Topic 1.2: Near field spray development and - PowerPoint Presentation

Topic 1.2:  Near field  spray development and
Topic 1.2:  Near field  spray development and

Topic 1.2: Near field spray development and - Description


coupled nozzle flow and spray simulations Alan Kastengren Argonne National Laboratory Qingluan Xue Argonne National Laboratory Julien Manin Sandia National Laboratory Chawki Habchi ID: 911097 Download Presentation

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nozzle spray simulations liquid spray nozzle liquid simulations mass ifpen les argonne needle density rans flow predict sandia ray

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Slide1

Topic 1.2: Near field spray development and coupled nozzle flow and spray simulations

Alan Kastengren*:

Argonne National Laboratory

Qingluan Xue:

Argonne National Laboratory

Julien

Manin

:

Sandia National Laboratory

Chawki

Habchi

:

IFPEN

Slide2

Modeling Part

Facilitate

dynamic coupling of in-nozzle flow and external spray approaches

Compare the different coupling approaches of in-nozzle flow and external spray

Study

the capability of the different modeling approaches (

Lagrangian-Eulerian

,

Eulerian-Eulerian

) and CFD frameworks (RANS, LES, DNS) for the simulation of the primary atomization and the cavitation

Encourage high-fidelity simulations near nozzle sprays and liquid jet atomization

Slide3

InstitutionModel approachCFD Code Compressibility

Turbulence model

Argonne

Single-mixture

EulerianCONVERGEIncompressible liquidCompressible gas (EOS)RANSStandard k-epsilonCMTSingle-mixture EulerianOpenFOAM (ESA)Compressible liquid (function of pressure & temperature) and gas (EOS)RANSSST k-omegaIFPENTwo-Fluid multi-species EulerianIFP-C3DCompressible liquid and gasLiquid : Stiffened gas EOS Gas : Perfect gas EOSLES SmagorinskySandiaMultiphase/multicomponent with transcritical thermodynamics Raptor (CRF-Sandia)Compressible liquid and gasLESdynamic SmagorinskyUMassSingle-mixture EulerianOpenFOAM (HRMFoam)Compressible liquid and gasLESone-eq. eddy

Model description

Slide4

Spray A

Slide5

InstitutionMesh resolutionNeedle motionInitial conditions inside injector

2-D or 3-D

Argonne

10

μm inside nozzle and first 6mm; fixed embeddingTransient needle motion – with wobbleFuel filled sac and orifice; 150 MPa and 343 K in Sac and orifice3-DHeight=200mm; D=50mmCMTAbout 30 μm uniformFixed needle lift at 100 μmFuel filled sac and orifice: 150 MPa and 343 K in sac and orifice2-D axisymmetricHeight = 12 mmWidth = 6 mmIFPENNon-uniform hexahedra : Minimum cell size=(5µm in the hole,2µm in the seat, 15µm near-nozzle region)With needle motion - Without wobble(LVF,P,T)=Chamber-needle-seat : (0.99, 150 Mpa, 343K)Sac and hole : (0.0001,2MPa,, 343K)Chamber : (0.0001,2MPa,303K)3D configuration including:The needle (15 cm) control volumeChamber (bore=6 cm, height =6cm)Sandia4 μm close to injector; stretched fixed messPlug-flow BC used a few nozzle diameter upstream of nozzle exit; needle not simulatedGas filled sac and orifice; 6MPa and 900K3-Dheight=90mmDiameter=45mmUMassAbout 12 μm cross nozzle and

50 μm for sprayWithout needle motion; fixed needle lift at 100 μmGas filled with sac and orifice at 2MP and 346K3-DHeight = 9 mmDiameter = 2 mm

Simulation set up (Spray A)

Slide6

InstitutionGeometry (210675)Total number of computational cellsComputational time for first

100

microseconds (CPU hours)

ArgonneLow resolution4.50 millions 12,288CMTLow resolution0.09 millions100IFPENHigh-resolution (CNRS scanned)1.10 millions6,144SandiaLow resolution50.00 millions 140,000UMassLow resolution 2.80 millions50,000Spray A: Computational time (first 100µs)

Note: the computational domain size, initial conditions, and needle motions are different for the institutions

