ABSTRACTThe spray plume geometry and fuel atomizationcharacteristics of the gasoline direct-injection (GDI) multi-hole injectors are of paramount importance with respect tothe GDI engine homogenous-charge combustion andemission characteristics. A major component of the GDIcombustion system development is the optimization of thespray-targeting and mixture preparation. Significant R&Defforts are directed towards optimization of the nozzle designand the manufacturing process in order to achieve optimummulti-plume spray characteristics.

The Volume-of-Fluid Large-Eddy Simulation (VOF-LES) ofthe injector internal flow and near-field primary atomizationhas been receiving attention as a tool to enable analysis of theinfluence of nozzle design on the key spray parameters andreduce reliance on hardware trial-and-tests for multi-objectivespray optimizations. In combination with current state-of the-art computational fluid dynamic (CFD) methods forsimulation of spray atomization and transport processes, theyafford a notable capability to expedite the injector valve-group and spray targeting optimization in order to reduce thetime and costly hardware iterations.

The present publication reports studies of a GDI multi-holeinjector valve-group and the corresponding spray plumes,with the aid of the current state-of-the-art CFD methods. TheLES method is applied to study the structure and primarybreakup of a single plume from a GDI multi-hole injector. Acomplementary study comprising the injector internal flowwith the conventional Reynolds-averaged CFD method,coupled to the simulation of the spray atomization andtransport processes using the stochastic Discrete Dropletmethod, has been performed. The correlation of simulatedspray geometry with experimental data is encouraging.

INTRODUCTIONThe advance of GDI engine technology has imposed stringentrequirements on the injector with respect to fuel meteringaccuracy, spray atomization and robustness against depositbuildup in the harsh combustion environment. The GDImulti-hole injector is required to deliver the exact desiredspray plume trajectory, plume cone angle, optimum sprayatomization (for minimum spray penetration), in addition touniform hole-to-hole volumetric flow rate. Theserequirements, in conjunction with the need for adaptation ofthe injector static flow and spray plume pattern to suitspecific engine geometry and in-cylinder charge motion, hasrendered the injector a key component of the GDI system. Inturn, it has rendered the valve group a crucial part of theinjector, as both the static flow rate and the spray plumepattern are determined by the valve group, and the selectionof geometrical parameters such as nozzle-hole diameter,necessary to achieve the required flow rate, simultaneouslyaffect both the spray plume geometry and atomization.

The optimization of the multi-hole GDI injector spray plumepattern in GDI combustion systems is a crucial step of thecombustion system development to meet the fuelconsumption and emission objectives [1, 2]. The goal is toachieve optimum in-cylinder mixture uniformity, for thebroadest engine load - speed operating conditions, withminimum spray-wall interactions. The definition of theoverall best spray pattern with respect to fuel economy andemission is accomplished through a process of (a) definingcandidate spray plume patterns (i.e. spray targeting) based ongeometric constraints (i.e. avoidance of spray interaction withintake valves, liner, etc.) and allowances for potential sprayplume deflections, due to intake charge motion interactions[3], (b) CFD simulations of in-cylinder mixture preparation inorder to analyze the in-cylinder charge-spray interactions,mixture preparation quality and wall wetting for a selection

GDI Multi-Hole Injector Internal Flow and SprayAnalysis

2011-01-1211Published

04/12/2011

Bizhan Befrui, Giovanni Corbinelli, Mario D'Onofrio and Daniel VarbleDelphi Powertrain Systems

Copyright © 2011 SAE International

doi:10.4271/2011-01-1211

of engine load-speed conditions, and (c) injector hard-warebuild and engine combustion test over a broad engine load-speed map. Hence, an accurate and general GDI spray model,capable of reflecting the influence of nozzle geometry on thespray structure and atomization, can significantly reduce thereliance on injector build-and-test iterations and expedite thecombustion system development process.

