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Reynolds equations for turbulent flow

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(1)

Reynolds equations for

turbulent flow

(2)

Turbulence

Jet in cross-flow

Instantaneous Vizualization

(3)

Turbulence

• Statistics – time mean quantities

Mean value Variance

(4)

Reynolds decomposition

• Dec.

Mean value Fluctuation

• Properties

• NS eq.

 

a t

a

 

a t

   

a t  a a t  

  0

a t a a t

    2

D a  a t

,t   ,t

u x u x u x

 ,    ,

p x t p x p x t

(5)

Ensemble average

• Quantity

Ensemble average

• Ergodic process

• Estimator

Choice of T, n

 

a t

1

1 n

i i

a a

n

T  

a t a a

   

lim T lim T

T n

a a t a t

 

  0

1

1 1

n .

T T

i

a t a t d a t n dt

T   n

(6)

EA – choice of n and T

• Statistically independent n > 200

• Pseudo-periodical sig. T >> Tsmax

Tsmax Tsmax

spectrum

(7)

Properties of averaging

• Linearity

• Commutativity

with der.

with int.

• Double averaging

• Averaging of product

• ATTENTION!!!

F of time const

Any nonlinear function!!!

a b a b a a

a dx a dx

 

a a

x x

a b a  b a t 

 

b t

a b a b

(8)

Continuity equation

Both mean and fluktuation velocity fields are solenoidal Averaging

instantaneous velocity field Is solenoidal

Reynolds:

0

k k

u div x

u

k k k

u u u

k 0

k

u x

 

k k 0

k k k

k k k k

u u

u u u

x x x x

k 0

k

u x

0

k k

u x

(9)

Substantial derivative

Averaging

?

NONLINEAR !

Integration per-partés:

= 0 (continuity)

i i i

k

k

Du u u

Dt t u x

i k

k i i k

k k k

u u

u u u u

x x x

k ki k i k

u u u u

x x

i i i

k

k

Du u u

Dt t u x

i 0 u 

(10)

Substantial derivative

Extra term !

     

 

i i i i i k

k

k k

i i k k

i i

k

i k i k i k i k

i

k

i i k i k

k k

i i k

k

Du u u u u u

Dt t u x t x

u u u u

u u

t x

u u u u u u u u u

t x

u u u u u

t x x

Du u u

Dt x

 

 

 

i i k

k

k k

u u u

u x x

(11)

Reynolds equations

Reynolds 1894

Extra term ! N-S eq.

Averaging

Reynolds eq.

0

2 2

i i i 1 i i k

k

k i k k

Du u u p u u u

Dt t u x x x x

 

 

2 2

i 1 i

i k

Du p u

Dt x x

 

2 2

i 1 i

i k

Du p u

Dt x x

 

(12)

Solvability of RANS

• Equations: 3 + 1

• Unknowns:

3 1 6 (symm)

Total 10 PROBLEM!!!

Extra eqs are needed!

2 2

1 ;

i i i i i k

k

k i k k

Du u u p u u u

Dt t u x x x x

 

 

k 0

k

u x

, 1, 2,3

ui i p u ui k , i k, 1, 2,3

(13)

Extra eqs for correlations

Eq for fluctuations (subtract RANS from NS):

Multiply by than averaginguj

(14)

Eqs for Reynolds stress

I the time change of the local correlation tensor,

II advection of Reynolds stress through a mean flow (not total!),

III interaction between the mean and fluctuation components of the flow and is related to the production of Reynolds stress,

IV advection in relation to the fluctuation part of the flow,

V effect of pressure,

VI diffusion and dissipation resulting from viscosity, which is expressed mainly in small scale perturbations

(15)

Eqs for Reynolds stress

4 + 6 = 10 eqs

Reynolds stress

Unknown tensors of 2nd order

Unknown tensor of 3rd order

Overall

75 unknowns !!!

(16)

Averaged Poisson eq.

