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www.cd-adapco.com Harry Lehtiniemi and Rajesh Rawat CD-adapco Karin Fröjd and Fabian Mauss Digital Analysis of Reaction Systems Efficient Engine CFD with Detailed Chemistry

Efficient Engine CFD with Detailed Chemistry - … Harry Lehtiniemi and Rajesh Rawat CD-adapco Karin Fröjd and Fabian Mauss Digital Analysis of Reaction Systems Efficient Engine CFD

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Harry Lehtiniemi and Rajesh RawatCD-adapco

Karin Fröjd and Fabian MaussDigital Analysis of Reaction Systems

Efficient Engine CFD

with Detailed Chemistry

Efficient Engine CFD with Detailed Chemistry 2

Challenges in CFD engine modeling

• The flow is turbulent

– Turbulence modeling required

• Spray injection and evaporation occurs

– Spray modeling is required

• Autoignition, combustion, pollutant formation chemistry

– Kinetic modeling required for various fuels

– Soot, NOx models required

Efficient Engine CFD with Detailed Chemistry 3

Efficient Engine CFD with Detailed Chemistry

Problem: Multidimensional modeling of turbulent reactive flow

Turbulent flowfield Combustion

Navier-Stokes equations ?

Efficient Engine CFD with Detailed Chemistry 4

• Species transport models

– ”Laminar”

– Techniques for speed-up

– Incorporation of turbulence interactions

• Flamelet models

– Transient interactive flamelets

– Transient flamelet progress variable model

Requirements for industrial production simulations:

Efficient handling of combustion chemistry

Fully parallel flow simulation capabilities

Outline

Efficient Engine CFD with Detailed Chemistry 5

STAR-CD and DARS-CFD

Problem: Multidimensional modeling of turbulent reactive flow

Solution I:

Turbulent flowfield Combustion

Navier-Stokes equations Species transport

Efficient Engine CFD with Detailed Chemistry 6

DARS-CFD – STAR-CD coupling

STAR-CD:

DARS-CFD

Species Yi0

Enthalpy hSpecies Yi

* Transport data Dij, ,

Efficient Engine CFD with Detailed Chemistry 7

DARS-CFD – STAR-CD coupling with DOLFA

STAR-CD:

DARS-CFD

Species Yi0

Enthalpy hSpecies Yi

*

Transport data Dij, , DOLFA

Database DOLFA

Efficient Engine CFD with Detailed Chemistry 8

Two options for considering turbulence interactions:

• Kong-Reitz model:

• User coding:

– Scaling of reaction rates

– User can modify the reaction rates for all species

DARS-CFD – STAR-CD with turbulence interactions

Efficient Engine CFD with Detailed Chemistry 9

STAR-CD and Transient Flamelet Models

Problem: Multidimensional modeling of turbulent reactive flow

Solution II:

Turbulent flowfield Combustion

Navier-Stokes equations Flamelet modeling

- Interactive

- Transient library

Efficient Engine CFD with Detailed Chemistry 10

Basics of the flamelet model

Flame: Surface of

Stoichiometric mixture

Physical Coordinates Mixture fraction coordinate Zi

1 2 3 2 3, , , , , ,t x x x Z Z Z

Efficient Engine CFD with Detailed Chemistry 11

Basics of the flamelet model

Flamelet transform:Transport of a generic scalar

Def. Scalar dissipation rate

Equations in flamelet space

Efficient Engine CFD with Detailed Chemistry 12

TIF

STAR-CD – TIF coupling

2

22

i i

i i

Y YW

t Z= +

STAR-CD

Transport of Z, Z”2, h, I

Update h and Get cell local T and Wq

Perform species pdf integration

Z, Z”2 T, Wq

Yi(Z)

Efficient Engine CFD with Detailed Chemistry 13

Soot modeling with TIF

• Turbulent diffusion flame (J. B. Moss et al. 1991) test case

• Flowfield post-processed with TIF

• Detailed kinetic soot model

– Soot precursors: cyclopentapyrene and larger PAH

– Surface growth: HACA with separate ring closure

– Oxidation: O2 and OH

– Condensation and coagulation

• Particle size distribution

– Method of moments with interpolative closure (4 moments)

– Sectional method (100 sections)

F Mauss, K Netzell, and H Lehtiniemi, Combust Sci and Tech 178 (10-11) (2006) 1871-1885

K Netzell, H Lehtiniemi, and F Mauss, Proc Combust Inst 31 (2007) 667-674

Efficient Engine CFD with Detailed Chemistry 14

Soot modeling with TIF

0

5 10-7

1 10-6

1.5 10-6

2 10-6

2.5 10-6

0 100 200 300 400

f v [:]

Height [mm]

Centerline soot volume fracition

F Mauss, K Netzell, and H Lehtiniemi, Combust Sci and Tech 178 (10-11) (2006) 1871-1885

