Scramjet

9/8/2017 Review of Numerical Modeling and Simulation Results Pertaining to High-speed Combustion in Scramjets
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Page 1
Review of Numerical Modeling and Simulation Results
Pertaining to High-speed Combustion in Scramjets
Ryan J. Clark* and S. O. Bade Shrestha†
Western Michigan University, Kalamazoo, Michigan, 49008
This paper is a reviewof numerical modeling of high-speedcombustion as it pertains to
scramjets. Simulation results are presentedfrom numerous researchers that have devoted
their time andeffort to numerically investigate high-speedcombustion in scramjets. In
addition to their findings validation work is presented, showing the validity of ANSYS
Fluent 12.1 in the application of high-speedcombustion in scramjets.
I. Introduction
OR approximately sixty years there has been a global effort to expand upon the understanding of supersonic
combustion through fundamental and experimental research. There are numerous fluid dynamic phenomena to
independently research within the area of supersonic combustion, specifically with the development of the scramjet
engine. Though much advancement has been made in the development of the scramjet, further understanding of the
fluid dynamic processes in high-speed combustion in the scramjet is required if it is to reach its long-termgoals
(e.g., implementation in responsive space access; long-range, prompt global strike; and future high speed
transportation). This paper reviews past numerical simulation research pertaining to scramjet combustion and
presents simulation results validating the use of ANSYS Fluent 12.1 in the application of scramjet combustion. It
begins with introducing past reviews conducted by the Air Force, NASA, and others, followed by a summary of
numerical simulations on scramjet combustion conducted in recent years.
II. Review
In 1996 a review was conducted as a joint effort by the Air Force Office of Scientific Research, the Air Force
Wright Laboratory Aero Propulsion and Power Directorate, and the NASA Langley Research Center1. The purpose
of their review was much more extensive than the one being presented within this work. Their review discussed the
scramjet in its entirety. The review by the Air Force and NASA concluded with a list of areas that need further
research. In regards to combustion there was an expressed need for the following: further research with emphasis on
unsteady analysis of combustion instability; improved turbulence modeling techniques of high speed reacting flows
to accurately predict the interactions between turbulence and chemical reactions; further research implementing
turbulence models based on the probability density functions; and advancements in large eddy simulation (LES)
with the development of subgrid scale models appropriate to high-speed compressible flow1.
A more recent review of scramjet combustion, including the mixing process, was presented in the 2010 issue of
the AIAA Journal. This review consisted of a summary of five papers which established the standing of scramjet
combustion and mixing as of 20102. The first summary was of the work conducted by Ingenito and Bruno, who
investigated supersonic reacting flow for the case of hydrogen injection at Mach 2.5 into an airstreamflowing at
Mach 2, using the NASA-Langley combustor model3. Three-dimensional, large eddy simulations were implemented
using a subgrid scale model, ISCM, which was developed specifically for supersonic combustion. More specifically,
F
Downloaded by UNIVERSITY OF OKLAHOMA on August 18, 2013 | http://arc.aiaa.org | DOI: 10.2514/6.2013-3724
49th AIAA/ASME/SAE/ASEE Joint PropulsionConference
July 14 - 17, 2013, San Jose, CA
AIAA 2013-3724

American Institute of Aeronautics and Astronautics
1
the ISCM model accounted for microscale physics through a subgrid kinetic energy equation that provided velocity
fluctuation required by the eddy viscosity subgrid scale closure, reacting turbulent structures were modeled by a
reactor burning at constant volume, and the reaction rate depended on the local Mach number3. Ingenito and Bruno
used the FLUENT 6.3TM commercial code to simulate experimental work conducted with the NASA-Langley
combustor model.
Some of their results are shown in Figures 1 and 2 which illustrate the instantaneous temperature field and
density gradients, respectively. Numerical results for instantaneous maximumtemperatures, shown in Fig. 1, were
* Ph.D. Student, Department of Mechanical and Aerospace Engineering, Kalamazoo, Michigan.
† Associate Professor, Department of Mechanical and Aerospace Engineering, Kalamazoo, Michigan.
Copyright © 2013 by the American Institute of Aeronautics and Astronautics, Inc. All rights reserved.
