miet 2394 cfd lecture 11

8/17/2019 Miet 2394 Cfd Lecture 11

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Computational FluidDynamics – Lecture 11

Prof. Jiyuan Tu

& Dr. Sherman C.P. Cheung


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RMIT University 2

Some Advanced Topics in CFD

Demands from real-world problems and industries


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RMIT University 3

Turbulent Reacting Flows

※ Combustion

Heavy modelling!

Turbulent flow

+Chemical reactions

Persistent Flame

Intermittent Flame

Buoyant Plume

A photographic image of a buoyant fire.

Complex Reacting Flow


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RMIT University 4

Concept of olumetric Heat ource

Heat


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RMIT University 5

tec"ler#s $xperiment


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RMIT University 6

isuali%ation of Computational model

X

Y

Z


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RMIT University 7

Results from olumetric Heat ource

X

Y

Z


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RMIT University

&ir Flow 'attern

X

Y

Z


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RMIT University !

elocity 'rofile at Doorway


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RMIT University "#

Temperature 'rofile at Doorway


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RMIT University ""

Temperature Distribution

X

Y

Z

T

52#

5#$42"

4!6$42

45$263

473$64

462$"#5

45#$526

43$!47

427$36

4"5$7!

4#4$2""3!2$632

3"$#53

36!$474

357$!5

346$3"6

334$737

323$"5

3""$57!

3##


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RMIT University "2

&dvantages

(t is simple

)ive reasonable prediction both in velocities and

temperatures

ave computational time


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RMIT University "3

Disadvantages

Fire*flame height should be obtained prior from

experimental data or analytical approximation

+,rong prediction at the flame

.isinterpretation of flame structure


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RMIT University "4

,hy needs Combustion .odel

(mprove prediction at near fire field

ome of the Fire problems re/uire the shape of

flame structure

Flame spread along combustible materials

Fire suppression by sprin"lers or water mists

$ddy 0rea" 1p 2$013 or presumed 'DF


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RMIT University "5

Fire Triangle

Fuel

Heat Oxygen


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RMIT University "6

.ixed is 0urnt Concept

Fuel 4xidant

Combustion

Turbulent .ixing

'roduct


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RMIT University "7

Flame hape by Combustion .odel

X

Y

Z

T

"7##

"6##

"5##

"4##

"3##"2##

""##

"###

!##

##

7##

6##

5##

4##

3##


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RMIT University "

Two Compartment Fire

3$6 m 3$6 m

2$4 m

%&en

'n(

Burn

Room

Adjacent Room

)P* Burner

2$# m

#$ m

+oor,ay

$xperimental setup by 5ielsen and Fleischmann 267773


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RMIT University "!

Temperatures at &d8oining Room

Temperature (K)

H e i g h t ( m )

3## 35# 4## 45# 5##

#

#$5

"

"$5

2

2$5

Meaurment

!rediction "y #om"ution Model


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RMIT University 2#

Temperatures at Doorway

Temperature (K)

H e i g h t ( m )

3## 35# 4## 45# 5## 55# 6## 65##

#$5

"

"$5

2

Meaurment

!rediction "y #om"ution Model


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RMIT University 2"

Temperatures above Fire ource

Temperature (K)

H e i g h t ( m )

4## 6## ## "### "2## "4## "6## "## 2### 22## 24#

#$5

"

"$5

2

$ncorrected experimental data

!rediction %ith #om"ution Model

#orrected experimental data (&' *)


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RMIT University 22

Disadvantages

$xtra e/uations involved in simulation

9nowledge of the fuel Thermal Decomposition is

re/uired 2Detail Chemistry3

Complicated to implement


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RMIT University 23

5eeds of Radiation and oot .odel


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RMIT University 24

oot Formation 'rocess

Describes fours chemical processes:

5ucleation

Coagulation

urface )rowth

4xidation


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RMIT University 25

5ucleation


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RMIT University 26

Coagulation


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RMIT University 27

urface )rowthinyl


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RMIT University 2

4xidation464H

C46

H64

C46

C46

H64


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RMIT University 2!

Radiation and oot Contribution Revisit the two compartment fire experiment

(ncorporate the radiation and soot model

Compare the prediction with previous results


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RMIT University 3#

Temperatures at &d8oining Room

Temperature (K)

H e i g h t ( m )

3## 35# 4## 45# 5###

#$5

"

"$5

2

2$5

Meaurment

!rediction %ith only gaeou radiation

!rediction %ith gaeou and oot radiation


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RMIT University 3"

Temperatures at Doorway

Temperature (K)

H e i g h t ( m )

3## 35# 4## 45# 5## 55# 6## 65##

#$5

"

"$5

2

Meaurment!rediction %ithout radiation



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RMIT University 32

Temperatures above Fire ource

Temperature (K)

H e i g h t ( m )

4## 6## ## "### "2## "4## "6## "## 2### 22## 24#

#$5

"

"$5

2

$ncorrected experimental data!rediction %ithout radiation


#orrected experimental data (&' *)


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RMIT University 33

A Buoyant FreeStanding Fire


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RMIT University 34

Advance in Computational!odels（ "） ;arge $ddy imulation 2 LES 3

4nly resolve large eddies < sub-modeling of small eddies－ ubgrid scale turbulent viscosity

