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

8

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

9

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

10

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

11

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

12

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,"

13

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

17

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

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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