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UTIAS
University of TorontoInstitute for Aerospace Studies
Towards Aerodynamic Shape Optimization ofRegional Class Blended-Wing-Body Aircraft
for Reduced Environmental Impact
Thomas A. Reist
David W. Zingg
May 16th, 2013
University of Toronto Institute for Aerospace Studies 2013 National Colloquium on Sustainable Aviation
Outline
1 Introduction
2 Blended-Wing-Body
3 Aerodynamic Shape Optimization
4 Optimization
5 Conclusions & Future Work
University of Toronto Institute for Aerospace Studies 2013 National Colloquium on Sustainable Aviation
Introduction
1 IntroductionMotivation
2 Blended-Wing-BodyDesign BenefitsDesign ChallengesRegional BWB Design
3 Aerodynamic Shape Optimization
4 OptimizationOptimization DefinitionOptimization Under Inviscid FlowOptimization Under Turbulent Flow
5 Conclusions & Future Work
University of Toronto Institute for Aerospace Studies 2013 National Colloquium on Sustainable Aviation
Airline Industry Factors
Increasing demand for air travel and air freight
Increasing and volatile fuel prices
Environmental pressures
Source: US Global Change Research Program
University of Toronto Institute for Aerospace Studies 2013 National Colloquium on Sustainable Aviation
Environmental Goals
Source: ICAO Environmental Report 2010
University of Toronto Institute for Aerospace Studies 2013 National Colloquium on Sustainable Aviation
Blended-Wing-Body
1 IntroductionMotivation
2 Blended-Wing-BodyDesign BenefitsDesign ChallengesRegional BWB Design
3 Aerodynamic Shape Optimization
4 OptimizationOptimization DefinitionOptimization Under Inviscid FlowOptimization Under Turbulent Flow
5 Conclusions & Future Work
University of Toronto Institute for Aerospace Studies 2013 National Colloquium on Sustainable Aviation
The Blended-Wing-Body (BWB)
The tube-and-wing design has served us well for over 60 years...
... But is a step change in configuration design required?
University of Toronto Institute for Aerospace Studies 2013 National Colloquium on Sustainable Aviation
Design Benefits
AerodynamicHigh wetted aspect ratio gives high lift-to-drag ratioNatural ‘area-ruling’ improves high-speed performance
StructuralNatural spanloading reduces bending loads
PropulsiveBoundary-layer ingesting engines reduce fuel-burn
AcousticBody-mounted engines are acoustically shieldedLow landing speed reduces airframe noise
Liebeck, JoA, Vol. 41, No. 1, 2004
University of Toronto Institute for Aerospace Studies 2013 National Colloquium on Sustainable Aviation
Design Benefits
AerodynamicHigh wetted aspect ratio gives high lift-to-drag ratioNatural ‘area-ruling’ improves high-speed performance
StructuralNatural spanloading reduces bending loads
PropulsiveBoundary-layer ingesting engines reduce fuel-burn
AcousticBody-mounted engines are acoustically shieldedLow landing speed reduces airframe noise
University of Toronto Institute for Aerospace Studies 2013 National Colloquium on Sustainable Aviation
Design Benefits
AerodynamicHigh wetted aspect ratio gives high lift-to-drag ratioNatural ‘area-ruling’ improves high-speed performance
StructuralNatural spanloading reduces bending loads
PropulsiveBoundary-layer ingesting engines reduce fuel-burn
AcousticBody-mounted engines are acoustically shieldedLow landing speed reduces airframe noise
Liebeck, JoA, Vol. 41, No. 1, 2004
University of Toronto Institute for Aerospace Studies 2013 National Colloquium on Sustainable Aviation
