Numerical DesignNumerical Design of Turbulent Wings for Small Aircraft · Aerodynamic design of Small Aircraft, Training Workshop, Prague, 18-19 March 2009 Planform of Selected Wing

Aerodynamic DepartmentInstitute of Aviation

Numerical DesignNumerical DesignNumerical Design of Turbulent WingsNumerical Design

of Turbulent Wingsgfor Small Aircraft

gfor Small Aircraft

Jerzy Żółtak

Aerodynamic design of Small Aircraft, Training Workshop, Prague, 18-19 March 2009

yWieńczysław Stalewski


Introduction

GOALS:

To develop a cost efficient methodologyf i ft / i d i d ti i tiof aircraft / wing design and optimisation.

To adapt the methodology to design processof AC1 and AC2 turbulent wings.

To design a turbulent wing for AC1 and AC2concepts of small aircraft, using MDO technique. The designed wing should fulfil as good as it is possible defined objectives and constraintsis possible defined objectives and constraints



Parametric Design and Optimisation

Designgn

em Environmental Objectives

De

ProDesign Variables

Des

igPr

oble Environmental

VariablesObjectives

& Constraints

esign oblem

to find optimal set of design variables definingal

G

to find optimal set of design variables defining optimal object (e.g. geometry of the wing)G

oa

Goal

Codes evaluating

Parametric model of Optimisationls

Toevaluating objectives

& constraints

model of optimised geometry

OptimisationmethodsTo

ol

ools



Methodology of Parameterisation (1)

Design Components

Design ParametersScalars describing Components

Scalars

Points

modifications of design components

Points

Curves (NURBS)

Surfaces (NURBS)

Set of Standard Actions

User Defined ProceduresSurfaces (NURBS)

Solids (NURBS)Library of Typical

Geometrical Procedures

Construction Algorithm

OBJECT GEOMETRY



Methodology of Parameterisation (1)

Airfoil (NURBS curve)Control Points

airfoil

forward swept wing

wing

helicopter rotor

air-intake



Parametric model of the aircraft / wing

Software implementation…

CODA3Dparam in house code ……… Two modes of work: I i d d i / difi h bj b h i Interactive mode: user designs/modifies the object by changing

values of design parameters, seeing the effects on the screen Batch mode: the code is executed automatically, usually called by

optimization code. In this case the input is the set of designvariables, the output is geometry of the wing/aircraft.

Speed: the geometry of parameterised object is generatedand visualized in real time.

Flexibility: the parameterisation may be easily customized, appropriatelyto given requirements. The design space may be both reduced g q g p yor expanded.

Export: the designed geometry of wing/aircraft may be exportedin different formats Particularly the smooth surface of the wingin different formats. Particularly, the smooth surface of the wingmay be exported in IGES format (readable by most of CADsystems). In presented work, the geometry of the wing was exported usually as the input data for codes evaluating objectives


exported usually as the input data for codes evaluating objectives and constraints.


Optimisation MethodsMultidisciplinary Optimisation

Multi-disciplinary , multi-objective formulation of the optimisation problem

i d d t d ti f th d i

Numerical Optimisation Di t

is recommended to decrease time of the design process.

pGenetic Algorithm

CODA3Dgenetics code I l i f l i

Direct Design

& OptimisationImplementation of: multi-

objectiveconstrained genetic

Based on designer experience

algorithm

Global search of optimal solutions across

the whole design space

“Manual” improvements and modifications of solutions obtained by


the whole design space numerical optimisation

Aerodynamic DepartmentInstitute of Aviation Multidisciplinary Optimisation

Optimisation Methods

CFD CSM+Aerodynamic load distribution along box-beam structure

Pressure distribution on aircraft surface Load [N/m]: 0 600 1200 1800 2400 3000 3600 4200 4800 5400 6000

Cp: -1.6-1.4-1.2 -1 -0.8-0.6-0.4-0.2 0 0.2 0.4 0.6 0.8 1

Bending moment distribution along box-beam structure

Bending Moment [Nm]: 0 20000 40000 60000 80000 100000

CODA3Dpanel3dbl: panel method coupled with boundary layer analysis (strong viscous-inviscid interaction)CODA3Dfps3dbl: solution of full potentialCODA3Dfps3dbl: solution of full potential equation coupled with boundary layer analysis (strong viscous-inviscid interaction)Coda3Dvlm2: Vortex Lattice Method taking into account viscous effects

Coda3Dstruct: structural analysis based on box-beam model. Evaluation of minimal weight of wing structure enable to keep aerodynamic loads.