• Poisson eq.

• Averaging

2

1 2 k l k l k l

l k l k k l

u u u u u u

p x x x x x x

     

 

     

1 2 k l

l k

u u

p x x

    

 

(17)

Reynolds stress

Stress

Stress 1

Mean pressure

Stress 2

Mean viscous

Stress 3

Velocity fluctuations

Reynolds stress

Rearrangement

2 2

i 1 i i k

i k k

Du p u u u

Dt x x x

 

 

i 1 i k

ik i k

k k i

Du u u

p u u

Dt x x x

 

(18)

Reynolds stress

• Reynolds stress tensor

• 2nd order tensor

Symmetric Semidefinite

 

2

1 1 2 1 3

2

2 1 2 2 3

2

3 1 3 2 3

ij ij i j

u u u u u

R u u u u u u u

u u u u u

   

     

   

   

x

(19)

Reynolds stress

• Physical meaning

• Mean momentum flux in i direction induced by fluctuations in j direction

• Mean momentum flux in j direction induced by fluctuations in i direction

• Always 3D!

ij i j

R  u u 

(20)

Reynolds stress

• Covariance tensor properties

• Symmetric

• Decomp. (isotropy):

Isotropic part Anisotropic part

Kinetic energy

IRROTATIONAL

ROTATIONAL

i j

u u 

i j ij ij

u u   i a 2

ij 3 ij

i k

2

ij i j 3 ij

a u u  k

1 1

2 2 k k

k u u   u u 

(21)

Reynolds stress

• A:

• B:

For any transversal movement within BL

the POSITIVE Reynolds stress is generated

x2

x1 A B

2 0, 1 0 12 1 2 0

u u R   u u 

2 0, 1 0 12 1 2 0

u u R   u u 

2 0

u 

1  2

u x

1 0

u 

2 0

u 

 

1 2

u x

1 0

u 

(22)

Reynolds stress

x2

x1 x2

x1

Isotropic fluctuations R12 = 0

Anisotropic fluctuations R12 > 0

BOUNDARY LAYER ISOTROPIC TURBULENCE

(23)

Quantities

• Kinetic energy

• Intensity of fluctuations

Isotropic turbulence

Intensity of turbulence

1 2 k k k u u

2 2 2

1 2 3

3 2

u u u

Iu Tu

u

2 2 2 2

1 2 3

u u u u Tu u2 u

(24)

Dissipation rate

rate of dissipation

Specific dissipation rate

Izotropic turbulence

2 s skl kl

1

2

i j ij

j i

u u

s x x

  k 1

2

k l k l

l k l k

u u u u

x x x x



2 1 1

15 u

x

(25)

Reynolds equations

Anisotropic part Rij

Joseph Valentin Boussinesq 1877 Hypotheses about RS:

1. >> turbulent viscosity

2. proportional to mean strain rate

i 1 i k

ik

k k

i k i

Du u u

Dt x p x u

x u

2 3

i j

ij T

j i

i j

u u u u

k x x

  

i 1 i k

eff

i k k i

Du P u u

Dt x x x x

 

 ,  ,

eff t T t

x    x

 2 3

P p  k

2 2

i 1 i k

i k

i k

Du u u u

D x

p

t x x

 

 

(26)

Turbulent viscosity

• Molecular viscosity – material „constant“, property of fluid

• Turbulent viscosity – property of flow

Function of space

Function of time (for nonstationary case) Is solution

Is input

 ,  ,

eff t T t

x    x

(27)

Prandtl mixing length

• Estimate

x1 x2

u1

Boundary layer

Border of the BL

x1

tot

t x2

2 1

2

t mix

l u

x

t

(28)

Transport equation

• Advection

• Production

• Transport

• Dissipation

0 A P T D   

1 2 2 i

i

u q

x

i i j

j

u u u

x

 

1 2 2 j

j

u q p

x

 

1 2

k l k l

l k l k

u u u u

x x x x



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