Design Benefits
AerodynamicHigh wetted aspect ratio gives high lift-to-drag ratioNatural ‘area-ruling’ improves high-speed performance
StructuralNatural spanloading reduces bending loads
PropulsiveBoundary-layer ingesting engines reduce fuel-burn
AcousticBody-mounted engines are acoustically shieldedLow landing speed reduces airframe noise
Daggett, NASA/CR-2003-212670, 2003
University of Toronto Institute for Aerospace Studies 2013 National Colloquium on Sustainable Aviation
Design Challenges
AerodynamicShock-free airfoils with sufficient thicknessMaintaining stability and control without a tail
StructuralDesign of non-cylindrical pressure vessel for the cabinMore complicated load-paths
PropulsiveRobust boundary-layer ingesting engine technology
Passenger comfortRide quality
Mukhopadhyay, 2012
University of Toronto Institute for Aerospace Studies 2013 National Colloquium on Sustainable Aviation
Design Challenges
AerodynamicShock-free airfoils with sufficient thicknessMaintaining stability and control without a tail
StructuralDesign of non-cylindrical pressure vessel for the cabinMore complicated load-paths
PropulsiveRobust boundary-layer ingesting engine technology
Passenger comfortRide quality
Mukhopadhyay, AIAA 2012-1999, 2012
Mukhopadhyay, 2012
University of Toronto Institute for Aerospace Studies 2013 National Colloquium on Sustainable Aviation
Design Challenges
AerodynamicShock-free airfoils with sufficient thicknessMaintaining stability and control without a tail
StructuralDesign of non-cylindrical pressure vessel for the cabinMore complicated load-paths
PropulsiveRobust boundary-layer ingesting engine technology
Passenger comfortRide quality
Daggett, NASA/CR-2003-212670, 2003
Mukhopadhyay, 2012
University of Toronto Institute for Aerospace Studies 2013 National Colloquium on Sustainable Aviation
Design Challenges
AerodynamicShock-free airfoils with sufficient thicknessMaintaining stability and control without a tail
StructuralDesign of non-cylindrical pressure vessel for the cabinMore complicated load-paths
PropulsiveRobust boundary-layer ingesting engine technology
Passenger comfortRide quality
Liebeck, JoA, Vol. 41, No. 1, 2004
Mukhopadhyay, 2012
University of Toronto Institute for Aerospace Studies 2013 National Colloquium on Sustainable Aviation
The Regional Jet Segment
Comprises 30% of global aircraft fleet
Fastest growing segment over the past 30 years
RAA 2011 Annual Report 21
Reg
ion
al Aircraft Statistics
US Regional Aircraft Fleet
Scheduled Passenger Aircraft by Type (see airline breakdown page 23)
average seating capacity of regional aircraft
3741 42
4547
50 50 5153
55 56
0
10
20
30
40
50
60
2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010
1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 20100
500
1000
1500
2000
2500
3000
3500
4000 Turboprop Aircraft
Regional Jets
Narrowbody*
Widebody
active in service aircraftREGIONAL MAINLINE
Notes:Includes most aircraft over 9 seats*Mainline narrowbody aircraft include Embraer 190 aircraft operated by US Airways and JetBlue Source: OAG Fleet iNet
“I see a day when the regional carrier is the face of a large and growing number of
small communities and not the mainline carrier as it is today...The regional sector will
increasingly become a large and larger face of the domestic market...but it will be done
with an increasing level of flying being done ‘at risk’. I can see a day when the regional
