numerical study of mixing in swirling coaxial jets ... · flow pattern based on swirl no. the nasa...

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PRACE days 15: Enable Science Foster Industry Dublin, Ireland 26-28 May 2015 NUMERICAL STUDY OF MIXING IN SWIRLING COAXIAL JETS NUMERICAL STUDY OF MIXING IN SWIRLING COAXIAL JETS. AN APPLICATION OF LARGE EDDY SIMULATION AN APPLICATION OF LARGE EDDY SIMULATION. Teresa PARRA SANTOS Dept. of Energy and Fluid Mechanics, University of Valladolid, Spain [email protected] Physical model 1 Numerical Model & Scalability Analysis 2 Physical model 1 Numerical Model & Scalability Analysis 2 Flow Pattern based on Swirl no. dr r 2 v rv S Geometry 3D Swirl number around 1 is produced by 8 flat blades of 62º of pitch angle and 40 mm chord Fuel Oxidizer provides experimental data on different lines of the test chamber for the isothermal case. dr r 2 v R S 2 z z Mesh 10 Million Hexahedral cells test chamber (~d/190) Fuel blades of 62º of pitch angle and 40 mm chord. Injection Central Nozzle Annular Nozzle The scalability Low-swirl injector (S < 0.5) Central Divergence Zone z Spatial resolution: test chamber ( d/190) central nozzle (~d/40) annular nozzle (~d/46) Air Composition CH 4 22% O 2, 78% N 2 performance for non reactive cases provided an Central Divergence Zone Shear Layer Swirl number around 1 2 is produced by 8 flat annular nozzle (~d/46) Scheme for l i Total Variation Diminishing Air 2 Temperature (K) 300 900 Velocity (m/s) 0 66 1 54 reactive cases provided an optimum of 64 processors. Shear Layer Outer Recirculation Zone Swirl number around 1.2 is produced by 8 flat blades of 62º of pitch angle and 25 mm chord. velocity P&V PISO Roback & Johnson Burner Roback R Johnson B V (1983) Mass Velocity (m/s) 0.66 1.54 Turbulence intensity (%) 12 7.5 8 9 10 cores IDEAL Hi h il ij t coupling PISO Solver for GeometricAlgebraic Roback R., Johnson B.V. (1983) Mass and momentum turbulent transport experiments with confined swirling (%) Specific Heat(J/kg/K) Polynomial function of t t 6 7 8 zed to 16 Speedup High-swirl injector (S > 0.5) Inner Recirculation Zone pressure MultiGrid 1000 cells coaxial jets, NASA CR-168252 temperature Thermal Conductivity (W/ /K) 0.0332 0.0242 3 4 5 normaliz Inner Recirculation Zone Shear Layer Multigrid 1000 cells In Coarsest Level Temporal (W/m/K) Viscosity (kg/m/s) 1.087.10 -5 1.7894.10 -5 1 2 3 Speedup Outer Recirculation Zone Temporal resolution: 10 5 s/time step Molecular Weight (kg/kmol) 16.04303 28.996 0 0 32 64 96 128 160 S Number of cores Validation with experimental data for Swirl no. 1 3 Large Eddy Simulations (LES) 4 Number of cores Velocity profiles V[m/s] vs radial length [m] Experimental (symbols) Numerical (solid lines) Large Eddy Simulations (LES) 4 Prerequisites: y + = 1 and van Driest’s wall damping function Axial Velocity Azimuthal Velocity Smagorinsky Model Radial Velocity Th NASA Space decomposition for minimum transfer of information among processors Explicit LES equations are obtained by applying a low-pass filter with width to the Navier Stokes equations Smagorinsky Model 0 mm The NASA report by Explicit LES equations are obtained by applying a low-pass filter with width to the Navier Stokes equations. gth 100 report by Roback and ߩ ݑ ߩ ݑ ݑ ̅ ߪ ̅ ݏ ݏal leng Johnson ߩ ݑ ݐ ߩ ݑ ݑ ݔ ݔ ߪ ݔ ݔ The unknown sub-grid stress Tensor is predicted by the Smagorinsky model as a function of the strain tensor S Axi provides experimental ̅ ݏ ݏ2 ̅ Wi h h b id i i m experimental data on ̅ ݏ ݏ2 ߤݏ ݏ ߤݏ ݏߩ ܥ ݏ2 2 ̅ ̅ With the sub-grid stress viscosity 60 mm data on different ݏ ݏ ݏ Implicit LES (ILES) ngth 1 lines of the h b Implicit_LES (ILES) On ILES models, the filter width is related to the mesh size i , then no subgrid model is applied. Since the Axial le test chamber for the subgrid stress tensor has a dissipative nature, this role is played by the numerical error. The numerical error is controlled using different kind of limiters and schemes, such a TVD limited looking for A