Slide7

Computational domain (Spray A)

CMT

IFPEN

Sandia

The inflow boundary conditions are specified at upstream for all simulations

Argonne

UMASS

Slide8

Spray A (675) modeling results

Mass flow rate

at the nozzle exit

Fuel spray penetration vs. time

(0.1% liquid mass fraction)Contour plots of projected density in the 0°plane at 0.1 and 0.5 ms after actual SOIProjected fuel mass/density (ug/mm2) profiles across nozzle axis at 0.5 ms after SOIx = 0.1, 0.6, 2, 6, and 10 mm downstream to nozzle exit@ x= 0.6 and 6 mm, @ 0.75 ms and 1 ms after SOI2D contours of liquid volume fraction at x = 0.1, 0.6, 2, 6, 10 mmTransverse integrated mass profiles at 0.5 ms after SOI: x = 0.1 mm, 0.6 mm, 2 mm, 6 mm, and 10 mm Mean droplet size (SMD) at x = 1, 4, 8 mm at 0.5 ms after SOIMean SMD at the above axial positions vs. axial positionDistributions of SMD vs. radial position at the above axial positions

Dynamics: peak projected density and Full Width Half Maximum (FWHM) of distribution at x = 0.1, 2, 6 mm from nozzle for entire duration of the injection event (in intervals of 20 μs)

Slide9

Spray A:

Predicted mass

flow rate at nozzle exit

All simulations predict similar mass flow rates as the ROI from CMT’s Virtual generator

The transient process at the start of injection is different from the modeling groups since the minimum or fixed needle lift used are differentStarting from empty sac, initial LES penetration for IFPEN (up to 10 μs) compares well with the ROI from CMT’s generator, but it is oscillating; LES for UMass under-predictsEnlarged @ first 0.1ms

The start of injection is defined as first evidence of liquid outside of the nozzle exit

Slide10

Spray A: spray

penetration

Note: Sandia simulated conditions (Ambient=N2@900K

and

60bar); Standard conditions for topic 1.2 are (Ambient=N2@303K and 20bar) The data measured by Argonne and SandiaArgonne, CMT and IFPEN: The liquid penetration defined by 0.1% mass fractionSandia: Mixture-fraction of 0.79 cut-off for the dense flow modelInitially Sandia simulations over-predict penetration but the liquid length is lowerCMT predict higher mass flow rate but lower penetration compared to Sandia Argonne over-predict penetration due to high initial minimum needle lift

Slide11

Mass/area(μg/mm2)

RANS

LES

Spray A: projected mass

density – 0.1ms ASOI

X-ray

data

Argonne

CMT

IFPEN

All simulations predict quite different liquid jets

A dense liquid core near nozzle region is captured by all simulations

All simulations

over-predict liquid penetration

RANS models tend to be overly diffusive compared to LES

LES over-predict the core

length and some averaging to be comparable to x-ray results

Sandia

Slide12

Spray A: projected mass

density – 0.5ms ASOI

X-ray

Argonne

CMT

IFPEN

Mass/area

(

μ

g/mm

2)

At steady-state, the observations are consistent with earlier injection time (0.1ms)

LES simulation captures the fact that spray is off-axis, because IFPEN consider a more detailed geometry with finer mesh

G

eometry

RANS

LES

UMASS

Slide13

Spray

A: IFPEN calculation @ 0.5ms

Velocity vector plots in 3-D (left) and 2-D show the asymmetric distributions

Geometry effect on downstream spray predicted

Slide14

Spray A: projected mass

density – 0.5ms ASOI

Argonne

CMT

IFPEN

RANS simulations tend to over-predict radial diffusion;

LES simulations tend to over-predict liquid core length

IFPEN consider a more detailed geometry with finer mesh and predict off-axis spray

G

eometry

RANS

LES

Sandia

@0.25ms

UMASS

Slide15

Spray A:

2-D (YZ) Liquid Volume Fraction (LVF)

Argonne

Very high LVF (close to 1) are seen from Tomographic reconstruction x-ray data

RANS results are symmetric due to symmetric geometry usedAsymmetric liquid jet is shown from LES due to asymmetric geometry used Low LVF (max=0.65) obtained LES results due to the presence of gaseous cavitation in the [0.1,2] mm region.