carriers of today are buyers of mainline domestic hubs. Consolidation inside the regional
sector is building companies with significant scope and scale on the operating side...”
Bill Swelbar, swelbar.org
at the RAA Fall Meeting December 2010
Source: Regional Airline Association 2011 Annual Report
University of Toronto Institute for Aerospace Studies 2013 National Colloquium on Sustainable Aviation
Design Problem
Passengers 100†
Cargo volume 683 ft3
Payload 23,380 lbsMax range 2,000 nmiCruise speed 0.80 Mach† Single class at 31” pitch
Similar mission to the CRJ1000ER and E-190
University of Toronto Institute for Aerospace Studies 2013 National Colloquium on Sustainable Aviation
Aerodynamic Shape Optimization (ASO)
1 IntroductionMotivation
2 Blended-Wing-BodyDesign BenefitsDesign ChallengesRegional BWB Design
3 Aerodynamic Shape Optimization
4 OptimizationOptimization DefinitionOptimization Under Inviscid FlowOptimization Under Turbulent Flow
5 Conclusions & Future Work
University of Toronto Institute for Aerospace Studies 2013 National Colloquium on Sustainable Aviation
Aerodynamic Shape Optimization
Range =aM
cT
L
Dln
(W0 + Wfuel
W0
) Flight condition effectsPropulsive effectsAerodynamic effectsStructural effects
Drag reduction under inviscid flow
Flow model: Euler equationsMinimize induced dragEliminate wave drag
Drag reduction under turbulent flow
Flow model: Reynolds-Averaged Navier-Stokes equationsMinimize induced dragEliminate wave dragMinimize profile drag
University of Toronto Institute for Aerospace Studies 2013 National Colloquium on Sustainable Aviation
Aerodynamic Shape Optimization
Geometry parameterization andmesh movement
B-spline geometryparameterization
Linear elastic mesh movementalgorithm applied to theB-spline grid
Robust for large shapechanges
University of Toronto Institute for Aerospace Studies 2013 National Colloquium on Sustainable Aviation
Aerodynamic Shape Optimization
Flow solver
Newton-Krylov-Schur parallelmultiblock implicit flow solver
Euler and Reynolds-AverageNavier-Stokes equations withthe one-equationSpalart-Allmaras turbulencemodel
University of Toronto Institute for Aerospace Studies 2013 National Colloquium on Sustainable Aviation
Aerodynamic Shape Optimization
Gradient evaluation
Via the discrete adjointmethod
Integrated with geometryparameterization, meshmovement, flow solver
Solution time independent ofnumber of design variables
76 CHAPTER 4. ANALYTIC SENSITIVITY ANALYSIS OF COUPLED SYSTEMS
0 400 800 1200 1600 2000
Number of design variables (Nx)
0
400
800
1200
Norm
aliz
ed tim
e
Complex step
2.1
+ 0
.92
× N
x
Finite difference
1.0 + 0.38 × N x
Coupled adjoint
3.4 + 0.01 × Nx
Figure 4-8: Computational time vs. number of design variables for finite differencing, com-plex step and coupled adjoint. The time is normalized with respect to the time required forone aero-structural solution.
The cost of computing sensitivities using the coupled-adjoint procedure is in theory inde-
pendent of the number of variables. Using our implementation, however, some of the partial
derivatives in the total sensitivity equation (4.17) are calculated using finite differences and
therefore, there is a small dependence on the number of variables. The line representing
the cost of the coupled adjoint in Figure 4-8 has a slope of 0.01 which is between one and
two orders of magnitude less than the slope for the other two lines.
