further analysis of multidisciplinary optimized metallic and composite...
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FURTHER ANALYSIS OF MULTIDISCIPLINARY OPTIMIZED METALLIC AND COMPOSITE JETS
Antoine DeBloisAdvanced Aerodynamics Department
Montreal, Canada
6th Research Consortium for Multidisciplinary System Design Workshop Ann Harbor, MichiganJuly 26th – 27th 2011
2
Presentation Plan
Theoretical Framework
Disciplinary modulesHigh-Speed AerodynamicsLow-Speed AerodynamicsSubspace Structural Optimization
Metallic WingboxComposite Wingbox
MDO results of a Business jet
Analysis of the final designs
Conclusion
3
Current MDO Ingredients
Multi-Disciplinary Optimization
StructuresStructures
SystemsSystems
AerodynamicsHigh-speedLow-speed
Icing
AerodynamicsHigh-speedLow-speed
Icing
OptimizerOptimizer
MaterialsMaterials
Composite
Metal
LoadsLoadsKEAS
VD
VCVA
2.5
Load factor
KEASVD
VCVA
2.5
Load factor
Mission Requirements
Mission Requirements
High-Performance Computing
High-Performance Computing
Sector Distance
Flight Time & Fuel
Block Time & Fuel
En route Climb
Descent
Approach &Landing
1500 ft
Initial Cruise
Step Cruise
Takeoff &Initial ClimbStart-up
&Taxi-out
Taxi-in
4
Conflicting Requirements
Design Variable
Aerodynamics High-Speed
Aerodynamics Low-Speed Structures Systems Buffet
Loads & Dynamics
Spanload
OUTBOARD INBOARD INBOARD INBOARD CASE DEPENDANT
Thickness distribution LOW HIGH HIGH LOW CASE
DEPENDANT
Leading edge thickness
THIN THICK THICK THICK CASE DEPENDANT
Span HIGH LOWCASE
DEPENDANT
Sweep HIGH LOW LOW HIGHCASE
DEPENDANT
DISCIPLINES
5
Optimization Challenges
Aerodynamics and Structural optimization differ in terms of scope
Need to develop an MDO architecture that suits every disciplinesBi-level formulation
[1] Metallic Wingbox[2] Aero: Transonic small Disturbance code, KTRAN; Structure: Full 3D FEM, NASTRANTM
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SUBSPACE OPTIMIZATIONMin Wstruct
w.r.t t’s, h’ss.t. 0.0.SM
criticalmax ,CL
0
1
2
3
4
5
6
7
8
0 100 200 300 400
span (in)
Twis
t (de
g)fuelW
CL
MOPTIMIZER
min
w.r.t Planform, Profiles
f
strucWu
DESIGN CASES
BUILD / UPDATE SOLVESTRUCTURAL FEM
AERODYNAMIC SOLVER
SPANLOAD
- TWIST
- CAMBER
HIGH-SPEED CFDSTRUCTURES
UPDATE GEOMETRY
LOW-SPEED CFD
MULTI-OBJECTIVECONSTRAINTS
MULTI-OBJECTIVECONSTRAINTS
VALAREZO CHECK
LOW-SPEED PRESSURES
i i
ii
sOBJw
FIELD PERFORMANCE
FLIGHT PERFORMANCE
METAL / COMPOSITE
MATERIALS
FUEL VOLUME
7
High-Speed Aerodynamics
MDO environment is linked to CFD code KTRAN
Solved modified Transonic Small Disturbance, TSD, equationsEmbedded cartesian grid generation
Despite low-order formulation:KTRAN provides accurate pressure distribution and Aerodynamic loadsEnables full aircraft configurations including engine, winglet, H-tail and nacellesComputes accurate drag with a mixture of semi-empirical and CFD-based routines
KTRAN allows trimming of aircraft, hence
Symmetrical maneuvers
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High-Speed Aerodynamics:CFD challenges
Challenger CL-601Cruise : Mach 0.82, = 1.5º
n
KEASVD
VC
VA
2.5
-1.0
1.0
Dive:Mach 0.90, CL = 0.45 (2.5g)
n
KEASVD
VC
VA
2.5
-1.0
CFD remains a challenge at the edges of the flight envelope due to:
Mach close to 1.0 ( )
Possible flow separation
Large deformations
07.0mod MM
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LOW-SPEED AERODYNAMICS
Traditionally, manual iterations alter the high-speed optimized design to meet low-speed requirements
Lengthy processFinal design not guaranteed to be true optimum
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Alpha (deg)
Lift
Coe
ffici
ent (
CL)
Pitc
hing
Mom
ent C
oeffi
cien
t (C
M)
LOW-SPEED REQUIREMENTS
Inboard stall
Stall
Lift curve
Cfx over the wing
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Alpha (deg)
Lift
Coe
ffici
ent (
CL)
Pitc
hing
Mom
ent C
oeffi
cien
t (C
M)
SLAT-LESS DESIGN:LOW-SPEED REQUIREMENTS / OBJECTIVES
stall
max LC
[1] Valarezo, et al., “Maximum Lift Prediction for Multi-element Wings" 30th Aerospace Sciences Meeting and Exibit, 1992.
