In-cylinder flows and combustion modeling: application and validation to real and engine-
like configurations
T. Lucchini, G. D'Errico, A. Della Torre, T. Cerri, A. Maghbouli, E. A. Tahmasebi, L. Sforza, D. Paredi
Politecnico di Milano, Department of Energy
Second Two-Day Meeting on Internal Combustion Engine Simulations Using the OpenFOAM technology, Milan 26-27th November 2016.
www.engines.polimi.it
Topics 2
In-cylinder flows and combustion modeling using OpenFOAM® technology
CFD methodologies
Validation
Application
Next steps…
Lib-ICE
OpenFOAM
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Lib-ICE 3
Internal combustion engine modeling using the OpenFOAM technology
OpenFOAM-x.x.x
Lib-ICE
Library: physical models, mesh management
Applications: solvers (cold flow, SI, Diesel, after-treatment), utilities
Mesh generation
Fuel-air mixing
Combustion
Spray modeling
Engine flows1 2 3
SI combustion
Diesel combustion
Development/validationEngine simulation workflow
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Engine simulation workflow 4
Methodology
Diesel engines
SI engines
Meshmanagement
Cold flowFuel-air mixing
Combustion
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Engine simulation workflow 5
Methodology
Diesel engines
SI engines
Meshmanagement
Cold flowFuel-air mixing
Combustion
• Automatic meshgeneration
• Mesh motion• Topological
changes
• Discretization• Turbulence
models• Mesh quality
• Lagrangianspray
• Sub-models• Nozzle flow
• Simplified or detailedkinetics
• Ignition• Pollutants
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Engine simulation workflow 6
Methodology
Diesel engines
SI engines
Meshmanagement
Cold flowFuel-air mixing
Combustion
• Automatic meshgeneration
• Mesh motion• Topological
changes
• Discretization• Turbulence
models• Mesh quality
• Lagrangianspray
• Sub-models• Nozzle flow
• Simplified or detailedkinetics
• Ignition• Pollutants
Fully integrated approaches Open-Source code
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Diesel engines 8
Methodology / model development
Automaticmesh
generation
Combustionmodels
Meshhandling
Cold flow
Nozzleflow
Spraymodels
Engine CAD data
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Diesel engines 9
Mesh management
a) Main engine data b) Spray oriented block mesh
c) Combustion chamber points fit
Mesh handling
d) Spray-oriented mesh
Automatic mesh generation
Dynamic layering
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Diesel engines 10
Mesh management
a) Main engine data b) Spray oriented block mesh
c) Combustion chamber points fit
Mesh handling
d) Spray-oriented mesh
Bowl #1 Bowl #2 Bowl #3
Bowl #4 Bowl #5 Bowl #6
From CAD to SIMULATION: 10 minutes
Automatic mesh generation
Dynamic layering
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Diesel Engines: spray modeling 11
Spray A from Engine Combustion Network
10
8 m
m
2d computational mesh Spray model setup
• Injection: blob• Breakup: KHRT• Evaporation: Spalding
Test conditions
CFD setup
• Turbulence model: standard k-e with modified C1
• Fuel n-dodecane
• Nozzle diameter: 90 mm
• pinj: 50-150 MPa
• Tamb: 700-1200 K
• ramb : 7.6 – 22.8 kg/m3
VaporLiquid
Baseline (pinj = 150 MPa; Tamb = 900 K; ramb= 22.8 kg/m3)
0.00
0.04
0.08
0.12
0.16
0.0 5.0 10.0
Mix
ture
Fra
cti
on
[-]
Distance from axis [mm]
Exp
PoliMI
z = 22.5 mm
z = 45 mm
Dashed: expContinuous: calc.
