LES methodologies.
— Less sensitive to boundary layer mesh with RANS methodology.
— Low Re mesh to accurately predict flow separation.
— LES methodology to predict wakes; sensitive to mesh wake refinements.
— Computationally less expensive than LES
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Product Validation Engineering
Vehicle Analysis
CFD ResultsRANS vs DES 1/6� The CFD models are created using STAR-CCM+ v6.06.017. The following numerical methods are
compared for this study
— RANS
� Turbulence model – Spalart Allmaras
� Time dependency – Steady
� Segregated Flow
Daimler Trucks North America12PVE Vehicle Analysis 09.04.2013
� Segregated Flow
� Wall Treatment – All y+
— DES (As per DTNA’s best practices)
� Turbulence model– Spalart Allmaras Detached Eddy
� Time dependency – Implicit Unsteady
� Segregated Flow
� Wall Treatment – All y+
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Product Validation Engineering
Vehicle Analysis
CFD ResultsRANS vs DES 2/6� The difference in total vehicle drag between RANS vs
DES is about 15% - 20% depending on yaw condition.
� Delta Cd on tractor is about 5% - 8%; resultant
difference is on trailer bogies and back face.
� Flow Comparison,
— Flow separation over the hood.
∆C
d ~
15
% -
20
%
∑=
−−
=
l
i
xxx iil
CdCdCumulative
1
1
∆Cd ~5% - 8%
Daimler Trucks North America13PVE Vehicle Analysis 09.04.2013
— More diffusion under the bumper.
� Effects underhood pressure.
� Higher drag on chassis and drive tires.
— Difference in T-T gap pressure (influences roof deflector
and side extenders’ performance).
Cumulative Cd[-] plot over the length of the Truck, normalized by
total vehicle Cd0yaw.
DES RANSTime Avg Velocity Magnitudes
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Product Validation Engineering
Vehicle Analysis
CFD ResultsRANS vs DES 3/6� RANS predicted drag on the trailer is ~12% - 15%
lower.
— Difference in drag is higher at 0yaw; can be accounted
to wake interaction.
— At 6yaw, the wake interaction is reduced due to free
stream effects; shift in wake direction.
— Similar differences on trailer back face at 0yaw and
∑=
−−
=
l
i
xxx iil
CdCdCumulative
1
1
∆C
d ~
12
% -
15
%
Daimler Trucks North America14PVE Vehicle Analysis 09.04.2013
— Similar differences on trailer back face at 0yaw and
6yaw.
� Transient phenomenon with controlled wake under the
trailer? For example, trailer skirts.Cumulative Cd[-] plot over the length of the Truck, normalized by
total vehicle Cd0yaw.
DES
RANS
DES
RANS
Time Avg Velocity Magnitudes
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Product Validation Engineering
Vehicle Analysis
CFD ResultsRANS vs DES 4/6� Trailer skirts shield high speed flow impinging the
trailer bogies.
� With controlled wake under the trailer, we expect less
transient phenomenon under the trailer.
� The difference in total vehicle drag from RANS vs DES
increased to 25% .
∑=
−−
=
l
i
xxx iil
CdCdCumulative
1
1
∆Cd ~5% - 8%
∆C
d ~
15
% -
25
%
Daimler Trucks North America15PVE Vehicle Analysis 09.04.2013
— Tractor drag difference remained at 5% – 8%; significant
differences on trailer drag.
� With larger wake, transient phenomenon becomes
more prominent.DES (0yaw)
RANS (0yaw)
DES (6yaw)
RANS (6yaw)
Cumulative Cd[-] plot over the length of the Truck, normalized by
total vehicle Cd0yaw.
Time Avg Velocity Magnitudes
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Product Validation Engineering
Vehicle Analysis
Degree of AccuracyRANS vs DES 5/6� Drag predictions using DES methods are
compared to WT testing for validation; the
results are within 2% accurate at a given
Re.
� Drag predictions using RANS are off by 15%
- 20%.
� Flow characteristics with DES methods
W/o Trailer Skirts With Trailer Skirts
[DES - RANS] [DES – Exp] [DES - RANS] [DES – Exp]
∆Cd 0yaw 20.84% 1.4% 25.49% 1.5%
Chassis 3.66% 3.89%
Tractor Tires 0.91% 1.36%
Trailer 14.81% 18.87%
∆Cd 6yaw 14.47% Not Avail 16.10% Not Avail
Chassis 2.52% 1.79%
Tractor Tires 0.79% 1.25%
Trailer 10.38% 11.81%
Daimler Trucks North AmericaPVE Vehicle Analysis 16
Source:
� Flow characteristics with DES methods
— The amplitude of Cd oscillations are
about10% - 20% of average Cd.
— Requires longer physical time to achieve
converged solution (say, 10ms of TS, 25s
total physical time with 5s/10s running
avg); computationally expensive.
— Not appropriate for design optimization
study when the Cd resolution per design
iteration is ∆Cd<1%.
� RANS applicability in Truck aerodynamics?
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Product Validation Engineering
Vehicle Analysis
Degree of AccuracyRANS vs DES 6/6� RANS methods applicability in Truck aerodynamics?
— Qualitative analysis of aero performance of design
variants., Eg., mirrors.
— Possible to obtain general drag trend due to the
variants.
— The drag trends can be misleading depending on the
location of aero device.
Daimler Trucks North AmericaPVE Vehicle Analysis 17
Source:
location of aero device.
� For example, validation of aerodynamic performance of
multiple design variants of a roof cap.
— Evaluating all the design variants using DES methods
can be very expensive.
— RANS methods to get preliminary understanding of the
performance of each variant.
— Best design was re-evaluated using DES methods for
final confirmation.
— Drag performance on the trailer showed inverse trend.
� In most cases, evaluating an aero component using DES methods becomes necessary!!!!
Truck image is only for reference. Actual
Truck used for this study is not shown.
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Product Validation Engineering
Vehicle Analysis
Conclusions
� To achieve accurate aerodynamic drag evaluation of Class-8 trucks, numerical methods capable of
predicting vortex shedding can be influential in design evolution.
� DES methods are
— Proved to be accurate during validation of CFD methods.
— Accurate evaluation of aero components.
— Computationally expensive.
Daimler Trucks North AmericaPVE Vehicle Analysis 18
Source:
— Sensitive to mesh refinement.
— Capturing aero performance of minor changes in design can be questionable.
� RANS methods are
— Good for qualitative analysis of aero performance of design variants.
— Capable of generating general drag trend of a given design modification.
— Trends can be misleading depending on the type of aero application.
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Product Validation Engineering
Vehicle Analysis
References
1. Bruce L. Storms Aerospace Computing Inc. “A Summary of the Experimental
Results for a Generic Tractor-Trailer in the Ames Research Center 7- by 10-Foot
and 12-Foot Wind Tunnels”
2. Product Validation Engineering – Analysis, DTNA LLC. “Computational Fluid
Dynamics Certification”
Daimler Trucks North AmericaPVE Vehicle Analysis 19
Source:
3. SAE J2966, “Guidelines for Aerodynamic Assessment of Medium and Heavy
Commercial Ground Vehicles Using Computational Fluid Dynamics”.