experimental flow characterization and heat...

EXPERIMENTAL FLOW CHARACTERIZATION AND HEAT FLUX AUGMENTATION ANALYSIS OF A

HYPERSONIC TURBULENT BOUNDARY LAYER ALONG A ROUGH SURFACE

D. Neeb, D. Saile, A. GülhanSupersonic and Hypersonic Technology Department, Institute of Aerodynamics and Flow Technology, DLR Germany

8th European Symposium on Aerothermodynamics for Space Vehicles2 - 6 March 2015, Lisbon, Portugal

Outline

Motivation

Theory

Numerical tools

Analytical correlations

Numerical prediction

Experimental tools

Wind tunnel

Model

Measurement techniques

Analysis

Boundary layer

Heat flux

Summary and Outlook

> Neeb, Saile, Gülhan > 7th ESASV > 03.03.2015Slide 2

Surface roughness increases skin friction drag and convective heat transfer above the turbulent level on aircrafts, missiles, re-entry vehicles and propulsion systems

Careful consideration in the prediction of the resulting heat load levels is required for the design of a vehicle

Better understanding is required

Motivation


IR of FS wind tunnel test

ESA ExoMars

IR of material wind tunneltests

Surface roughness has measureable effect on

Velocity

Turbulence

Skin friction

Heat flux

…

Key parameter to scale is the (equivalent) sand grain roughness height ks

Theory


ks+ [-]

St r

/St s

[-]

100 101 102 103 104

1

1.2

1.4

1.6

1.8

2

2.2

2.4

2.6

2.8 Hill et al (sand grain)

Young (v-grooves)

Holden (sand grain/spheres)

model1

model2

model5

model2013.1

model2013.2

Seidman

Powars

FCII

FCIII

FCV

FCVII

FCVIII

(Neeb, Merrifield, Gülhan, 2014)(Sahoo,2009)

Generic cone model enables the use of analytical and numerical predictions to support analysis

Several analytical smooth Van Driest and via Reynolds analogy St

and rough wall heat flux predictionsPowars (St based on Passive Nosetip Technology (PANT) data)

Boundary layer code (Harris, NASA, 1982) enables prediction of smooth & rough heat flux and boundary layer parameters

Compressible modified Krogstad model for rough surfaces implemented (based on equivalent sand grain roughness) as proposed by FGE

CFD code (DLR TAU) enables prediction of smooth heat flux and boundary layer parameters

Numerical toolsSmooth and rough wall predictions


Mach number

Rey

nold

snu

mbe

r[1

06 ·m

-1]

4 5 6 7 8 9 10 11 120

5

10

15

20

25

Rough cone 7deg

5 bar

2 kg/s

5 kg/s

10 kg/s

15 kg/s

20 kg/s

45 bar10 bar 30 bar20 bar Total pressureMass flow

Experimental toolsDLR Hypersonic wind tunnel H2K


Blow down facility

Exchangeable contoured nozzles Ma= 5.3; 6.0; 7.0; 8.7; 11.2

Electrical heaters with capacity of up to 5 MW

Testing time: ~30s

FlowCond.

MaReL(106)

p0(bar)

T0(K)

p(bar)

T(K)

u(m/s)

inflow 6.1 11.5 20.0 500 0.0119 75 940edge 5.4 15.1 19.8 500 0.0236 73 926

λ

k

w

i

roughness

L = 0.73 m

x = 0.44 L

Sharp 7° cone configuration

Smooth sharp metallic nose

Smooth PEEK middle and end segment to be assessed by infrared thermography

Rough PEEK end segment with technical roughness

2D square bar topology with λ/w = (w + i)/w = 4

Existing literature data to compare in incompressible (ks / k = 2.0-6.0) and compressible regime (ks / k = 0.7-1.9)

Experimental toolsModel


Global quantitative infrared thermography

Heat flux derived by solving the one dimensional heat equation

Particle Image Velocimetry (PIV)

Solid particle seeding (dp,mean=3.5µm, tp=2.6µs)

Velocities are derived within the boundary layer in specific regions of interest (9x12mm²)

Experimental toolsMeasurement techniques


ROI at x/L=0.68

~200 images per run post-processed (leveling, rotation)

Amount of particles nearly equally distributed

Post-processing with different validation parameters to ensure well correlated results

Different interrogation window sizes tested

Best results with iw64x96 (0.48x0.72 mm²)

Mean streamwise normalized velocities show clear boundary layer structure with

Increased rough BL height

Lower velocities above rough surface

Slight waviness in rough case

AnalysisBoundary layer topology


u [m/s]

y[m

]