Page 2
15%-20%
reaction w
hydrogen-a
periodicall
Following
is forced b
quench. F
the shockw
anchor and
reaction ra
mixing rat
dilatation t
As me
further stu
higher than the
ith no radicals
air shear laye
ly. Point 2 on
point 2 the fla
by reactants ig
igure 2 shows
wave at which
d quench was a
ate. Ingenito an
tes caused by
termon the rea
entioned, Ingen
udied, resulting
Figure 1. In
Figure 2. V
e experimental
in the product
er, which is a
Fig. 1 is the
ame develops d
gniting at poin
that the locatio
the density gra
a result of high
nd Bruno furthe
vorticity tran
action rate3.
nito and Bruno
g in the follow
nstantaneous t
Visualization o
l temperatures.
s3. Point 1, in F
about 5 cmfr
location of ig
downstream, lif
nt 13. Figures 1
on at which the
adient is the hi
h temperature g
er credited the
sport being in
observed an u
wing explanati
temperature f
of shock waves
. This result w
Fig. 1, indicate
romthe fuel
gnition of the
fts off and mov
1 and 2 show
e flame anchor
ighest. It was s
gradients cause
positive impa
nduced by bar
unsteady flame
ons for their o
fieldandstrea
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was attributed to
es the start of c
injector3. From
mixture at ab
ves towards th
the periodic n
rs to the upper
suggested that
ed by shock w
act of shocks o
roclinic effects
with periodic
observations. T
amlines in the
el3.
o the use of a s
combustion on
mthat point
out 15 cmfro
he exit; this per
nature of the f
wall correspon
the periodic n
waves and local
n flame ancho
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behavior. Thes
The unsteadine
middle XYpl
single-step oxi
the upper side
the mixture i
omthe fuel inj
riodical phenom
flame to ancho
nds to the locat
nature of the fla
l compression
oring to the inc
the influence
se observation
ess of the flam
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idation
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menon
or and
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attributed t
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across the
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ikely lead to c
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elay time is les
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a result of lar
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merical simulat
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öhler, Reynold
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When
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Page 3
LES w
high-speed
that mainta
developme
focused the
parameters
Genin
for both n
wedge in a
combustion
includes m
critical issu
model wer
(DLR), Re
closure.
Figure
for the non
experimen
Figure 3
was also implem
d computationa
ain their integr
ent of valid tu
eir efforts on L
s, and subgrid s
n and Menon ad
on-reacting an
a co-flowing ai
n, referred to
molecular diffus
ues for modelin
re compared to
eynolds-averag
es 3 and 4 show
n-reacting case
tal data than th
. Mean veloci
mented in the w
al fluid dynam
rity throughou
urbulence closu
LES with an em
scale closures t
ddressed the af
nd reacting cas
ir free-stream.
as the linear e
sion effects wi
ng H2 – O2 mi
experimental
ged Navier-Sto
w the mean vel
e. The LES-LE
he LES and RA
ity profile at d
work conducte
mics (CFD)4. T
t the entirety o
ures for a ran
mphasis on ada
that do not hav
forementioned
ses using LES
A subgrid mix
eddy mixing (
thin the subgri
xing and comb
data fromthe I
okes equations
locity and axia
EM predictions
ANS results, sp
different statio
ed by Genin an
hese challenge
of the flow, in
nge of aerospa
aptable numeri
ve adjustable co
d challenges thr
. In these simu
xing and comb
(LEM) model,
id and closes th
bustion4. Resul
Institute for Ch
s (RANS) pre
al velocity fluct
for the mean
pecifically at th
ons for non-re
nd Menon, who
es are as follow
ncluding region
ace engineering
ical algorithms
onstants.
rough simulati
ulations hydro
bustion model
was impleme
he reaction kin
lts fromthe nu
hemical Propu
dictions, and
tuation profile
velocity profil
he location of 5
eacting LES4.
o focused on tw
ws: first, deve
ns of discontin
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s, dynamically
ions of a hydro
ogen was injec
previously dev
ented in this re
netics in an exa
umerical simula
ulsion of Germa
LES with sub
s, respectively
les show better
58 mmfromthe
wo challenges
elopment of sc
nuities; second
. Genin and M
y obtained turbu
ogen-fueled sc
cted at the bas
veloped for sub
esearch. This
act manner, the
ation using the
an Aerospace C
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e base of the w
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ly, the
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ulence
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Center
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tations
ith the
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Figure 4 . Axial veloci
Americ
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can Institute of
profiles at tw
f Aeronautics a
3
wo different sta
and Astronauti
ations for non
ics
n-reacting LES S4.
