optimisationforthermo-fluids engineeringpiet/edu/dos/pdf/4m020-flow.pdf · 4m020 design tools...
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OptimisationforThermo-Fluids
Engineering
Dr.
R.J
.M. (R
ob
) B
as
tia
an
s
Co
mbu
stio
n T
ech
no
log
y
Me
ch
an
ica
l E
ng
ine
eri
ng
4M020 Design Tools
4M
020
De
sig
n T
oo
ls; O
ptim
isa
tion
in T
he
rmo
-Flu
ids
En
gin
ee
rin
g
Optimisation
Eg
ge
rt20
00:
En
gin
ee
rin
g d
es
ign
�E
ng
ine
eri
ng d
esig
n is the
se
t o
f de
cis
ion
-makin
g
pro
cesses a
nd
activitie
s u
se
d to
de
term
ine
the
form
of
an
ob
ject g
ive
n the
fu
nction
s d
esire
d b
y th
e c
usto
mer.
�D
uri
ng th
e p
ara
me
tric
de
sig
n p
ha
se
we
de
term
ine v
alu
es
for
the
con
tro
llab
le p
ara
mete
rs, ca
lled
desig
n v
ari
ab
les,
ide
ntifie
d a
s u
nkn
ow
n d
uri
ng
the
co
nfigu
ratio
n p
ha
se.
�C
AE
re
fers
to c
om
pu
ter
so
ftw
are
and
ha
rdw
are
syste
ms
used
in
th
e a
na
lysis
of e
ngin
ee
rin
g d
esig
ns to
va
lida
te
fun
ctio
na
l p
erf
orm
ance
.
4M
020
De
sig
n T
oo
ls; O
ptim
isa
tion
in T
he
rmo
-Flu
ids
En
gin
ee
rin
g
Thermo-FluidsEngineering
Wh
at
is T
he
rmo
-Flu
ids
En
gin
ee
rin
g
�C
ove
red
by
�E
nerg
y T
echno
log
y
�P
rocess
Technolo
gy
�C
om
bustion
Technolo
gy
�C
om
mo
nfa
cto
r: F
luid
flo
w
�O
ften
mu
lti-
sca
lem
ulti-
physic
sp
rob
lem
s
�M
uch
rese
arc
h le
ss
optim
ald
esig
n
�Im
plic
atio
non
ho
wto
use
co
mpute
r-cap
acity
4M
020
De
sig
n T
oo
ls; O
ptim
isa
tion
in T
he
rmo
-Flu
ids
En
gin
ee
rin
g
FluidFlow
Ma
ny
pro
ble
ms
in m
an
ya
reas
�M
ete
oro
log
y
�A
str
op
hysic
s
�B
iolo
gy
�A
gri
cu
lture
�P
roce
ss
techn
olo
gy
Co
mm
on
facto
r: N
avie
r S
tok
es
Eq
ua
tio
ns
4M
020
De
sig
n T
oo
ls; O
ptim
isa
tion
in T
he
rmo
-Flu
ids
En
gin
ee
rin
g
Multi-Scaleflows
Ex
am
ple
s
�T
urb
ule
nce
�A
tmo
sph
eri
cd
isp
ers
ion
4M
020
De
sig
n T
oo
ls; O
ptim
isa
tion
in T
he
rmo
-Flu
ids
En
gin
ee
rin
g
Multi-Physics
Oft
en
flo
wis
no
tth
e p
rob
lem
bu
tin
tera
cti
on
sare
�B
uo
ya
ncy
indu
ced
flo
ws
�M
ixin
go
f d
iffe
ren
t flu
ids
�D
isp
ers
ion
of p
ollu
tan
ts
�F
low
sw
ith
hea
t tr
ansfe
r
�R
ea
ctive
flo
ws; co
mb
ustion
�C
om
pre
ssib
leflo
ws
�A
coustics
�S
hock w
aves
�M
HD
(M
ag
neto
Hydro
-Dyna
mic
s)
�F
low
str
uctu
rein
tera
ctio
n
�C
om
bin
ation
so
f th
e a
bo
ve
4M
020
De
sig
n T
oo
ls; O
ptim
isa
tion
in T
he
rmo
-Flu
ids
En
gin
ee
rin
g
Multi-ScaleMulti-Physicsflowsresearch
Ex
am
ple
s
�T
urb
ule
nt com
bustio
n:
�C
om
pre
ssib
leflo
w
�H
eat
transfe
r
�M
an
ychem
icalspecie
s a
nd r
eactions
�A
coustics,
sta
bili
ty
�F
lam
e-t
hic
kn
ess
indep
end
ent
length
scale
�A
pplic
ation:
Ga
s-t
urb
ines
for
aero
pla
nes
and e
l. p
ow
er
gene
ration
�V
ery
import
ant
for
socie
ty:
Em
issio
ns,
Clim
ate
, E
nerg
y
�O
ptim
isation
??
