Applied Computational Fluid Dynamics by Hyoung Woo Oh - HTML preview

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 as density, t as time and xi , xj as space coordinates. The R(T) = ¼ T (1 – T) stands for Air Movement Within Enclosed Road-Objects with Contra-Traffica CFD-Investigation

75

reaction rate[24] where the reciprocal value of reaction time-scale is represented by 1/T and 

is here again a constant average density. Temperature T will be used as expression for reaction-progress-variable as well, whose purpose is to distinguished burned, unburned and

partially burned state, providing facile interpretation of flame propagation. The term  g 

i

T

denotes buoyancy, treated according to the Boussinesq approximation, where  T is showing the difference between local and reference temperature. The symbol g denotes the gravity and

 is coefficient of the thermal linear deformation. The model for the unknown Reynolds

stress[25],  ij, s is related to the local strain rate:

  ( )  ( )

ij

ij N

ij T (4)

where we distinguish between Newtonean stress ( )  2

ij N

i

S j featuring molecular

viscosity; and turbulent Reynolds stress ( )  2

ij T

T i

S j featuring turbulent viscosity

recognising again i

S j as local strain stress rate reads:

1  

v

v

Sij  

j

i

 (5)

2   x

x

j

i

2

k

Here we recognise the turbulent viscosity:  

T

C

( 6 )

The applied k- model[26] is a two-equation eddy viscosity model [27, 28] uses transport

equations for these two variables[29]. One of these equations governs the distribution through the field of k, the local kinetic energy of the fluctuating motion. The other one is explaining a turbulence characteristic of different dimensions, the energy dissipation rate  [30].

2

2

k

k

k

2

   C

k   C

P    

N (7)

t

d

v

2

k

   C

   C kP

d

2

C N C

1

3 v

2  (8)

t

k

The d

P , the production term for the squared shear frequency is:

     T

d

P

V

V 2

1

(9)

2

where    T

V

V is the 2-norm matrix. The constants are given: C1 = 0.126, C2 = 1.92, Cµ =

0.09, C= 0.07. The variable N denotes the Brunt-Väisälä frequency, with the N2, related

following squared buoyancy:

v g

2

N   v

   (10)

t

0

z

Here is constant   1

t

and following expressions of eddy coefficients vv ,  v should include

the stability parameters to account for the turbulence damping in the stratified fluid flows: 76

Applied Computational Fluid Dynamics

2

k

2

k

v S

  S

 

v

u

v ,

(11)

v

b

b

0.108  0.0229

S

N

,

0.177

S

(12)

u

1  0.47  0.0275

b

 

N

N

1

0.043 N

where  b =10-6 and the following stability coefficients  N and C3 can be expressed as: 2

k

2

 

N

N

2

2

C  

N  (13)

3

0.4;

0

2

C N

3

1;

0

During these investigations, the wall shear stress was obtained from the logarithmic law of

wall (“wall function”) for the distance from the wall, y, the von Karman constant =0,41 and v

1

the constant C=9,793:

v y

ln

C

(14)

v

v

Energy transfer within the computational domain of such non-premixed turbulent flow in

tunnel cavity is governed by next equation:

H   vH

    t H   Q (15)

t

c

h

p

where contribution to the energy budget, characterised through turbulent thermal

conductivity  t is performed through the heat conduction and diffusion combined in term

 

   t H  , accompanied by the heat-increase component

Q due to the chemical reaction

c

h

p

rate R of a species n and it’s molar mass M:

0

h

Q   n

h

n

R (16)

n Mn

In the governing energy equation is total enthalpy H based onto particular enthalpy of the

nth species Hn and it’s mass fraction Yn

H   n

Y Hn (17)

n

with

0

H h

n

n

hn (18)

having so species n characterised through it’s thermal capacity cp,n and nth enthalpy

T

h

T

n

cp, ndT with referent temperature

293,15

ref

K that makes an impact on the

ref

T

formation enthalpy 0 n

h r

T

.

ef , n

Air Movement Within Enclosed Road-Objects with Contra-Traffica CFD-Investigation

77

The radiative transfer equation (RTE) for an absorbing, emitting and scattering medium at

the position r in the direction s reads:

 

4

4

dI( r , s)

 

2  T

 

 

 ( a   ) I( r , s)  ax

s

I( r , s ' 

) ( s, s ') 

d '

s

(19)

ds

 

4 0

The applied Discrete Ordinate approach for treating the radiation considers the RTE in the

direction s as a field equation, allowing the modelling of non-gray radiation, using the gray-

 

band model. So, for the spectral intensity I( r , s) the RTE can be written as: 4

  

 

 

 

2

 (

s

I( r , s) s)  ( 

a   )

s I ( r , s )  

a x Ib 

I( r, s')( s, s') 

d ' (20)

4 0

Here is r a position vector and s a direction vector. I denotes the radiation intesity, i.e.

radiation intensity I for a certain wawe-lenght  . The radiation intensity for the black body reads Ib . Scattering coefficient is represented by  s and Stefan-Bolzman-constant reads  =5.672x10-8W/m²K4.  stands for phase function, T is local temperature and x is

refraction index. Path length is s and s ' denotes direction vector. ' stands for solid angle and a is absorption coefficient, i.e. absorption coefficient for a particular wave-length 

a .