Page 4
The LE
fluctuation p
experimental
location of 1
shows the LE
the far-field. W
Menon sugge
predictions an
subtle effect o
LEM approac
the LES-LEM
a lack of suf
predictions f
agreement w
suggested tha
extending the
perfect gas a
method to the
boundary laye
Berglund
mixing and co
scramjet com
finite-rate che
step reaction
used the mixe
the stress ten
most of the p
Prandtl numbe
for each react
mechanism, t
closest agreem
mechanismto
data and also
Some of the
following figu
averaged wall
wall as it com
comparison b
time-averaged
a comparison
time-averaged
images were
cases 6 and
S-LEM pred
profiles show
data than the
15 mmfrom
S-LEM approa
With regards t
ested that bett
nd experimenta
of how the sca
ch4. It was cite
M profiles, as se
fficient data in
fromthe LE
with experime
at there is po
e calorically pe
and implement
e base scheme,
ers4.
et al. conduct
ombustion for
mbustor5. LES
emistry model
mechanisms w
ed model for m
nsor, energy fl
parameters, inc
ers, were assum
tion mechanis
the seven-step
ment. Addition
o give the best
resulted in th
results fromB
ures. Figure 6
l pressure distr
mpares to exp
between OH-P
d OH mass frac
n between OH
d OH mass fra
obtained by S
7 refer to the
dictions for
w better agr
e LES and R
the base of th
ach to better pr
to the non-reac
ter agreement
al data could b
alar width is r
ed that the flu
een in Figures
n the statistica
ES-LEM meth
ental data4. G
otential for f
erfect gas assu
ting an efficie
, along with pr
ted LES simul
a joint French
with an expl
was used. On
were investiga
modeling three
flux, and speci
cluding the tur
med constant.
smwere comp
p mechanisms
nal results reve
comparison w
he highest com
Berglund et a
shows the pre
ribution along
perimental data
PLIF images
ction distributi
H-PLIF images
action distribut
Sunami et al.6.
e one and tw
the axial ve
reement with
RANS results
he wedge. Fig
redict temperat
cting case Gen
between LES
be dependent
resolved in the
uctuation featu
3-5, were a re
al analysis4. O
hod showed
Genin and M
furthur accura
umption to ther
ent shock cap
roperly resolvi
ations of supe
h-Japanese labo
licit partially
ne-, two-, and
ated. Berglund
subgrid-scale
ies flux. Valu
rbulent Schmid
The induction
pared with a 1
showed to hav
ealed the seve
with the experim
mbustion effici
al. are shown
dictions of the
the lower com
a. Figure 7 sh
and predicted
ions. Figure 8
and predicted
tions. The OH
In Figures 7
o step mechan
elocity
h the
at the
gure 5
ture in
nin and
S-LEM
on the
e LES-
ures of
esult of
Overall,
good
Menon
acy by
rmally
pturing
ing the
ersonic
oratory
stirred
seven-
d et al.
terms:
ues for
dt and
n times
19-step
ve the
en-step
mental
iency5.
in the
e time-
mbustor
hows a
d short
shows
d long
H-PLIF
and 8
nisms,Downloaded by UNIVERSITY OF OKLAHOMA on August 18, 2013 | http://arc.aiaa.org | DOI: 10.2514/6.2013-3724

Figure 5
different
5. Temperatur
t stations for t
Americ
re profiles
the reacting ca
can Institute of
at three
ase4.
f Aeronautics a
4
respectively. C
and Astronauti
Case 8 refers to
ics
o the seven-steep mechanism.
Page 5
Fig
cas
ure 6. Time-a
e of combustio
averagedwall
on5.
l pressure dis
Case 6
stribution alon ng the lower
Case 7
combustor w
Ca
wall for the
ase 8

Figu
YOH
Not
exp
ure 7. Compa
H mass fractio
te that the sca
eriments5.
Americ
arison of OH-P
on distribution
ale is the same
can Institute of
PLIF images
ns from cases
e for all comp
f Aeronautics a
5
from Ref. 6 (
6, 7, and8, r
utational case
and Astronauti
(far left) with
respectively at
es 6, 7, and8
ics
predictedsho
t a) xte = 4 h a
andcorrespo
ort time-avera
andb) xte = 1
nds to that of
aged
0 h.
f the
Page 6
In case
fuel inject
quantitativ
observation
with the se
and OH) an
For the
complex-sh
pockets sm
reactions. U
in turn affe
acceleratin
important,
species tha
Figur
avera
xte = 1
that o
e 8 (the seven-
tor jets in add
ve agreements
ns it was conc
even-step mech
nd mixing to o
e seven-step me
haped pockets
mall-scale mixi
Upon satisfyin
fects the surrou
ng the flow5. F
for its produc
at accumulate i
re 8. Compari
aged<YOH> m
10 h. Note tha
of the experim
step LES) of F
dition to being
with the mea
luded that the
hanismis suffi
occur5.
echanismthese
s (shown in F
ng dominates
ng these condit
unding vortical
For the seven-s
cts react with t
n the pockets5.
ison of mean
mass fraction d
at the scale is
ments5.