for the isothermal good accuracy. Selective Scale Discretization (SSD) mm isothermal case. Selective Scale Discretization (SSD) The separation of the scales is performed using a high-pass filter. The laplacian filter has the expression: 2 th 200 Two source terms are added on the RHS of the momentum equation as forces ݑ ݔ ߨ2 ݑ ݔal lengt Where the fields u’ 1i and u’ 2i are equal. Each term must be solved with different schemes of high and low order . ݔ ߨ ݔ Axia 1i 2i , ݔ ݑ ݑ1 ݔ ݑ ݑ2 Influence of conical diffuser Non Reactive Flow Pattern 5 ݔ ݔ 6 Results for Swirl no. 1 Averaged Axial Velocity with Diffusers 60º, 90º, 120º, 140º, 160º and no-Dif. 5 6 I-LES ILES-SSD Swirl no. 0.6 Swirl no. 1.2 UMean U Uprime2Mean<0.5 S f SSD 0 05 Source of SSD<0.05 ‐‐‐ Ps VORTEX KERNELS Strong swirl numbers produce larger IRZ and smaller ORZ than mild swirls. Diffusers prevent the formation of counter - rotating vortex rings (Taylor-Couette instabilities) for mild swirls and the ORZ for strong swirls. VORTEX KERNELS Criteria to visualize the vortex kernel may be lambda2 (λ 2 ) lower than 0 or positive values Frequency Domain Analysis 7 Criteria to visualize the vortex kernel may be lambda2 (λ 2 ) lower than 0 or positive values of Q, both calculated from the strain and rotation tensors Energy spectrum Proper Orthogonal Decomposition Lambda2 is defined as the intermediate eigenvalue of the tensor S 2 +2 Other criterion Q defined as: Q 1 S ij S ij ij ij Energy of each modes Modes 1-2 3 / 5 3 / 2 L 5 . 1 f f ) ( E Other criterion Q defined as: Q 2 S ij S ij ij ij . Taylor’s hypothesis L Taylor s hypothesis of frozen turbulence. Taylor-scale and t bl R ld turbulence Reynolds no. let identify 126 R 2400 R Kolmogorov scale mm 17 0 126 Re 2400 Re L Conclusions mm 17 . 0 LES was performed to model the interaction of swirling jets. SSD is a challenging approach to model flows. Averaged fluid field was validated with experimental results provided by Roback and Johnson Isosurfaces of Lambda2 equal to I f fQ lt 30000 Sli Averaged fluid field was validated with experimental results provided by Roback and Johnson. The analysis on the frequency domain let identify energetic vortex structures using POD. S il b d l IRZ d ll ORZ h ild il b minus 500000. Slices at axial positions z = 15mm and 25 mm with axial Isosurfaces of Q equal to 30000. Slices at axial positions z = 17.5mm and 25 Strong swirl numbers produce larger IRZ and smaller ORZ than mild swirl numbers. Diffuser prevents or reduces the ORZ z = 15mm and 25 mm with axial velocity ranging from -0.3 to 0.8 ms -1 . Acknowledgment mm with axial vorticity ranging from -120 to 120 s -1 . Peripheral stream lines. The work has been developed in the framework of the project reference ENE2011-25468 from the Spanish Ministry of Science and REFERENCES htt // h id / id/L 9473 2014 Acknowledgment 120 to 120 s . Peripheral stream lines. Innovation. Authors acknowledge PRACE for awarding access to resources Curie-GENCI@CEA based in France and MareNostrum@BSC based in Spain Ref 2010PA1766 The Implementation Phase of PRACE receives funding from the EUs Seventh Framework Programme REFERENCES: http://www.researcherid.com/rid/L-9473-2014 http://orcid org/0000-0002-2274-3185 based in Spain. Ref. 2010PA1766. The Implementation Phase of PRACE receives funding from the EUs Seventh Framework Programme (FP7/2007-2013) under grant agreement RI-312763 http://orcid.org/0000-0002-2274-3185 ESCUELA de Universidad de INGENIERÍAS INDUSTRIALES Valladolid INDUSTRIALES

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Page 1: NUMERICAL STUDY OF MIXING IN SWIRLING COAXIAL JETS ... · Flow Pattern based on Swirl no. The NASA report by Roback and Johnson rv v 2 rdr S Swirl number around 1 is produced by 8

PRACE days 15: Enable Science Foster Industry Dublin, Ireland 26-28 May 2015

NUMERICAL STUDY OF MIXING IN SWIRLING COAXIAL JETS NUMERICAL STUDY OF MIXING IN SWIRLING COAXIAL JETS. AN APPLICATION OF LARGE EDDY SIMULATION AN APPLICATION OF LARGE EDDY SIMULATION.