into account viscous effects g p y


Evaluation of Objectives & Constrains

Direct Evaluation using codes:

Response Surface Methodologyg

CODA3Dpanel3dbl

CODA3Dfps3dbl

gy

Design of Experiment

ch: 2-ndCODA3Dfps3dbl

Coda3Dvlm2

Coda3Dstruct

Design of Response

SurfacesApp

roac

d ApproaSurfaces

1-st

ach:

Exact values Approximated valuesExact values of objectives &

constraints

Approximated values of objectives &

constraints

Optimisation methods



Methodology of Design & Optimisation

Design Variables

PARAMETERISATIONAutomatic Mode

OPTIMISATION: Genetic AlgorithmEnvironmental Variables

Wing / AircraftGeometryy

Analysis of physicalproperties

Objectives& Constraints

ParetoSetproperties & Constraints Set

DESIGN & OPTIMISATIONDirect Mode

Selection of the best solutions

PARAMETERISATIONInteractive Mode

Direct Mode

Wing / AircraftGeometry

Environmental Variables

Detailed analysisof physical properties

Final geometryof design cycle


of physical propertiesof design cycle


NumericalNumericalNumericalDesign of Turbulent

NumericalDesign of Turbulentg

Wing for Small Aircraftg

Wing for Small AircraftAerodynamic design of Small Aircraft, Training Workshop, Prague, 18-19 March 2009


AC1 Wi AC2 Wi

Design & Optimisation of Turbulent Wing (1)

AC1 Wing AC2 WingWing Segmentation Two Segments (Rolled Surfaces)

Aileron Segment Area – Fixed

Root Section Chord Fixed FixedAirfoil ILL518 ILM115

Middle Segment Chord Free Defined by mixing of root and tip airfoilsAirfoil Free

Tip Segment Chord Free FixedAirfoil ILL513 ILM111

Sweep Angle Free FixedSpan Free FixedSpar position [%chord] FixedSpar position [%chord] Fixed

Distribution of Twist Free FreeMean Line Free Free

line of 60% chord is V l f f l t kOther%

perpendicular to symmetry plane

Volume of fuel tank greater then fixed value

Number of Parameters 11 6


Definition of Basic Geometric Parameters


L L


maxLM CF c

cC D

LF w

wW W

LF Where:CLmax – maximum of CL for landing/take off conditionLC – lift of the wing at cruise condition, DC – drag of the wing at LCC g g CLW – global lift of aircraft for 2.5 g acceleration, WW – minimal weight of the wing structure enabled

to keep aerodynamic load at LW

Basic Design Points Objective Functions

Design & Optimisation Objectives

Basic Design Points Objective Functions

AC1 Wing Priority 1 (cruise)Priority 2 (landing/take off) FM, FC1 , FW1

AC2 WingPriority 1 (cruise)Priority 2 (cruise)Priority 3 (cruise)

FM, FC1 , FC2 , FW1


Priority 3 (cruise)Priority 4 (landing/take off)



Additionally some aerodynamic constraints were established.They expressed following requirements:They expressed following requirements:

pitching moment must be limited

lli i i stalling must not occur at wing tip

maximum of local Mach on the wing upper/lower surface must not exceed assumed limitssurface must not exceed assumed limits (for transonic design points)

Design & Optimisation Objectives

No geometrical constraints were established because all of them were taken into consideration within the parametric

d l f th i

g p j

model of the wing.



The objectives and constraints were calculated using


The objectives and constraints were calculated using cost effective, simplified in house codes:

CODA3Dfps3dbl - full potential solver coupled with boundary l l i (i l di fl ti )layer analysis (including flow separation)

CODA3Dpanel3dbl - panel method coupled with boundary layeranalysis (including flow separation)

CODA3Dstruct - structural analysis based on box-beam model

CODA3Dvlm2 - Vortex Lattice Method taking into accounti ff t ( ti ti f C )viscous effects (estimation of CLmax)

Additionally analysis were done also using commentarial codes:MSES - pre and post analysisMSES pre and post analysisFLUENT - post analysis

D i i l ti i ti i G tiDuring numerical optimisation using Genetic Algorithm (CODA3Dgenetics), objectives and constraints were evaluated by Direct Calculations


and Response Surface Methodology.