So will the RTE be integrated over each wave-length-interval  resulting in transport

equation for entity Icontaining the radiant energy of the wave-length . The total

 

intensity I( r , s) in each direction s at some position r is computed as:

 

 

I( r , s)   Ir s

, ( , )

n

n (21)

n

The weighted-sum-of grey-gases model (WSGGM), that was applied in this study for

handling the irradiance in the complicated phenomenon of the confined combustion[31]

presents a reasonable compromise between the oversimplified grey gas model and a

complete model which takes into account particular absorption bands. Within the Discrete

Ordinate approach, where the soot generation[32] was described by the Magnussen

model[28], the basic assumption of the WSGGM means that the emissivity E of the any nth

gray gas characterised by pSUM, the sum of itś partial pressures p and the absorption 

within the computational domain over a distance d is presented by:

i

E   a

T

n S

p UMd

E, n  1

e

 (22)

n0

Here

n pd

E

a , n denotes the emissivity weighting factor for the nth gray gas and 1

e

 is

emissivity of the nth gray gas. The temperature dependence of E

a , n is commonly

J

approximated by the relation:

n1

a

E, n

Eb, nT

(23)

n1

where polynomial coefficient E

b , n , depending on the gas temperature emissivity is obtained

experimentally. The coefficients E

b , n and  n are slowly changing for broad range of the

78

Applied Computational Fluid Dynamics

pressure ( 0.001 bar p  10 bar ) and temperature ( 600 K T  2400 K ) which simplifies J

relation (22) to:

E   a

E, n n S

p UM

(24)

n1

J

ln(1  E)

for

4

a   a p ; s  10 m

4

E, n n

and a  

; s

 10 m (25)

n1

s

The combustion – the chemistry development is explained by fast chemistry assumption

including the prePDF [33] and in the ideal stoichiometric conditions the reaction runs as

foolows:

ignition



energy

C H

O

N

CO H O

N  

7

16

11 2 3,76 2 

7

2

8 2

41,36 2

H (26)

However, in a case of unfulfilled combustion, soot is influencing the radiation absorption.

Employed generalised model estimates the effect of the soot onto the radiative heat transfer by determining an effective absorption coefficient for soot. In this case, absorption

coefficient is a sum of the one for the pure gas ag and that one for the pure soot s a :

a   a

s g

s

ag (27)

The ag is obtained from presented WSGGM approach and

a b    b T

s

1

1

m

T

2000 (28)

with

b

4

1

1232,4

and

4,8 10

1

kg

T

b

, where 

K

m denotes soot density.

3. Numerical approach

Discretizing the governing equations in both space and time[28, 34] while choosing the

numerical method of the standard finite volumes [22, 34, 35], the CFD-tool is “adapted” for

the time-dependent modelling of the explored event. The spatial discretization of time-

dependent equations within here-employed segregated solution method are linearized in an

implicit way. Since variables described the flow by their value at the centre of a single mesh-cell in explored computational domain, the system of linear equations occurs, containing

mentioned unknown variable at the cell centre as well as their unknown values in

neighbour cells. A scalar transport-equation within such method is also used to discretize the momentum equations; in the same mode for the pressure-field (if cell-face mass-fluxes

were known). This applies for velocity-field as well. In case that the pressure-field and face mass fluxes are not known, applied commercial software of FLUENT [28] uses a co-located scheme, whereby the local values for pressure and velocity are stored at centres of a single mesh-cell. A need for interfacial values includes an application of an interpolation scheme to compute pressure and velocity out of mesh-cell values. The integration over the observed

control-volume, where is a mesh-cell in a computational domain, can be performed yielding

the discretised equation for the mass-flux through a control-surface – a mesh-face on the

mentioned mesh-volume. Procedure of the segregated solver that follows as a mechanism in

this research, the continuity equation, is used as an equation for pressure as well[28].

Air Movement Within Enclosed Road-Objects with Contra-Traffica CFD-Investigation

79

However, the pressure does not appear for an incompressible flow in explicit way, since the

density is not directly related to pressure. However, through the application of the SIMPLE-

algorithm-family[34] during this investigation (within the commercial software package of

FLUENT) the won values for pressure were introduced into the continuity equation and in this way supported the pressure-velocity coupling. This was done through the NITA-

algorithm for the unsteady.. Further, the SIMPLE uses a relationship between velocity and pressure corrections to enforce mass conservation and to obtain the pressure field. So,

executing these numerical steps, the equations can express the state for each other cell in the computational grid, the mesh. This will result in a set of algebraic equations with a

coefficient-matrix. In this way the segregated solver is “updating” variable-field by

considering all the cells of the domain in the same time, solving the governing equations

sequentially (segregated one from another). What follows are the iterations of the solution-

loop before one wins the converged solution. Subsequently, the next field of another

variable will be solved by again considering entire cells at the same time, etc. Finally,

determining of the boundary conditions relied on some previous done studies [19, 36] that

were basis for the estimation.

4. Objects of investigation - Two different tunnel-shapes

Todayś major two shapes of the underground traffic (road) facilities that are having their

cross-section as a “horse-shoe” and rectangular shape – we explored here. And according to

the final use, these traffic covered object, were taken as very frequently used ones.

Additionally, those tunnels (one, having bifurcation – is going under Slovenian Capital of

Ljubljana, and another is situated in a curvy valley of the river Bosna, between Bosnian cities of Travnik and Zenica) are “offering” interesting geometry for a CFD-based investigation;

such is air-movement and the movements of air-pollutants and other gaseous products (in

accidental situations).

4.1 The “Sentvid” tunnel

As mentioned, the northern tube of tunnel “Sentvid” (undergoing the city of Ljubljana) was

investigated with the CFD-approach, where the “chimney-effect” was expected (coming