internal combustion engines - princeton university...q a i d i aa t b gas soot π πσ = = − ∝+...

Copyright ©2018 by Rolf D. Reitz. This material is not to be sold, reproduced or distributed without prior written permission of the owner, Rolf D. Reitz.

1 PCI-3-7, 2018

Internal Combustion Engines I: Fundamentals and Performance Metrics

Prof. Rolf D. Reitz,

Engine Research Center, University of Wisconsin-Madison

2018 Princeton-Combustion Institute Summer School on Combustion

Course Length: 9 hrs (Mon.- Wed., June 25-27)

Hour 7: Heat transfer and Spray Combustion Research

2 PCI-3-7, 2018


Short course outline:

Internal Combustion (IC) engine fundamentals and performance metrics, computer modeling supported by in-depth understanding of fundamental engine processes and detailed experiments in engine design optimization.

Day 1 (Engine fundamentals)

Hour 1: IC Engine Review, Thermodynamics and 0-D modeling Hour 2: 1-D modeling, Charge Preparation Hour 3: Engine Performance Metrics, 3-D flow modeling

Day 2 (Computer modeling/engine processes)

Hour 4: Engine combustion physics and chemistry Hour 5: Premixed Charge Spark-ignited engines Hour 6: Spray modeling

Day 3 (Engine Applications and Optimization) Hour 7: Heat transfer and Spray Combustion Research Hour 8: Diesel Combustion modeling Hour 9: Optimization and Low Temperature Combustion

Scorching Detonation Cracking

Engine heat transfer

Up to 30% of the fuel energy is lost to wall heat transfer Can influence engine ignition/knock Engine durability – catastrophic engine failure

Challen, 1998

3 PCI-3-7, 2018


Heat transfer

( ) ( ) c s rI I p Q Q Qtρ

ρ ρε∂

+∇ = − ∇ −∇ + + + +∂

u u J

Gas phase energy equation

Radiation source term

( ) ( ) ( )4

, 4r bQ I d Iπ

κ π=

= −

∫

Ω

r r Ω Ω r

( ) ( )( )

* *ln 2.1 33.34

2.1ln 2.5g p g g w

w

C u T T T y G uq

y

ρ υ+

+

− +=

+

( )( )

* ln

2.1ln 2.5p g g w

w

C u T T Tq

y

ρ+

=+

2.1 2.1wg p

qdT Gdy C yρ ν

++

= +

( )2.1 * ln

2.1ln 2.5

gg

w

Tu T TdTdy y yυ + +

=

+

Wall heat flux (account for compressibility) With radiation Without radiation

G radiative heat flux = qwr

Han, 1995 Wang, 2012

4 PCI-3-7, 2018

wall

∆y

qw * /y y u ν+ = ∆ u*


Radiative heat transfer • Radiation Transfer Equation (RTE):

• Discrete Ordinates Method (DOM)

Absorption & out-scattering

Blackbody emission

In-scattering

Direction Number m

Ordinates Weights wm ξm ηm μm

1 0.4719707 0.2158271 0.8547879 0.2617994

2 0.2158271 0.4719707 0.8547879 0.2617994

3 0.2158271 0.8547879 0.4719707 0.2617994

4 0.4719707 0.8547879 0.2158271 0.2617994

5 0.8547879 0.4719707 0.2158271 0.2617994

6 0.8547879 0.2158271 0.4719707 0.2617994


5 PCI-3-7, 2018

Wiedenhoefer, 2003

Soot and gas absorption Total absorption coefficient Soot absorption Wide band model for CO2 and H2O

2 2net soot CO H Oa a a += +

-11260 msoot soota C T= CO2 absorption bands

( )2

31

2,1b band center C T band center

CTeη η

ηε η

= −

( ) ( )1, , ln 1 , ,g e g ee

a T P L T P LL

ε = −

( )( )( )( )2 21 1 1 1 1fuel CO CO H Oε ε ε ε ε= − − − − −

Importance of soot:

1gasa T

∝ soota T∝

( ) ( ) ( ) 44

, 4r b gas sootQ a I d I a a Tπ

π σ=

= − ∝ +

∫

Ω

r r Ω Ω r 3 5gas sootT Tσ ∝ +

6 PCI-3-7, 2018


Wiedenhoefer, 2003a

Radiative heat transfer • Radiative property of absorbing gas (CO2, H2O, CO)

