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The structure of the velocity and scalar fields in a multiple-opposed jets reactor. L. Danaila J.F. Krawczynski , B. Renou A. Mura, F.X. Demoulin, I. Befeno, G. Boutin. CORIA, Saint-Etienne-du-Rouvray, FRANCE LCD, Futuroscope, Poitiers, FRANCE.

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slide1

The structure of the velocity and scalar fields in a

multiple-opposed jets reactor

L. Danaila

J.F. Krawczynski, B. Renou

A. Mura, F.X. Demoulin, I. Befeno, G. Boutin

CORIA, Saint-Etienne-du-Rouvray, FRANCE

LCD, Futuroscope, Poitiers, FRANCE

Prof. P.E. Dimotakis of Caltech was responsible for the conceptual and detailed design of the PaSR and contributed to the initial experiments.

Financial support: ANR ‘Micromélange’

slide2

OUTLINE

I. Motivation of the great work: theoretical vs. applied research

II. Experimental set-up: Partially Stirred Reactor (PaSR)

Experimental methods: PIV, LDV (1 and 2 points), PLIF

III. Description of the flow

Instantaneous aspect: instabilities in the central region

Mean velocity field

Fluctuating field and isotropy

Spectral analysis

Fine-scale properties of the flow

IV. Characterization of the mixing

V. Conclusions

slide3
Why?

Combustion, propulsion, chemical and other industrial problems

How?

Create SHI – Stationary, (nearly) Homogeneous, and (nearly) Isotropic flow and mixing:closed vessels and/or propellers, HEV…

The ‘porcupine’: R. Betchov, 1957

Synthetic jets’ in cubic chamber - W. Hwang and J.K. Eaton (E. Fluids, 2003)

Propellers - Birouk, Sahr and Gokalp (F. Turb. & Comb, 2003)

Synthetic jets - J.P. Marié

French Washing Machine

Ignition, stability, extinction ? Pollutants emissions ? Better efficiency ?

I. MOTIVATION: Improved understanding of Turbulent Mixing

slide4

Z0

Z1

Z0

Z1

Exit

I. MOTIVATION: Improved understanding of Turbulent Mixing

  • Issues?
    • Optimal configuration: basic PaSR (Partially Stirred Reactor) model

S.M. Correa and M.E. Braaten (1993)

Assumptions:

Mean: Homogeneity at large scales, Stationary case

Fluctuations of the smaller scales

Main advantages:

Ideal tool to test micro-mixing

models

(IEM, Curl, Curl modified, …)

Characteristic times:

tR (Residence time); tT (Turbulence time);

tM (Mixing time); tC (Chemical time)

slide5

I. MOTIVATION: Improved understanding of Turbulent Mixing

  • Question
  • Why a SHI flow must be created since few such flows exist in reality ?
    • Turbulent flows are very complex by nature  interest to examine simpler flows
    • Create a reference and an academic experimental configuration
    • Ideal to develop and valid statistical theories of turbulence

 Analytical approaches

    • Limitation of DNS for high Rel

 High Rel can be reached in forced turbulence

Ultra Low-NOx Combustion Dynamics

slide6

II. EXPERIMENTAL SET-UP

  • Design of the PaSR versus objectives:
  • Large range of Reynolds number Rel: 60 – 1000
  • Pressure variations 1- 3 bars
  • Different flow configurations
      • Pairs of Impinging jets
      • Sheared flow
  • Modularity of the system
  • Large range of flow rates and internal volumes
  • Characteristic times tRandtT compatible with chemical time
  • Reactive configuration for future work

P. Paranthoen, R. Borghi and M. Mouquallid (1991)

slide7

II. EXPERIMENTAL SET-UP*

  • Volume PaSR: V = 11116 cm3
  • Injection velocity: UJ = 4.5 - 47 m/s
  • Return flow= porous top/bottom plates
  • Residence time: tR = 8 -46 ms

Reynolds number 60 Rl 1000 (center)

*Prof. P.E. Dimotakis of Caltech was responsible for the conceptual and detailed design of the PaSR and contributed to the initial experiments.

slide8

II. EXPERIMENTAL SET-UP and measurements

Velocity field:

1) Particle velocimetry

  • Resolution and noise limitations
  • PIV resolution linked to size of interrogation/correlation window, e.g., 16, 32, and 64 pix2, and processing algorithm choices
    • Does not resolve small scales: the smallest 100% =1.7 mm
    • Problem to estimate energy dissipation directly
  • Towards adaptive/optimal vector processing/filtering

2) LDV in (1 point and) 2 points

  • Simultaneous measurements of One velocity component in two points of the space: spatial resolution 200 * 50 microns; sampling frequency= 20 kHZ

Scalar field: PLIF on acetone

Small-scale limitations set by spatial resolution (pixel/laser-sheet size)

The smallest resolved scale 100% =0.7 mm

Signal-to-noise ratio per pixel

  • Adaptive/optimal image processing/filtering
slide9

26252

8 injection

conditions

6089

II. EXPERIMENTAL SET-UP and measurements

Re 104

2 Geometries:

H/D=3

H/D=5

slide10

z

y

x

III. DESCRIPTION of the FLOW: Mean flow properties

A forced box turbulence

-locally, in each part of the PaSR, we recognize a ‘classical’ zone,

e.g. Injection zone = impinging jets

« Mixing » zone = stagnation zone

Return flow (top/bottom porous)

Presence ofgiant vorticity rings

=16 French

Washing

machines

slide11

III. DESCRIPTION of the FLOW: Mean flow properties

Strong circomferential

mixing layers

GIANT COHERENT RINGS

slide12

2

3

z

y

Strong energy injection

1

l

x

III. DESCRIPTION of the FLOW: fluctuating field

slide13

III. DESCRIPTION of the FLOW: fluctuating field

Energy

Isotropy?

II

I

Structures: azimuthal enstrophy

slide14

III. DESCRIPTION of the FLOW: fluctuating field; spectral approach from PIV

  • Horizontal and vertical cut in 2D spectrum
  • Energy injection
  • Restricted scaling range E(k) k-5/3
  • Scaling range E(k)  k-3  1D spectra in
  • k-2.33
  • Properties similar to turbulence in rotation presence of coherent structures

CUT-OFF

k-3

Energy

injection

What about the small scales? Unresolved by PIV

Large-scale information from PIV

LDV measurements in 1 and 2 points.

slide15

Vinj=7m/s

III. DESCRIPTION of the FLOW: fluctuating field; local approach

Vinj=17m/s

II

II

I

I

I : Impinging point

II: Return zone

(Gaussian)

From LES, vortices (Q criterium)

Local approach

slide16
3-rd order SF

2-nd order SF with the Kolmogorov constant Ck=2 ..

Normalized dissipation which L? Attention to initial conditions versus universality .. However, a reliable test

The most reliable test is the 1—point energy budget equation, when the pressure-related terms could be neglected (point II).

III. DESCRIPTION of the FLOW: fluctuating field; local approach; PIV for determining small-scale properties

‘Traditional’ Spectral method  Inertial range

 Corrected spectra (see Lavoie et al. 2007);

Drawback: the theoretical 3D spectrum E(k)

should be known ..

Drawback: spectra are to be calculated over locally homogeneous regions of the flow, and require 2^N points

Here:

slide17

III. DESCRIPTION of the FLOW: fluctuating field; PIV for determining small scale properties 3-rd order SF

  • Iterative Methodology
  • Measure , consider the Kolmogorov constant as 4/5 and infer Epsilon
  • Determine the turbulent Reynolds number, infer the Kolmogorov constant (forced turbulence) and start again

Grid turbulence data:

Mydlarski & Warhaft 1996,

Danaila et al. 1999

slide18

III. DESCRIPTION of the FLOW: fluctuating field; PIV for determining small scale properties 3-rd order SF

JETS

Antonia & Burattini, JFM 2006

iii description of the flow fluctuating field piv for determining small scale properties
The other tests

2-rd order SF with the Kolmogorov constant

Normalized dissipation which L? Attention to initial conditions versus universality .. However, a reliable test

for

The most reliable test is the 1—point energy budget equation, when the pressure-related terms might be neglected (point II).