X=0.1mmX=0.6mmX=2mm

RANS

0.5ms ASOI

LES

IFPEN

Sandia

Tomographic

Reconstruction

from x-ray

G

eometry

IFPEN

Others

Slide16

Spray A:

Radial profiles of projected density

density 0.5ms ASOI

0 degree view from x-ray is asymmetric at all locations

Argonne and CMT use the same geometry, and fair comparison between the EE model is obtained Sandia and UMass LES predict quite symmetric with the geometry usedAll simulations capture the shape of the radial profile, however, significant differences in the peak values and tails (IFPEN GERM model predicts some gaseous cavitation in the [0.1,2] mm region)Note: The profiles from simulations are shifted to have the same phase as the x-ray data

0.5ms ASOI

Slide17

Spray A: Radial profiles of projected density

Multiple realizations are necessary for LES to get smoother profiles

Significant difference between Argonne and CMT, although the similar EE model used (some difference in details)

Suggest

to use the new geometry for the RANS cases in future work0.5ms ASOI

Slide18

Spray A: Projected

fuel

density

0.5, 0.75,

1.0 ms Argonne RANS predicts liquid jet reaches steady-state after 0.5 ms ASOI similar than x-ray experiments.IFPEN Single-realization LES shows liquid jet reaches steady state after 0.5 ms, and may be at 0.75 ms

LESRANS

Slide19

Spray A:

Transverse Integrated Mass (TIM)

TIM increases with axial distance, all the simulations capture this trend

All simulations over-predicted the TIM which may be due to over dispersion in the radial direction

TIM at nozzle exit corresponds with the mass flow rate trends from topic 1.1CMT profile is not monotonic perhaps due to initial conditions0.5ms ASOI

Slide20

Spray A:

peak density & FWHM vs. time

Similar peak values predicted by ANL and CMT at 0.1mm and 2.0mm, IFPEN under-predicted

We see variations from RANS results from CMT due to pressure wave and compressibility effect

Fluctuations are expected from LES @ SGS which may enhance primary atomization

PeakprojecteddensityFWHM

Slide21

Spray A

:

SMD

at first 50

μs for IFPENSub-microns droplets observed for IFPEN simulation which is consistent with x-ray measurement

Slide22

Spray A:

EE vs. LE at Argonne

Projected mass density along spray axis

Mass-averaged velocity along axis

Eulerian model is better than traditional Lagrangian approach in the near nozzle region Lagrangian simulations: 62.5μ

m minimum resolution, blob injection model, 300,000 parcelsX-ray dataEulerianLagrangian

Slide23

Spray B

Slide24

Spray B: Internal flow to external sprayHole 1

Hole 2

Hole 3

UMass contribution

Mass fraction of gasHole # 3 has wider distribution Phoenix geometry

Slide25

Spray

B: spray velocity at 100

μ

s ASOI

Hole #1Hole #2Hole #3Argonne contributionPreliminary results for 3-D transient simulation at 10 microns resolutionZoomed-in view shows holes #3 has wider spray compared to other holesThe effect of geometry, needle wobble, grid alignment and

resolution to be investigated in the future workCONVERGE reduced High-resolutiongeometry

Slide26

Conclusions

Eulerian

model is suitable for the coupling nozzle and near-field dense spray

For the first time, quantitative data on spray morphology in the near nozzle region was extracted from simulation

Significant insight from different simulation approaches were obtained when compared against experimental dataThe Eulerian simulations seem to work better than Lagrangian simulations in the near nozzle regionA few key challenging areas for modeling:Liquid compressibilityTemperature variationGas in the sac

Grid resolution2-D results are good and computationally cheap, needle off-axis motion and geometric asymmetries need 3-D simulations

Slide27

All Contributors:Argonne National Laboratory: Qingluan Xue, Michele Battistoni, Sibendu SomCMT - Motores Térmicos: Pedro Martí, Raúl Payri

IFPEN:

Chawki

Habchi, Rajesh KumarSandia National Laboratories: Guilhem Lacaze, Joseph C. OefeleinUniversity of Massachusetts Amherst: Maryam Moulai, David P. SchmidtAcknowledgements

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