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Arning-Scalabilty of Model Flight Test Results

Oct 08, 2015

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Mitchell Goez

Scalability of RC aircraft
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  • Page 1 Microsystems & Electronics; Optronic Systems & Signal Processing

    Scalability of Model Flight Test ResultsR. Arning

    DGLR-Workshop on System Identification, Parameter Estimation and Optimisation

    Ottobrunn, June 9th, 2005

    Ingenieurbro Dr. Richard K. Arning

  • Page 2 Microsystems & Electronics; Optronic Systems & Signal Processing

    Overview Overview

    Motivation of scaled model flight testing

    Applicability of method

    Quality influences

    Results

  • Page 3 Microsystems & Electronics; Optronic Systems & Signal Processing

    Applicability of methodApplicability of method

    Quality and relevance vs. model size ?

    X-38ALFLEX

    F-18

    X-33NASA

    NASA

    NASA

  • Page 4 Microsystems & Electronics; Optronic Systems & Signal Processing

    Motivation of scaled model flight testingMotivation of scaled model flight testing

    Advantages:

    Full set (6-DOF) measurement of dynamic derivatives

    No wind tunnel / sting mounting interference

    Early flight data

    Low cost

    Low risk

  • Page 5 Microsystems & Electronics; Optronic Systems & Signal Processing

    Applicability of methodApplicability of method

    Regions of constructional realisation for dynamically scaled models below 200 N MTOW and 200 N/m2 wing loading

    0

    20

    40

    60

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    G[N

    ]

    1 2 3 4 5Spannweite [m]

    Segelflzg.

    Motorsegler

    Raumflzg.

    0

    20

    40

    60

    80

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    1 2 3 4 5Spannweite [m]

    Segelflzg.

    Motorsegler

    Sportflzg.+Transportflzg.

    Verkehrsflzg.

    Glider

    SailplaneMotor GliderGeneral Aviation

    Spaceplane

    Airliner

    Span [m]

    W

    e

    i

    g

    h

    t

    [

    N

    ]

    Limit for airliner models due to extreme high wing loading;

    In general: To small Reynolds numbers

    Wing loading for fighter aircraft models above limit

  • Page 6 Microsystems & Electronics; Optronic Systems & Signal Processing

    Applicable to aircraft:

    with relative low relative mass ratio:

    at low speeds (uncompressible flow)

    with acceptable chord length at scale sized (wing, tail)

    Applicable to general aviation and below category aircrafts &

    space planes during take-off and landing phase

    NOT applicable: In stall region and for performance testing

    Applicability of methodApplicability of method

    bSm

    =

    ))original

    1

    altitude original

    altitude model

    5,1

    original

    modelmodel ReRe

    =

    ll

    ))

  • Page 7 Microsystems & Electronics; Optronic Systems & Signal Processing

    RS 180 Sportsman1:4,8-scale

    Tail-Spin testing Tail-Spin testing

    Speed Canard1:4-scale

    MS 893 Morane1:4-scale

    ELAC1:31.3-scale

    ASK-211:3-scale

    PHOENIX1:7-scale

    System identification of winglets influence

    System identification(closed and open loop)

    Proof-of Concept /Engine failure characteristics

    System identification of airbrakes influence

    TT-621:5-scale

    Applicability of methodApplicability of method IngenieurbroDr. Richard K. Arning

  • Page 8 Microsystems & Electronics; Optronic Systems & Signal Processing

    scale center of gravity

    dynamically scaled mass m

    dynamically scaled moments of inertia I

    dynamically scaled control system (if relevant)

    quality of sensors and calibration (integrated), redundancy of sensor information

    additional external equipment (e.g. nose-boom)

    simplification of aerodynamic model

    coverage of flight envelope and maneuvers by recorded flight data

    Quality influencesQuality influences

    *lr

    *lplll0ll rCpCCCCCC +++++=

  • Page 9 Microsystems & Electronics; Optronic Systems & Signal Processing

    Sensors and data acquisition system

    Telemetriebodenstation

    Quality influencesQuality influences

  • Page 10 Microsystems & Electronics; Optronic Systems & Signal Processing

    Quality influencesQuality influences

    Sensors and data acquisition system

  • Page 11 Microsystems & Electronics; Optronic Systems & Signal Processing

    Sensors and data acquisition system

    Quality influencesQuality influences

    150

    200

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    K

    [

    P

    a

    /

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    ]

    D

    -12.0 -8.0 -4.0 0.0 4.0 8.0 12.0

    []

    = -5 = 0 = 5

    = 10 = 15 = 20

    = 25 = 30

  • Page 12 Microsystems & Electronics; Optronic Systems & Signal Processing

    Sensors and data acquisition system

    Quality influencesQuality influences

    1.E-03

    1.E-02

    1.E-01

    1.E+00

    1 . E -03 1. E -02 1 . E -01 1. E +00 1. E +01 1 . E +02 1. E +03 1 . E +04 1. E +05

    0.01

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    Gyro

    Integration Time [s]

    0.001 0.1 1 10 100 1000 104 1050.01

    10-4

    10-3

    10-2

    10-5 Ac

    c

    e

    l

    .

