Lib-ICE: a C++ object oriented library for ICE simulation...

Lib-ICE: a C++ object oriented libraryfor ICE simulation - acoustics and aftertreatment

F. Piscaglia , A. Montorfano, G. Montenegro, A. OnoratiDipartimento di Energia, POLITECNICO DI MILANO

Hrvoje JasakFSB - UNIVERSITY OF ZAGREB and WIKKI LTD

Henrik RuscheWIKKI GMBH

The Lib-ICE R© project: an overview

Lib-ICE R©is a set of libraries and solvers for IC engine simulations developed using the OpenFOAM R©

technology:

Class : user defined type representing one part of the problem to solve (mesh, matrix, field, ...)

Library : definition and implementation of related classes and functions (finite volume library, turbu-lence model library, mesh tools library..)

Applications : collection of object of different classes interacting each others

2/31 Federico Piscaglia, Dip. di Energia, Politecnico di Milano

Outline

Classes :

- Boundary conditions for noise simulation

- pressureJump class

Applications and Solvers :

- Silencer simulation

- Numerical solvers for flows through porous media

- Diesel Exhaust Aftertreatment modeling (DPFs, SCR systems)


Silencers performance: calculation of the Noise Reduction

Noise reduction in ICE is defined as the ratio of Sound Pressure Level spectrums (Lp ) between points Aand B

200 400 600 800 1000 1200 1400 1600 1800 200010

20

30

40

50

60

70

Frequency [Hz]

Tra

nsfe

r F

unct

ion

[dB

]

NoiseReduction(fn ) = TF (fn) = −Lp,B (fn)

Lp,A(fn)= −

20logpB,n(rms)

pref

20logpA,n(rms)

pref

(pref = 2 · 10−5 Pa)

The location of microphone B is not included in the computational domain. For small perturbations , theoutlet may be considered as a monopole source radiating spherical waves (Lifshitz):

p(r , t) =ρ0Send

4πr

d

dt

[

Uend

(

t −r

a0

)]

where Uend is the predicted trace of flow velocity at the outlet patch


Fluid-dynamic response of silencersTo calculate the acoustic performance (Transfer Function, Transmission Loss) of silencers, all acousticfrequencies of the field of interest must be excited: hence, large-band acoustic sources are needed.

200 400 600 800 1000 1200 1400 1600 1800 20000

5

10

15

20

25

30

35

40

45

50

Frequency [Hz]

Tra

nsfe

r F

unct

ion

[dB

]

2DW.case

ExperimentalOpenFOAM

A new boundary condition acousticSourceFvPatchField to model different types of acousticsources has been developed in the OpenFOAM R© technology and has been used together with thecompressible solver sonicFoam for the acoustic simulation of engine mufflers

SINGLE SINUSOID PULSE WHITE NOISE FREQUENCY SWEEP

0 0.02 0.04 0.06 0.08 0.1101.26

101.28

101.3

101.32

101.34

101.36

101.38

101.4

time [s]

Pre

ssur

e [k

Pa]

0 0.02 0.04 0.06 0.08 0.1101.2

101.4

101.6

101.8

102

101.2

101.4

101.6

101.8

time [s]

Pre

ssur

e [k

Pa]

0 0.02 0.04 0.06 0.08 0.1101.15

101.2

101.25

101.3

101.35

101.4

time [s]

Pre

ssur

e [k

Pa]

0 0.02 0.04 0.06 0.08 0.1101.26

101.28

101.3

101.32

101.34

101.36

101.38

101.4

time [s]

Pre

ssur

e [k

Pa]


acousticSourceFvPatchFieldinlet

type acousticSourceTotalPressure;

sourceType "whiteNoise";

U U;

phi phi;

rho rho;

psi none;

gamma 1.4;

refPressure 100000;

f0 10;

fn 2000;

step 10;

amplitude 50;

value uniform 100000;

Different kinds of time-varying perturbations areapplied at the inlet boundary patch

Discretisation schemes and solver parametershas been set when sonicFoam is used with thenew b.c.