Since it is not possible to decouple the metering functionfrom the spray generation function, it is crucial to gain anunderstanding of the relations between the geometricalparameters of the GDI multi-hole valve group and the flowrate, spray trajectory and atomization characteristics [4] inorder to be able to define a valve group that deliversoptimized injector spray pattern and atomization to achievethe optimum fuel consumption and emissions. The capabilityto analyze the influence of nozzle hole design parameters onthe spray plume characteristics with a computational methodis of significant value in the GDI injector valve-group designoptimization. It affords major reduction of the hardwareiteration loop for spray targeting optimization, and enablesprediction of the spray characteristics, a priori, for in-cylinderCFD simulations of mixture preparation.

The recent studies of the GDI conical and planar sprays haveshown strong dependence of the spray structure andatomization on details of the injector valve group design [5,6]that necessitate simulation of the injector internal flow inorder to correctly predict the spray primary breakup structure.The experimental evidence indicates similar dependence ofthe spray plume structure on the geometric features of theGDI multi-hole nozzles, in addition to the expected influenceof the of pintle-sack geometry on the flow upstream of thenozzle holes. The implication is that accurate prediction ofthe spray macro-structure and atomization requires simulationof the injector internal flow in order to adequately describethe influence of nozzle geometry on the nozzle-exit liquid jethydrodynamic conditions.

This paper describes investigations of the GDI multi-holeinjector internal flow and spray simulations, with the aid ofthe multi-fluid VOF-LES and the CFD standard RANScomputational methods. The VOF-LES method offers thelargest capability for analysis of the GDI primary jet breakupand influence of the nozzle design parameters, but itsindustrial application is constrained by the substantialcomputational requirements. The Reynolds-averaged Navier-Stokes method is the CFD standard method adopted in allcommercial CFD codes and is broadly employed for Eulerianmultiphase analysis of the injector internal flow [7, 8]. Thisprovides the nozzle-exit flow conditions required foradequate definition of the spray initial conditions within theframe-work of the Lagrangian “discrete droplet model” [9]for stochastic spray atomization and transport processes. Thespray simulation results are compared with the experimental

data, in order to ascertain the predictive accuracy of thecomputational method.

INJECTOR NOZZLE-FLOWANALYSISLARGE- EDDY SIMULATION METHODConservation Equations of Multi-Phase SystemThe mathematical model comprises the transport equationsfor conservation of mass and momentum of a two-phase flowsystem that is composed of two immiscible, compressible orincompressible, Newtonian fluids, and includes the interfacesurface tension. Accordingly, the single set of conservationequations that describe the flow of the two-phase mixture are[5]:

(1)

(2)

Where, U is the velocity, ρ is the density, σ is the surfacetension coefficient, τ is the stress tensor, κ is the curvature ofthe liquid surface, n represents a unit vector normal to theliquid surface, and the operators ▿ () and ▿ · () signify thegradient and the divergence operations, respectively. Theintegral term on the right-hand-side of equation (2) representsthe momentum source due to surface tension: it acts only atthe interface (indicated by the Dirac function δ (x)) over theentire liquid surface S (t).

The VOF-Based Interface Tracking MethodThe principle idea of the “Volume-of-Fluid” approach is thata two- (or indeed multi-) phase system can be represented asa mixture of phases in which the phase-fraction distributionincludes sharp, yet resolvable, transitions between the phases.Accordingly, the interface in a two-phase flow system iscomputed with the aid of the transport equation for the liquidvolume fraction as the indicator function to locate theinterface. The transport equation for the phase fraction a is:

(3)

According to the definition of α, the mixture thermo-physicalproperties are calculated as

(4)

(5)

The VOF interface capturing/tracking method is a simple andflexible approach to simulation of multi-phase systems withfree surfaces, especially for circumstances that the surfacetension effects are not dominant. The main problems of VOFmethod relate to the accuracy of the numerical approachesused to ensure that the interface remains sharp, yet not undulyaffected by numerical dispersion, conservation and meshalignment bias.