4M
020
De
sig
n T
oo
ls; O
ptim
isa
tion
in T
he
rmo
-Flu
ids
En
gin
ee
rin
g
Multi-ScaleMulti-Physicsflowsresearch
Ga
s t
urb
ine
s:
4M
020
De
sig
n T
oo
ls; O
ptim
isa
tion
in T
he
rmo
-Flu
ids
En
gin
ee
rin
g
Modellingof reactive flows
Tu
rbu
len
t c
om
bu
sti
on
�N
ot o
nly
in
tere
stin
g fro
m a
n in
dustr
ial po
int o
f
vie
w, b
ut a
lso fro
m a
n a
ca
de
mic
po
int o
f vie
w
�L
arg
e r
an
ge
of tim
e a
nd
len
gth
sca
les m
ake
s
nu
meri
ca
l sim
ula
tio
n o
f tu
rbu
lent co
mbu
stio
n
far
fro
m e
asy a
nd
very
expe
nsiv
e
�D
eve
lop
men
t o
f accura
te a
nd
effic
ien
t m
od
els
for
turb
ule
nt co
mb
ustio
n is o
ne
of th
e m
ost
ch
alle
ng
ing
ta
sks facin
g the
com
bustio
n
co
mm
un
ity tod
ay
DLR, Germany
4M
020
De
sig
n T
oo
ls; O
ptim
isa
tion
in T
he
rmo
-Flu
ids
En
gin
ee
rin
g
Approach
Fro
m s
ma
ll t
o la
rge
sc
ale
, fr
om
fu
nd
am
en
tals
to
ap
plic
ati
on
�O
ne-d
ime
nsio
na
l fla
me
mo
de
llin
gw
ith
de
taile
d d
escri
ptio
n o
f
ch
em
istr
y a
nd
tra
nsp
ort
�F
lam
ele
t-ba
sed r
eduction (
FG
M)
to s
implif
y c
hem
istr
y m
odel
�D
ire
ct n
um
eri
ca
l sim
ula
tio
n (
DN
S)
of tu
rbu
len
t fla
me
to
unra
ve
l
ch
em
istr
y-t
urb
ule
nce
in
tera
ctio
n
�M
odel fo
r tu
rbu
lence-c
hem
istr
y inte
raction (
e.g
. a s
ub-g
rid s
cale
model fo
r la
rge
-edd
y s
imu
latio
ns)
�L
arg
e-e
dd
y s
imu
latio
n (
LE
S)
of la
b-s
ca
le fla
mes
�R
eyn
old
s-a
vera
ge
d N
avie
r-S
tokes (
RA
NS
) sim
ula
tio
ns o
f
ind
ustr
ial a
pplic
atio
ns
4M
020
De
sig
n T
oo
ls; O
ptim
isa
tion
in T
he
rmo
-Flu
ids
En
gin
ee
rin
g
DNS of turbulent flame kernels
DN
S o
f s
ph
eri
ca
lly e
xp
an
din
g p
rem
ixe
d
turb
ule
nt
flam
es
�V
alid
atio
n o
f F
GM
vs
deta
iled
che
mis
try
�A
na
lyse
turb
ule
nce
/ch
em
istr
y in
tera
ctio
n
�P
ractica
l re
leva
nce
is fo
und
in
IC
en
gin
es
Leeds, U
K
4M
020
De
sig
n T
oo
ls; O
ptim
isa
tion
in T
he
rmo
-Flu
ids
En
gin
ee
rin
g
Validation of FGM
Ma
ss fra
ctio
n o
f O
H r
ad
ica
l.
FG
M 1
00
tim
es fa
ste
r th
an d
eta
iled
ch
em
istr
y!
Th
is e
nab
les p
ara
mte
ric
stu
die
s.