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    9

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    8

    1

    m

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    Accelerometer

    Allan-plot of MEMS accelerometer and gyro

  • Page 13 Microsystems & Electronics; Optronic Systems & Signal Processing

    Estimated 1-Sigma Value of measurement systemELAC 1997 2005 possible

    rotational rates 1,5 /s < 0,5 /s

    acceleration 0,05 g < 0,01 g

    , 1 0,5 control surfaces deflection 0,3 0,3

    dynamic pressure ? combine with vel. measurement

    mass 10 g 2 gIx, Iy, Iz 3% 3%Ixz 2 deviation from main axis 1 Ixy, Iyz set to 0 measure

    position of center of gravity 2 mm 1 mm ?

    position of aerodynamic 30 mm 30 mm

    measurements

    Quality influencesQuality influences

  • Page 14 Microsystems & Electronics; Optronic Systems & Signal Processing

    Example: Minaturised control system

    Quality influencesQuality influences

    Autopilot HW with fully integrated MEMS-based flight control sensors, 100 Hz control frequency

    Weight < 25 grams

    Micro UAV: DO-MAV

    500 grams

    0,42 m span

  • Page 15 Microsystems & Electronics; Optronic Systems & Signal Processing

    ELAC-space plane configuration with additional external installations(e.g. noseboom, skids)wind tunnel model scale factor 1:65

    ELAC-space plane configuration free flyingmodel (rudderactuation)

    Quality influencesQuality influences

  • Page 16 Microsystems & Electronics; Optronic Systems & Signal Processing

    -0,20

    -0,15

    -0,10

    -0,05

    0,00C [-]l

    6,0 8,0 10,0 12,0 14,0 16,0 [-]

    Freiflug

    Windkanal

    -0,8

    -0,6

    -0,4

    -0,2

    0,0C [-]l

    6,0 8,0 10,0 12,0 14,0 16,0 [-]

    Freiflug

    Windkanal

    0,00

    0,02

    0,04

    0,06

    0,08

    0,10C [-]l

    6,0 8,0 10,0 12,0 14,0 16,0 [-]

    Freiflug

    Windkanal

    -0,40

    -0,30

    -0,20

    -0,10

    0,00C [-]lp

    6,0 8,0 10,0 12,0 14,0 16,0 [-]

    Freiflug

    Windkanal

    0,0

    0,2

    0,4

    0,6

    0,8

    1,0C [-]lr

    6,0 8,0 10,0 12,0 14,0 16,0 [-]

    Freiflug

    Vortex-Lattice

    Comparison of roll moment derivatis btweenflight test and wind tunnelmeasurements

    Results: Comparison wind tunnel / free flightResults: Comparison wind tunnel / free flight

  • Page 17 Microsystems & Electronics; Optronic Systems & Signal Processing

    From differences in wind tunnel and flight tests derived parameter uncertainties of rolling damping moment coefficient for space plane X-33

    (Cobleigh: Development of the X-33 Aerodynamic Uncertainty ModelNASA TP-1998-206544, April 1998)

    Results: Comparison with literature about deviation of wind tunnel and free flight dataResults: Comparison with literature about deviation of wind tunnel and free flight data

  • Page 18 Microsystems & Electronics; Optronic Systems & Signal Processing

    Results: Comparison with literature about typical deviation of wind tunnel and free flight dataResults: Comparison with literature about typical deviation of wind tunnel and free flight data

    FALKE-Orbiter Space-Shuttle Orbiter

    Study 1 Study 2 ELAC model

    AC +0.08 +/- 0.050 +0.008 +0.036 AC +12.5% +0.8% +15.7%

    WC -0.04 +0.07 +/- 0.0125 -0.010 +0.036mC +0.008 +/- 0.022 +/- 0.008 -0.009 -0.001 mC -5% -20% +40% +/- 28% -6.4% +0.3%

    mqC +/- 80% -33.3% -19.2%mqC VL +13.0% +19.1%mqC DC -10.0% -1.2% QC -15% +/- 25% -0.140 +0.200 0.067 0.104 QC +/- 0.028 0.043 0.063 QC +/- 0.086 -0.046 -0.030 lC +0.024 +/- 0.030 +/- 0.045 0.001 0.042 lC -10% -25% +40% +/- 25% -10.8% 4.2% lC -6% -30% +60% +/- 0.011 -0.040 -0.200

    lpC -16 +57% -40% +70% -1.2% 16.6%lrC VL -200% +150% 36.0% 152.7% nC +0.009 +/- 0.030 -0.065 +0.046 -0.070 -0.007 nC +/- 0.024 +/- 0.017 -0.056 -0.025 nC -17% -30% +60% +/- 26% -41.3% -25.2%

    npC VL -200% +100% -42.4% -13.9%nrC +/-4% -35% +40% -27.5% 0.5%

    VL: Vortex-Lattice DC: DATCOM-Methode

  • Page 19 Microsystems & Electronics; Optronic Systems & Signal Processing

    Comparison of ELAC result (deviation modelflight testing / wind tunnel) with parameteruncetainties from literature for X-33

    Results: Comparison with literature about typical deviation of wind tunnel and free flight data

    Results: Comparison with literature about typical deviation of wind tunnel and free flight data

    -150

    -100

    -50

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    C

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  • Page 20 Microsystems & Electronics; Optronic Systems & Signal Processing

    Method is applicable to subsonic/low speed flight regime and configurations with specific lower mass density (e.g. GA)

    Quality of miniaturised (low-cost) sensors (drift & sensitivity) has been improved significantly over the recent years; aerodynamic sensors and nose-boom integration remain challenging

    Even miniaturised autopilots are available today to investigate configurations with closed control loop and realistic position of center of gravity

    For applications to determine the quasi-unsteady aerodynamics of these configuration the method is reliable enough today

    SummarySummary