Teresa PARRA SANTOS Dept. of Energy and Fluid Mechanics, University of Valladolid, Spain [email protected]

Physical model1 Numerical Model & Scalability Analysis 2Physical model1 Numerical Model & Scalability Analysis 2Flow Pattern based on Swirl no. The NASA report by Roback and Johnson drr2vrv

SGeometry 3DSwirl number around 1 is produced by 8 flat

blades of 62º of pitch angle and 40 mm chord Fuel Oxidizer

p yprovides experimental data on different lines of the test chamber for the isothermal case.

drr2vRS

2

z

zMesh 10MillionHexahedralcells

test chamber (~d/190)Fuel

blades of 62º of pitch angle and 40 mm chord. Injection Central

Nozzle

Annular

Nozzle The scalability Low-swirl injector (S < 0.5)

Central Divergence Zone

zSpatialresolution:

testchamber( d/190)centralnozzle(~d/40)annular nozzle (~d/46)Air

Composition CH4 22% O2,

78% N2

yperformance for non reactive cases provided anCentral Divergence Zone

Shear Layer Swirl number around 1 2 is produced by 8 flat

annularnozzle(~d/46)Scheme forl i

TotalVariation Diminishing

Air 2

Temperature (K) 300 900

Velocity (m/s) 0 66 1 54

reactive cases provided an optimum of 64 processors.

Shear LayerOuter Recirculation Zone

Swirl number around 1.2 is produced by 8 flat blades of 62º of pitch angle and 25 mm chord.

velocityTotalVariation Diminishing

P&VPISO

Roback & Johnson Burner

Roback R Johnson B V (1983) Mass

Velocity (m/s) 0.66 1.54

Turbulence intensity

(%)

12 7.5 8

9

10

cores

IDEAL

Hi h i l i j t

couplingPISO

Solverfor Geometric‐Algebraic

Roback R., Johnson B.V. (1983) Mass and momentum turbulent transport experiments with confined swirling

(%)

Specific Heat(J/kg/K) Polynomial function of

t t6

7

8

zed to 16

Speedup

High-swirl injector (S > 0.5)

Inner Recirculation Zonepressure

gMulti‐Grid1000 cells

coaxial jets, NASA CR-168252 temperature

Thermal Conductivity

(W/ /K)

0.0332 0.0242 3

4

5

norm

aliz

Inner Recirculation ZoneShear Layer

Multigrid1000cellsInCoarsestLevel

Temporal

(W/m/K)

Viscosity (kg/m/s) 1.087.10-5 1.7894.10-5 1

2

3

Speedup

yOuter Recirculation Zone

Temporalresolution:

10‐5 s/timestepMolecular Weight

(kg/kmol)

16.04303 28.996 0

0 32 64 96 128 160

S

Number of cores

Validation with experimental data for Swirl no. 13 Large Eddy Simulations (LES)4Number of cores

pVelocity profiles V[m/s] vs radial length [m] Experimental (symbols) Numerical (solid lines)

Large Eddy Simulations (LES)4Prerequisites: y+ = 1 and van Driest’s wall damping function

Axial Velocity Azimuthal Velocity

Smagorinsky Model

Radial Velocity

Th NASA

Space decomposition for minimum transfer of information among processors

Explicit LES equations are obtained by applying a low-pass filter with width to the Navier Stokes equations

Smagorinsky Model

0 m

m The NASA report by Explicit LES equations are obtained by applying a low-pass filter with width to the Navier Stokes equations.

gth

100 report by

Roback and

al le

ng Johnson

The unknown sub-grid stress Tensor is predicted by the Smagorinsky model as a function of the strain tensor SAxi provides

experimental 2

Wi h h b id i im

experimental data on

2 ∆ 2 2

With the sub-grid stress viscosity

60 m

m data on different

Implicit LES (ILES)

ngth

1

lines of the h b

Implicit_LES (ILES)

On ILES models, the filter width is related to the mesh size i , then no subgrid model is applied. Since the

Axi

al le test chamber

for thesubgrid stress tensor has a dissipative nature, this role is played by the numerical error. The numerical error is controlled using different kind of limiters and schemes, such a TVD limited looking for

A for the isothermal

good accuracy.