Ad-hoc developed run time controls ensure correctcase setup and avoid aliasing due to poorfrequency resolution or to non physical frequencysignals distorting the spectrum in the chosen range(Oppenheim and Schaffer)

Algorithms to post process data have been developed to improve the quality of the results:

- Numerical filtering to eliminate non physical high frequency components (above fmax )

- Ensemble averaging of data over time

- Data smoothing

GEOMETRY A: E130 GEOMETRY B: E178


Simulation results: expansion chamber E130

2D 2D Wedge 3D

200 400 600 800 1000 1200 1400 1600 1800 20000

5

10

15

20

25

30

35

40

45

50

Frequency [Hz]

Tra

nsfe

r F

unct

ion

[dB

]


200 400 600 800 1000 1200 1400 1600 1800 20000

10

20

30

40

50

60

Frequency [Hz]

Tra

nsfe

r F

unct

ion

[dB

]


200 400 600 800 1000 1200 1400 1600 1800 20000

10

20

30

40

50

60

Frequency [Hz]T

rans

fer

Fun

ctio

n [d

B]



Simulation results: expansion chamber E178

2D 2D wedge 3D

200 400 600 800 1000 1200 1400 1600 1800 20005

10

15

20

25

30

35

40

45

Frequency [Hz]

Tra

nsfe

r F

unct

ion

[dB

]

5mm.case


200 400 600 800 1000 1200 1400 1600 1800 20000

5

10

15

20

25

30

35

40

45

50

Frequency [Hz]

Tra

nsfe

r F

unct

ion

[dB

]

2DW.case


200 400 600 800 1000 1200 1400 1600 1800 20005

10

15

20

25

30

35

40

45

Frequency [Hz]

Tra

nsfe

r F

unct

ion

[dB

]

3D.case



New Internal Face Condition: Pressure Jump

Development and validation of a new internal face condition (pressureJump) to model a steady-statepropagation of a sudden finite change in flow properties within the computational domain

pressureJump class has been used to model thin membranes with known velocity/pressure-dropcharacteristics , by the implementation of the Darcy law

Development of transientSimplePorousFaceFoam solver for flows through thin porous mem-branes

Validation on the basis of experimental measurements carried out on ICE simulations


porousJump: mathematical model

The formulation of the Navier Stokes equations for flows through porous media is:

∫

Ω

∂(ρ~u)

∂tdΩ +

∫

A

ρ~u~u · ~n dA = −

∫

Ω

~∇p dΩ +

∫

Ω

~∇ · ~σ dΩ +

∫

Ωρ~g dΩ + ~S

where the sink term ~S is written as follows:

~S =

npor∑

i=1

(

µ · ws

kp~ufi⊥ +

1

2βρ~u2fi⊥

)

Afi

and the face-normal velocity uw is defined as:

~ufi⊥ =(

~Uf · ~n)

~n

Being the porous jump term a discountinuous surface sink term, a special handling procedure is re-quired to correctly insert it into Navier-Stokes continuous equations.


porousJump: variables arrangement

Discretization in OpenFOAM R©is based on the collocated arrangement , that allows significantadvantages in complicated solution domains, especially when the boundaries have slope disconti-nuities or the boundary conditions are discontinuous.

Across the porous jump, velocity and pressures between neighbour cells may be very different;hence, the pressure-velocity handling of the collocated variable arrangement may cause that massis poorly conserved .

The problem does not occur if a staggered variable arrangement is used. A pseudo-staggeredapproach has been used to preserve sharp value changes in pressure and velocity field acrossthe porous jump. The method mimics the operation of a solution procedure devised for astaggered variable arrangement, but keeping the collocate d variables .


transientSimplePorousFaceFoam: solver implementation

Governing equations are solved for steady flows by means of the segregated pressure correctionTRANSIENT-SIMPLE algorithm.