Fig. 7 OH is fo
g wrinkled by
asured OH di
difference in i
icient to allow
e transport pro
Figures 7 and
over large-scal
tions combustio
l flow through
step mechanism
the H2 to produ
. In summary, t
OH-PLIF im
distributions fr
the same for
Case 6
ound in thick c
y the vorticity
istributions. T
ignition delay t
large scale con
cesses lead to
8) between la
le vertical mix
on is very fast
volumetric ex
m, the chain-br
uce H, which
the seven-step
mages from R
from cases 6, 7
all computati
C
complexstruct
y field5. This
This is similar
time between t
nvective transp
local accumula
arge-scale coh
xing, creating t
t, rapidly releas
xpansion, raisin
ranching step H
reacts again to
mechanismal
Ref. 6 (far left
7, and8, respe
ional cases 6,
Case 7
tures surround
image is in g
rly shown in
the one- and tw
port of interme
ation of the int
herent vertical
the proper cond
sing large amo
ng the pressure
H + O2 ↔ OH
o produce H, O
llowed for tran
t) with predic
ectively at a) x
7, and8 and
Cas
ding the second
good qualitativ
Fig. 8. From
wo-step mecha
ediate species
termediate spe
structures. In
ditions for con
ounts of energy
e, exothermici
H + O is partic
O, and OH, th
nsport and conv
ctedlong time
xte = 4 h andb
corresponds t
se 8
d stage
ve and
these
anisms
(O, H,
cies in
n these
ntinued
y. This
ity and
cularly
he very
vective
e-
b)
to

mixing of O
Baurle
using RAN
used for th
heliumas t
number an
displayed a
This is sho
O, H, and OH,
and Edwards
NS and hybrid
he validation o
the inner fluid.
nd the predictio
a strong sensit
own in Fig. 9.
Americ
as well as app
investigated s
d RANS/LES7.
of CFD simula
. The behavior
on of superson
tivity to choice
can Institute of
propriate reacti
scramjet comb
Experimental
ations. The co
of the jet was
nic-mixing-lay
e of turbulent S
f Aeronautics a
6
on kinetics5.
ustion and mi
work conduc
oaxial free jet
investigated w
er spreading r
Schmidt numb
and Astronauti
ixing of a coax
cted at the NA
consisted of a
with respect to t
rates. The RAN
er, with a valu
ics
axial supersoni
ASA Langley R
air as the outer
the values of th
NS simulation
ue of 1.0 being
ic freejet exper
Research Cente
r fluid and arg
he turbulent Sc
for the helium
g an optimal ch
riment
er was
gon or
chmidt
mcase
hoice7.
Page 7

For th
to mixing,
under pred
significant
Figure
he argon case, a
the hybrid RA
dicted the rate
uncertainty w
9. Comparis
Americ
a turbulent Sch
ANS/LES appr
of mixing wh
with choosing
on of normali
can Institute of
hmidt number
roach over pre
hen argon was
appropriate v
izedhelium m
f Aeronautics a
7
of 0.5 provide
dicted the mix
used. The res
values for the
ass fraction (R
and Astronauti
ed the best ma
xing-layer spre
sults fromBau
RANS mode
RANS predict
ics
atch with measu
eading rate for
urle and Edwa
eling paramete
tions) with me
urements. In r
the heliumca
ards indicate th
ers. This uncer
easuredvalues
egards
se and
here is
rtainty
s7.
Page 8
highlights the difficulty with using these approaches for predictive simulations. In regards to LES or hybrid
RANS/LES, these methods resolve a substantial fraction of the turbulent flow field thereby potentially reducing this
uncertainty7. However, in this case study the hybrid simulations were no more predictive than the baseline
Reynolds-averaged predictions. The discrepancy between the hybrid RANS/LES results and the measurements was
attributed to how the RANS state transitions to a state with resolved turbulent content7.