Large-Eddy-Simulation MethodThe LES-VOF equations are derived from equations (1), (2),(3), through a process of local volume averaging of phase-weighted properties, that entails decomposition of thedependent variables into resolvable and sub-grid scales ofturbulent fluctuations and application of a filter that removesthe sub-grid scales fluctuations from direct simulation. Thefiltering process, in conjunction with the non-linear terms inequation (2), produce additional terms, involving correlationof the variable fluctuations at sub-grid scales that requireclosure through mathematical models. The most notable ofthese terms is the sub-grid-scale (SGS) stress that representsthe effect of unresolved scales of turbulence on themomentum transport process and its viscous dissipation. TheSub-Grid-Scale stress is defined as:

(6)

The closure of the sub-grid-scale stresses is affected througha sub-grid-scale eddy-viscosity model that adopts a one-equation transport model for the sub-grid turbulent kineticenergy (κ), in conjunction with the Smagorinski's dissipationmodel. A detailed description of the adopted sub-grid scalemodels and the associated literature can be found in Ref. 5.

The Numerical Solution MethodThe OpenFOAM finite-volume CFD code [10] is used forsolution of the LES-VOF system of conservation equations.OpenFOAM incorporates special treatment of the phase-fraction transport equation in order to preserve a sharp liquid-gas interface, and employs temporal and spatial discretizationschemes that are second order accurate but preserve theproper limits on physically-bounded flow variables.

Simulation Domain and MeshThe simulation domain, boundary conditions and thecomputational mesh are presented in Figure 1. Thecomputational domain is comprised of a segment of theinjector valve-group geometry containing one nozzle holeand its immediate downstream ambient. The structuredcomputational mesh consists of a 550k mesh of the injectorvalve group (seat, nozzle hole, counter-bore) and a 300kmesh of the ambient environment. The mesh distributionprovides mesh resolution of O (3-5 μm) within the valvegroup and resolution of O(5-20 μm) in the ambient. As shownin Figure 1(b) the highest mesh resolution is in the vicinity ofnozzle hole domain, with the mesh expansion (in the stream-wise and lateral directions) in the ambient domain. Asystematic mesh refinement study was not performed, butincrease of mesh resolution to 1.4M has not altered thesignificant fluid dynamic features of the jet breakup. Thecomputational time-step is dynamically controlled duringcalculations, according to the Courant-Friedrichs-Lewy [11]stability criterion.

The flow boundary conditions are:

• Inlet: Uniform velocity profile, with a prescribed magnitudecorresponding to the fuel system pressure.

• Circumferential symmetry planes: symmetric flowboundary conditions

• Ambient: uniform pressure boundary condition for allambient boundaries

The pintle motion is not included in the simulation.Instationary simulation of the fuel injection is performed onthe fixed geometry mesh, without representation of the pintlemotion. To this effect, the simulation initial condition is thatthe valve-group - from the inlet to the pintle sealing band - isfilled with liquid at rest (the remaining volume of thecomputational domain is air at ambient condition). At theinlet boundary, the liquid phase velocity is accelerated to itsfinal value (corresponding to the nozzle hole static flow) overa short time interval (of order 2-3 μs) and then is keptconstant.

The liquid phase physical properties in the simulation arethose of n-Heptane, but evaporation is not considered.

Simulation ResultsFigure 2 presents the LES simulations of a single plume of aGDI multi-hole injector for the fuel system pressure of20MPa. The results show a non-uniform liquid flow atentrance of the nozzle hole. The streamlines highlight theinfluence of the pintle presence on the flow entrancecondition to the nozzle hole, showing a predominant flowdirection from the injector seat periphery (i.e. upstream of the

nozzle hole) and insubstantial flow contribution from theinjector sac region.

The flow at the nozzle entrance and within the nozzleresembles a waterfall, with liquid phase separation at thenozzle entrance and a segregated two-phase flow within thenozzle hole, due to the small nozzle 1/d typical of the GDImulti-hole injectors. The LES results in Figure 2 showinitiation of Kelvin-Helmholtz instabilities within the nozzleand most pronounced growth of the instabilities in thecounter-bore domain. The simulation result indicatesinitiation of the liquid jet breakup in the downstream vicinityof the counter-bore exit plane.

