Optimization of Hybrid Wingbody Aircraft Meng

Report
National Aeronautics and Space Administration
Optimization of
Hybrid Wingbody Aircraft
Spring Progress in Mathematican and Computational Studies
on Science and Engineering Problems
May 3-5, 2014, National Taiwan University
Meng-Sing Liou
NASA Glenn Research Center
A Tribute
A cumulative effort, by postdocs and students under various
NASA programs, developing and piecing together a set of
necessary elements for performing MDAO.
•
•
•
•
•
•
•
•
•
Akira Oyama
Hyoungjin Kim
Byung Joon Lee
Justin Lamb
Angelo Scandaliato
Nick Stowe
Weigang Yao
Mattia Padulo
May-Fun Liou
• SFW, SUP
• NASA Postdocs
Program
• NASA USRP
Knowledge
Capabilities
Applications
NASA’s Technology Development Goals
Current Commercial Aircraft
Hybrid Wingbody vs Current Aircraft
N2-B
Tube and wing
Hybrid (blended) wingbody
• Pros: lighter weight, higher lift to drag ratio, and lower fuel burn,
reduced community noise
• Cons: aerodynamic interferences may reduce aerodynamic
performance, propulsive efficiency and structural tolerance to distortion
• A complex system requires simultaneous consideration of of multiple
disciplines and design objectives
Historical Development of HWB Vehicles
Northrop YB-35, 1946
Northrop YB-49, 1947
Northrop Gruman B-2, 1989
Airfoil: NACA 65-019 root, NACA 65-018 tip
Historical Development of HWB Vehicles
Boeing UAV X-48, 2007
Boeing UCAV X-45C, 2002
Burnelli CBY-3, 1955
Commercial Transport ???
Dassault nEUROn, 2012
Hybrid Wingbody Aircraft – N3-X
• HWB (hybrid wing body) configuration for N+3 requirements
• Turboelectric Distributed Propulsion
–
–
–
–
Embedded fans driven by electric motors in a mail-slot nacelle
Wingtip mounted superconducting turbo-generators
Decoupling of generator and motor speeds
Ingestion of upper surface boundary layer
• Expected to reduce fuel burn by more than 70% relative to
Boeing 777-200LR
Kim, H. and Liou, M.-S., AIAA-2013-0221.
Fuel Efficiency and Noise Data
Fuel Efficiency=
nmi x
payload/range
Nmi x Payload / Fuel Burned
Fuel Efficiency Comparison
7000
6000
5000
B747-8
B777F
4000
B747-400ERF
A330-200F2
26%
B767-300F
Current
B747-400F
B767-300ER
Best Current
A330-200F2
A330-500FX
B777-200ER
3000
N2A
A330-300
2000
N2B
1000
N2A-EXTE
0
0
100
200
300
400
Payload (1000 lbs)
Expected
improvement by 26%
Noise Relative to FAR 36 Stage 3
Table 21
N2A-EXTE FAR-36
assessment.
Table 21noise
N2A-EXTE
FAR-36 noise assessment.