0
4
8
12
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24
700 800 900 1000 1100
Ave
rage
Liq
uid
Le
ngt
h [m
m]
Ambient Temperature [K]
Experimental
Computed
Parametric variations (Tamb, ramb)
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Diesel Engines: spray modeling 12
FPT C11 Spray (collaboration with TU/e – DI N. Maes and Prof. B. Somers, FPT support)
TU/e optical vessel
• Liquid penetration: DBI• Vapor penetration: Schlieren
Operating conditions• Nozzle diameter: 0.205 mm• Ambient temperature: 900 K
CFD Setup
(a) (b)
• Consistent with the engine gridin size and structure
Spray
3D mesh
• Huh-Gosman atomization• Pilch-Erdman breakup
Turbulence modeling
• k-e with modified C1
Validation• Liquid: exp vs computed extinction
profiles
ANR C1 C2
Pinj [MPa] 150 80 150
ramb [kg/m3] 22.8 40 40
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Diesel Engines: spray modeling 13
FPT C11 Spray (collaboration with TU/e – DI N. Maes and Prof. B. Somers, FPT support)
TU/e optical vessel
• Liquid penetration: DBI• Vapor penetration: Schlieren
Operating conditions• Nozzle diameter: 0.205 mm• Ambient temperature: 900 K
CFD Setup
(a) (b)
• Consistent with the engine gridin size and structure
Spray
3D mesh
• Huh-Gosman atomization• Pilch-Erdman breakup
Turbulence modeling
• k-e with modified C1
Validation• Liquid: exp vs computed extinction
profiles
ANR C1 C2
Pinj [MPa] 150 80 150
ramb [kg/m3] 22.8 40 40
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Diesel Engines: spray modeling 14
FPT C11 Spray (collaboration with TU/e – DI N. Maes and Prof. B. Somers, FPT support)
TU/e optical vessel
• Liquid penetration: DBI• Vapor penetration: Schlieren
Operating conditions• Nozzle diameter: 0.205 mm• Ambient temperature: 900 K
CFD Setup
(a) (b)
• Consistent with the engine gridin size and structure
Spray
3D mesh
• Huh-Gosman atomization• Pilch-Erdman breakup
Turbulence modeling
• k-e with modified C1
Validation• Liquid: exp vs computed extinction
profiles
• Vapor: exp (Schlieren), calc. (mixture fraction threshold)
ANR C1 C2
Pinj [MPa] 150 80 150
ramb [kg/m3] 22.8 40 40
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Diesel Engines: cold flow 15
Steady state flow bench simulations (FPT Industrial, Gilles Hardy)
Mesh generation
Cartesian, body fitted grids with boundary layer generated with cartesianMesh (cfMesh) or snappyHexMesh (OpenFOAM)
CFD Setup
• Steady-state flow• Turbulence model: standard k-e• Porous media acts as a flow straigthner in the computational
mesh: computation of the swirl torque• Verification of angular momentum conservation across the mesh
boundaries.
This work was part of Davide Paredi MSc Thesis
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16
Computed flow field
Lift = 5 mm Lift = 10 mm0
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0.8Flow coeff. Cd [-]
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Lift = 5 mm Lift = 10 mm
Swirl number Ns [-] from Torque
Calc.
Exp.
Calc.
Exp.
Diesel Engines: cold flowSteady state flow bench simulations (FPT Industrial, Gilles Hardy)
This work was part of Davide Paredi MSc Thesis
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Diesel Engines 17
Combustion modeling
Characteristic time-scale model (CTC)
Well-mixed model
mRIF modelPassenger-car Diesel engine
Medium-duty engine operating at low-load with iso-octane fuel.
• N-dodecane spray combustion at constant volume conditions• ECN Spray-A experiment• Variation of ambient temperature, density, oxygen and injection
pressure
Density Inj. Press. O2 conc. Amb. Temp
Computed
Experimental
• Kinetic mechanism: Luoet al. (111 species, 467 reactions)
Ignitiondelay
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Diesel Engines 18
Combustion modeling
Characteristic time-scale model (CTC)
Well-mixed model
mRIF modelPassenger-car Diesel engine
Medium-duty engine operating at low-load with iso-octane fuel.
• N-dodecane spray combustion at constant volume conditions• ECN Spray-A experiment• Variation of ambient temperature, density, oxygen and injection
pressure
Computed
Experimental
• Kinetic mechanism: Luoet al. (111 species, 467 reactions)
Density Inj. Press. O2 conc. Amb. Temp
Flame lift-off
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Diesel Engines: validation 19
Spray B in Engines (from ECN, collaboration with Dr. Eagle, Dr. Malbec, Dr. Musculus)
Optically accessible engine with three hole injector
Nozzle design very similar to spray A: possibility to perform same studies in engine and constant-volume vessel.