MOMENTUM EQUATION is solved for the face flux φ in-stead of cell-centered velocity U. Face velocities ~uf are calcu-lated from the corrected flux fields.

The cell-centred velocity is regarded as a secondary vari-able , which is used in the construction of the momentumequation

Pressure gradient ~∇p is also calculated on cell faces

∂

∂t

∫

Ωρ~udΩ +

∫

Ω

~∇ ·(

ρ~un−1· ~un

)

· ~n d~A = −

∫

~A∇p · ~n d~A+

∫

Ω

~∇ · ~σ dΩ + ~Sn

where the sink term ~S is calculated explicitly and is written as follows:

~Sn =

npor∑

i=1

[

µn−1fi

wth

kfi~unfi⊥

+1

2ρn−1fi

βfi~un−1fi⊥

· ~unfi⊥

]

· Af +

∫

Ω

F · µfn−1

a2~un−1ax · dΩ


transientSimplePorousFaceFoam: governing equations

According to the pseudo-staggered arrangement , the momentum equation may be written in terms offace-based variables:

af unf +

∑

l

af ,lunf ,l = Qn

f −

(

δp

δxi

)n−1

f

−1

δx

(

µ · wth~uf

kp+

1

2βρ~u2f

)

- Convection term is treated in a semi-implicit fashion

- Stress tensor is treated in a fully-implicit fashion

- Other source terms are treated either explicitly or implicitly

af , af ,l and Qf are respectively the diagonal, the off-diagonal coefficients and the source termsinterpolated on cell faces

In the term Q (RHS of the linear system) sink terms depending on the velocity at the previous timestepun−1i,P are included

Gas density ρ is computed by the energy equation; it does not vary significantly , because gasflow is almost incompressible ( Ma < 0.3).


transientSimplePorousFaceFoam: governing equations

Then, the predicted face velocity ~uf may be obtained from the source and the neighbouring values:

u∗f =Qn

f−

∑

l af ,lunf ,l

Af

−1

Af

[(

δp

δxi

)n

f

−1

δx

(

µ · wth~u∗

f

kp+

1

2βρ~un−1

f· ~u∗f

)]

hence:

u∗f =

Qnf −

∑l af ,l u

nf ,l

Af−

1Af

(

δpδxi

)n

f[

1−1Af

1δx

(

µ·wthkp

+ 12βρ~un−1

f

)] =

HfAf

−~∇pAf

[

1−1Af

1δx

(

µ·wthkp

+ 12βρ~un−1

f

)]

The substitution of u∗f

into the continuity equation for steady compressible flows:

~∇ · (ρf ~u∗

f ) = 0

is written as:

~∇·

φ− ρf∇pAf

1−1Af

1δx

(

µ·wthkp

+ 12βρ~un−1

f

)

= 0

where:

φ =

[

ρfHf

Af

]

· ~Sf = ρf uf · ~Sf


DPF Modeling by OpenFOAM R©: basic assumptionsFor ICE applications , the volume of the porous medium may be neglected and porous wall char-acteristics may be defined as a cell-face properties.

1D schematization of filter channels : cell size over the transverse direction is taken equal to thechannel size

- Straightforward mesh generation of the filter, easier definition of the whole layout

- Faster simulations , reduced number of computational cells to model detailed geometry

- New class dpfPorousWall: derived from porousJump, it implements some DPF-specificfeatures:

- Automatic geometry detection and selection of porous faces;

- Gas-channel walls friction model;

- Soot transport and deposition with filtration model;

- New solver dpfFoam makes use of dpfPorousWall functionalities with modified RAS tur-bulence models


Case Setup and Automatic Mesh Handling

The computational domain is partitioned into two regions, corresponding to different sub-domains:

FLUID REGION

- inlet pipe

- plug-ends

- filter channels

- outlet pipe

SOLID REGION

- filter segments

Any block of the computational mesh is generated separately by a grid generator. During this firststep, all the inner cells (and their faces) in the computational domain are defined as fluid

Blocks are merged into one block

Plug-ends, filter channels and closed-ends in the monoliths are set as cell face properties in the DPFby AUTOMATIC ALGORITHMS developed as applications in the OpenFOAM R© technology


Case Setup: Filter Monolith

The three-dimensional mesh geometry of the monolith is generated from a 2D sketch; faceSetscustomization for DPF applications is performed by an automatic algorithm.

inlet and outlet ends of the monolith show a typical “chessboard”arrangement, where channels are alternatively open and closed; cell-faces representing the closed-ends of filter channels are automati-cally set as ”walls ”

plug ends are automatically generated by extruding inlet and outletends of the monolith and then adding the resulting mesh to the originalone; they have non-permeable walls, that are automatically groupedand set as ”walls”

porosity is modeled as a cell-face property ; porous walls dividinginlet and outlet channels of the monolith are grouped in a faceSetdefined as ”porous”

The solid region for the DPF material and the cement strips is usedto model the heat exchange to the surroundings


Turbulence models

Flow conditions in after-treatment devices are characteri zed by very different Reynolds num-bers:

- flow regime in outlet and inlet cones is fully turbulent;

- flow into the filter monolith is laminar;

Standard turbulence class in OpenFOAM R© requires modifications to be used with after-treatmentcomponents:

- turbulent viscosity is not calculated in monolith cells;

- particular interpolation techniques are needed for turbulent fields (k, ε,ω);


Hydrodynamics

Table: Specification of the Filter Used in theExperiments and Simulations [7].

filter type EX-80 100/17

channel length [mm] 114/165

plug length [mm] 10

channel width [mm] 2.28

porous wall thickness, ws [mm] 0.432

cell density [CPSI] 100

porosity 48%

mean pore size [µm] 12

- The experimental setup was though to have only a core (having a diameter of 67.5 mm ) of the filtersubjected to the flow ; dry air flow supplied from a compressor was directed through a 50.8 mmdiameter pipe, where a flow straightener was included to minimize the upstream flow fluctuations

- Downstream of the flow straightener, air passed through a flow meter (for flow rates measurements),then through a pipe having a length of 10 pipe diameters, to be sure that the turbulent flow velocitywas completely developed before approaching the filter

- Static pressure drop across the filter was measured by a differential manometer (0-1500 Pa)

- Minor flow temperature variations were monitored using a thermocouple inserted in the flow pathupstream of the filter


Code validation: hydrodynamicsTwo filters of different length were tested

- L=114 mm

- L=165 mm

Flow conditions : pout = 101325 Pa, T = 300 K

Clean trap permeability of the porous mediumkp= 8.2 · 10−13 m2, in order to match the ex-perimental point at the lowest flow rate ( V = 15Nm3 /h)

kp was kept constant as the inlet flow rate wasvaried through the simulations

Numerical simulations were carried out on agrid having 160590 computational cells (23618hexahedra, 1954 pyramids, 54858 tetrahedraand 80160 prisms)

The code is configured to run fully parallel onany number of processors


Filter Hydrodynamics

Velocity field Pressure field


Soot transport and deposition

Soot is transported as a chemical specie : pre-vious studies [8, 9] indicates that Stokes numberof soot particles in engine exhaust gas flow is verylow (St < 10−4);

∂(

ρ~Y)

∂t+ ~∇ · (ρ~u~Y ) + ~D = 0

Soot is removed by an implicit sink term ~D ap-plied on porous faces: the amount of soot re-moval is determined by the filtration efficiency ofthat particular face;

During filter loading the trapped soot parti-cles change the following quantities, defined asporous-cell face properties:

- soot cake thickness

- collection efficiency

- hydrodynamic resistance (Darcy coefficient)