Malo-Molina et al. conducted 3-D simulations, using HEAT3D, to investigate the effects of inlet velocity
distortion on injection strategies for supersonic combustion at a Mach 6 flight8. Various injector locations and inlet
profiles were investigated. The inlet profiles that were considered were two streamlined-traced inlets (Scoop and
Jaws) and a baseline uniforminflow boundary condition. Frozen and finite rate chemistries were investigated for
each inlet profile type. The fuel, gaseous ethene, was injected at 400 m/s. A 20-step reduced–kinetic mechanismfor
ethene-air combustion was used. The steady RANS and unsteady RANS were based on the k-w model.
It was observed that the profiles fromboth the Jaws and Scoop inlet led to greater fuel-air mixing efficiency
than the uniformprofile. This was attributed to additional vortical structures and circulation near the wall8. The
vortical structures and near-wall circulation increased the shock-boundary layer interactions promoting further
diffusion. The results showed that the Jaws inlet profile yielded greater levels of mixing and a greater thrust ratio in
comparison to the Scoop’s inlet profile8. The development of shear layers and downstreamcombustion were
observed to be affected by reactions moving forward fromthe cavity8. The unsteady RANS predictions of mixing
efficiency were 5% greater than the steady RANS predictions. Results indicate the potential to optimize the fuel
injection strategy in order to take advantage of the flow features at the inlet exits.
More recently, Fulton et al. compared the RANS method to a hybrid LES/RANS method9. Results fromthe
numerical simulations were compared to experimental data for a reacting and non-reacting case for two tested
equivalence ratios (0.17 and 0.34) as conducted at the University of Virginia’s Scramjet Combustion Facility. The
numerical simulation implemented a 9-species, 19-reaction hydrogen-air kinetics mechanismby Jachimowski and
utilized the Menter BSL turbulence model9. The computational domain consisted of an isolator with a ramp injector
and a divergent combustor and extender.
The LES/RANS method captured the direct effects of larger turbulent eddies and local straining of the flame,
allowing for better predictions of reactant mixing and combustion in the flame stabilization region downstreamof
the fuel injector9. There was also good agreement between predictions fromthe LES/RANS method and the OH-
PLIF and SPIVmeasurements. The OH-PLIF measurements, for the test case in which the equivalence ratio was
0.17, are shown in Fig. 10. The top three images in Fig. 10 compare ensemble-averages of fluorescence intensity
(2000 images) with time averaged OH mass-density predictions fromthe LES/RANS and RANS methods9. The
bottomimages compare an instantaneous OH-PLIF image fromexperimental work with an OH mass density image
fromthe LES/RANS simulations9. Figure 10 shows the extent of variation between the time-averaged result and the
instantaneous value. It is evident that the influences of finite rates of reactant mixing and large turbulence-induced
strain rates disrupt a continuous flame front as shown in the RANS solution9.

8
Page 9
With re
temperatur
downstream
model and
LES/RAN
by shock/b
features (e
over-predic
A chal
method. T
highlightin
of the RAN
predict par
Figure 10
images; l
espsect to the
re near the inj
mfromthe co
d the RANS mo
S model under
boundary layer
e.g., shock trai
cted the flame
llenge to simu
Turbulence mo
ng the limitatio
NS-based turbu
rameters such
0. Compari
left to right: O
equivalence ra
jector while th
ombustor whil
odel either und
r-predicted the
r interactions9
in oscillations)
temperature an
ulating high-sp
odeling framew
ons to RANS-b
ulence models,
as wall heat tr
ison with OH
OH-PLIF, LES
atios, the flam
he flame corr
e still being a
der-predicted o
displacement
. However, th
) to a greater f
nd the rate of r
peed combusti
work poses its
based turbulenc
using constan
ransfer10. This
H-PLIF Imag
S/RANS, RAN
me correspondin
responding to
anchored to th
or over-predicte
effects of reac
e LES/RANS
fidelity than th
reactant mixing
ing flow is de
s own limitati
ce models in sc
nt Prandtl and S
s is due to the
ges (top: time
NS)9.
ng to an equiv
an equivalenc
he injector9. In
ed certain prop
cting plumes a
simulations c
he RANS mod
g and consump
etermining an
ions. Ott and
cramjet applic
Schmidt numbe
turbulence mo
e averagedi
valence ratio o
ce ratio of 0.3
n conclusion, b
perties or featu
and low momen
captured large-
dels. In contra
ption9.