The plots of instantaneous distributions of VOF and thevelocity magnitude (at t = 25μs) on a display-plane through

the centre of the nozzle hole are presented in Figure 3. Theseillustrate: (a) the flow separation at the flow-approach part ofthe nozzle entrance edge, (b) segregated two-phase flow inthe nozzle, (c) initiation and growth of Kelvin-Helmholtzinstabilities on the liquid jet free surfaces, especially withinthe counter-bore domain, (d) primary jet breakup in thevicinity of the counter-bore exit, (e) significant acceleration,accompanied by velocity perturbations of the liquid jet, at theentrance to the nozzle and downstream. Interestingly, theresults show a deviation of the liquid jet trajectory from thenozzle-hole axis angle for this nozzle geometry, layout andfuel pressure. The simulation indicates two potential causesof the plume deviation angle, namely the lateral jet inertiadue to flow separation at the nozzle entrance and the patternof the jet primary breakup downstream of the nozzle hole.The phenomenon is in accord with the experimental data

Figure 1. Geometry and computational mesh for VOF-LES simulation of a single GDI nozzle-hole flow (1/5 full geometry)

Figure 2. VOF-LES simulation results, Fuel Pressure = 20MPa

reported in the literature [4] (and the measurement data inFigure 10) and provides evidence of the spray plumedeviation angle as a “nozzle” fluid dynamic phenomenadependent on the valve-group geometric parameters.

It worth noting that the “bubbles” shown in the VOF plot inFigure 3 (in the sac volume and nozzle entrance) is not due tocavitation, but due to the slow scavenging of the air in thisregion (at the start of simulation) by the liquid flow.

REYNOLDS-AVERAGED SIMULATIONMETHODThe Mathematical Method for a Multi-PhaseSystemThe commercial CFD code AVL-FIRE [12] is employed forthe simulation of the multi-fluid (liquid, vapor, ambient air)flow within the injector and its near-field ambientenvironment. The computational method adopted in AVL-FIRE involves solution of independent, coupled sets ofReynolds-averaged conservation equations of a multi-fluidsystem. The set of conservation equations, for every fluid-stream, comprises of the Reynolds-averaged equations of theconservation of mass (of the components), momentum (theNavier-Stokes equations) and the total enthalpy [7]. In

addition, transport equations for the k-epsilon turbulencemodel are solved to account for the stochastic effects ofturbulence on the mass, momentum and enthalpy transportprocesses. The simultaneous solution of the three equationsystems enables determination of the field-distributions of theliquid, the fuel vapor and the air volume fractions.

Commonly, this CFD method is referred to as ReynoldsAveraged Navier Stokes (RANS) method, and is a standardCFD methodology for turbulent flow applications in industry.The main draw-back of the method, inherent in the Reynoldsaveraging methodology, is that the simulation resultsrepresent statistical averages of the flow variables, andtherefore stochastical variations (such is shot-to-shot sprayatomization variation) are assimilated in the simulationresults. In addition, owing to the limitations of the turbulencemodels for complex flows (e.g. separated or rotational flows)the predictive accuracy of the method needs to be verified forthe specific flow of interest.

Here, the results of isothermal three-fluid (liquid, vapor,ambient air) simulations of the injector internal and thenozzle downstream ambient domain are performed.

Figure 3. Contour plots of the instantaneous VOF and velocity fields at t = 25 μs ASOI (fuel pressure = 20MPa)

Computational Domain and MeshFigure 4 presents the solution domain and the computationalmesh for the three-fluid simulation of the injector internalflow and the nozzle near-field down-stream ambient. Thecomputational mesh is comprised of 900K cells - with spatialresolution of 10μm - in the injector domain and 300K cells inthe ambient. The computational mesh spatial distribution isnon-uniform: the highest mesh resolution is in the nozzle holeand counter-bore domains, with gradual successive meshcoarsening in the downstream ambient, as depicted in Figure4. The “ambient domain” boundaries are defined at sufficientdistance from the valve-group, to minimize potentialinfluence of their prescribed boundary condition on the liquidphase solutions.