In short, the cost of computing sensitivities with respect to hundreds or even thousands
of variables is acceptable when using the coupled-adjoint approach, while it is impractical to
use finite-differences or the complex-step method for such a large number of design variables,
even with current state-of-the-art parallel computing systems.
4.5.2 Coupled-Adjoint Solution
The constant terms in the equations for the straight lines of Figure 4-8 represent the cost
of each procedure when no sensitivities are required. For the finite-difference case, this is
Martins, 2002
University of Toronto Institute for Aerospace Studies 2013 National Colloquium on Sustainable Aviation
Optimization
1 IntroductionMotivation
2 Blended-Wing-BodyDesign BenefitsDesign ChallengesRegional BWB Design
3 Aerodynamic Shape Optimization
4 OptimizationOptimization DefinitionOptimization Under Inviscid FlowOptimization Under Turbulent Flow
5 Conclusions & Future Work
University of Toronto Institute for Aerospace Studies 2013 National Colloquium on Sustainable Aviation
Baseline Design
Car
go
Car
go
M M
C.G. location
M
Wing box
Monument
CapacityPassengers 98Crew 4
Cabin floor area 593 ft2
Cargo volume 683 ft3
Geometry
Planform area 2177 ft2
Total span 90 ftLength 74 ftMAC 44 ftAspect ratio 3.7Wetted aspect ratio 1.6
WeightMTOW 96,760 lbOEW 54,710 lbPayload 23,380 lb
Wing load at MTOW 44 lb/ft2
Cruise conditionsDesign range 500 nmiAltitude 40,000 ft
Reynolds number 69 ×106
Mach number 0.80xCG/ccenter-line 0.65
University of Toronto Institute for Aerospace Studies 2013 National Colloquium on Sustainable Aviation
Optimization Problem
Objective:Minimize drag
Design variables:B-spline control points
Angle-of-attack
Geometric constraints:Cabin shape
Span and area
Geometric limits
Optimization under inviscid flow:Stability-constrained
Optimization under turbulent flow:Trim-constrained
University of Toronto Institute for Aerospace Studies 2013 National Colloquium on Sustainable Aviation
Optimization Under Inviscid Flow
X/cC
p0.0 0.2 0.4 0.6 0.8 1.0
-2.0
-1.5
-1.0
-0.5
0.0
0.5
1.0
Y/b = 0.20
X/c
Cp
0.0 0.2 0.4 0.6 0.8 1.0
-2.0
-1.5
-1.0
-0.5
0.0
0.5
1.0
Y/b = 0.40
X/c
Cp
0.0 0.2 0.4 0.6 0.8 1.0
-2.0
-1.5
-1.0
-0.5
0.0
0.5
1.0
Y/b = 0.80
X/c
Cp
0.0 0.2 0.4 0.6 0.8 1.0
-2.0
-1.5
-1.0
-0.5
0.0
0.5
1.0
Y/b = 0.00
X/c
Cp
0.0 0.2 0.4 0.6 0.8 1.0
-2.0
-1.5
-1.0
-0.5
0.0
0.5
1.0
Y/b = 0.60
X/c
Cp
0.0 0.2 0.4 0.6 0.8 1.0
-2.0
-1.5
-1.0
-0.5
0.0
0.5
1.0
Y/b = 0.98
Baselinepressure profiles
Y/b0.00.20.40.60.81.0
Y/b0.0 0.2 0.4 0.6 0.8 1.0
0.05
0.10
0.15
0.20
L/Ltotal
Cp: -1 -0.8 -0.6 -0.4 -0.2 0 0.2 0.4 0.6 0.8 1
Center of gravityNeutral point
OptimizedCenter of gravityNeutral point
Baseline
Baseline and optimized surface pressure andspanwise lift distributions
X/c
Cp
0.0 0.2 0.4 0.6 0.8 1.0
-2.0
-1.5
-1.0
-0.5
0.0
0.5
1.0
Y/b = 0.20
X/c
Cp
0.0 0.2 0.4 0.6 0.8 1.0
-2.0
-1.5
-1.0
-0.5
0.0
0.5
1.0
Y/b = 0.40
X/c
Cp
0.0 0.2 0.4 0.6 0.8 1.0
-2.0
-1.5
-1.0
-0.5
0.0
0.5
1.0
Y/b = 0.80
X/c
Cp
0.0 0.2 0.4 0.6 0.8 1.0
-2.0
-1.5
-1.0
-0.5
0.0
0.5
1.0
Y/b = 0.00
X/c
Cp
0.0 0.2 0.4 0.6 0.8 1.0
-2.0
-1.5
-1.0
-0.5
0.0
0.5
1.0
Y/b = 0.60
X/c
Cp
0.0 0.2 0.4 0.6 0.8 1.0
-2.0
-1.5
-1.0
-0.5
0.0
0.5
1.0
Y/b = 0.98
Optimizedpressure profiles
University of Toronto Institute for Aerospace Studies 2013 National Colloquium on Sustainable Aviation
Inviscid Performance
AoA CM Kn L/D
Baseline 1.85 -0.021 -2.8 18.3Optimized 3.01 0.000 +4.9 39.6
Drag reduction of 55% while creating a
trimmed and stable design