appropriate t
Dash recogn
cations, stating
ers, limits rese
odel not being
images; botto
of 0.17 had a g
34 displaced f
both the LES/R
ures in the flow
ntumregions c
-scale unsteady
ast the RANS
turbulence mo
nized this chal
that implemen
archers to accu
g able to accou
om: instantan
greater
further
RANS
w. The
caused
y flow
model
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large variaregions as
Ott and Da
low (near-
damping fu
This un
data. The
as shock b
kinetic ene
revealed a
Prandtl nu
for modeli
reliable in
Recent
specifically
supersonic
focused on
axisymmet
ations in shocka result of lim
ash addressed t
-wall) Reynold
unction, consis
nified k-e base
validation anal
boundary layer
ergy levels and
need to model
mbers yielded
ng compressib
the types of flo
work by Mi
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Americ
k wave/turbulemits posed by c
this issue by pr
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stent with the v
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interations. D
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l Prandtl numb
an over-predi
bility effects. T
ows that were a
illigan et al.
t number11. Mi
facility, Resear
ombustion in
past studies w
can Institute of
ent boundary laonstant Prandt
roposing a unif
s are blended
velocity dampin
ulence model w
d significant ty
Data analysis sh
fluctuations. E
ber variations in
icted heat trans
The unified mo
analyzed10.
revealed insig
illigan et al. c
rch cell (RC22
a scramjet wi
were conducted
f Aeronautics a
9
ayer interactiotl and Schmidt
fied k-e based
and a scalar f
ng termin the b
was calibrated
ypes of flow, in
howed that the
Experimental d
n order to mor
sfer rate. The
odel was able t
ghts into the
conducted wor
2), at a U.S. Ai
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RANS turbule
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basic turbulenc
and validated u
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data for shock
re accurately pr
experimental d
to reliably add
significance o
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ir Force Resea
tor which has
ular cross secti
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ixing, and intehe RANS-base
ence model. In
odel with a mo
ce model, is im
using LES, DN
dary layer, shea
el was able to
boundary laye
redict heat tran
data also revea
dress these need
of modeling p
ed numerical c
arch Laboratory
s a circular cr
ioned combust
eractions in injed turbulence m
n this model hig
odified therma
mplemented10.
NS and experim
ar layer flow, a
predict the tur
er interaction s
nsfer rates. Co
aled the signif
ds and showed
parameters as
characterization
y. Their efforts
ross-section (i
tors. A circula
jectionmodel.
gh and
al wall
mental
as well
rbulent
studies
onstant
ficance
d to be
s well,
n of a
s were
i.e., is
ar flow
Page 10
path has it
corner effe
challenges
Milliga
effective i
predictions
remain con
of dual-mo
establish a
A calib
measured p
second had
ts own set of
ects; it is more
in regards to f
an et al. made
n tuning mod
s, and understa
nstant in the pr
ode combustio
baseline nume
brated turbulen
pressure for tw
d an equivalenc
Figu
benefits and c
efficient in he
fuel penetration
reference to p
els to specific
anding uncerta
resence of shea
on. Milligan e
erical approach
nt Schmidt num
wo different tes
ce ratio of 1.0.
ure 11. Wall
challenges. The
eat load distrib
n into the air st
previous studie
c combustion
inties11. Calibr
ar layers and sp
et al. utilized
h for examining
mber equal to 0
sting condition
These results
l pressure dist
e benefits are
bution; and redu
treamand flam
es which show
experiments fo
ration of the Sc
pecies gradient
a constant, ca
g the efforts in
0.7 predicted th
ns11. The first c
are shown in F
tribution, step
as follows: it
duces weight11.
me propagation
wed a calibrate
for the purpose
chmidt numbe
ts, which are pr
alibrated turbu
n RC2211-12.
he peak pressur
condition had a
Figures 11 and
pcombustor, t
eliminates ch
The circular f
.
d turbulent Sc
e of performin
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resent in the co
ulent Schmidt
re within 1% o
an equivalence
d 12.
total φ = 0.511.
hallenges induc
flow path does
chmidt number
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t because it do
omplexinterna
number in or
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e ratio of 0.5 a
.
ced by
s poses
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Figure 1
Americ
12. Wall pr
can Institute of
ressure distrib
f Aeronautics a
10
bution, stepco
and Astronauti
ombustor, tota
ics
al φ = 1.011.