• Radiative property of soot:

• Total absorption coefficient:

Narrow-band model (RADCAL)

Planck-mean absorption coefficient:

1000 1500 2000 25000.0

0.1

0.2

0.3

0.4

Narrowband Model

ab

sorp

tion

coef

ficie

nt (a

tm c

m)-1

CO2 H2O CO

Temperature (K)Absorption coefficients as function of temperature

Yoshikawa, 2009


7 PCI-3-7, 2018

Wall heat transfer Conjugate heat transfer modeling ERC - Heat Conduction in Components code (HCC)

Iterative coupling between HCC and CFD code

Unstructured HCC Mesh

Wiedenhoefer, 2000

8 PCI-3-7, 2018


9 PCI-3-7, 2018

Wall heat transfer

Cut Plane

Cummins N14 engine

. . . . . . . . .

Caterpillar SCOTE engine

Wiedenhoefer, 2000


-20 -15 -10 -5 0

560

580

600

620

640

660

680

700

720

740No Radiation

Run 1 Run 2 Run 3

With Radiation Run 1 Run 2 Run 3

Peak

Pist

on T

empe

ratu

re [K

]

Start of Injection, ATDC

Φ = 0.7

Predicted piston temperature - CDC

Effect of radiation on wall heat loss Total heat loss increased by 30% due to radiation. 34% - head, 19% - liner, 47% - piston. Lowers bulk gas temperatures Results in lower NOx and higher soot NOx reduced by as much as 30% (ave)

-20 -15 -10 -5 0

2

4

6

8

10

12

14

16

NOx

[g/k

Wh]

Start-of-injection, ATDC

Φ = 0.5 Uniform Temp / No rad Non-uniform Temp / With Rad

Φ = 0.7 Uniform Temp / No rad Non-uniform Temp / With Rad

Wiedenhoefer, 2003

10 PCI-3-7, 2018


Diesel and other fuels; Constant volume chamber; various temperatures; Varying chamber densities: 13.9, 28.6, 58.6kg/m3. Schlieren imaging

Spray Combustion Research Naber, 1996

Pickett, Sandia National Laboratory, "Engine Combustion Network", https://share.sandia.gov/ecn/

Siebers, 1998

11 PCI-3-7, 2018


Liquid Penetration Length

0 1 2 30

20

40

60

80

100

Liquid

Pene

tratio

n (m

m)

time ASI [ms]

Experiment CFD

Tamb=900Kρamb=22.8 kg/m

3

Pinj=150 MPa

Vapor

Wang, 2014

https://share.sandia.gov/ecn/

Diesel combustion (Conceptual model of Dec, 1997) Time to mix fuel/air to “combustible” ratios Time at given T and P to initiate combustion

Dec, 1997

12 PCI-3-7, 2018


Diesel combustion regimes

Conventional Diesel

Dec used optical diagnostics to develop a conceptual model of conventional diesel combustion

OH exists only at periphery of the jet thin diffusion flame surrounding a soot filled jet

LTC diesel Combustion

Musculus developed a similar conceptual model for diesel LTC

Low temperature reactions fill the head of the jet with intermediates (e.g., CH2O) OH is observed across the entire jet cross-section

Dec’s conceptual model LTC conceptual model

Dec, 1997

Musculus 2006

13 PCI-3-7, 2018


Soot Modeling

Soot models

Two-step model Multi-step

Phenomenological (MSP) model

PAH chemistry

Patterson, SAE 940523 Kong, ASME 2007 Vishwanathan & Reitz, SAE 2008-01-1331 Vishwanathan & Reitz, 2009

Kazakov & Foster, SAE 982463 Tao, 2009 Tao, SAE 2006-01-0196 Tao, 2006 Vishwanathan & Reitz, SAE 2008-

01-1331

Vishwanathan & Reitz, CST 2010

Models of soot formation/oxidation – Kennedy, Prog. Energy Comb. Sc., 1997 Soot processes in engines - Tree and Svenson, Prog. Energy Comb. Sc., V2007