Wave drag eliminatedInduced drag reduced
Stability constraint incurs a 2% dragpenalty
Mach number
ML/
D
0.70 0.75 0.80 0.85 0.900
5
10
15
20
25
30
35
40BaselineSP trim-constrainedSP stability-constrainedMP trim-constrained
Mach number
CD
0.70 0.75 0.80 0.85 0.900.000
0.005
0.010
0.015
0.020
0.025
0.030
0.035
0.040
0.045
0.050BaselineCmCm/KnCm-CGCm/Kn-CGCm MP
Mach number
CD M
2
0.70 0.75 0.80 0.85 0.900.000
0.005
0.010
0.015
0.020
0.025
0.030
0.035
0.040BaselineCmCm/KnCm-CGCm/Kn-CGCm MP
Mach number
Ran
ge F
acto
r
0.70 0.75 0.80 0.85 0.900
5
10
15
20
25
30
35
40
45BaselineCmCm/KnCm-CGCm/Kn-CGCm MP
R =aM
cT
L
Dln
(W0 +Wfuel
W0
)
University of Toronto Institute for Aerospace Studies 2013 National Colloquium on Sustainable Aviation
Optimization Under Turbulent Flow
X/cC
p0.0 0.2 0.4 0.6 0.8 1.0
-2.0
-1.5
-1.0
-0.5
0.0
0.5
1.0
Y/b = 0.20
X/c
Cp
0.0 0.2 0.4 0.6 0.8 1.0
-2.0
-1.5
-1.0
-0.5
0.0
0.5
1.0
Y/b = 0.40
X/c
Cp
0.0 0.2 0.4 0.6 0.8 1.0
-2.0
-1.5
-1.0
-0.5
0.0
0.5
1.0
Y/b = 0.80
X/c
Cp
0.0 0.2 0.4 0.6 0.8 1.0
-2.0
-1.5
-1.0
-0.5
0.0
0.5
1.0
Y/b = 0.00
X/c
Cp
0.0 0.2 0.4 0.6 0.8 1.0
-2.0
-1.5
-1.0
-0.5
0.0
0.5
1.0
Y/b = 0.60
X/c
Cp
0.0 0.2 0.4 0.6 0.8 1.0
-2.0
-1.5
-1.0
-0.5
0.0
0.5
1.0
Y/b = 0.98
Baselinepressure profiles
Y/b0.00.20.40.60.81.0
Y/b0.0 0.2 0.4 0.6 0.8 1.0
0.05
0.10
0.15
0.20
L/Ltotal
Cp: -1 -0.8 -0.6 -0.4 -0.2 0 0.2 0.4 0.6 0.8 1
Center of gravityNeutral point
OptimizedCenter of gravityNeutral point
Baseline
Baseline and optimized surface pressure andspanwise lift distributions
X/c
Cp
0.0 0.2 0.4 0.6 0.8 1.0
-2.0
-1.5
-1.0
-0.5
0.0
0.5
1.0
Y/b = 0.20
X/c
Cp
0.0 0.2 0.4 0.6 0.8 1.0
-2.0
-1.5
-1.0
-0.5
0.0
0.5
1.0
Y/b = 0.40
X/c
Cp
0.0 0.2 0.4 0.6 0.8 1.0
-2.0
-1.5
-1.0
-0.5
0.0
0.5
1.0
Y/b = 0.80
X/c
Cp
0.0 0.2 0.4 0.6 0.8 1.0
-2.0
-1.5
-1.0
-0.5
0.0
0.5
1.0
Y/b = 0.00
X/c
Cp
0.0 0.2 0.4 0.6 0.8 1.0
-2.0
-1.5
-1.0
-0.5
0.0
0.5
1.0
Y/b = 0.60
X/c
Cp
0.0 0.2 0.4 0.6 0.8 1.0
-2.0
-1.5
-1.0
-0.5
0.0
0.5
1.0
Y/b = 0.98
Optimizedpressure profiles
University of Toronto Institute for Aerospace Studies 2013 National Colloquium on Sustainable Aviation
Turbulent Performance
AoA CM Kn L/D
Baseline 3.96 0.007 -15.6 10.3Optimized 2.98 0.000 -4.0 16.7
Drag reduction of 40% while creating
trimmed design
Wave drag eliminatedInduced drag reducedProfile drag reduced
Baseline
Optimized
University of Toronto Institute for Aerospace Studies 2013 National Colloquium on Sustainable Aviation
Conclusions
1 IntroductionMotivation
2 Blended-Wing-BodyDesign BenefitsDesign ChallengesRegional BWB Design
3 Aerodynamic Shape Optimization
4 OptimizationOptimization DefinitionOptimization Under Inviscid FlowOptimization Under Turbulent Flow
5 Conclusions & Future Work
University of Toronto Institute for Aerospace Studies 2013 National Colloquium on Sustainable Aviation
Conclusions & Future Work
Conclusions
Aerodynamic shape optimization is a powerful tool for dragreduction
High-fidelity aerodynamic shape optimization applicable tofull configuration optimization
Future Work
Aerodynamic shape optimization of an equivalenttube-and-wing design
Aerostructural optimization is required to demonstratefeasibility of regional jet BWB concept
University of Toronto Institute for Aerospace Studies 2013 National Colloquium on Sustainable Aviation
Questions
Thank You
Questions?
Financial support provided by:
University of Toronto Institute for Aerospace Studies 2013 National Colloquium on Sustainable Aviation