Numerical Numerical Design Design

of AC1 Turbulent Wing for Small Aircraft

of AC1 Turbulent Wing for Small Aircraftfor Small Aircraftfor Small Aircraft



Design & Optimisation of AC1 Turbulent Wing (1)

PARETO SETAC1T-IOA-01

Projection of on FM-FC space GENETIC ALGORITHMPopulation: 48

CLm

ax

Number of Generations: 300Number of Pareto-Optimal Solutions: 1093

L /D

SELECTION OF „THE BEST” SOLUTIONAssumed Priorities: 1) FC



L1/DW1

Projection of on FM-FW space Projection of on FW-FC space

) C

2) FM

3) FW

CLm

ax

L 2/W

W2 SELECTED

WINGL

AC1T-IOA-01


L2/WW2 L1/DW1



TwistCamber of Mean LineThickness

ST

[deg

]

NE

SS

[%c]

LIN

E[%

c]

Δ=1

TWIS

THIC

KN

ME

AN

Δ=0.5Δ=1

Eta0 0.2 0.4 0.6 0.8 1

Eta0 0.2 0.4 0.6 0.8 1

Eta0 0.2 0.4 0.6 0.8 1

Geometrical Properties of Selected Wing AC1T-IOA-01Geometrical Properties of Selected Wing AC1T-IOA-01

AC1T-IOA-01AC1T-BASELINE


Planform of Selected Wing AC1T-IOA-01



Cruise Flight Conditions

The Pitching MomentThe Drag PolarCruise Flight Conditions

)


Cruise Flight Conditionsm

2 ]


Cruise Flight Conditions

Δ=0.2 Δ=0.01

Δ=0.1Δ=5

Cm

(Win

g)

CD

(win

g)·S

[m

crui

se

limit of pitching moment

CL (Wing)

Conditions of optimization:

CL (aircraft)·S [m2]

Conditions of optimization: Minimum drag at cruise design point Minimum pitching moment related to wing aerodynamics

centre in cruise configuration


g Pitching moment coefficient for CL= 0 limited



The Maximise Lift Coefficient

Referencemaximumliftcoefficient

CL (aircraft)CL (wing)

Δα=2

Δ=0.2

Δ=0.2

Δα=2

AC1T-IOA-01

LowSpeed, ISA, SL

AC1T-IOA-01

LowSpeed, ISA, SL

AngleofAttack

AC1T-BASELINE

AngleofAttack

AC1T-BASELINE

Aerodynamic Properties of the AC1T-IOA-01 Wing


y p g



Initial stalling calculated using

separation

Initial stalling calculated using CODA3Dpanel3dbl

(panel method coupled with boundary layer analysis)

+

1

+ 2 + 3

IN

IT

IN

IT

IN

IT +

IN

IT +




Design & Optimisation of AC1 Turbulent Wing (6)High Lift System

CRUISEFlap deflection =0 deg Two end-sections of flap zone

were selected to 2D design of

Y=985 mm TAKE-OFF

high lift system.For both sections the Fowler type flap was designed by

Y=5195 mmY=985 mm TAKE OFF

Flap deflection =15 deg adaptation of ILL518 high lift systemThe following deflections of the

Y=5195 mmY=985 mm

LANDINGFlap deflection = 35 deg

gflap were chosen:

TAKE-OFF: 15 degLANDING: 35 degLANDING: 35 deg

The 2D optimisation of gap and overlap (flap position) for selected sections is in the

Y=5195 mmY=985 mm

selected sections is in the progress.

High Lift System for AC1T-IOA-01 Wing


High Lift System for AC1T-IOA-01 Wing


Numerical Numerical Design Design

of AC2 Turbulent Wing for Small Aircraft

of AC2 Turbulent Wing for Small Aircraftfor Small Aircraftfor Small Aircraft




PARETO SETAC2T-IOA-08Projection of on FC1-FM space GENETIC ALGORITHM

Population: 380L 1/D

W1

Number of Generations: 180Number of Pareto-Optimal Solutions: 2559

Pareto Set evaluated using RSMg

SELECTION OF „THE BEST” SOLUTIONAssumed Priorities: 1) FC1



CLmax

Projection of on FC2-FM space Projection of on FW-FM space2) FC2

3) FM4) FW

L 3/W

W3

L 2/DW

2 SELECTED WINGL

AC2T-IOA-08


CLmaxCLmax



Thickness Camber of Mean Line Twist

Δ=1

KN

ES

S[%

c]

NLI

NE

[%c]

WIS

T[d

eg]

