Topic 3 – Vaporizing Diesel SprayGA Tech Sandia Sandia - 675 Simulations of quasi-steady liquid...
Transcript of Topic 3 – Vaporizing Diesel SprayGA Tech Sandia Sandia - 675 Simulations of quasi-steady liquid...
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Topic 3 – Vaporizing Diesel Spray Spray A and Spray B
Presenter: Caroline Genzale, Georgia Tech September 5th, 2015
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ECN1: Detection of liquid boundary near the LL is sensitive to optical method and setup
Extinction offers referenced intensity measurement.
Some history: We’ve made several attempts to standardize liquid length measurements within the ECN.
Side-illumination, high-res., f/4
Side-illumination, fast, f/4
Side-illumination, saturated, f/1.2
Sheet-illumination, saturated, f/1.2
Head-illumination, f/2
Diffuser back-illumination
I/I0
532 nm CW
532 nm CW
532 nm CW
532 nm CW
Halogen lamp
Halogen lamp
0 2 4 6 8 10 12 14 16 18 200
0.20.40.60.8
11.21.41.61.8
2
Axial distance [mm]
Cen
terli
ne o
ptic
al th
ickn
ess
τ [-]
Beam steering
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• “Extinction profiles measured on the centerline are somewhat different between institutions.”
• “The variations observed are believed to come from differences in optical arrangement (mainly illumination and collection angles).”
• “A methodology must be setup to consistently measure liquid length from extinction without the influence of beam steering.”
Some history: We’ve made several attempts to standardize liquid length measurements within the ECN.
ECN2: Adoption of DBI imaging to measure I/Io
Beam steering
ECN4: Fredrick Westlye will provide us an update on this topic next!
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More history: We’ve seen consistent predictions of liquid/vapor penetration between CFD codes, but not in the details of the spray.
ECN2: Significant differences between CFD codes in the predicted spray structure.
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More history: We’ve seen consistent predictions of liquid/vapor penetration between CFD codes, but not in the details of the spray.
ECN3: Even when downstream profiles are consistent, upstream spray structure can vary greatly. These regions can be coincident with LOL region.
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Following up on prior themes: •Further assess institutional variations in DBI measurements and develop a standardized (and consistent) measurement approach for liquid penetration. •Pursue further insight into phase transition behavior at Spray A conditions. Vaporization data at new target conditions: •Spray A multiple injection conditions •Spray B •Spray C and D injectors
Experimental Objectives for Vaporizing Diesel Sprays
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Following up on prior themes: • Deep dive into near-nozzle spray structure variations between
codes and sensitivities to ambient conditions. • Understand impact of these differences on combustion
predictions. Simulations at new target conditions: • Spray A multiple injection conditions.
Modeling Objectives for Vaporizing Diesel Sprays
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Spray A Parametric Modeling Study
CMT Adrian Blanco, Raul Payri
PoliMi Tommaso Lucchini, Gianluca D’Errico
GA Tech Gina Magnotti, Caroline Genzale
Bosch Edward Knudsen
Sandia Guilhem Lacaze, Joe Oefelein
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• Injector 675
• 89.4 µm, Ca = 0.98, Aeff = 6.15x10-
9 m2, ρliq = 713 kg/m3
• Standard injection rate profile provided to all institutions
Target conditions for Spray A parametric modeling study
Parametric Variable O2 [%] Tamb [K] ρamb [kg/m3] Pinj [bar]
Standard Spray A 0 900 22.8 1500
Temperature 0 700 22.8 1500
0 1200 22.8 1500
Density 0 900 7.6 1500
0 900 15.2 1500
Injection Pressure 0 900 22.8 500
0 900 22.8 1000
00.5
11.5
22.5
3
-0.5 1.5 3.5 5.5
Mas
s Flo
w R
ate [
g/s]
Time [ms]
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Comparison of spray and CFD models
PoliMi GA-Tech CMT Bosch Sandia
Code OpenFOAM CONVERGE OpenFOAM Cascade Technologies Raptor
Spray model Blob, KH-RT Blob, KH-RT Eulerian Σ-Y model Eulerian dense fluid
Eulerian dense fluid
Evaporation model
Frossling drop evaporation
Frossling drop evaporation
State relationships from locally
homogeneous flow assumption
Peng-Robinson EOS
Real fluid model
Turbulence model RANS, k-ε RANS, k-ε RANS, k-ε LES LES Dynamic
Model Mesh
Dimensionality Grid size
2D 0.5 mm
3D 0.0625 –
2 mm
2D 0.009 mm –
0.7 mm
3D w/ internal nozzle
3.2M cells
3D 0.002 mm –
0.1 mm
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Standard Spray A Condition
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Time ASI [ms]0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 2
LP [m
m]
0
5
10
15
BoschPolimiCMTGA TechSandiaSandia - 675
Simulations of quasi-steady liquid penetration cluster around the experimental data, similar to previous workshops.