But …
FPR=1.4
FPR=1.5
FPR=1.6
FPR=1.4
FPR=1.7
FPR=1.5
FPR=1.6
FPR=1.7
mulative EPNdB with elevon noise
242.4
Cumulative EPNdB with elevon noise
246.9
251.0
242.4
256.5
246.9
251.0
256.5
mulative EPNdB without elevon noise
233.5
Cumulative EPNdB without elevon
noise
239.3
244.3
233.5
252.0
239.3
244.3
252.0
250.4
250.4
250.7
250.4
250.4
250.4
250.4
dB Margin with elevon noise EPNdB Margin with elevon noise
-8.3
-3.5
+0.6
-8.3
+6.1
-3.5
+0.6
+6.1
dB Margin without elevon noise
EPNdB Margin without elevon-17.2
noise
-11.1
-6.1
-17.2
+1.6
-11.1
-6.1
+1.6
Goal
N+2 Goal
250.7
Challenges
• Integration of propulsion and airframe
– Inlet ingesting thick boundary layer, resulting in a
considerably distorted flow with total pressure
loss at the compressor face
– Significant loss in aerodynamic performance
resulting from their mutual interferences
HWB Configurations Studied by NASA
Boeing UAV X-48, 2007
N2-B
N2-A
N3-X
Outline of Presentation
• Integrated Configuration
• Mitigation of inlet flow distortion and loss of
propulsive efficiency
• Aerodynamic analysis and optimization for N2-B and
N3-X
Flow Features in Embedded
Boundary Layer Ingestion (BLI) Inlet
N2-B
Advantages:
Reduced ram drag
Reduced structural weight
Reduced wetted area
Reduced noise
Increased propulsive efficiency
Pt/P
Hybrid Wing Body Aircraft: N2B
Hybrid wingbody
Boundary-Layer Ingestion
Forces:
Viscous stresses
Streamwise adverse pressure gradient
Centrifugal force
Impact on Propulsion System:
Thick low-momentum layer ingested into inlet,
 Significant distortion and
Horseshoe vortex,
Lip flow separation
 Total pressure loss at AIP
S-bend separation,
Secondary flow
Non-uniform flow
at AIP
BLI Inlet
Vortex generator
Wall bleeding
Allen et al.
Taming Distortion and Losses in BLI Inlets
• Alternative way to conventional
flow control, without incurring
system losses.
• Shape optimization: properly
conditioning the flow before it
entering the inlet.
Yu the Great – Xia Dynasty
Design Optimization: Problem Statement
• Design Formulation
Minimize : DPCPavg
Subject to :
zi £ z L
zi : z coordinate of ith control point
zL : limit of design variable (10% of Inlet Height)
• Design Condition
• M0=0.85, Re0=3.8mil., A0/Ac=0.533
• BL thickness : 35% of Inlet Height
• Design Variables
• Control Points on the NURBS Patch, -1.8 £ x/D £ 0.5
Liou, M.-S. and Lee, B. J., “Minimizing Inlet Distortion for Hybrid Wing Body Aircraft,” ASME
J. Turbomachinery, Vol. 134, #3, 2012.
Lee, B. J. and Liou, M.-S., “Optimizing Shape of Boundary-Layer-Ingestion Offset Inlet
Using Discrete Adjoint Method,” AIAA J. Vol. 48, No 9, 2008-2016, 2010.
Detailed Flow Structures: Near Inlet Throat
Y/D=0.5 Plane
flow separation at lip
 Eliminated lip flow separation
 Establishing a global pressure field,
resulting in flow acceleration
Performance at Off-design Conditions
• Simultaneous improvements in total pressure
recovery and distortion
• Superior performance is maintained by the
optimized design at all off-design conditions
Oil Flow Patterns at Off-Design Conditions
Baseline Model
A0/Ac=0.533
A0/Ac=0.506
A0/Ac=0.401
Optimized Model
A0/Ac=0.557
A0/Ac=0. 523
A0/Ac=0. 423
Inlet-fan Coupling
• Mitigate deficiency in traditional specification of
outflow pressure condition for assessing the inlet
performance
• Direct coupling of, hence specification by the fan
operating condition
• Need for fan flow analysis
– Full-scale simulation
– Reduced-order modeling
Reduced-order Model for Fan Flow
• R4 Fan—1/5-scaled model tested in NASA Glenn Research Center, 22 in.