CFD setup and tested points
• Same CFD setup used in Spray A simulations, two different combustion models tested: mRIF and well-mixed.
Tested conditions• T@SOI: 800-1000 K• Pinj [bar]: 500 – 1500 bar• O2 [%]: 13-21 %• r @ SOI: 15.2 – 22.8 kg/m3
Fuel: n-dodecane
Validation: non reactingLiquid length
Vapor distribution
CALC.
EXP
CALC.
EXP
This work is part of Amin Maghbouli PhD project
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Diesel Engines: validation 20
Spray B in Engines (from ECN, collaboration with Dr. Eagle, Dr. Malbec, Dr. Musculus)
Optically accessible engine with three hole injector
Nozzle design very similar to spray A: possibility to perform same studies in engine and constant-volume vessel.
CFD setup and tested points
Automatically generated grid
• Same CFD setup used in Spray A simulations, two different combustion models tested: mRIF and well-mixed.
Tested conditions• T@SOI: 800-1000 K• Pinj [bar]: 500 – 1500 bar• O2 [%]: 13-21 %• r @ SOI: 15.2 – 22.8 kg/m3
Fuel: n-dodecane
This work is part of Amin Maghbouli PhD project
Validation: reacting
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Diesel Engines: validation 21
EU 6 FPT Engine MD (support from FPT, DI Gilles Hardy)
Five operating points: with different EGR levels
Grid automatically generated
75% load, 15% EGR, 2 injections
25% load, 20% EGR, 3 injections
0
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350
400
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80
90
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Heat
rele
ase r
ate
[J/k
g]
Pre
ssu
re [
bar]
Crank Angle [deg]
Exp. m-RIF Well-mixed
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400
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rele
ase r
ate
[J/k
g]
Pre
ssu
re [
bar]
Crank Angle [deg]
Exp. m-RIF Well-mixed
[rpm]
bm
ep/b
mep
ma
x
800 4000
1
Cylinder pressure validation (mRIF and well-mixed)
• Initial conditions from 1D simulations
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Diesel Engines: validation 22
EU 6 FPT Engine MD (support from FPT, DI Gilles Hardy)
Five operating points: with different EGR levels
Cylinder pressure validation (mRIF and well-mixed)
10% load, 35% EGR, 3 injections
Full load, 0% EGR, 1 injection
0
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100
150
200
250
300
350
400
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20
30
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60
70
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Heat
rele
ase r
ate
[J/k
g]
Pre
ssu
re [
bar]
Crank Angle [deg]
Exp. m-RIF Well-mixed
[rpm]
bm
ep/b
mep
ma
x
800 4000
0
50
100
150
200
250
300
350
400
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160
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He
at
rele
as
e r
ate
[J
/kg
]
Pre
ss
ure
[b
ar]
Crank Angle [deg]
Exp. m-RIF Well-mixed
1
Grid automatically generated
• Initial conditions from 1D simulations
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Diesel Engines: validation 23
PCCI engine (support from FPT, DI Gilles Hardy)
PCCI combustion conditions
• High EGR rate (50%)• 3000 rpm
Computational mesh generated automatically with
the Polimi tool
0
20
40
60
80
100
120
140
-30 -10 10 30 50
Cyl.
Pre
ss
ure
[b
ar]
Crank Angle [deg]
Exp.
Well-mixed
0
50
100
150
200
250
300
350
-30 -10 10 30 50
He
at
Re
lea
se
Ra
te [
J/d
eg
]
Crank Angle [deg]
Exp.
Well-mixed
Combustion model: Well-mixed
Diesel fuel: n-dodecaneKinetic mechanism: Faravelli et al. (110 species, 300 reactions)
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Diesel Engines: validation 24
PCCI engine (support from FPT, DI Gilles Hardy)
PCCI combustion conditions
• High EGR rate (50%)• 3000 rpm
Computational mesh generated automatically with
the Polimi tool
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1
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1
1.2
OP.1 OP.2 OP.3
so
ot
(no
rmali
ze
d)
NO
x (
no
rmali
ze
d)
Calc.
Exp.