III. DESCRIPTION of the FLOW: fluctuating field; PIV for determining small scale properties
iii description of the flow fluctuating field back to piv for determining small scale properties
III. DESCRIPTION of the FLOW: fluctuating field; back to PIV for determining small scale properties

For the stagnation point I,

The pressure-velocity correlation

Term cannot be neglected, since

The mean pressure is important

At high Reynolds and low ratios H/D

slide21
III. DESCRIPTION of the FLOW: fluctuating field; back to PIV for determining small scale properties RESULTS: Point I

PIV 3 other methods

PIV finite differences

slide22
III. DESCRIPTION of the FLOW: fluctuating field; back to PIV for determining small scale properties RESULTS: Point I

Conclusion (point I) R_lambda maximum=750

slide23
III. DESCRIPTION of the FLOW: fluctuating field; back to PIV for determining small scale properties RESULTS: Point II

PIV 4 other methods

PIV finite differences

slide24

III. DESCRIPTION of the FLOW: fluctuating field; back to PIV for determining small scale properties RESULTS: Point II

Conclusion (point II) R_lambda maximum=350

slide25

Residence time

Cascade time

Kolmogorov time

Red circles: point I

Blue diamonds: point II

iii description of the flow fluctuating field ldv for determining small scale properties
a) LDV in 1 point  mean velocity, RMS, small-scales quantities (definitions, correlations, SF2, SF3, 1-point energy budget equation… ). Good to determine the RMS and to compare with the PIV results (15% difference).

Drawback: Taylor’s hypothesis is needed, in a flow where the turbulence intensity varies from 100% to infinity (stagnation points ..).

LDV in two points simultaneous measurements of one velocity component in 2 spatial points (separation parallel to the measured velocity direction)… many points.

Different methods: SF2, SF3, definition of

1-point energy budget equation (pressure … good for point II).

III. DESCRIPTION of the FLOW: fluctuating field; LDV for determining small scale properties

These measurements only reinforce the

Conclusions pointed out by large-scale PIV

slide27

Interface probability, along the jets axis

l

IV. DESCRIPTION of the scalar mixing: fluctuating field

z = 1

z = 0

  • Jets instabilities

(Denshchikov et al. 1978)

Gaussian shape of the Pdf

slide28

IV. Description of the scalar mixing: fluctuating field

Instantaneous fields of the mixing fraction z

H/D=3

H/D=5

Large pannel of structures

Large-scale instabilities (jets flutter)

Mechanisms controlling the mixing?

slide29

H/D=3

H/D=5

Invariance / injection conditions

Similarity

IV. Description of the scalar mixing: mean field

slide31

Conclusions

  • Pairs of impinging jets
  • Return flow by top/bottom porous locally axisymmetric flow
  •  strong sheared layers
  • Flow only (very) locally homogeneous  difficulties to apply the classical spectral approach (spectral corrections because of finite size of the probe, and so on ..)
  • Techniques to infer the (local) dissipation and turbulent Reynolds number
  • Structure functions (SF2, SF3) are better adapted
  • Inertial-range properties are quite useful to infer small-scale properties of the flow (dissipation)
  • 1-point energy budget equation- where the pressure velocity correlations are negligible
slide32

Conclusions

  • The turbulent Reynolds number goes up to
  • 750 in the points among opposed jets
  • 350 in the return flow (Gaussian statistics)
  • Mixing is done more rapidly than the velocity field: one injection
  • point, and at one very small scale
  • The velocity field is injected at several scales and in several points
  • Analogy kinetic energy- scalar does not hold
slide33

IV. Description of the scalar mixing: fluctuating field

Influence des grandes structures de concentration uniforme

Evolution du pic vers des niveaux de concentration inférieure  présence de structures à petites échelles

Plus grande stabilité  gradients plus importants  mélange aux petites échelles plus efficace

slide34

III. Description of the flow: fluctuating field; PIV for determining small scale properties 3-rd order SF

MID-SPAN

JETS

The sign changes at

Large scales (inhomogeneity)

results
Results

IV. Description of the scalar mixing: fluctuating field

  • Champ instantané de la vitesse azimutale dans le plan des jets

expérience

simulation