4M
020
De
sig
n T
oo
ls; O
ptim
isa
tion
in T
he
rmo
-Flu
ids
En
gin
ee
rin
g
From DNS to LES of reactive flows
�A
ve
rag
ing
DN
S r
esu
lts e
na
ble
s a
-pri
ori
te
stin
g o
f L
ES
su
b-g
rid
sca
le
mo
de
ls.
�A
pp
lica
tio
n o
f L
ES
-FG
M in
pre
mix
ed
turb
ule
nt B
unse
n fla
me
:
4M
020
De
sig
n T
oo
ls; O
ptim
isa
tion
in T
he
rmo
-Flu
ids
En
gin
ee
rin
g
RANS of gas turbine combustor
NO
xfo
rmati
on
in
ga
s t
urb
ine
co
mb
usto
r
�F
ire
d in
le
an
pre
mix
ed
mod
e:
�F
ire
d in
diffu
sio
n m
ode
(sta
rt-u
p):
NO
max
is ~
10
0x larg
er
�In
ve
stig
ate
the
in
flu
en
ce
of h
yd
rog
en a
dd
itio
n
4M
020
De
sig
n T
oo
ls; O
ptim
isa
tion
in T
he
rmo
-Flu
ids
En
gin
ee
rin
g
Application to biomass conversion
�A
pp
lica
tio
n o
f fu
nda
men
tal kn
ow
led
ge
of re
active
flo
ws to
bio
mass
co
nvers
ion
�M
ulti-
sca
le, m
ulti-
ph
ysic
s a
ppro
ach
:
�S
mall
scale
: sin
gle
part
icle
kin
etics,
pyro
lysis
, heat/
mass t
ransfe
r
�In
term
edia
te s
cale
: fixed/f
luid
ized b
ed
two-p
hase f
low
, heat/
mass t
ransfe
r
�Larg
e s
ca
le:
reacto
r, f
urn
ace
flo
w p
att
ern
, ra
dia
tio
n,
contr
ol
Information
4M
020
De
sig
n T
oo
ls; O
ptim
isa
tion
in T
he
rmo
-Flu
ids
En
gin
ee
rin
g
Multi-scalemulti-physics
�M
ulti-
sca
lem
ultip
hysic
sp
rob
lem
sre
qu
ire
mu
lti-sca
lem
ulti-
ph
ysic
s
ap
pro
ach
�B
eca
use
ph
ysic
sa
t th
e s
ma
llestsca
les
ca
nh
ave
a la
rge
imp
act on
larg
e
sca
led
esig
n c
onstr
ain
ts
�N
Ox form
ation
in turb
ule
nt co
mb
ustio
nha
s its
ori
gin
in v
ery
thin
oxid
atio
nla
ye
rs
�ty
pic
ally
100 µ
m
�com
busto
r: t
yp
ically
1 m
�fo
raccura
cy
yo
uneed
10 p
oin
tsfo
ra r
ele
van
t gra
die
nt
to r
esolv
e:
10 µ
m g
rid
�3D
pro
ble
ms
requir
e(1
05)3
=10
15
calc
ula
tio
npoin
ts
�T
ime d
epende
nt
pro
ble
ms
require
10
5tim
este
ps
�P
roble
msiz
e:
n x
10
20
opera
tions.
4M
020
De
sig
n T
oo
ls; O
ptim
isa
tion
in T
he
rmo
-Flu
ids
En
gin
ee
rin
g
Largecomputer power forsolvingphysics
Tu
rbu
len
t c
om
bu
sti
on
in g
as
tu
rbin
es
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p:/
/ww
w.c
erf
ac
s.f
r/cfd
/
He
lic
op
ter
en
gin
e, u
sin
g2
00
0 p
roc
s:
4M
020
De
sig
n T
oo
ls; O
ptim
isa
tion
in T
he
rmo
-Flu
ids
En
gin
ee
rin
g
Largecomputer power forsolvingphysics
Big
ma
ch
ines
re
qu
ire
d:
Wo
rld
wid
e:
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p:/
/ww
w.t
op
50
0.o
rg/lis
t/2
00
8/0
6/1
00
Ne
therl
an
ds:
htt
p:/
/ww
w.s
ara
.nl/
(Hu
yg
en
s)
4M
020
De
sig
n T
oo
ls; O
ptim
isa
tion
in T
he
rmo
-Flu
ids
En
gin
ee
rin
g
Optimisationof design
Ca
lcu
lati
ng
for
de
sig
n
�B
OE
ING
(co
nserv
atio
n)
�B
ern
ou
lli
�P
ote
ntia
lflo
wm
ode
ls
�P
ote
ntia
lflo
ww
ith
vis
cou
sla
ye
rs
�E
ule
r
�N
avie
r-S
tokes
�In
com
pre
ssib
le
�B
oussin
esq
�V
ariab
lede
nsity
�C
om
pre
ssib
le
Ana
lytica
l
Part
ial
diffe
rentia
l
equ
atio
ns
4M
020
De
sig
n T
oo
ls; O
ptim
isa
tion
in T
he
rmo
-Flu
ids
En
gin
ee
rin
g
Flowmodels and optimisation
Ge
nera
l: T
rad
eo
ff
�A
na
lytica
l/E
xa
ct b
utcru
de
ph
ysic
s
�A
ccura
te p
hysic
sb
utcru
de
ap
pro
xim
atio
ns; n
um
eri
cs
�A
cc
ura
cy
ve
ryim
po
rta
nt
in o
pti
mis
ati
on
!!