Diesel Engines: validation 25
Heavy Duty engines (support from GE Global Research, Dr. Pasunurthi)
Automatic mesh generation
Operating conditions
• SOI variation• Soot/NOx trade-off• Dual-fuel combustion
Diesel: mRIFDual-fuel: PaSRNOx: Zeldovich, soot: Moss
Engine 1: SOI variation
-20 -10 0 10 20 30
Crank Angle [deg]
Exp.
Calc.
-20 -10 0 10 20 30
Crank Angle [deg]
Exp.
Calc.
p/p
max
p/p
max
Engine 2: pollutant prediction
OP.1 OP.3
-20 0 20 40
Pcyl/P
max
Crank Angle [deg]
SOI #1, Exp.
SOI #1, Calc.
SOI #2, Exp.
SOI #2, Calc.
SOI #3, Exp.
SOI #3, Calc.
Conventional Diesel Combustion
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Diesel Engines validation 26
Heavy Duty engines (support from GE Global Research, Dr. Pasunurthi)
Setup
• Reduced mechanism for Diesel (C7H16) and natural gas•Combustion model: PaSR
-20 0 20 40
Ro
HR
/Ro
HR
ma
x
Crank Angle [deg]
Exp.
Calc.
OP 2
Validation
• Pollutants NOx : Zeldovich Soot: Moss
•Two operating points: same air/fuel ratio, different amount of injected Diesel fuel 0
0.2
0.4
0.6
0.8
1
1.2
OP 1 OP 2
NO
x/
NO
x,m
ax
Exp.
Calc.
-20 0 20 40
Ro
HR
/Ro
HR
ma
x
Crank Angle [deg]
Exp.
Calc.
OP 1
Dual-fuel combustion
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Diesel Engines 27
Next steps…
…and more…Internal nozzle flow modeling (RANS, cavitation)
Spray C & Spray D
These two single holeinjectors are defined by ECNto compare the effect ofgeometry on flow behavior.
Spray Ck factor=0, sharp edge
Spray Dk factor=1.5,
rounded edge
blockMesh grid
Spray D
Spray C
Presssure across the hole axisSpray C
Spray Ccavitated
Spray DNot cavitated
ECN contributors results
Tabulated kinetics:• Homogeneous reactors• Unsteady RIF
Transported PDF combustion modeling:• Eulerian Stochastic fields with
tabulated kinetics!
10.07
10.51
11.72
10.92
9
9.5
10
10.5
11
11.5
12
Experiments POLIMI
spray C mdot (g/s)
spray D mdot (g/s)
• mRIF with multiple injections
This work is part of Ehsan Tahmasebi PhD project
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SI Engines 29
Methodology / model development
Nozzleflow
Automaticmesh
generationSpray
models
Combustionmodels
Meshhandling
Cold flow
Engine CAD data
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SI Engines: cold flow 30
Darmstadt optical engine (collaboration with Dr. B. Bohm and DI C. P. Ding)
Four-valve engine, fully optically accessible
0 10 20 30Velocity Magnitude (m/s)
PIV measurement techniques: low repetition rate planar PIV high-speed PIV (HS-PIV) stereoscopic PIV (SPIV) tomographic PIV (TPIV).
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SI Engines: cold flow 31
Full cycle SI: Darmstadt optical engine – automatic mesh generation
snappyHexMeshGeometry-oriented block
structured meshSTL + data
• A python program automatically recognizes the direction of ducts, cylinder and valves and generates a geometry-oriented background grid
• snappyHexMesh is then run using the geometry-oriented background mesh
• The user provides combustion chamber geometry and data (bore, stroke, valve lifts)
0
2.5
5
7.5
10
0 180 360 540 720
Lift
[mm
]
Crank Angle [deg]
Exhaust
Intake
Bore 80 mm
Stroke 60 mm
Conrod 160 mm
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SI Engines: cold flow 32
Full cycle SI: Darmstadt optical engine – automatic mesh generation
snappyHexMeshGeometry-oriented block
structured meshSTL + data
• A python program automatically recognizes the direction of ducts, cylinder and valves and generates a geometry-oriented background grid
• snappyHexMesh is then run using the geometry-oriented background mesh
• The user provides combustion chamber geometry and data (bore, stroke, valve lifts)
0
2.5
5
7.5
10
0 180 360 540 720
Lift
[mm
]
Crank Angle [deg]
Exhaust
Intake
Bore 80 mm
Stroke 60 mm
Conrod 160 mm
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SI Engines: cold flow 33
Full cycle SI: Darmstadt optical engine – mesh management
Full-cycle simulations:
- Multiple meshes- Mesh to mesh interpolation
strategy.