14 PCI-3-7, 2018


ssf so

d(M ) =M -Mdt

0.5sf sf sf C2H2M =A P exp(-E /RT) M⋅ ⋅ ⋅

so nsc ss nom

6M = W Mρ D

⋅ ⋅

Two-step model

Hiroyasu soot formation

Nagle and Strickland-Constable (NSC)

oxidation

Net soot mass

C2H2 soot precursor

ρs = Soot density = 2 g/cm3

Dnom = assumed nominal soot diameter

= 25 nm

Wnsc = NSC oxidation rate/area

Mc2h2 = C2H2 Mass, Ms = Mass of soot

“tuning” const

Hiroyasu & Kadota, SAE 760129 Nagle & Strickland-Constable, 1962

15 PCI-3-7, 2018


SANDIA spray chamber:

Vishwanathan, 2008

C2H2 inception occurs at lift-off location

Inclusion of PAH chemistry needed for accurate prediction of soot form/oxid.

Soot mass comparison

0

0.5

1

1.5

2

0 20 40 60 80 100 120Distance from Injector (mm)

Soot

Mas

s (m

icro

gm

s)

Expt.Model

Model predicted soot inception location → Lift-off length position

Performance of two-step soot model

Pickett, 2004

16 PCI-3-7, 2018


Heptane injection

C2H2 inception occurs at lift-off location

Inclusion of PAH chemistry needed for accurate prediction of soot form/oxid.

Performance of two-step soot model

Sandia experiment

Model

Pickett, 2004

17 PCI-3-7, 2018


Vishwanathan, 2008

18 PCI-3-7, 2018

Phenomenological soot models


Tao, 2006

Reduced PAH mechanism Reduced PAH mechanism of Xi & Zhong, 2006 based on detailed mechanism of Wang &Frenklach, 1997 was integrated (20 species and 52 reactions) A1 formation through propargyl radical (C3H3) Higher aromatics formed through HACA scheme (hydrogen abstraction, carbon addition)

Reaction Arrhenius parameters-A, n, E. (Units of A in mole-cm-sec-K and units of E in cal/mole)

C3H3 + C3H3 → A1 2.0E+12, 0.0, 0.0 A1- + C4H4 ↔ A2 + H 2.50E+29, -4.4, 26400.0

A1+ A1-↔ P2 + H 1.10E+23, -2.9, 15890.0 A2-1 + C4H4 ↔ A3 + H 2.50E+29, -4.4, 26400.0 A1C2H* + A1 ↔ A3 + H 1.10E+23, -2.9, 15890.0 A3-4 + C2H2↔ A4 + H 3.00E+26, -3.6, 22700.0

A1 = benzene, A2 = naphthalene, P2 = biphenyl, A3 = phenanthrene, A4= pyrene, A1- = phenyl, A2-1 = 1-naphthyl, A3-4 = 4-phenanthryl, A1C2H* = phenylacetylene radical

Vishwanathan, 2009

19 PCI-3-7, 2018


Amount of dry-carbon mass locked-up in aromatic precursors small compared to measured soot

PAH species

0 20 40 60 80 1001E-5

1E-4

1E-3

0.01

0.1

1Expt. soot mass

A4

A3

A2

A1

C2H2

Soot

/Car

bon

mas

s in

pre

curs

ors

(µg)

Distance from Injector (mm.)

15% O2

15% O2, A3 is precursor

Expt.

CFD

Improvement in soot location

Reduced PAH mechanism implemented considering up to 4 aromatic rings (pyrene) - A3 (Phenanthrene) used as precursor for soot formation model

~ peak of 0.016 ppm

Sandia expts: Pickett & Idicheria, 2006

20 PCI-3-7, 2018


Vishwanathan, 2009

Soot model implementation

1. Soot inception through A4:

2. C2H2 assisted surface growth:

3. Soot coagulation:

1 1 1ω-1= k [A ], k = 2000 {s }4⋅

2 2 2 2 2

p

ω { }

N { }p

{

4 -1= k [C H ], k = 9.0 10 exp(-12100/T) S s 2 -1S = πd cm

1/36Y ρc(s)d = cm}πρ Nc(s)

⋅ ⋅ ⋅

Surface area per unit volume

Particle size

Graphitization

YC(S) = soot mass fraction

N = soot number density (per cc)