Liquid boundary definition: Axial position where path-averaged liquid volume fraction is 0.15%
0.5 mm x 0.5 mm LVF computation grid
Spray A
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Differences in fuel vapor fraction upstream arise from combined effects of spray model and momentum coupling.
Spray A
Axial Distance [mm]0 2 4 6 8 10 12
Ua
vg
[m/s
]
0
100
200
300
400
500
600CMTPolimiSandia
Axial Distance [mm]0 5 10 15 20 25
Z [-]
0
0.1
0.2
0.3
0.4
0.5
0.6
CMTPolimiSandia
Axial Distance [mm]0 2 4 6 8 10 12
LVF
[-]
0
0.02
0.04
0.06
0.08
0.1
0.12
0.14
0.16
0.18
0.2
CMTPOLIMIGATechSandia
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14 T Di t [ ]-2 -1 0 1 2
LVF
[-]
0
0.005
0.01
0.015
0.02
CMTPOLIMIGA Tech
Jet dispersion well matched, but predicted spray structures vary significantly between institutions as we approach the LL.
Transverse Distance [mm]-2 -1 0 1 2
Z [-]
0
0.1
0.2
0.3
0.4
CMTPOLIMI
Spray A time averaged spray structure
1 - 3 ms
7.5 mm
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Predicted spray structures vary significantly between institutions as we approach the LL.
Spray A time averaged spray structure
1 - 3 ms
9.0 mm
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SMD profiles can take on different distribution behaviors as breakup and evaporation proceed.
Spray A time averaged spray structure
1 - 3 ms
Which solution is the “accurate” one?
3 mm
7.5 mm
9 mm
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Spray A Parametric Study: Exploration on what information we’d really like to have
to validate evaporating sprays
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4
6
8
10
12
14
16
18
20
650 850 1050 1250
LL [m
m]
Temperature [K]
CMTPolimi - MassGA TechSandia Data
4
6
8
10
12
14
16
18
20
650 850 1050 1250
LL [m
m]
Temperature [K]
CMTPolimi - MassPolimi - LVFGa Tech - MassGA Tech - LVFSandia Data
Revisit of global model response to parametric variations in ambient and operating conditions.
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0
5
10
15
20
25
5 10 15 20 25
LL [m
m]
Density [kg/m3]
CMTGA Tech - MassGA Tech - LVFPolimi - MassPolimi - LVFSandia Data - 675
Revisit of global model response to parametric variations in ambient and operating conditions.
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4
6
8
10
12
14
16
18
20
40 80 120 160
LL [m
m]
Injection Pressure [MPa]
CMTPolimi - MassPolimi - LVFSandia Data - 677Sandia Data - 675
Revisit of global model response to parametric variations in ambient and operating conditions.
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-1 -0.5 0 0.5 1
1 0 5 0 0 5 1
How do the spray and evaporation models respond to changes in ambient and operating conditions?
CMT
PoliMi
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-1 -0.5 0 0.5 1
Comparison of LVF behavior and accumulated mass… they both show *some* sensitivity to ambient conditions.
PoliMi
-1 -0.5 0 0.5 1
Acc
umul
ated
Mas
s [%
]
96.5
97
97.5
98
98.5
99
99.5
100
= 22.8 kg/m 3
= 15.2 kg/m 3
= 7.6 kg/m 3
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Axial Distance from LPL [mm]-1 -0.5 0 0.5 1
Ta m b
= 1200 K
Ta m b
= 900 K
Ta m b
= 700 K
1 0 5 0 0 5 1
LVF
av
g
-0.03
-0.02
-0.01
0
0.01
0.02
1
Axial Distance from LPL [mm]-1 -0.5 0 0.5 1
Pin j
= 50 MPa
Pin j
= 100 MPa
Pin j
= 150 MPa
Gradients near LL show that LVF shows more sensitivity to correctly capture the liquid boundary
PoliMi
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Is there a potential pathway forward to validated modeling of the local liquid structure and evaporation process?
Magnotti & Genzale, Atomization and Sprays, 2015.
10-2 10-1 100 101 10210-25
10-20
10-15
10-10
10-5
Droplet Size [µm]
Cex
t [m2 ]
Cext data
Rayleighα d 6
Mie α d 2
Theoretical dependence of light-scattering cross-section on drop size
Modeling of light extinction measurements could provide some validation at vaporizing conditions.
Quality extinction measurements needed (next talk).
Validation of near-spherical droplets in these regions (previous talk).