�Y
ou
cann
ot
optim
ise
in %
if
yo
ur
calc
ula
tion/p
redic
tio
n
accura
cy
is n
ot
on
the s
am
ele
vel
�Lo
w R
eyn
old
s lam
inar
ste
ad
yflo
ws
(nan
o-t
echnolo
gy,
mic
ro c
om
pact,
heat
exchan
gers
, la
b-o
n-a
-chip
)
�C
ontr
olpro
ble
ms
(e.g
. suppre
ssin
gvort
ex
shedd
ing)
�F
utu
re:
Optim
isation
for
more
and m
ore
com
ple
x p
roble
ms
Ge
nera
l: T
rad
eo
ff/lim
itati
on
s
4M
020
De
sig
n T
oo
ls; O
ptim
isa
tion
in T
he
rmo
-Flu
ids
En
gin
ee
rin
g
Optimisationin CFD
Ap
pro
ac
h
�G
ood
str
ate
gy
requ
ires
de
taile
dkn
ow
ledg
eo
f flu
idd
yn
am
ics
an
d
co
mp
uta
tio
nalm
eth
od
s.
�U
se
of C
om
pu
tatio
na
lF
luid
Dyn
am
ics (
CF
D),
�S
olv
ing
sets
of
part
iald
iffe
rentialeq
uatio
ns
(PD
E’s
);
�sta
rted
in t
he 8
0s;
�philo
sop
hy:
ca
lcula
tean
d a
na
lyse a
cert
ain
desig
n
�R
ecen
t: B
. M
oh
am
ma
di&
O. P
iron
ne
au, S
ha
pe
Optim
iza
tio
nin
Flu
id
Me
ch
an
ics, A
nn
ua
lR
ev. F
luid
Mech
., 2
00
4, 36
, p
p 2
55
-27
9.
4M
020
De
sig
n T
oo
ls; O
ptim
isa
tion
in T
he
rmo
-Flu
ids
En
gin
ee
rin
g
Optimisationin CFD
Ap
pro
ach
�H
igh
lyeducate
ddesig
ner
dete
rmin
es
the p
ara
mete
rs t
o o
ptim
ize
�C
han
gin
gpara
mete
rs w
illoft
en
lead
to e
dge
(pre
defined)
op
tim
a
�P
ushin
gth
e b
oundari
es
will
oft
en
result
in c
hangin
gph
ysic
s
�e
.g.
be
co
me
su
nste
ad
y,
no
Sto
ke
sflo
wa
nym
ore
etc
.
�C
FD
learn
sd
esig
ners
wh
at
para
mete
rs m
ight
be
import
ant
�P
ara
me
ter
stu
dy
lea
rns
de
sig
ne
rs t
o r
ea
llylo
ok a
t n
ew
co
nce
pts
�A
uto
matic
optim
ization
in m
ulti-para
mete
r/m
ulti-ph
ysic
sstill
far
aw
ay
�M
ulti-
pa
ram
ete
ris
do
ma
in o
f m
ath
em
aticia
ns,
ge
ne
tic
alg
ori
thm
se
tc.