Page 11
It was
shock posi
acceptable
yielded pre
for two dif
and diverg
Other
combustion
based flam
strut at the
turbulent c
network (A
Figures
data for th
configurati
the velocity
Figure 13.
also observed
ition and gradu
for the case i
edicted peak p
fferent tested e
ent combustor
work investig
n in a cavity-b
meholder config
e leading edge
combustion; thi
ANN) based fil
s 13 and 14 sh
e non-reacting
ion, respective
y measuremen
. Numerica
that the same
ual pressure ris
n which a dive
ressure values
equivalence rat
)11.
gating turbulen
ased flamehold
gurations. The
of the cavity.
is approach is
ltered chemical
how a comparis
g case using the
ely. FromFigu
nts obtained usi
lly predictedv
calibrated Sch
se inside the is
ergent combus
that agreed w
ios (0.5 and 1.
nce modeling i
der13. Non-reac
first configura
The LES use
referenced as
l rates modelin
son between th
e no-strut cavi
res 13 and 14
ing Hydroxyl T
velocity profil
hmidt number r
solator. In add
stor was tested
within 1% of th
0) and two dif
is that of Gho
cting and react
ation was a cav
d a linear eddy
LEM-LES. Gh
ng technique.
he numerically
ty configuratio
it is seen that
Tagging Veloci
les compared
resulted in acc
dition, the calib
d11. In conclusi
he experimenta
fferent combus
odke et al. wh
ting flows were
vity with no str
dy mixing (LEM
hodke et al. als
y predicted velo
on and the cav
the numerical
imetry (HTV)
to experiment
curate numeric
brated Schmid
ion, the turbul
al data and prov
stor configurati
ho investigated
e analyzed for
rut; the second
M) model as a
so implemente
ocity profiles a
vity with a stru
l data was in g
in non-reactin
tal data, no st
cal predictions
t number of 0
lent Schmidt n
ved to be acce
ions (step com
d LES of supe
two different c
d configuration
a subgrid closu
ed an artificial
and the experim
ut at the leading
good agreemen
g flow13.
rut configurat
of the
.7 was
number
eptable
mbustor
ersonic
cavity-
n had a
ure for
neural
mental
g edge
nt with
tion13.

Fromt
region whi
developed
aiding in fl
Figure 1
this case study
ich can potent
behind the str
lameholding13.
4. Numeric
Americ
y results reveal
tially stabilize
rut, causing inc
cally predicted
can Institute of
led multiple sh
the flame13. I
creased mass t
dvelocity prof
f Aeronautics a
11
hear layers in t
In addition to
transfer betwee
files compared
and Astronauti
the wake of th
the wider mix
en the cavity a
dto experimen
ics
he strut, provid
xing region a
and the main f
ntal data, stru
ding a wider m
low pressure
flow streaman
ut configuratio
mixing
region
nd also
on13.
Page 12
Figure
15. there is
study, the
proved to b
Anothe
ANSYS-C
CFD-predi
was good
For the rea
combustor
allowing fo
prior to 20
Some of th
in the expe
future work
Furthe
Fig
15 shows reac
s good agreem
LEM-LES wa
be able to pred
er investigation
CFX was used i
icted wall pres
agreement betw
acting case the
walls14. The
for greater intak
011 has reveale
hese insights ar
eriment was no
k will investiga
er research con
gure 15. Nu
cting flow com
ment between th
as able to sim
dict the same fla
n of both non-r
in their efforts
ssure distributio
ween experim
e radical farmin
radical farmin
ke efficiency, l
ed further insig
re shown in Re
ot reproduced i
ate heat release
ncerning reacti
umerically pre
mputational pre
he numerical pr
mulate the sma
ame physics w
reacting and re
to evaluate th
ons were comp
ental data and
ng process occ
ng process allo
less total press
ght into the ra
eferences 15-1
in the simulati
e in simulation
ing and non-re
edictedbottom
edictions using
redictions and
all scale subgr
while being less
eacting flows in
he detailed sho
pared with exp
computationa
curred, though
ows for combu
sure loss, and o
dical farming
8. Xing et al. o
ons at the sam
ns.
eacting cases,
m wall pressur
g LEM-LES an
the experimen
rid processes a
s computationa
n a scramjet m
ock-induced-co
perimental data
al predictions f
not completel
ustion to occu
overall greater
process and it
observed that s
me location as i
with impleme
re comparedt
nd Turbulent-A
ntal data. In co
and the Turbu
ally expensive1
model was cond
ombustion proc
a. For the non
for the wall pr
ly, in the flow
ur with mild i
r scramjet perf
ts benefit for s
significant com
in the experim
entation of both
to experiment
ANN. As seen
onclusion to thi
ulent-ANN app
3.