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• Old news revisited: Validation of evaporating sprays solely against liquid and vapor penetration measurements does not adequately validate the evaporation process.
• Somewhat old news revisited: It is difficult to isolate effects of spray model choices on near-nozzle mixture discrepancies. – Lagrangian models lead to errors in gas momentum exchange
• Error cascades to affect breakup and vaporization models – Eulerian models don’t necessarily predict evaporation well either
• To accurately validate evaporating sprays, we need a validation methodology that responds to changes in the mixing and evaporation rate appropriately.
• Liquid volume fraction is physically consistent with extinction and scattering measurements AND drops rapidly near the liquid length.
• High quality extinction measurements may help.
Conclusions from Spray A parametric modeling study:
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Spray A Multiple Injections
Modeling CMT: Adrian Blanco, Raul Payri
Polimi: Tommaso Lucchini, Gianluca D’Errico Experiments
Sandia: Julien Manin, Scott Skeen, Lyle Pickett
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Spray A multiple injection target conditions
O2 [%] Tamb [K] ρamb [kg/m3] Pinj [bar]
Standard Spray A 0 900 22.8 1500
Split Injection 0.5 ms – 0.5 ms dwell – 0.5 ms Pilot-Main 0.3 ms – 0.5 ms dwell – 1.2 ms
• Same model setup as parametric study. Nozzle 675.
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Multiple injection simulations compare well between institutions and with Sandia vapor penetration data.
CMT PoliMi
Split Injection 0.5 ms – 0.5 ms dwell – 0.5 ms Pilot-Main 0.3 ms – 0.5 ms dwell – 1.2 ms
Sandia vapor data
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Transient mixing process is well matched between CMT and PoliMi downstream of liquid regions.
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Spray B
Experiments CMT: Alberto Viera, Raul Payri
Nozzle 211200 Sandia: Julien Manin, Scott Skeen, Lyle Pickett
KAIST: Yongjin Jung Nozzle 211201
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Simultaneous Mie scatter and DBI at CMT
Continuous light source
Blue LED
HS Camera Mie-scatter 32 kfps HS Camera with long-range
microscopic lens DBI 82.1 kfps
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Two different liquid penetration measurement techniques and two spray orientations: •Horizontal Configuration
– Mie scattering: Phantom v710, 105 mm, f/2.8, 80 kfps
•Vertical Configuration – Diffused back illumination (DBI),
Photron, 100 kfps
Mie scatter and DBI imaging at Sandia
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Sandia has shown that liquid penetration profile is correlated with transient spreading angle behavior.
Jung et al. SAE 2015-01-0946
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CMT also measures a transient liquid penetration rate, but with a shorter penetration length.
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• First look at modeling multiple injections: predictions of mixture profiles and transient behavior is not any worse that steady-state Spray A. – Near-nozzle mixture discrepancies, but these are rapidly diffused by
vaporization and transient mixing process. Spray B measurements: • Transients in measured liquid penetration is well correlated with
transient spreading angle behavior. • Measurements at CMT display similar transient behavior, but injection
conditions are different so it’s hard to make further conclusions. • Seems to be a consistent trend that CMT measures shorter LL’s than
Sandia. • Modeling of the transient behavior will require more than the usual
Lagrangian spray modeling approach.
Moving forward with Spray A multiple injections and Spray B:
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• Old news revisited: Validation of evaporating sprays solely against liquid and vapor penetration measurements does not adequately validate the evaporation process.
• Somewhat old news revisited: It is difficult to isolate effects of spray model choices on near-nozzle mixture discrepancies. – Lagrangian models lead to errors in gas momentum exchange
• Error cascades to affect breakup and vaporization models – Eulerian models don’t necessarily predict evaporation well either
• To accurately validate evaporating sprays, we need a validation methodology that responds to changes in the mixing and evaporation rate appropriately.
• Liquid volume fraction is physically consistent with extinction and scattering measurements AND drops rapidly near the liquid length.
• High quality extinction measurements may help.
Conclusions from Spray A parametric modeling study:
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EXTRA SLIDES
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ECN4: Fredrick Westlye will provide us an update on this topic next!
Some history: We’ve made several attempts to standardize liquid length measurements within the ECN.
ECN3: Still differences in measured LL between institutions. No significant advancement of “standardized”
LL measurement method. Spray A Measured Liquid Length
Sandia - 675 CMT - 675 IFPen - 678 TU/e - 679
11.7 9.7 10.5 10.3
Parametric Spray A Conditions
Sandia - 675 CMT - 675 ∆
900 K, 7.6 kg/m3 16.0 22.8 43%
700 K, 22.8 kg/m3 14.5 17.6 21%