Selective Scale Discretization (SSD)

mm

isothermal case.

Selective Scale Discretization (SSD)

The separation of the scales is performed using a high-pass filter. The laplacian filter has the expression:∆ 2

th 2

00

Two source terms are added on the RHS of the momentum equation as forces ′∆ 2

al le

ngt q

Where the fields u’1i and u’2i are equal. Each term must be solved with different schemes of high and low order.

Axi

a W e e t e e ds u 1i a d u 2i a e equa . ac te ust be so ved w t d e e t sc e es o g a d ow o de .

, ′1 ′2

Influence of conical diffuserNon Reactive Flow Pattern5,

6Results for Swirl no. 1 Averaged Axial Velocity with Diffusers 60º, 90º, 120º, 140º, 160º and no-Dif.

5 6

I-LES ILES-SSD Swirl no. 0.6Swirl no. 1.2 UMean

U

Uprime2Mean<0.5 p

S f SSD 0 05

Source of SSD<0.05 ‐‐‐

Ps

VORTEX KERNELS

Strong swirl numbers produce larger IRZ and smaller ORZ than mild swirls. Diffusers prevent the formation of counter-rotating vortex rings (Taylor-Couette instabilities) for mild swirls and the ORZ for strong swirls.

VORTEX KERNELS

Criteria to visualize the vortex kernel may be lambda2 (λ2) lower than 0 or positive values Frequency Domain Analysis7Criteria to visualize the vortex kernel may be lambda2 (λ2) lower than 0 or positive valuesof Q, both calculated from the strain and rotation tensors Energy spectrum Proper Orthogonal Decomposition

q y y

Lambda2 is defined as the intermediate eigenvalue of the tensor S2+Ω2

Other criterion Q defined as: Q1SijSij ΩijΩij

Energy of each modes Modes 1-23/53/2L 5.1ff)(E

Other criterion Q defined as: Q 2SijSij ΩijΩij .

Taylor’s hypothesis

L)(

Taylor s hypothesis of frozen turbulence.Taylor-scale and t b l R ldturbulence Reynolds no. let identify

126R2400R

Kolmogorov scale

mm170

126Re2400ReL

Conclusions

mm17.0

•LES was performed to model the interaction of swirling jets. SSD is a challenging approach to model flows. • Averaged fluid field was validated with experimental results provided by Roback and Johnson

Isosurfaces of Lambda2 equal to I f f Q l t 30000 Sli

• Averaged fluid field was validated with experimental results provided by Roback and Johnson. • The analysis on the frequency domain let identify energetic vortex structures using POD.S i l b d l IRZ d ll ORZ h ild i l b

qminus 500000. Slices at axial positions

z = 15mm and 25 mm with axial

Isosurfaces of Q equal to 30000. Slices at axial positions z = 17.5mm and 25

•Strong swirl numbers produce larger IRZ and smaller ORZ than mild swirl numbers.• Diffuser prevents or reduces the ORZz = 15mm and 25 mm with axial

velocity ranging from -0.3 to 0.8 ms-1. Acknowledgment

mm with axial vorticity ranging from -120 to 120 s-1. Peripheral stream lines.

The work has been developed in the framework of the project reference ENE2011-25468 from the Spanish Ministry of Science and REFERENCES htt // h id / id/L 9473 2014

Acknowledgment120 to 120 s . Peripheral stream lines.

p p j p yInnovation. Authors acknowledge PRACE for awarding access to resources Curie-GENCI@CEA based in France and MareNostrum@BSC based in Spain Ref 2010PA1766 The Implementation Phase of PRACE receives funding from the EUs Seventh Framework Programme

REFERENCES: http://www.researcherid.com/rid/L-9473-2014http://orcid org/0000-0002-2274-3185 based in Spain. Ref. 2010PA1766. The Implementation Phase of PRACE receives funding from the EUs Seventh Framework Programme

(FP7/2007-2013) under grant agreement RI-312763http://orcid.org/0000-0002-2274-3185

ESCUELA deUniversidad deINGENIERÍAS

INDUSTRIALESValladolid

INDUSTRIALES