The filtration sub-model used is based on the Konstandopoulo s and Johnson’s model [10]: theparticulate matter is trapped inside the porous media and it is also deposited on the filter substratemicrostructure.

msoot = φ ·mcake + (1 − φ)mtrapped

where the partition coefficient φ determines the amount of soot which that fills the porous mediumor that builds up the soot cake:

φ =d2c − d2

c,0

(ψb)2 − d2c,0

and it is a function of the unit collector diameter dc defined as:

dc = 2

[

3

4π·

mc

ρsoot,w+

dc,0

2

]1/3



Local wall porosity ε change continuously asfiltration proceeds:

ε = 1−

(

dc

dc,0

)3

(1− ε0)

Collection efficiency is determined by two con-curring mechanisms:

- Direct interception by spherical collectorsηR

- Brownian diffusion ηD

E = 1−exp

[

−3(1− ε)(ηD + ηR − ηDηR)wsoot

4εdc

]

Wall resistance is given by the sum of porouswall and soot cake:

∆P =

[

wwall

kwall+

wsoot

ksoot

]

· µw · un

Wall permeability changes accordingly tothe wall porosity:

kwall = kwall,0

(

dc

dc,0

)2 f (ε)

f (ε0)·1− ε0

1− ε


SCR systems modeling

Unsteady flow solver with Lagrangian transport of particles with transport of gas chemical composition

Chemistry integration operated by an ODE solver based on to the SIBS method

WATER VAPOR AMMONIA

The chemical and physical processes taken into account are:

- injection and evaporation of urea solution

- thermal decomposition in gas phase of urea

- hydrolysis of isocyanic acid

- NOx reduction (fast and standard)

NH2 − CO − NH2 → NH3 + HNCO

HNCO + H2O → NH3 + CO2

2NH3 + 2NO + 0.5O2 → 2N2 + 3H2O

NH3 + NO + NO2 → 2N2 + 3H2O

2NH3 + 1.5O2 → N2 + 3H2O


Reacting regionA reacting region has been defined within the fluid region having specific properties in terms of:

- flow resistance (flow through a porous media)

- chemical reactions (new definition of Reaction)

- substrate properties

+ =The reaction heat is included as a source term in the heat balance of the substrate mesh

Surface chemistry is solved only in region where reactions are supposed to occur: active sites

Kinetic model by Ciardelli et al. accounting for reactants adsorption/desorption and reaction rate de-pendence on the surface coverage

Dependence of the reaction rate from the substrate temperature

SOLID PHASE BALANCE

Ωδθ

δt= (rdes − rads − rox − rNO )

rads = k0adsCNH3

(1 − θ)

rdes = k0desexp

EdesRT

(1−αθ)θ

GAS PHASE BALANCE

YNH3= (rd − ra), YNO = ΩrNO

rNO = kNOexpENORT CNOC

β

O2θ

rox = koxexpEoxRT θ

The hydrolysis and ammonia oxidation processes have been modeled on the basis of the work of Yim26/31 Federico Piscaglia, Dip. di Energia, Politecnico di Milano

Conclusions

The latest development of the Lib-ICE R© library (fluid dynamic, numerical solvers, aftertreatment andnoise simulation) have been presented.

NUMERICAL SOLVERS

porousJump class to introduce step change in flow properties across thin porous media layers

dpfFoam solver based on the transient SIMPLE algorithm with implicit formulation of the poroussource term: high stability and strongly improved computational performance (Courant num-ber up to 104)

Applications, classes and utilities for Diesel Particulate Filter simulation

These features will be included in the future release of the OpenFOAM R©-dev project.