Initial and Boundary ConditionsThe methodology for simulation of the flow and cavitationrequires prescription of the liquid and the gaseous-phase(s)thermo-physical conditions for the initial conditions, and atthe boundaries of the solution domain. With respect thegaseous phases, this entails additional prescription of thefluids' physical conditions (c.f. bubble number density [12])at the start of calculations and at the boundaries.

The initial conditions for all calculations are the injectorinternal flow domain filled with liquid, at rest, with nominal-zero (1. e-6) volume-fraction(s) of the gaseous phase(s). Inaddition, the ambient domain contains air at rest (withrelevant thermodynamic conditions). The flow boundaryconditions at inlet are prescribed static pressure, withnominal-zero vapor and air volume fractions. The boundarycondition at the ambient domain surface is prescribed staticpressure.

Single-hole Multi-Fluid Flow SimulationFigure 5 presents the RANS multi-fluid simulation results forthe single-hole geometry of Figure 1 on a display-planethrough the axis of the nozzle hole, which corresponds to thedisplay-plane for presentation of VOF-LES results in Figure3. The results pertain to a fuel pressure of 20MPa.

The contour plot of the statistical average VOF distribution at= 25 μs ASOI, in Figure 5, is similar to the instantaneousresults of VOF-LES simulation in Figure 3. It depicts theflow separation at the nozzle entrance and a two-phase (liquid- air) flow in the nozzle and the counter-bore domains. Thenotable difference is the absence of prediction of the jetprimary breakup process. This is due to the significantinherent physical and numerical momentum diffusion of themethodology employed and lack of an accurate diffusion-preventive liquid-air interface tracking method. The contourplots of velocity show flow acceleration at the entrance andthrough the length of the nozzle, concurrent with thereduction of the flow area indicated by the VOF contour plot.However, the diffusive effect of turbulent viscosity (andnumerical discretization scheme) is substantial to smear thesignificant velocity gradients within the liquid jet, and at itsinterface with the ambient air, predicted by the VOF-LESsimulations in Figure 3. In addition, the RANS simulationdoes not predict the jet - nozzle axis deviation angle for thisnozzle layout / geometry.

In spite of these differences, the RANS and VOF-LESmethod predict closely similar valve-group hydrodynamicflow parameters (nozzle static flow rate, pressure loss,discharge coefficient) in close agreement with theexperimental data, providing indirect support that thepredicted mean liquid-phase flow pattern and velocitydistribution are correct. This suggests that the RANSsimulation of the injector internal flow may be sufficient for

Figure 4. Geometry and computational mesh of the GDI multi-hole injector and ambient domain

describing the conditions of the issuing liquid jet forsimulation of the ensuing spray.

Complete Injector Multi-Fluid Flow SimulationFigure 6 presents the RANS multi-fluid simulation of thecomplete injector internal flow, for a fuel pressure of 10 MPa.This fuel pressure is the condition of the experimental spraydata that are used for assessment of the computationalmethod in the succeeding section. The liquid phase in thesimulation is n-Heptane, with the cavitation enabled.

As evident in Figure 6, the injector valve-group has a 6-holesymmetric pattern. The contour plots of VOF and velocitydistribution at the nozzle and counter-bore exit planesillustrate the extent of hole-to-hole variations of the liquid jetmass flow rate and the stream-wise velocity profile, hence thehole-to-hole variations of the liquid jet momentum flux. Thetransformation and lateral spread of the VOF distributionsbetween the nozzle exit and at the counter-bore exit planesare indicative of the extent of the liquid jet - ambient airinteractions within the counter-bore domain.