4M
020
De
sig
n T
oo
ls; O
ptim
isa
tion
in T
he
rmo
-Flu
ids
En
gin
ee
rin
g
Optimisationin CFD
Cert
ain
lya
gre
at
futu
refo
r
Op
imis
ati
on
in C
FD
!!�
Re
lative
lyune
xp
lore
d
4M
020
De
sig
n T
oo
ls; O
ptim
isa
tion
in T
he
rmo
-Flu
ids
En
gin
ee
rin
g
Optimisationin CFD
Ex
am
ple
s:
4M
020
De
sig
n T
oo
ls; O
ptim
isa
tion
in T
he
rmo
-Flu
ids
En
gin
ee
rin
g
Optimisationin CFD
Ex
am
ple
s:
�Q
. L
i e
t a
l.,
Evo
luti
on
ary
Str
uc
tura
lO
pti
miz
ati
on
, In
t.J
.He
at
Ma
ss
Tra
ns
fer,
42
, (1
99
9)
�A
. G
ers
bo
rg-H
an
se
ne
t a
l.,
To
po
log
yo
pti
miz
ati
on
of
ch
an
ne
l fl
ow
pro
ble
ms
, S
tru
ct.
M
ult
idis
c.
Op
tim
., 3
0,
(20
05
)
�D
.N.
Sri
na
th,
S.
Mit
tal,
A s
tab
iliz
ed
fin
ite
ele
me
nt
me
tho
dfo
rs
ha
pe
op
tim
iza
tio
nin
lo
w R
eyn
old
s n
um
be
rfl
ow
s,
Int.
J.
Nu
m.
Me
th.
Flu
ids
, 5
4,
(20
07
)
�A
. G
ers
bo
rg-H
an
se
ne
t a
l.,
To
po
log
yo
pti
miz
ati
on
of
he
at
co
nd
uc
tio
np
rob
lem
su
sin
gth
e f
init
evo
lum
e m
eth
od
, S
tru
ct.
Mu
ltid
isc
. O
pti
m.,
31
, (2
00
6)
�D
.E.
He
rtzo
g e
t a
l.,
Op
tim
iza
tio
no
f a
mic
rofl
uid
icm
ixe
r fo
rs
tud
yin
gp
rote
info
ldin
gk
ine
tic
s,
An
al.
Ch
em
., 7
8,
(20
06
)
�H
. A
nti
le
t a
l.,
Op
tim
al
de
sig
n o
f s
tati
on
ary
flo
wp
rob
lem
sb
yp
ath
-fo
llo
win
gin
teri
or
po
int
me
tho
ds
, S
tru
ct.
Mu
ltid
isc
. O
pti
m.,
su
bm
itte
d(2
00
7)
�L
.De
bia
ne
et
al.
, T
em
pe
ratu
rea
nd
po
llu
tio
nc
on
tro
lin
fla
me
s,
Pro
c.
Su
mm
er
Pro
gr.
, C
en
ter
for
Tu
rbu
len
ce
Re
se
arc
h,
(20
04
).
4M
020
De
sig
n T
oo
ls; O
ptim
isa
tion
in T
he
rmo
-Flu
ids
En
gin
ee
rin
g
Optimisationin CFD
Ex
am
ple
s:
�L
imit
ed
ap
plic
ati
on
�M
ath
em
ati
calm
eth
od
s
�L
imit
ed
para
mete
r sp
ace
�H
ert
zo
g e
t a
l.:
�N
avie
r S
toke
s
�C
on
ve
cti
on
-Dif
fusio
n
�C
om
so
l
�40 %
red
ucti
on
in m
ixin
gti
me
�D
eb
ian
ee
t al., C
en
ter
for
Tu
rbu
len
ce
Re
se
arc
h 2
00
4:
�A
pp
licati
on
in f
lam
es
�I w
as t
here
bu
tI
fou
nd
this
art
icle
on
lyye
ste
rda
y!!