THIC

K

ME

AN

TW

Δ=1Δ=0.4

Eta0 0.2 0.4 0.6 0.8 1

Eta0 0.2 0.4 0.6 0.8 1

Eta0 0.2 0.4 0.6 0.8 1

Eta Eta Eta

Geometrical Properties of Selected AC2T-IOA-08 Wing




The Moment CoefficientThe Drag Coefficient

CODA3Dfps3dblFLUENT required CLmax

CODA3Dfps3dblFLUENT

tcoe

ffici

ent required CLmax

ΔC 0 2

CLCL

g

tchi

ngm

omen

t

effic

ient

ΔCL=0.2ΔCL=0.2

ΔCm=0.1ΔCD=0.002

required CLmax

CL rangerequired CLmax

limit

ofpi

t

CL range

ngm

omen

tcoe

CL range

C i P i it 1

CODA3Dfps3dblFLUENT

C i P i it 2 C i P i it 1

CL rangeCODA3Dfps3dblFLUENT

C i P i it 2

limit

ofpi

tchi

n

C C C CCruise Priority 1 Cruise Priority 2 Cruise Priority 1 Cruise Priority 2CD CD Cm Cm





The Maximise Lift CoefficientThe Maximise Lift Coefficient

required CLmax (Wing)

CL (wing)

ΔCL=0.2

Δα = 2

AC2 aircraft - CODA3Dpanel3dblisolated wing CODA3Dvlm2

Low Speed Priority 4

α[°]


isolated wing - CODA3Dvlm2α[°]



Aerodynamic DepartmentInstitute of Aviation 1.4

M=0.716, H=31000 ft M=0.716, H=31000 ftPriority 1 CruisePriority 1 Cruise


Aerodynamic Properties of the AC2T-IOA-08 Wing 1.0

1.2Priority 1 CruisePriority 1 Cruise

M

0.6

0.8

Pressure distribution on wing at selected section and different value of lift 0 0

0.2

0.4 CL=0.16CL=0.23CL=0.35

y/ymax = 0.10

CL=0.16CL=0.23CL=0.35

y/ymax = 0.40

minmaxexp

minmaxexp

and different value of lift coefficient

0 0M=0.716, H=31000 ft

1 0

1.2

1.4M=0.716, H=31000 ft

Priority 1 Cruise Priority 1 CruisePriority 1 CruisePriority 1 Cruise

M

0 6

0.8

1.0

CL=0.16CL=0.23CL=0.35

0.2

0.4

0.6

CL=0.16CL=0.23CL=0.35

minmaxexp

minmaxexp


y/ymax = 0.900 0

y/ymax = 0.70


Design & Optimisation of AC2 Turbulent Wing (6)1.4

M=0.610, H=41000 ft1.4

M=0.610, H=41000 ftPriority 2 Cruise Priority 2 Cruise

Aerodynamic Properties of the AC2T-IOA-08 Wing 1.0

1.2

1.0

1.2Priority 2 Cruise Priority 2 Cruise

M

0.6

0.8

M

0.6

0.8

Pressure distribution on wing at selected section and different value of lift

0.2

0.4 CL=0.33CL=0.49CL=0.75

y/ymax = 0.400.2

0.4 CL=0.33CL=0.49CL=0.75

y/ymax = 0.10

minmaxexp

minmaxexp

and different value of lift coefficient

1.2

1.4M=0.610, H=41000 ft M=0.610, H=41000 ft

0 00 0

Priority 2 CruisePriority 2 Cruise

M

0.8

1.0

0 2

0.4

0.6

CL=0.33CL=0.49CL=0.75

CL=0.33CL=0.49CL=0.75

minmaxexp

minmaxexp

Aerodynamic design of Small Aircraft, Training Workshop, Prague, 18-19 March 20090 0

0.2y/ymax = 0.70 y/ymax = 0.90


Initial stalling calculated using


separation

Initial stalling calculated using CODA3Dpanel3dbl

(panel method coupled with boundary layer analysis)

separation

T T +

2

T +

4

IN

IT

IN

IT

IN

IT




Conclusions

The cost efficient methodology of aircraft / wing d i d ti i ti d l ddesign and optimisation was developed.

The methodology was adapted to specific design process of AC1 and AC2 t rb lent ingdesign process of AC1 and AC2 turbulent wing.

The MDO technique was applied to designa turbulent wing for AC1 and AC2 concept of small aircrafta turbulent wing for AC1 and AC2 concept of small aircraft.

The final results of performed design process are the wings AC1T-IoA-01 and AC2T-IoA-08 respectivelyAC1T-IoA-01 and AC2T-IoA-08 respectively. The designed wing fulfils most of defined objectives and constraints.





Methodology of Parameterisation

P t 1Parameter 1

eter

2Pa

ram

e


Example: Two-Parametric Family of Air-Intakes

Documents

Numerical DesignNumerical Design of Turbulent Wings for Small Aircraft · Aerodynamic design of Small Aircraft, Training Workshop, Prague, 18-19 March 2009 Planform of Selected Wing