ρC(S) = 2.0 gm/cm3

MC(S) = MW of carbon

Kbc = Boltzmann’s constant

Ca = agglomeration constant = 9

1ωC H (A ) 16C(s) + 5H 16 10 4 2→

3ωnC(s) C(s)n→

3

1/6 1/26M ρY6K Tc(s) c(s) 1/6 11/6 -3 -1bcω = 2C [ ] [N] {particles cm s }a πρ ρ Mc(s) c(s) c(s)

⋅ ⋅ ⋅

Mono –disperse locally: All soot in a comp. cell have same diameter

Vishwanathan, 2010

Leung, 1991

Leung, 1991

21 PCI-3-7, 2018


4. O2 assisted soot oxidation (NSC model):

5. OH assisted oxidation (Modified Fenimore and Jones model):

4c(s)

K PA O12 -3 -12ω = x+K P (1-x) S {mol cm s }B OM 1+K P 2Z O2

⋅ ⋅ ⋅ ⋅

x = P (P + (K /K ))T BO O2 2-2 -1 -1K = 30.0 exp (-15800/T) {g cm s atm }A

-3 -2 -1 -1K = 8.0 10 exp (-7640/T) {g cm s atm }B5 -2 -1K = 1.51 10 exp (-49800/T) {g cm s }T

-1K = 27.0 exp (3000/T) {atm }Z

⋅

⋅ ⋅

⋅ ⋅

⋅

x = fraction of A sites

(1-x) = fraction of B sites

PO2 = partial pressure of O2 KA,B,T,Z = rate constants

XOH = mole fraction of OH

γOH = OH collision efficiency = 0.13


Fenimore, 1967

22 PCI-3-7, 2018


Vishwanathan, 2010

6. PAH-assisted surface-growth

k = number of carbon atoms and j = number of hydrogen atoms,

γks = 0.3 is the collision efficiency between soot and PAH, βks = collision frequency,

di = collisional diameter of PAH, dA = size of single aromatic ring = 1.393√3 Ǻ,

μi,j = Reduced mass of colliding species = Mass of PAH,

mi = mass of PAH expressed in terms of number of carbon atoms - k

Most models consider only mono-aromatic benzene as growth species.

{ }2 3 -1bcks p PAHi,j

π K Tβ = 2.2 (d + d ) cm s2 μ⋅ ⋅

⋅ ⋅⋅

iPAH A

2md = d3

⋅


23 PCI-3-7, 2018


Vishwanathan, 2010

7. Transport equations:

M = ρYc(s) (soot species density) and N (number density) with N being treated

as passive species Thermophoresis term implemented as a source term

dnuci = 1.25 nm (~100 carbon atoms)

πηξ= 0.75 (1+ ) , η = 0.98

M 1 3

Mc(s) -3 -1S = 16ω - ω {particles cm s } for NMnuci

π 3 M = d ρ nuci nuci c(s)6

⋅

⋅ ⋅

Thermophoresis Source terms diffusion convection


24 PCI-3-7, 2018


Vishwanathan, 2010

ECN Spray A modeling

25 PCI-3-7, 2018

Temp [K] 800 850 900 1000 1100 1200 O2 [vol%] 15 13/15/17/21 13/15/17/21 13/15/17/21 13/15/17/21 13/15/17/21 Density [kg/m3] 22.8

7.6/15.2/ 22.8/30.4

7.6/15.2/ 22.8/30.4

7.6/15.2/ 22.8/30.4

7.6/15.2/ 22.8/30.4

7.6/15.2/ 22.8/30.4

Pinj [MPa] 150 50/100/150 50/100/150 50/100/150 50/100/150 50/100/150

Computational grid Related sub-models

Lift-off length Onset of the averaged OH concentration Ignition delay Maxmium dT/dt Maxmium dOH/dt

Phenomenon Model

Spray breakup KH-RT instability Evaporation Discrete multicomponent (DMC) Turbulence Generalized RNG k−ε model Combustion SpeedChem Droplet collision ROI model Near nozzle flow Gas-jet model Soot formation Multi-step phenomenological

Wang, 2014



26 PCI-3-7, 2018

Non-reacting mixing process

0 1 2 3 4 50

5

10

15

20

25

30

Liqu

id P

enet

ratio

n [m

m]

Time ASI [ms]

Expt. Simulation

ECN Spray-An-C12 non-reactingTamb=900K

Density=22.8kg/m3

Inj Dur=6.0 ms

0 1 2 3 40

20

40

60

80

100

Vap

or P

enet

ratio

n [m

m]