Duration of each mesh: - User defined + quality
criteria
Initial mesh at Crank angle q0
Move mesh for Dq
Mesh quality and duration
satisfied?
qcurr = q0
qcurr = qcurr + Dq
YES
NO
Move surface geometry to current crank
angle qcurr
qcurr = qend ?
End of meshing
NO
YES
Generate a new mesh with
snappyHexMesh
q0 = qcurr
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SI Engines: cold flow 34
Full cycle SI: Darmstadt optical engine – case setup
Models and boundary conditions
Bore 86 mm
Stroke 86 mm
Compression ratio 8.5
IVO 325 CAD
IVC 485 CAD
EVO 105 CAD
EVC 345 CAD
Speed 850 rpm
Combustion no
Engine geometry data Boundary conditions
• Unsteady boundary conditions (from exp. data) imposed at inlet and outlet ports.
CFD models
• Second-order discretization(TVD)
• Turbulence model: standard k-e
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SI Engines: cold flow 35
Full cycle SI: Darmstadt optical engine – case setup
Computational mesh
• 4 mm mesh size in the ducts region;• 2 mm mesh size in the cylinder and valve region;• local refinement up to 1 mm close to cylinder head,
piston and liner boundaries;• local refinement up to 0.25 mm close to the valves
boundaries.
Mesh layouts
a) Cartesian mesh (automatically generated + snappyHexMesh)
b) Flow-oriented mesh (automatically generated + Polimitool + snappyHexMesh)
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SI Engines: cold flow 37
Full cycle SI: Darmstadt optical engine – validation
x
y
0
-10
-20
-30
x and y velocity components along four different
measurement lines located at different distances from the
cylinder head.
Uy
[m/s
]
Flow-oriented Cartesian Experimental
Y = 0 mm Y = -20 mm Y = -30 mmY = -10 mm
450 CADmid-intake
Similar behavior
between the two
grids, flow
dominated by the
incoming air jet
Flow-orientedCartesianExperimental
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SI Engines: cold flow 38
Full cycle SI: Darmstadt optical engine – validation
x
y
0
-10
-20
-30
x and y velocity components along four different
measurement lines located at different distances from the
cylinder head.
450 CADmid-intake
Similar behavior
between the two
grids, flow
dominated by the
incoming air jet
Flow-orientedCartesianExperimental
Ux
[m/s
]
Flow-oriented Cartesian Experimental
Y = 0 mm Y = -20 mm Y = -30 mmY = -10 mm
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SI Engines: cold flow 39
Full cycle SI: Darmstadt optical engine – validation
x
y
0
-10
-20
-30
x and y velocity components along four different
measurement lines located at different distances from the
cylinder head.
Flow-orientedCartesianExperimental540 CADBDC, intake
Better prediction of
the flow oriented grid:
Vortex location,
distribution of the two
main streams
Uy
[m/s
]
Flow-oriented Cartesian Experimental
Y = 0 mm Y = -20 mm Y = -30 mmY = -10 mm
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SI Engines: cold flow 40
Full cycle SI: Darmstadt optical engine – validation
x
y
0
-10
-20
-30
x and y velocity components along four different
measurement lines located at different distances from the
cylinder head.
Flow-orientedCartesianExperimental540 CADBDC, intake
Better prediction of
the flow oriented grid:
Vortex location,
distribution of the two
main streams
Ux
[m/s
]
Flow-oriented Cartesian Experimental
Y = 0 mm Y = -20 mm Y = -30 mmY = -10 mm
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SI Engines: cold flow 41
Full cycle SI: Darmstadt optical engine – validation
x
y
0
-10
-20
-30
x and y velocity components along four different
measurement lines located at different distances from the
cylinder head.