COUPLED NOZZLE FLOW - SPRAYSIMULATIONMETHODOLOGY ANDCOMPUTATIONAL MESHWith the objective of a simulation methodology potentiallycapable of accurate prediction of the spray plume structure ofa GDI multi-hole injector, the VOF, mean velocity andturbulence distributions at the injector nozzle exits, obtainedfrom the injector internal flow simulation, are utilised forprescription of the spray initial conditions in the Lagrangian“discrete droplet method” (DDM) for stochastical spraysimulation [9].

The spray simulation method incorporates adapted WAVEspray atomisation models [12, 13] for the primary andsecondary atomisation, including mechanism of the dropletshedding process. The initial droplet conditions for individualplumes are calculated from their respective liquid-phasecondition (the liquid core geometry, velocity and turbulenceintensity) at the injector counter-bore exit plane, from theRANS injector internal flow simulations. The VOF-LESsimulation of the valve-group is utilised to estimate the initial“blob” size distribution.

Figure 5. Contour plots of instantaneous VOF and Velocity fields at t = 25 μs ASOI (fuel pressure=20MPa)

The spray simulation replicates the experimental set-up forthe “patternator” measurement of the spray foot-print. Figure7 depicts the spray simulation domain, which contains aportion of the ambient (partitioned by a cylindrical surface)that surrounds the injector nozzles and the spray, and extendsbeyond the patternator plate (included in order to account foreffect of its presence on the spray).

SIMULATION RESULTS ANDCOMPARISON WITH DATAFigure 8 presents the simulation of the spray plume geometry,atomization, spray impingement on the patternator plate andformation of the liquid film footprints. In the presentsimulation, the droplet-wall interactions are disabled, thus alldroplets that impinge the patternator plate will adhere to itand form liquid foot-prints associated with the plumes.

Figure 6. Contour plots of mean VOF and velocity fields (fuel pressure=10MPa)

The simulation results pertains to n-Heptane fuel andinjection conditions of fuel system pressure 10 MPa, a pulse-width of 1.5 ms and a spray simulation time of 2.5ms.

The trajectory and cone angle of individual spray plumes arepredicted using the corresponding nozzle exit velocity profileand turbulence intensity data, from the injector internal flowsimulation, and the common WAVE primary and secondaryatomization models. Thus they present a measure of thepredictive capability of the simulation method. The results inFigure 9 present a comparison of the predicted spray plumegeometry with the optical imaging data, from two orthogonalview directions. The spray cone angles are defined accordingto the SAE J2715 [14] from the spray imaging data andsuperimposed on the simulation results. There is goodagreement, with respect to the plume cone angles (especiallyup to 40 mm from nozzle) and the spray total angle. There isindication of smaller lateral dispersion of spray plume fronts(penetration > 40 mm) in the simulation: the potential sourcesof this discrepancy are the atomization model, induced airentrainment (prohibiting dispersion) or vaporization of the

droplets within the periphery of the plumes (comparison ofthe injected and collected fuel on the patternator, in bothexperiments and simulation, indicate significant sprayvaporization).

Figure 10 presents a comparison of the experimental sprayplume foot-prints, measured with the patternator at Z=50 mmdownstream of the injector tip, with the simulations. Theexperimental spray plume foot-prints present accumulation ofmany injections repetitions (∼ 500), so assimilate the shot-to-shot variations of the spray plume trajectories. In addition tothe foot-prints, the locations of intersection of thecorresponding nozzle-hole axes trajectories with thepatternator plane are marked. Figure 11 provides thecorresponding quantitative comparison of the measured andpredicted spray plume-centre trajectory angles.

Several aspects of the results are notable:

• Extent and pattern of deviations of the measured plumefoot-print centres from the corresponding nozzle-hole axes

Figure 7. Computational mesh (1/4 of the complete domain) for the Lagrangian spray simulations

Figure 8. Simulated spray plume geometry and interaction with the patternator plate

trajectory intersection locations, illustrating the influence ofthe valve-group geometry (nozzle layout, angle, etc.)