Time ASI [ms]

Expt. Simulation

ECN Spray-An-C12 non-reactingTamb=900K

Density=22.8kg/m3

Inj Dur=6.0 ms

Ambient conditions

O2 0.0

N2 0.8971

CO2 0.0652

H2O 0.0377

Pressure 60.45 bar

Temperature 900 K

Density 22.8 kg/m3

Injector specifications

Type Common-rail

Nozzle Single-hole, 0.89

Nozzle diameter 0.084 mm (0.090mm)

Injection pressure 150 MPa

Injection duration 6.0 ms

Injection fuel mass 13.77 mg

Liquid and vapor penetrations1

1. Engine Combustion Network, http://www.sandia.gov/ecn/

Wang, 2014


http://www.sandia.gov/ecn/


27 PCI-3-7, 2018

0.0 1.5 3.0 4.5 6.00.00

0.04

0.08

0.12

0.16

0.20ECN Spray-An-C12 non-reactingTamb=900K

Density=22.8kg/m3

Inj Dur=6.0 ms

Mix

ture

Fra

ctio

n [-

]

Radial distance [mm]

Expt. Simulation

Z=20mm

0 2 4 6 80.00

0.03

0.06

0.09

0.12

0.15 ECN Spray-An-C12 non-reactingTamb=900K

Density=22.8kg/m3

Inj Dur=6.0 ms

Mix

ture

Fra

ctio

n [-

]


Expt. Simulation

Z=30mm

0.0 2.5 5.0 7.5 10.00.00

0.03

0.06

0.09

0.12


Density=22.8kg/m3

Inj Dur=6.0 ms

Mix

ture

Fra

ctio

n [-

]


Expt. Simulation

Z=40mm

0.0 2.5 5.0 7.5 10.0 12.50.00

0.02

0.04

0.06

0.08

0.10 ECN Spray-An-C12 non-reactingTamb=900K

Density=22.8kg/m3

Inj Dur=6.0 ms

Mix

ture

Fra

ctio

n [-

]


Expt. Simulation

Z=50mm

20 25 30 35 40 45 50 55

0.05

0.10

0.15

0.20


Density=22.8kg/m3

Inj Dur=6.0 ms

Mix

ture

Fra

ctio

n [-

]

Axial distance [mm]

Expt. Simulation

Axial

Non-reacting mixing process - Fuel mixture fraction

1. Engine Combustion Network, http://www.sandia.gov/ecn/

Predicted mixture fraction distributions agree reasonable well with experimental data in both radial and axial directions by calibrating the spray model constants

Axial

Wang, 2014 Hour 7: Heat transfer and Spray Combustion Research

http://www.sandia.gov/ecn/

Reacting conditions - Soot formation vs. Ambient temperature

28 PCI-3-7, 2018

R(mm)

Z(m

m)

-10 0 10

0

10

20

30

40

50

60

0

0.2

0.4

0.6

0.8

1

1.2

1.4

R(mm)

Z(m

m)

-10 0 10

0

10

20

30

40

50

60

0

1

2

3

4

5

6

7

R(mm)

Z(m

m)

-10 0 10

0

10

20

30

40

50

60

0

2

4

6

8

10

12

14

R(mm)

Z(m

m)

-10 0 10

0

10

20

30

40

50

60 2

4

6

8

10

12

14

16

R(mm)

Z(m

m)

-10 0 10

0

10

20

30

40

50

60

5

10

15

20

800 900 1000 1100 12000

15

30

45

60

Expt. 255 species Present

Lift-

off l

engt

h [m

m]

Ambient Temperature [K]

ECN_Spray-A n-C12Ambient density 22.8 kg/m3

Solid-Expt.Open-Simulation

15% O2

800 900 1000 1100 12000.0

0.5

1.0

1.5

2.0

2.5

3.0

Expt. Simultion

Igni

tion

dela

y [m

s]

Ambient Temperature [K]

ECN_Spray-A n-C12Ambient density 22.8 kg/m3

15% O2

0 1 2 3 4 5 60

15

30

45

60

75

Soot

[ug]

Time [ms]