－1nsteady simulation－Depending on grid si%e

－(ndustrial applications possible

RANS-LES Coupling

Reynolds &veraged-5～ 5ear-wall uses

～ (nternal domain uses ;$

Hybrid Coupling

SGS

T µ

V ∆

= - RANS κ ε


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RMIT University 35

Bac#ward Facing Step

+-. .olution /rom .tan/or( University


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RMIT University 36

Advance in Computational!odels（ ""）Direct 5umerical imulation 2 DNS 3

Resolve all scales of turbulent eddies

For fundamental understanding of turbulence

Challengesignificant grid numbers

mall time step

Higher order discreti%ation1n"nown initial < inlet 0C

>? Re

? t ∆ ↓↓


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RMIT University 37

!ultip$ase Flows（ "）

※ )as olid particle flow

'hase@ 'hase6

.ining industry

'ollutants $nvironment

Coal fired power

DustA soilB

$lectricity

※ )as Droplet particle flow

&ir ;i/uid

5asal prayer

&erosol

(C $ngines pray


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RMIT University 3

!ultip$ase Flows（ ""）

※ 0ubble ,ater particle flow

0oilers

5uclear 'ower

Chemical reactor

&ir ;i/uid

※ 4il ,ater &ir olid particle flow

'hase@ 6 >

※ &ir ,ater free surface

5umerical methods

※$ulerian-$ulerian .ethod orTwo- fluid .ethod※$ulerian-;agrange .ethodor 'article trac"ing .ethod

※olume-of-fluid 2VOF 3Trac"ing free surface


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RMIT University 3!

Typical Flow be$aviour inbubble columns

Bu00ly Flo, 1a&Bu00ly /lo, .lu Flo, 1urnTur0ulent Flo,


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RMIT University 4#

Bu00le 1oaleseneBu00le 1oalesene 0ubbles may +merge together

forming larger bubbles

Coalescence reduces number of

bubbles but increases si%e of

bubbles

estern Miian University

-D p8

D p


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RMIT University 4"

Bu00le Brea9aeBu00le Brea9ae

Revuelta et al$ 2##68 :$F$M$

0ubbles may brea"-up due toturbulence impact

0rea"age increases number of

bubbles but decrease si%e of

bubbles

-D p8

D p


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RMIT University 42

Po&ulation Balane ;&&roaesPo&ulation Balane ;&&roaes 'opulation 0alance $/uation 2'0$3

Three .ain &pproaches has been proposed: .oment of .ethod 2.4.3 ;east /uare .ethod 2;.3

Class .ethod 2C.3

( )( ) +−=⋅∇+

∂

∂3A23A23AA2

AAt f t bt r f v

t

t r f ξ ξ ξ

ξ

−∫ @

73A23A23AA2 dst s f t sbt sh ξ

+∫ @

73A23AA23A2 dst s f t sC t s f ξ

∫ −−ξ

ξ ξ 7

3A23A23AA26

@dst s f t s f t s sC

+eat rate (ue to 0rea9ae

Birt rate (ue to 0rea9ae

+eat rate (ue to 1oalesene

Birt rate (ue to 1oalesene


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RMIT University 43

1lass Meto(s /or Po&ulation Balane1lass Meto(s /or Po&ulation Balane

-D p8

D p

;verae -um0er

.im&le

)oss (istri0ution in/ormation

1om&le< an( e


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RMIT University 44

Average Bubble %umberDensity &AB%D'

&dopt a single averaged value to describe the

changes of local bubble number

4nly one additional e/uation is needed

&dvantages: Fast in terms of computational time

imple to implement

Disadvantages: 4nly one averaged value can be obtained

Fluid +elocity

n n n n n

n’

n’

n’ n’ n’ n’

( ) Breakagen

eCoalesen

n g n!t

nφ φ +=⋅∇+

∂

∂

n’


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RMIT University 45

!(ltiple S")e *roup &!(S"*'!odel &"' 1sed 5 si%e group 2scalar3 to describe bubble population

5 extra e/uations have to be solved 2depends on number of

group used3

&dvantages:

Higher resolution for bubble classes

Disadvantages: &dditional computational time needed

( ) BC BC " g " D D # # n!t

n−−+=⋅∇+

∂∂


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RMIT University 46

!(ltiple S")e *roup &!(S"*'!odel &""'

Fluid +elocity

n" n" n" n" n"

n"’ n’ n"’ n"’ n"’

# B D B

( ) $" $ N

" $

B nvv% # :@

∑+=

= "" B n% D =

# C DC

BC BC n D D # # S " −−+=

n" n"

n"n"

∑∑= =

="

k

"

l

$"kl &"C nn # @ @6

@ χ ∑=

= N

$

$""$C nn D@

χ

kl &"kl &" χ χ = if "l k vvv =+

else7=kl &" χ "l k vvv ≠+

-n"8

n"

-n"8

n"


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RMIT University 47

Bu00le MeanismBu00le MeanismBu00le 1oalesene

Ran(om 1ollision

Bu00le Brea9ae

a9e 'ntrainment

Tur0ulene Im&at

.earino// .ur/ae insta0ility


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RMIT University 4

Free Sur+ace Flow in BuildingDrainage system


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RMIT University 4!

Fluid Structure "nteraction

Fluid flow tructural &nalysis

.ethod：

→ F # C

)eometry Ne'

32

32

CF(

Fl!ent 32 ANS)S

Fluid .odelling

2CFD3

!olid .odelling

2F$!.3

Coupling

Intera5tion

(5T$RF&C$

2middle-ware3

• Turbulence

• 'ressure

• Fluctuations

• !tress

• Deformation

• ibration.4are

In/ormation


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RMIT University 5#

0iomedical &pplication

CT

.R(

)eometry

.odel

2C&D3

CFD .odel of &ir way

0lood vessel

'ressureA hear stressA

Drug depositionA Temperature etcBB


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RMIT University 5"

Blood ,essel – -all S$earStress &-SS'

Carotid 0ifurcation


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Blood ,essel – FS"

miet 2394 cfd lecture 11

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