diameter and 22 blades
• Reduced-order model built based on the CFD solutions
1.38
Fan test data [Hughes]
0.045
Swift
1.36
Euler + body force
0.04
Euler + body force
0.035
1.34
del_S / R
Fan pressure ratio
0.05
Fan test data [Hughes]
1.32
1.30
0.03
0.025
0.02
0.015
1.28
0.01
0.005
1.26
35
36
37
38
39
40
41
42
Corrected mass flow (kg/s)
43
44
45
0
35
37
39
41
Corrected mass flow rate (kg/s)
43
45
The Need for Analyzing Integrated Configuration
Propulsion Model for N2-B
mi = fm (hi ) , Tt i = ( constant )i , i = 1,2,3
Pt i = f pi (hi ) , i = 1,2,3
f p2 = f p 3
Effects of Propulsion System Installation
Impacts on
Flowfield and Aerodynamic Performance
Inlet Performance
Outer inlet
Center inlet
0.99
X=0.718
X=0.777
Recovery
0.98
0.97
0.96
0.95
X=0.740
X=0.800
0.94
0.93
0.92
AIP1
AIP2
AIP3
AIP4
AIP5
AIP1
AIP2
AIP3
AIP4
AIP5
Present simulation
0.9650
0.9758
0.9644
0.9401
0.9553
Boeing estimation
0.9671
0.9751
0.9671
N/A
N/A
Design Optimization
• Nacelle geometry
• Minimize drag, and
• Minimize distortion
Drag Minimization
0.35
Clean wing
0.30
CL
N2B
0.25
Design 1
0.20
Design 2
0.15
0.10
0.05
0.00
1.0
-0.05
1.5
2.0
2.5
3.0
AOA (deg)
3.5
4.0
4.5
5.0
Distortion Minimization
X=0.718
X=0.740
AIP1
AIP2
AIP3
X=0.718
X=0.740
AIP1
AIP2
AIP3
N3-X
• Turbo-electric distributed propulsion (TeDP)
• Targeted benefits: fuel burn savings by 70% relative to Boeing
777-200LR, M=0.84
Why Electric Propulsion
• Exhaust of current
airplanes, CO2, NOx,
particulates, …
contributes climate
changes
• Noise mitigation
• Allowing solar energy as
power source
Solar Impulse II
Fan Model
Clean inflow + R4 ( Exp) [Hughes]
1.54
0.95
Clean inflow + R4 (Body force)
Inlet A + R4 (full CFD) [Webster et al.]
1.52
Stage adiabatic efficiency
1.48
1.46
1.44
0.90
0.85
0.80
1.42
Clean inflow + R4 (Exp) [Hughes]
0.75
Inlet A + R4 (Body force)
1.40
1.38
38
40
42
44
46
0.70
48
38
Corrected mass flow (kg/s)
40
42
44
Corrected mass flow (kg/s)
100%
0.05
95%
0.045
0.04
87.5%
0.035
del_S / R
Fan pressure ratio
Inlet A + R4 (Body force)
1.50
77.5%
0.03
70%
0.025
60%
0.02
50%
0.015
0.01
0.005
0
15
20
25
30
35
corrected mass flow rate (kg/s)
40
45
50
46
48
Flowfield near and inside the propulsion system
Symmetry
place
Centerplane
of Outermost
passage
Propulsion Performance
1.00
1.45
Clean inflow CFD (SWIFT)
0.90
1
0.85
Fan pressure ratio
Fan efficiency
0.95
8
0.80
0.75
0.70
Clean inflow CFD (SWIFT)
0.65
Installed on N3-X
120
130
140
150
Corrected mass flow rate (kg/s)
Installed on N3-X
1.35
1.30
1
1.25
8
1.20
0.60
110
1.40
160
1.15
110
120
130
140
150
Corrected mass flow rate (kg/s)
160
Design by Drag Minimization
Baseline
Optimized
Concluding Remarks & Outlook
• Using high fidelity analysis and optimization in early design
phase can reveal areas of importance and shed insight on
technological challenges.
• Have discovered an effective way to improve inlet
performance, without sacrificing system efficiency.
• Geometry, geometry, geometry …
• MDAO has received considerable emphasis, developed
fast, and its future for prime time is very promising.
Leonardo di ser Piero da Vinci
April 15, 1452~May 2, 1519, Florence, Italy
http://www.solar-impulse.com/
http://www.youtube.com/watch?feature=play
er_embedded&v=FWvgpngKIW4
Keep up your dream,
Look up to those pioneering dreamers, and
Follow their spirits.
Thank you for your attention and
Best wishes!

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