outbdTEstallTE CpCp max
[1]reqMAXCLEANMAX CLCL __
MAXCL
warningstall maxcrit
reqcritcrit _
sw
bucket max
stall
min MC
DTO icing conditions
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Low-Speed Aerodynamics
AUTOMATIC VSAERO1
DLR F-6 Isolated wing
FANSC2
DLR F-6 Wing-body
10 sec (1 CPU)
94 min ! (32 CPU’s
P5-575)
An automatic isolated wing VSAERO mesh generator
[1] Analytical Methods, Inc., A Code for Calculating the Nonlinear Aerodynamic Characteristics of Arbitrary Configuration[2] Full Airfcraft Navier-Stokes Code, Laurendeau, E., “Development of the FANSC Full Aircraft Navier-Stokes Code,"
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Low-Speed Aerodynamics
AUTOMATIC VSAERO1
DLR F-6 Isolated wing
FANSC2
DLR F-6 Wing-body
An automatic isolated wing VSAERO mesh generator
[1] Analytical Methods, Inc., A Code for Calculating the Nonlinear Aerodynamic Characteristics of Arbitrary Configuration[2] Full Airfcraft Navier-Stokes Code, Laurendeau, E., “Development of the FANSC Full Aircraft Navier-Stokes Code,"
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StructuresAWSOM[1] automatically generates a 3D FEM
All principal Structural Elements are modelizedThe FEM methodology is the same as the one used for certification models
[1] DeBlois, A, et al., AIAA 2010-9191, 13th AIAA/ISSMO Multidisciplinary Analysis Optimization Conference
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Structures module:Load transfer
gnnqSCL L 0.1
BALANCED MANEUVER
LANDING
Ref BM7015.01.03
Whole Flight envelope to be analyzed: Speed, altitude and weight
W(envelope)
gnnqSCL L 5.2
RLOOP
W(envelope)
BALANCED MANEUVER
CL = 2.5g
W = MTOW
M = Md
CL = -1.0g
W = MTOW
M = Mc
CL = 1.0g
W = MLW
V = Va
WL
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Optimization procedure is decomposed into:Multiple, Sequential;Reduced scope;
Skin-stringer panels are Geometrically dependant chord-wiseGeometrically independent span-wise (different for composite …)
Algorithm:MPI_LoadBalance();for rib = 0 Number of rib bays
for str = 0 Nstr[rib]-1Optimize Skin w.r.t skin constraints
end loop strfor str = 0 Nstr[rib]
Optimize Stringer w.r.t skin-stringer constraintsend loop str
end loop rib
Structures module: Wing Box Sizing Procedure
ribrib + 1
rib - 1
AA
Section A-A
CPU
CPUCPU
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Wing Box Sizing Program:Composite vs Metallic
Optimized CompositeOptimized MetallicWsk-str = 7.603 lbs Wsk-str = 4.401 lbs
Same applied loads
Same boundary conditions
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DLR F-6 Wingbox Weight and Stiffness Comparison
Assumed StructuralLayout
Bending Stiffness Comparison Torsional Stiffness Comparison
Structural Weight Comparison
Assumptions:• MTOW = 100, 000 lbs
• MZFW = 60, 000 lbs• No applied gear loads
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MDO Application on a Business Jet
Problem statement: Flight and Field performance Optimization of a business jet aircraft through:
Optimization of the wing planform shape;Wing sectional profiles;Optimization of the wing-box structure
The MDO environment is ISIGHT™
Decomposition method is used:
Lower Bound
Upper Bound
Win
g Se
ctio
nal
airfo
ils 13 shape function parameter for each airfoil (x 7 airfoil)
-1.0 3.0
Wing Aspect Ratio 5.5 8.0
Wing Leading edge sweep 32.0 o 40.0 o
Root Trailing edge sweep 0.0 o 15.0 o
Wing Taper Ratio 0.10 0.30
Spanwise Break Location 0.28 0.37