800 K 850 K 900 K 1000 K 1200 K

ECN Spray-Adensity-22.8 kg/m3

oxygen-15%

850K 900K 1000K 1100K 1200K

Soot ppm

Skeen, 2016

Wang, 2014 Hour 7: Heat transfer and Spray Combustion Research

Reacting conditions - Soot formation & model sensitivity

29 PCI-3-7, 2018

0 1 2 3 4 5 60

5

10

15

20

Soot

[g/k

g-fu

el]

Time [ms]

baseline surface*1.5 coagulation/3

ECN Spray-A900K, 22.8 kg/m3

R(mm)

Z(m

m)

-10 0 10

0

10

20

30

40

50

60

0

1

2

3

4

5

R(mm)

Z(m

m)

-10 0 10

0

10

20

30

40

50

601

2

3

4

5

R(mm)

Z(m

m)

-10 0 10

0

10

20

30

40

50

60

0

1

2

3

4

5

R(mm)

Z(m

m)

-10 0 10

0

10

20

30

40

50

60

0

0.2

0.4

0.6

0.8

1

1.2

1.4

1.6

1.8x 10

-6

R(mm)Z(

mm

)

-10 0 10

0

10

20

30

40

50

60

0

0.2

0.4

0.6

0.8

1

1.2

1.4

1.6

1.8x 10

-6

R(mm)

Z(m

m)

-10 0 10

0

10

20

30

40

50

60

0

0.2

0.4

0.6

0.8

1

1.2

1.4

1.6

1.8x 10

-6

C2H2 surface growth

Soot particle coagulation

baseline

C2H2 assisted surface growth process is the most important process that affects the soot emission, followed by OH oxidation process;

The surface growth process and the coagulation process affect the soot particle size;

Wang, 2014 Part 5: Diesel and SI Engine combustion

Summary and current directions Integration of soot model with multi-component vaporization and chemistry models Extension to GDI and H/P/RCCI

Organic fraction modeling: OF correlates with premixedness

Soot diameter comparisons with TEM measurements obtained from various combustion modes

InceptionH2 +

C2H2 assisted surface growth

Coagulation

Coag

ulatio

n

Oxidation by OH

Oxidation by O2

+ CO + H2

Gasoline/Diesel

Fuel-aromatic assisted

surface growth

H2 +

Need development/improvement

Fuel breakdown + fuel aromatic led PAH growth

30 PCI-3-7, 2018


Qiu, 2015 Jiao, 2015

References

31 PCI-3-7, 2018


3-7:3 Diesel Engine Reference Book, Fig. 5.1, 2nd Edition, Challen, B. and Baranescu, R., Eds., 1998.

3-7:4 Han, Z. and Reitz, R.D., "Turbulence Modeling of Internal Combustion Engines Using RNG k-e Models," Combust. Sci. and Tech. 106, 4-6, p. 267, 1995.

3-7:4 Wang, B.-L., Bergin, M.J., Petersen, B.R., Miles, P.C., Reitz, R.D., and Han, Z., " Validation of the Generalized RNG Turbulence Model and Its Application to Flow in a HSDI Diesel Engine," SAE paper 2012-01-0140, 2012.

3-7:5,10 Wiedenhoefer, J.F., and Reitz, R.D., “Multidimensional Modeling of the Effects of Radiation and Soot Deposition in Heavy-duty Diesel Engines,” SAE paper 2003-01-0560, SAE Transactions, Volume 112, Section 3, Journal of Engines, pp. 784-804, 2003.

3-7:6 Wiedenhoefer, J.F., and Reitz, R.D., “A Multidimensional Radiation Model for Diesel Engine Simulations with Comparison to Experiment,” Numerical Heat Transfer: International Journal of Computation and Methodology Part A: Applications, 44 (7): 665-682, 2003a.

3-8:7 Yoshikawa, T., and Reitz, R.D., "Effect of Radiation on Diesel Engine Combustion and Heat Transfer," JSME Journal of Thermal Science and Technology, February, 2009.

3-7:8,9 Wiedenhoefer, J., F., and Reitz, R.D., “Modeling the Effect of EGR and Multiple Injection Schemes on I.C. Engine Component Temperatures,” Journal of Numerical Heat Transfer, Part A, Vol. 37, pp. 673-694, 2000.

3-7:11 Naber, J. D. and Siebers, D. L., "Effects of Gas Density and Vaporization on Penetration and Dispersion of Diesel Sprays, SAE Technical Paper 960034, 1996.