• Good to moderate agreement between the measured andpredicted location and geometry of the plume foot-printcentres, depending on the lay-out of the nozzle holes. Thediscrepancy in the foot-print size is in part due to under-prediction of the plume front dispersion (indicated in Figure9) and in part due to the shot-to-shot variation of the plumetrajectories in the experiment (causing enlargement of thefoot-print).

• Good agreement of the measured and predicted hole-to-holevariation of the injected mass (as indicated by the liquid filmheight), taking into consideration the manufacturingtolerances (evidenced by absence of the x-coordinatesymmetry of the plume foot-prints in the experimental data)

• The simulated spray plume trajectories are aligned with thenozzle-hole axes trajectories. Hence, the largest discrepancybetween the predicted and measured foot-print centrelocations is for the plumes with largest deviation of the plumecentre from the associated nozzle-hole axis trajectorylocation. Therefore, although the spray-aerodynamic andgravitational-field interactions could play a role, the expectedprimary cause of this discrepancy is the deviation of theliquid jet trajectory at the counter-bore exit from the nozzle-hole axis.

Overall, the results provide evidence of the predictiveaccuracy of the methodology for simulation of the spraygeometry, hole-to-hole injected mass distribution and theindividual plume trajectory and cone angle. The mainshortcoming of the methodology stems from the evidentinability of the RANS method to reproduce the deviationangle between the issuing liquid jet and the nozzle hole axis,depending on the valve-group geometric parameters. Furtherinvestigation of this topic is in progress.

CONCLUSIONSThe VOF-LES results highlight the specific flowcharacteristics of the GDI multi-hole valve group. Theinfluence of pintle presence on the non-uniform flowseparation at entrance to the nozzle is notable. The resultsshow significant velocity gradients (hence turbulence andvorticity generation) caused the flow separation at the nozzleentrance and within the core of the liquid jet in the nozzle.This is responsible for the pressure loss and low dischargecoefficient of the nozzle hole, but it promotes the liquid jetbreakup. The VOF-LES simulations show initiation andgrowth of the Kelvin-Helmholtz instabilities, caused by theliquid jet - air interactions within the counter-bore space, andthe ensuing jet primary breakup in close downstream vicinityof the injector.

Figure 9. Comparison of the simulated spray plume trajectories and cone angles with imaging data (two orthogonal viewdirections)

The results highlight the potential capability of the VOF-LESmethod for analysis of the hydrodynamics of liquid jetbreakup and the influence of the GDI multi-hole valve-groupdesign details on the spray breakup / atomization process.The capability of VOF-LES to predict the deviation anglebetween the nozzle-hole axis and the issuing liquid jettrajectory is notable. The RANS counter-part simulationdemonstrates that it predicts the nozzle flow separation and

the significant hydrodynamic variables (pressure drop, nozzledischarge coefficient, etc) closely similar to the VOF-LESmethod and the experimental data. The notable shortcomingof the RANS method is the evident inability to predict the jettrajectory deviation from the nozzle hole-axis.

A corollary of the combined LES / RANS simulation activityis that the discrepancy between measured and predicted spray

Figure 10. Comparison of the predicted and measured spray plume patternator foot-prints (location, geometry and liquid-filmheights)

Figure 11. Quantitative comparison of the predicted and measured plume foot-print centre of gravity

plum foot-print geometry is likely associated with theinability of the RANS simulation of the injector internal flowto predict the deviation angle between the nozzle hole axisand the issuing liquid jet.

The coupled Eulerian-Lagrangian method for spraysimulation has shown potential for correlation of the GDImulti-hole valve-group design and the important features ofthe spray plume geometry and atomization. The goal is toenable analysis of the spray targeting - from the GDI multi-hole valve-group geometry to the in-cylinder mixtureformation - through CFD simulation, prior to injectorhardware build and dynamometer combustion tests. Furtherevaluation and refinement of the components of themethodology are under progress.

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ACKNOWLEDGMENTSThe authors would like to thank N. Mastro and L. Markle ofDelphi Technical Center Rochester for support of theexperimental investigations and valuable exchanges.

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