Wing Reference Area 180000.0 191000.0
Analytical Descriptor
Win
g Pl
anfo
rm
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Objective Function
Objective function analysed:
Maximize CLmax
MTOW Scaling Factor CLmax Scaling Factor
Minimize MTOW
CLmax Weighting FactorMTOW Weighting Factor
0.150.0
1000050.0 maxCLOBJ mass
[1]
[1] The purpose of the objective function chosen is to validate the MDO setup, but does not reflect an actual wing design formulation
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Metallic MDO results
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“Pareto” front post-processed
Initial Point
Mas
s Fue
l
CLMAX
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Pressure Coefficient Comparison
INITIALMid Cruise flight conditions:
• MACH = mid-cruise
• CL = mid-cruise
24
Pressure Coefficient Comparison
INITIALMid Cruise flight conditions:
• MACH = mid-cruise
• CL = mid-cruise
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Composite MDO results
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Analysis of final design:Stall characteristics
Outboard stall
Stall margin inexistent
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Analysis of final design:Sensitivity to contamination
Optimization formulation:Min CLclean-DTO
s.t CLmax CLmax_ini
w.r.t 2D Leading edge
Results:CLclean-DTO reduced by 29%
Conclusion:There exist profiles that yield the same CLmax, with less sensitivity to contamination
Clean characteristics
Wing Design
Contaminated characteristics
CLiniCLopt
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Initial cruise Mid Cruise Final Cruise
Drag Rigid Drag elastic
Analysis of final design:Aeroelastic effect on drag
Jig
Initial
Mid
Final
0.5%
DE
SIG
N P
OIN
T
Drag underestimated
Drag overestimated
Therefore, jig twist design allows proper aeroelastic twists at any condition, thus optimal off-design performance
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Analysis of final design:Aeroelastic effect on structural weight
3141.49
3065.48
Weight Rigid Weight ElasticSt
ruct
ural
Wei
ght (
lbs)
2.5% over estimated
CL
Wing deformed shape @ 2.5g
Cl*c
/Cav
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Conclusion
An industrial multi-fidelity MDO framework was presentedAllows to compute the best compromise between
High-speed AerodynamicsLow-speed AerodynamicsStructureMaterial choice
A DLR F-6 was sized and composite wingbox shown to be:20% lighter compared to metallic wingbox
MDO results were presented on a generic business jet:Composite structures allows
lighter designsbetter Aerodynamics characteristics
Manufacturing constraints were ignored for composites, which gave them an unfair advantage
Blending on stacking sequence typically increases weight
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Final thoughts
The design obtained from MDO process is not final
The framework has some inherent assumptions and simplifications that force the engineer to fine tune the optimized design
Nonetheless, the simplifications do not invalidate the design
MDO does not replace the job of experienced engineers
Future work:Improve the fidelity of the CFD codeIntroduce stall progression characteristics (slat-less and slat designs)Introduce icing contaminationIntroduce manufacturing constraints for composite design
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Questions ?
Acknowledgements:
• Cedric Kho
• Awot Berhe
• Temesgen Mengistu