3-7:11 Siebers, D.L., “Liquid-Phase Fuel Penetration in Diesel Sprays,” SAE 980809, 1998.

3-7:11 Pickett, L., Sandia National Laboratory, "Engine Combustion Network", https://share.sandia.gov/ecn/ , 2007.

References

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3-7:12,13 Dec, J. E., “A Conceptual Model of D.I. Diesel Combustion Based on Lased Sheet Imaging,” SAE Technical Paper No. 970873, SAE Transactions, 106(3), 1319-1348, 1997.

3-7:13 Musculus, M. P. B., “Multiple Simultaneous Optical Diagnostic Imaging of Early-Injection Low-Temperature Combustion in a Heavy-Duty Diesel Engine,” SAE Paper 2006-01-0079, 2006.

Slide 3-7:14

Patterson, M. A., Kong, S.-C., Hampson, G. J. and Reitz, R.D., "Modeling the Effects of Fuel Injection Characteristics on Diesel Engine Soot and NOx Emissions," SAE Paper 940523, SAE Transactions, Vol. 103, Section 3, Journal of Engines, pp. 836-852, 1994.

Kong, S.-C., Sun, Y., and Reitz, R.D., “Modeling Diesel Spray Flame Lift-Off, Sooting Tendency and NOx Emissions Using Detailed Chemistry with Phenomenological Soot Model,” ASME J. Gas Turbines and Power, Vol. 129, pp. 245-251, 2007.

Vishwanathan, G., and Reitz, R.D., "Numerical Predictions of Diesel Flame Lift-off Length and Soot Distributions under Low Temperature Combustion Conditions," SAE 2008-01-1331, SP-2185, Compression Ignition Combustion Processes, 2008.

Vishwanathan, G., and Reitz, R.D., "Modeling Soot Formation Using Reduced PAH Chemistry in n-Heptane Lifted Flames with Application to Low-Temperature Combustion," ASME J. Gas Turbines and Power, Vol. 131 / 032801/1-7, 2009.

Kazakov, A., and Foster, D.E., “Modeling of Soot Formation during DI Diesel Combustion Using a Multi-Step Phenomenological Model,” SAE paper 982463, 1998.

Tao, F., Reitz, R.D., Foster, D.E., and Liu, Y., "A Nine-Step Phenomenological Diesel Soot Model Validated Over a Wide Range of Engine Conditions," International Journal of Thermal Sciences, Vol. 48, pp. 1223–1234, 2009.

Tao, F., Foster, D.E., and Reitz, R.D., “Soot Structure in a Conventional Non-Premixed Diesel Flame,” SAE Paper 2006-01-0196, SAE Transactions, Vol. 115, Section 4, Journal of Fuels & Lubricants, 2006.

Tao, F., Foster, D.E., and Reitz, R.D., “Characterization of Soot Particle Distribution in Conventional, Non-Premixed DI Diesel Flame Using a Multi-Step Phenomenological Soot Model,” Proceedings of 31st International Symposium on Combustion, The Combustion Institute, Pa, 2006

Kennedy, I. M. (1997) Models of soot formation and oxidation. Prog. Energy Combust. Sci., 23, 95.

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Vishwanathan, G., and Reitz, R.D.,”Development of a Practical Soot Modeling Approach and its Application to Low Temperature Diesel Combustion,” Combustion Science and Technology, Vol. 182, Issue 8, pp.1050-1082, 2010.

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3-7:15 Hiroyasu, H., and Kadota, T., “Models for Combustion and Formation of Nitric Oxide and Soot in DI Diesel Engines,” SAE paper 760129, SAE Transactions, 85, 1976.

3-7:15 Nagle, J., and Strickland-Constable, R.F., “Oxidation of Carbon between 1000-2000°C,” Proceedings of the fifth carbon conference, 1, Pergammon Press, 154, 1962.

3-7:16,17 Pickett, L. M., and Siebers, D.L., “Soot in Diesel Fuel Jets: Effects of Ambient Temperature, Ambient Density, and Injection Pressure,” Combustion and Flame, 138, 114-135, 2004.

3-7:16,17 Vishwanathan, G., and Reitz, R.D., "Numerical Predictions of Diesel Flame Lift-off Length and Soot Distributions under Low Temperature Combustion Conditions," SAE 2008-01-1331, SP-2185, Compression Ignition Combustion Processes, 2008.