K Netzell, H Lehtiniemi, and F Mauss, Proc Combust Inst 31 (2007) 667-674

Efficient Engine CFD with Detailed Chemistry 15

Soot modeling with TIF

Particle size distributions in the turbulent diffusion flame

K Netzell, H Lehtiniemi, and F Mauss, Proc Combust Inst 31 (2007) 667-674

Efficient Engine CFD with Detailed Chemistry 16

Transient flamelet progress variable model

• Progress variable defined using chemical enthalpy integrated over the

flamelet 1 1

298 2981 10 0

1 1

298 2981 10 0

( ( ) ) ( ( ) 0),

( ( ) ) ( ( ) 0)

s s

s s

N N

i i i u ii i

N N

i b i i u ii i

h Y Z dZ h Y Z dZ

C

h Y Z dZ h Y Z dZ

, , ,= =

, , , ,= =

, ,=

, ,

2

298 298 298

2982

1

sN

i i

i

h h hv D h

t x x,

=

+ =

Transport eqn for chemical enthalpy Transform to Z – C spaceZ C

t Z t C t t= + +

Z C

x Z x C x= +

H Lehtiniemi, F Mauss, M Balthasar and I Magnusson, Combust Sci and Tech 178 (10-11) 2006 1977-1997

2

298

2

298

hC C Cv D C

t x x h C t+ =

/

Transport eqn for the progress variable

Efficient Engine CFD with Detailed Chemistry 17

TFPV – Coupling to STAR-CD

To library

To CFD

Flamelet library module

IdentifyFlamelet, ( ), ( , ), ( , ), ( , )oxEGR p t T t t C tx x x

CFD

Transport of

2, , ,C Z Z h

( , )flameleth T Z

2( , ), ( , )Z t Z tx x

( , ) , ( , )guessT t h tx xIterateTemperature

( , ) ( ( , ), ( , ), ( ))= guess flameletT t f T t h t h Tx x x

( , )C tx

( , )T tx

( , )

( , )

T t

C t

x

x

, ( ), ( , ),

( , ), ( , )

oxEGR p t T t

t C t

x

x x

1

2

0

( ) ( ; , )i ih T Y P Z Z Z dZ

( )flameleth T

Efficient Engine CFD with Detailed Chemistry 18

TFPV – Sample engine calculation

0.32EGR ratio

361 CAStart of injection

1.24

74.35 mgFuel amount

DieselFuel type

1176 rpmSpeed

0.2 mmNozzle hole diameter

6Number of nozzle holes

15.3Compression ratio

2.0 LSwept volume

H Lehtiniemi, F Mauss, M Balthasar and I Magnusson, SAE 2005-01-3855

Efficient Engine CFD with Detailed Chemistry 19

TFPV – Sample engine calculation

Combustion progress Pressure and rate of heat release

0

5 105

1 106

1.5 106

2 106

2.5 106

3 106

3.5 106

4 106

0

100

200

300

400

500

600

700

350 360 370 380 390 400 410

Pressure [P

Rate of heat rel

Crank angle [deg]

0

0.2

0.4

0.6

0.8

1

350 360 370 380 390 400 410

Progress [:

Crank angle [deg]

___ Max progress___ Mean progress

H Lehtiniemi, F Mauss, M Balthasar and I Magnusson, SAE 2005-01-3855

Efficient Engine CFD with Detailed Chemistry 20

TFPV – Sample engine calculation CA 380

Temperature Mixture fraction T [K] Z [-]

2300

300

0.4

0

H Lehtiniemi, F Mauss, M Balthasar and I Magnusson, SAE 2005-01-3855

Efficient Engine CFD with Detailed Chemistry 21

TFPV – Sample engine calculation, CA 385

Temperature Mixture fraction T [K] Z [-]

2300

300

0.4

0

H Lehtiniemi, F Mauss, M Balthasar and I Magnusson, SAE 2005-01-3855

Efficient Engine CFD with Detailed Chemistry 22

TFPV – Sample engine calculation, CA 395

Temperature Mixture fraction T [K] Z [-]

2300

300

0.4

0

H Lehtiniemi, F Mauss, M Balthasar and I Magnusson, SAE 2005-01-3855

Efficient Engine CFD with Detailed Chemistry 23

Summary

• Strategies for efficiently incorporating detailed chemistry in

multidimensional simulations were presented:

– Direct integration of chemistry with DARS-CFD

– Flamelet approach

» Transient interactive flamelet (TIF)

» Transient flamelet progress variable model (TFPV)

• The DARS-CFD model allows for

– Turbulence interactions (Kong-Reitz) or user

– Coupling to DOLFA

– Full parallelism

Efficient Engine CFD with Detailed Chemistry 24

Summary

• The TIF model allows for

– Efficient treatment of chemistry

– Consistent handling of turbulence interactions

– Efficient treatment of complex soot and emission chemistry

– Fully parallel simulations

• The TFPV model allows for

– Consideration of effects of local inhomogeneities and local

variations of scalar dissipation rate on the chemistry

– Arbitrary large chemistry can be used in the tabulation without

influencing the CFD simulation CPU time

– Coupling to library based emission models

– Fully parallel simulations