Flow-orientedCartesianExperimental660 CADmid-compression
Flow-oriented grid
better describe the
tumble vortex
structure
Uy
[m/s
]
Flow-oriented Cartesian Experimental
Y = 0 mm Y = -20 mm Y = -30 mmY = -10 mm
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SI Engines: cold flow 42
Full cycle SI: Darmstadt optical engine – validation
x
y
0
-10
-20
-30
x and y velocity components along four different
measurement lines located at different distances from the
cylinder head.
Flow-orientedCartesianExperimental660 CADmid-compression
Flow-oriented grid
better describe the
tumble vortex
structure
Ux
[m/s
]
Flow-oriented Cartesian Experimental
Y = 0 mm Y = -20 mm Y = -30 mmY = -10 mm
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SI Engines: GDI fuel-air mixing 43
Stratified engine (collaboration with IM-CNR, Ing. Sementa, Ing. Montanaro)
Optically accessible GDI engine
bmep = 7.2 bar, SA = 13 BTDC; l = 1.15 (lean)
Injection pressure[bar]
SOI[° BTDC]
Chargestratification
1 100 60 High
2 100 110 Low
3 60 60 High
4 60 120 Low
Operating points
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Pinj = 100 bar; SOI = 110 BTDC
Pinj = 100 bar; SOI = 110 BTDCFuel m.f.
Wall-film
Soot chemiluminescence
l distribution
0 0.12
SI Engines: GDI fuel-air mixing 44
Stratified engine
Optically accessible GDI engine: optical/computed data correlation
Possible sources of soot:
• Rich pockets• Wall-film
Correlated with optical soot chemiluminescence
Pinj = 60 bar; SOI = 70 BTDC
Pinj = 60 bar; SOI = 60 BTDCFuel m.f.
Wall-film
Soot chemiluminescence
l distribution
0 0.12
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SI Engines: combustion 45
Modeling
Comprehensive combustion model•Detailed description of the flame kernel growth process
via Lagrangian approach and suitable sub-models(breakdown, electrical circuit, wrinking)• Coherent flamelet model for flame propagation in the
Eulerian phase (gas)• Strict coupling between Eulerian and Lagrangian phases
Lagrangian particles for the spark-channel
Mass and energy equations solved for
the flame kernel particles
Particles convectedby the flow,
possibility to predict restrike
Sub-models
Rp Rs
Lp LsSpark
gap
Secondary circuit energy transfer
Breakdown
ri
Ti (>10000 K) Tu (300-600 K)
hQel
cell
N
i
ii
spkV
Sf
1
Flame surface density
Possibility to predict the effects of local flow, mixture conditions, turbulence, electrical circuit properties (voltage, current). Prediction of misfire also possible.
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SI Engines: combustion 46
Assessment and validation
Fully turbulent flame
(Eulerian model only)
Initial combustion stage
(Lagrangian – Eulerian coupling)
• Pressurized vessels
Applications Results
• Multi-ignition systems
• Fan-generated flow velocity and turbulence fields at the spark-gap
This work is part of Lorenzo Sforza PhD project
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SI Engines: combustion 47
Experimental validation: Herweg and Maly Engine
This work is part of Lorenzo Sforza PhD project
0
0.4
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1.6
2
0 0.2 0.4 0.6 0.8 1
En
fla
mm
ed
vo
lum
e [
cm
3]
Time after spark [ms]
Calc., 1000 rpm, l = 1.0
Calc., 1000 rpm, l = 1.0
Exp., 1000 rpm, l = 1.0
Exp., 1000 rpm, l = 1.0
l
l
l
l
Peripheral
Central
0
0.4
0.8
1.2
1.6
2
0 0.2 0.4 0.6 0.8 1
En
fla
mm
ed
vo
lum
e [
cm
3]
Time after spark [ms]
Calc., 1000 rpm, l = 1.0
Calc., 300 rpm, l = 1.0
Calc., 1250 rpm, l = 1.0
Exp., 1000 rpm, l = 1.0
Exp., 300 rpm, l = 1.0
Exp., 1250 rpm, l = 1.0
l
l
l
l
l
l
Flow field, flame propagation and plasma temperature details
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Conclusions 48
CFD modeling of in-cylinder phenomena at Polimi with OpenFOAM
• Detailed models continuously validated and improved: Fundamental studies Applied research
• Consolidated methodologies, currently applied in the context of industrial collaborations
• …but there is still a lot to do!