3-7:18 Tao, F., Foster, D.E., and Reitz, R.D., “Characterization of Soot Particle Distribution in Conventional, Non-Premixed DI Diesel Flame Using a Multi-Step Phenomenological Soot Model,” Proceedings of 31st International Symposium on Combustion, The Combustion Institute, Pa, 2006

3-7:19 Xi, J. and Zhong, B., 2006, “Reduced Kinetic Mechanism of n-Heptane Oxidation in Modeling Polycyclic Aromatic Hydrocarbon Formation in Diesel Combustion,” Chemical Engineering and Technology, 29, pp.1461-1468.

3-7:19 Wang, H. and Frenklach, M. (1997) A detailed kinetic modeling study of aromatics formation in laminar premixed acetylene and ethylene flames. Combust.Flame, 110, 173.

3-7:19,20 Vishwanathan, G., and Reitz, R.D., "Modeling Soot Formation Using Reduced PAH Chemistry in n-Heptane Lifted Flames with Application to Low-Temperature Combustion," ASME J. Gas Turbines and Power, Vol. 131 / 032801/1-7, 2009.

3-7:20 Pickett, L.M., and Idicheria, C.A., “Effects of Ambient Temperature and Density on Soot Formation under High EGR Conditions,” THIESEL 2006 Conference on Thermo- and Fluid Dynamic Processes in Diesel Engines, 2006.

3-7:21-24 Vishwanathan, G., and Reitz, R.D., ”Development of a Practical Soot Modeling Approach and its Application to Low Temperature Diesel Combustion,” Combustion Science and Technology, Vol. 182, Issue 8, pp.1050-1082, 2010.

3-7:21 Leung, K. M., Lindstedt, R. P. and Jones, W. P. (1991) A simplified reaction mechanism for soot formation in nonpremixed flames. Combust.Flame, 87, 289.

3-7:22 Fenimore, C. P. and Jones, G. W. (1967) Oxidation of soot by hydroxyl radicals. J.Phys.Chem., 71, 593.

3-7:25-29 Wang, H., Ra, Y., Jia, M., and Reitz, R.D., "Development of a Reduced n-dodecane-PAH Mechanism and its Application for n-dodecane Soot Predictions," FUEL, Vol. 136, pp. 25-36, http://dx.doi.org/10.1016/j.fuel.2014.07.028, 2014.

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3-7:28 Skeen, S., Manin, J., Pickett, L., Cenker, E., Bruneaux, G., Kondo, K., Aizawa, T., Westlye, F., Dalen, K., Ivarsson, A., Xuan, T., Garcia-Oliver, J.M., Pei, Y., Sibendu Som, S., Hu, W., Reitz, R.D., Lucchini, T., DErrico, G., Farrace, D., Pandurangi, S.S., Wright, Y.M., Chishty, M.A., Bolla, M., and Hawkes, E. , "A Progress Review on Soot Experiments and Modeling in the Engine Combustion Network (ECN)," SAE Int. J. Engines 9(2): doi:10.4271/2016-01-0734., 2016

3-7:30 Qiu, L., and Reitz, R.D., "Investigating Fuel Condensation Processes in Low Temperature Combustion Engines," Journal of Engineering for Gas Turbines and Power, Vol. 137, pp. 101506-1, DOI: 0.1115/1.4030100, 2015.

3-7:30 Jiao, Q., and Reitz, R.D., "The Effect of Operating Parameters on Soot Emissions in GDI Engines," SAE Int. J. Engines 8(3):2015, doi: 10.4271/2015-01-1071, 2015

Slide Number 1Slide Number 2Slide Number 3Heat transferSlide Number 5Soot and gas absorptionSlide Number 7Slide Number 8Slide Number 9Slide Number 10Spray Combustion ResearchSlide Number 12Diesel combustion regimesSoot ModelingTwo-step modelSlide Number 16Slide Number 17Phenomenological�soot modelsReduced PAH mechanismPAH speciesSoot model implementationSlide Number 22Slide Number 23Slide Number 24Slide Number 25Slide Number 26Slide Number 27Slide Number 28Slide Number 29Summary and current directionsReferencesReferencesReferencesReferences

internal combustion engines - princeton university...q a i d i aa t b gas soot π πσ = = − ∝+...

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