4M
020
De
sig
n T
oo
ls; O
ptim
isa
tion
in T
he
rmo
-Flu
ids
En
gin
ee
rin
g
Optimisationin CFD
4M
020
De
sig
n T
oo
ls; O
ptim
isa
tion
in T
he
rmo
-Flu
ids
En
gin
ee
rin
g
Optimisationin CFD
4M
020
De
sig
n T
oo
ls; O
ptim
isa
tion
in T
he
rmo
-Flu
ids
En
gin
ee
rin
g
Optimisationin Comsol
Co
nc
lus
ion
:
Le
t u
sju
st
sta
rt o
urs
elv
es
wit
ha
ne
xp
eri
me
nt
in C
om
so
l:
Do
ub
le g
lazin
g:
4M
020
De
sig
n T
oo
ls; O
ptim
isa
tion
in T
he
rmo
-Flu
ids
En
gin
ee
rin
g
Optimisationin Comsol
�O
pti
mis
ed
ou
ble
gla
zin
gd
es
ign
�O
pti
mis
ati
on
pa
ram
ete
rs:
�M
inim
izati
on
of
heat
flu
x
�M
axim
izati
on
of
aco
usti
cis
ola
tio
n
�M
axim
izati
on
of
mech
an
ical
str
en
gth
, re
sit
an
ce
to i
mp
act
�M
inim
izati
on
of
co
sts
4M
020
De
sig
n T
oo
ls; O
ptim
isa
tion
in T
he
rmo
-Flu
ids
En
gin
ee
rin
g
Optimisationin Comsol
�H
yp
oth
es
is 1
�T
he t
hic
ker
the a
ir l
ayer
the m
ore
iso
lati
ng
�B
ut
the a
ir i
s n
ot
sta
gn
an
t, s
o
�H
yp
oth
es
is 2
�A
t la
rge
rd
ista
nce,
L,
the R
a n
um
ber
beco
mes
hig
her
–T
hir
dp
ow
er:
–F
low
beco
mes
mo
re v
igo
rou
s
–E
ven
tuall
yin
sta
tio
nary
–H
eat
tran
sfe
r b
yco
nvecti
on
incre
ases
–M
ore
heat
losses
4M
020
De
sig
n T
oo
ls; O
ptim
isa
tion
in T
he
rmo
-Flu
ids
En
gin
ee
rin
g
Optimisationin Comsol
�P
hys
ica
lp
rob
lem
:
�C
on
du
cti
on
�N
atu
ral
co
nve
cti
on
�P
art
iald
iffe
ren
tiale
qu
ati
on
s:
�C
on
vecti
on
an
d C
on
du
cti
on
(CC
)
�N
avie
r-S
tok
es
eq
uati
on
s(N
S)
�M
utu
al
infl
uen
ce
•B
uo
yan
cy
forc
eas f
un
cti
on
of
T s
olv
ed
by
CC
in
NS
•V
elo
cit
ies
for
co
nve
cti
on
of
heat,
so
lved
fro
mN
S i
n C
C
4M
020
De
sig
n T
oo
ls; O
ptim
isa
tion
in T
he
rmo
-Flu
ids
En
gin
ee
rin
g
Optimisationin Comsol
�S
etu
pa
nd
bo
un
da
ryc
on
dit
ion
s
�A
ll (
oth
er)
wa
lls:
no
slip
, a
dia
bati
c
�H
=0
.1 m
, L
(in
itia
l)=
0.0
1 m
, d
=0
.00
2 m
T=
320 K
T=
280 K
4M
020
De
sig
n T
oo
ls; O
ptim
isa
tion
in T
he
rmo
-Flu
ids
En
gin
ee
rin
g
Equationsin Comsol
�E
qu
ati
on
s
T=
320 K
T=
280 K
4M
020
De
sig
n T
oo
ls; O
ptim
isa
tion
in T
he
rmo
-Flu
ids
En
gin
ee
rin
g
Optimisationin Comsol
�P
ara
mete
rs:
�D
ista
nce
betw
een
gla
zin
g
�T
hic
kn
ess
of
the g
lass
�H
eig
ht
of
the g
lass/h
ow
to s
imu
late
full
heig
ht
–V
ari
ati
on
of
heig
ht
–In
flo
w/o
utf
low
�R
ele
van
t te
mp
era
ture
dif
fere
nce
4M
020
De
sig
n T
oo
ls; O
ptim
isa
tion
in T
he
rmo
-Flu
ids
En
gin
ee
rin
g
Optimisationin Comsol
�P
ara
mete
rs:
�P
hysic
al
pro
pert
ies
of
the g
lass
–C
on
du
cti
vit
y
–D
en
sit
y
–H
eat
cap
acit
y
�P
hysic
al
pro
pert
ies
of
the m
ed
ium
(arg
on
, w
ate
r)
�P
ressu
re:
Wh
at
iso
late
sb
ett
er
–L
ow
pre
ssu
re(l
ow
den
sit
y,
cap
acit
y)
–H
igh
pre
ssu
re(h
igh
er
forc
en
eed
ed
for
mo
men
tum
)
�In
sta
tio
nary
beh
avio
ur?