0 200 400 600 800 10000

0.002

0.004

0.006

0.008

TAU - turb. - Tu nom.TAU - turb. - Tu0.01TAU - turb. - Tu0.02BLcode turb.Run7 iw256x256Run7 iw128x128Run7 iw96x96Run7 iw256x256 to 96x96Run7 iw256x256 to 64x96Run7 iw256x256 to 48x96Run7 iw256x256 to 24x96

AnalysisBoundary Layer profiles


Smooth surface profiles with mean streamwise velocities in between 0.494<x<0.500m

Different interrogation window sizes show good agreement

Good agreement to numerical data for fully turbulent flow

u/u e

y/δ

0 0.2 0.4 0.6 0.8 1 1.20

0.2

0.4

0.6

0.8

1

1.2

Run7 smooth iw64x96Run8 smooth iw64x96Run12 rough iw64x96Run14 rough iw64x96BLcode turb.TAU turb. Tu nom.BLcode Krogstad ks=0.5mmBLcode Krogstad ks=1.0mm

AnalysisBoundary Layer normalized smooth and rough profiles


Smooth and rough surface profiles with mean velocities in between 0.494<x<0.500m scaled with corresponding δ and ue

Good repeatability in smooth and rough case

Good agreement of smooth results to fully turbulent numerical profiles

Rough wall velocity shift clearly detectable

Good agreement of computed rough profile by Krogstad model with ks = 0.5mm (ks / k = 1)

AnalysisHeat flux smooth surface


Ree,x

St e

0 5E+06 1E+07 1.5E+070

0.0005

0.001

0.0015

0.002TAU lam.TAU turb Tu nom.TAU turb. Tu0.02BLcode lam.BLcode turb.Korkegi lam.VanDriestII turb.Fenter turb. smoothRun3Run4Run5Run6Run7Run8Run11

Very good repeatability of laminar level, transition onset and turbulent level

Seeding has clear influence on transition onset but not on turbulent level

Turbulent level in good agreement with TAU 2% inflow turb. intensity

Analytical and BL code predictions overestimate

Ree,x

St e,

r/St e,

s

5E+06 1E+07 1.5E+070.8

1

1.2

1.4

1.6

1.8

2

2.2

2.4

2.6

2.8

3BLcode Krogstad ks=0.5mmBLcode Krogstad ks=1.0mmBLcode Krogstad ks=1.5mmPowars ks=0.5mmPowars ks=1.0mmPowars ks=1.5mmRun12 to Run3Run13 to Run3

AnalysisHeat flux rough wall augmentation


Rough wall augmentation slightly oscillates around mean of approx. 20% due to topology

Powars and Krogstadoverpredicts

Ree,x

St e,

r/St e,

s

5E+06 1E+07 1.5E+070.8

1

1.2

1.4

1.6

1.8

2

2.2

2.4

2.6

2.8

3BLcode Krogstad ks=0.5mmBLcode Krogstad ks=1.0mmBLcode Krogstad ks=1.5mmPowars ks=0.5mmPowars ks=1.0mmPowars ks=1.5mmRun16 to Run3

Results in increased augmentation with oscillations of higher amplitude and higher mean level of approx. 30%

Peak values are captured by Krogstad model with ks = 0.5 -1.0mm (ks / k = 1 - 2), which is in the same range as compressible literature data and velocity profile prediction

AnalysisHeat flux rough augmentation zoomed


AnalysisHeat flux rough augmentation zoomed


x [m]

∆Tin

it[K

]

z[m

]

0.324 0.328 0.332 0.336 0.34 0.344-50

-40

-30

-20

-10

0

10

20

30

40

50

0.04

0.05

contourRun_0003Run12Run13Run14Run16

Results in increased augmentation with oscillations of higher amplitude and higher mean level of approx. 30%

Peak values are captured by Krogstad model with ks = 0.5 -1.0mm (ks / k = 1 - 2), which is in the same range as compressible literature data and velocity profile prediction

Zoomed view of the rough surface with increased resolution of ~2pixel per square bar

PIV successfully applied for the first time in the hypersonic regime of H2K

Velocity profiles along smooth cone in good agreement to predictions

Roughness velocity shift clearly detectable and profiles along rough cone

Direct sand grain roughness height extraction via fitting very sensitive and non-unique

higher resolved profiles near the wall with highly stretched interrogation windows will be tested

cumulative rough data analysis of several runs to extract fluctuations for skin friction velocity extraction

2nd profile position data exploitation

Pitot pressure profile measurements

Heat flux augmentation along rough cone sensitive to resolution

With highest possible resolution mean level of augmentation is 30%

higher resolution will be tested to see if result is converged

3D heat flux calculation based on IR data

Both velocity shift and heat flux augmentation are predicted by compressible Krogstadmodel ks = 0.5 -1.0mm (ks / k = 1 - 2), which is in the same range as compressible literature data

Summary and Outlook


experimental flow characterization and heat...

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