NOISE SIMULATION

Development of applications, classes and utilities for non linear acoustic simulation of silencers

Solver testing and validation with complex silencer geomet ries


Current development and Future Work

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1−0.02

−0.01

0

0.01

θ [rad/π]

Uf [m

/s]

Face−normal velocity on porous layer

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1−5

0

5

10

θ [rad/π]

∆P [P

a]

Pressure drop acros porous layer

Generalization of the pressureJump class to any kind of formulation of pressure jumps

Implementation of a new formulation of the friction term between the flow and the p orous sur-faces

Submodels for DPF simulation : THERMAL and CHEMICAL models for filter regeneration

Acoustic simulation : prediction of gas-dynamic noise radiation of silencers having complex geome-tries

LES turbulence modeling


Thanks for your attention!


Federico Piscaglia, Ph.D.Assistant Professor of Internal Combustion Engines

CONTACT INFORMATION

Address Dipartimento di Energia, Politecnico di Milano (campus Bovisa)

via Lambruschini 4, 20156 Milano (ITALY)

E-Mail: [email protected]: (+39) 02 2399 8620Fax: (+39) 02 2399 3863

Web page: http://www.engines.polimi.it/


References

[1] F. Piscaglia, A. Montorfano, and A. Onorati . Development of a Multi-Dimensional Parallel Solver for Full-Scale DPF Modeling in OpenFOAM. SAE paper n.2009-01-1965, SAE 2009 International Powertrains, Fuels and Lubricants Meeting, June 15-17, 2009, Florence, Italy, 2009, 2009.

[2] F. Piscaglia, Ferrari G., A. Montorfano, A. Onorati, and Pid ria M. F. Development of an open source C++ toolkit for full scale diesel particulate filterssimulation. SAE paper n. 2009-24-0137, SAE 9th International Conference on Engines & Vehicles, September 13rd-17th, Capri, Naples, Italy, 2009.

[3] F. Piscaglia, A. Montorfano, and A. Onorati . Multi-dimensional computation of compressible reacting flows through porous media to apply to internalcombustion engine simulation. Mathematical and Computer Modelling, In Press, Corrected Proof, 2010.

[4] T. Lucchini, G. D’Errico, F. Piscaglia, D. Ettorre, and M. A. Development of openfoam for the simulation of the combustion process and the exhaust-aftertreatment system in diesel engines. 4th OpenFOAM workshop, June 2nd, Montreal, 2009.

[5] F. Piscaglia, A. Montorfano, A. Onorati, and Ferrari G. Modeling of pressure wave reflection from open-ends in ice duct systems. SAE paper n. 2010-01-1051,SAE Int. Congress & Exp. (Detroit, Michigan), 2010.

[6] J. H. Ferziger and M. Peri c. Computational Methods for Fluid Dynamics. Springer, 1997.

[7] M. Masoudi, A. Heibel, and P. Then . Predicting pressure drop of wall-flow diesel particulate filters – theory and experiment. SAE paper n. 2000-01-1084, SAE2000 Int. Congress & Exp. (Detroit, Michigan), 2000.

[8] F. Piscaglia, C. J. Rutland, and D. E. Foster . “Development of a CFD model to study the hydrodynamic characteristics and the soot deposition mechanism onthe porous wall of a diesel particulate filter”. SAE paper n. 2005-01-0963, SAE 2005 Int. Congress & Exp. (Detroit, Michigan), 2005.

[9] F. Piscaglia, A. Onorati, C. J. Rutland, and D. E. Foster . “Multi-dimensional modeling of the soot deposition mechanism in diesel particulate filters”. In SAETransactions, Journal of Fuel & Lubricants. SAE paper n. 2008-01-0444, SAE 2008 Int. Congress & Exp. (Detroit, Michigan), 2008.

[10] A. G. Konstandopoulos and J. H. Johnson . “Wall-flow diesel particulate filters - their pressure drop and collection efficiency”. SAE paper n. 890405, SAE 1989Int. Congress & Exp. (Detroit, Michigan), 1989.


Lib-ICE: a C++ object oriented library for ICE simulation...

Documents

Transcript of Lib-ICE: a C++ object oriented library for ICE simulation...