4M
020
De
sig
n T
oo
ls; O
ptim
isa
tion
in T
he
rmo
-Flu
ids
En
gin
ee
rin
g
Optimisationin Comsol
�S
etu
pth
e m
od
el in
Co
ms
ol;
sa
ve
in
Matl
ab
�W
hat
do
we d
o w
ith
the p
ressu
re?
�W
e a
re g
oin
gto
ch
an
ge
the g
eo
metr
y, w
hat
do
es
this
mean
for
the g
rid
din
g?
�C
on
sta
nts
:
�A
ir:
density
1.2
, k=
0.0
25,
Cp=
1006,
eta
=1.7
10
-5
�G
lass:
density
2500,
k=
1.1
, C
p=
840
�U
nits?
4M
020
De
sig
n T
oo
ls; O
ptim
isa
tion
in T
he
rmo
-Flu
ids
En
gin
ee
rin
g
Optimisationin Comsol
Heat
flu
x a
naly
sis
:
4M
020
De
sig
n T
oo
ls; O
ptim
isa
tion
in T
he
rmo
-Flu
ids
En
gin
ee
rin
g
Optimisationin Comsol
Flo
wan
aly
sis
:
4M
020
De
sig
n T
oo
ls; O
ptim
isa
tion
in T
he
rmo
-Flu
ids
En
gin
ee
rin
g
Optimisationin Comsol
Flo
wan
aly
sis
:
Insta
tio
nary
beh
avio
ur?
4M
020
De
sig
n T
oo
ls; O
ptim
isa
tion
in T
he
rmo
-Flu
ids
En
gin
ee
rin
g
Assignment
3 p
ossib
ilit
ies:
�D
ou
ble
gla
zin
g:
mo
re p
ara
mete
r va
riati
on
s
–R
ese
arc
h p
ossib
leu
nste
ad
yb
eh
avio
ur
–In
flu
en
ce
of
gla
ss
thic
kn
ess
–U
se
arg
on
an
d w
ate
r (d
ete
rmin
ech
an
ges
in
Ra a
nd
Pr
in a
dvan
ce)
�N
ew
: C
ilin
der
in a
bo
x,
dis
turb
ing
co
nvecti
on
–B
ox i
s a
lid
dri
ven
ca
vit
y
–S
cala
rfl
ux (
tem
pera
ture
, sp
ecie
s)
at
the t
op
–F
ixed
valu
eat
the b
ott
om
–R
ese
arc
h i
nfl
uen
ce
of
po
sit
ion
an
d s
ize
of
a
cil
ind
er,
wit
hn
oslip
walls.
4M
020
De
sig
n T
oo
ls; O
ptim
isa
tion
in T
he
rmo
-Flu
ids
En
gin
ee
rin
g
Assignment
Cil
ind
er
in a
bo
x:
4M
020
De
sig
n T
oo
ls; O
ptim
isa
tion
in T
he
rmo
-Flu
ids
En
gin
ee
rin
g
Assignment
Cil
ind
er
in a
bo
x:
–D
ete
rmin
eb
ase f
low
–A
dd
the s
cala
rp
rob
lem
–P
ut
cil
ind
er
in
–V
ary
, d
ete
rmin
eco
st
an
d a
naly
se
4M
020
De
sig
n T
oo
ls; O
ptim
isa
tion
in T
he
rmo
-Flu
ids
En
gin
ee
rin
g
Assignment
3rd
po
ssib
ilit
y:
Yo
ur
ow
no
pti
mis
ati
on
pro
ble
m
(in
th
iscase y
ou
need
to k
no
wan
d d
iscu
ss
wit
h
me t
od
ay)
4M
020
De
sig
n T
oo
ls; O
ptim
isa
tion
in T
he
rmo
-Flu
ids
En
gin
ee
rin
g
Fu
rth
er
info
rma
tio
n:
Dr.
R.J
.M. B
astia
ans
(Rob
)C
om
bu
stio
n T
ech
no
log
yM
ech
an
ica
l E
ng
ine
eri
ng
, W
H 3
.14
1E
ind
ho
ve
n U
niv
ers
ity o
f T
echn
olo
gy
P.O
. B
ox 5
13, 5
600
MB
Ein
dh
ove
n, T
he N
eth
erl
and
sE
: r.
j.m
.ba
stia
an
s@
tue
.nl
T: +
31
40
247
48
36
F: +
31
40
243
34
45
ww
w.c
om
bu
stio
n.tu
e.n
l