ducted by Xing
cesses in scram
-reacting cases
essure distribu
field adjacent
ntake compres
formance14. Re
scramjet combu
mbustion heat r
ment. It was cite
h RANS and h
al data13.
in Fig
is case
proach
g et al.
mjets14.
s there
ution14.
to the
ssions,
esearch
ustion.
release
ed that
hybrid

LES/RAN
used by th
sonic cond
combustor
velocity an
predicted a
S techniques w
he Institute of
ditions through
. For the non
nd static press
axial velocity p
Americ
was conducted
Chemical Prop
h fifteen orific
n-reacting case
ure measurem
profiles and exp
can Institute of
by Potturi and
pulsion of the
ces located at
e RANS predi
ments than the
perimental data
f Aeronautics a
12
d Edwards19. Th
German Aero
the base of a
ctions showed
LES/RANS m
a.
and Astronauti
hey based their
ospace Center
a wedge which
d better agreem
model19. Figure
ics
r model on the
(DLR). Hydro
h was placed
ment with the
e 16 shows a c
e experimental
ogen was injec
in the center
e experimental
comparison be
set-up
cted at
of the
l axial
etween
Page 13
Pottur
species an
ri and Edward
nd 9-species. T
Figure 16.
s simulated th
The LES/RAN
Axial velocit
he reactive flo
NS methodolog
ty profiles for
ow using two
gy along with
non-reacting
different hydr
h the 7-specie
case19.
rogen oxidatio
es hydrogen ox
n mechanisms
xidation mech
s, a 7-
hanism

resulted in
temperatur
Figur
n the most acc
re19. Figure 17
re 17. Static
Americ
curate predicti
shows the stati
c temperature
can Institute of
ions for axial
ic temperature
profiles for re
f Aeronautics a
13
velocity, axia
predictions.
eactive case19.
and Astronauti
al velocity fluc
.
ics
ctuation measu urements, and d static
Page 14
Figure
The locatio
18 indicate
LES/RAN
LES/RAN
cooling the
predictions
models we
be pursued
18 shows the c
on of the lifted
es that near the
S 7-species c
S predictions.
e flame19. Furt
s that are in be
ere unable to pr
d in future work
contours for th
d flame is in th
e base of the we
case. The RAN
This implies t
ther fromthe f
etter agreement
redict the flam
k.
he time-average
he recirculation
edge the flame
NS peak temp
that the resolv
flameholder th
t with experim
me stabilization
ed temperature
n region, just b
e width is the g
perature predi
ved eddy struct
he LES/RANS
mental measurem
location and m
e. As seen, all t
beyond the trail
greatest for the
ictions are al
tures have an
7-species case
ments19. Pottur
mentioned in th
three cases pre
ling edge of th
RANS case an
so highest in
effect on the l
e yielded temp
ri and Edwards
heir work that t
dicted a lifted
he combustor. F
nd the smallest
comparison
locally strainin
perature and ve
s recognized th
this discrepanc
flame.
Figure
t in the
to the
ng and
elocity
hat the
cy will

Others
researchers
combustor
obtained a
between th
It was
ramp injec
using an e
s have also n
s being Fulton
using RANS
at the Universit
he predictions a
observed that
ctor exit plane
equivalence rat
Figure 18
Americ
noticed differe
n et al., who
and hybrid LE
ty of Virginia’
and the experim
at a higher eq
e and stabilized
tio of 0.17, in
8. Contour
can Institute of
ences in flam
investigated
ES/RANS20. C
’s Supersonic
mental data for
quivalence ratio
d near the com
which case th
s of time-aver
f Aeronautics a
14
e characteriza
hydrogen-air
Computational p
Combustion F
r the wall press
o of 0.34 the n
mbustor entran
he flame stabi
ragedtempera
and Astronauti
ation between
combustion in
predictions we
Facility. Genera
sure measurem
numerically sim
nce, contrastin
ilized just dow
ature19.
ics
different mo
n a modeled
ere compared t
ally good agre
ments20.
mulated flame
ng predictions
wnstreamof th
odels, one gro
dual-mode sc
to experimenta
eement was ob
lifted away fro
fromthe simu
he ramp injecto
oup of
cramjet
al data
btained
omthe
ulation
or exit
Page 15
plane20. Fromthis study and the one conducted by Potturi and Edwards it can be seen that flame stabilization shows
sensitivity to multiple variables.
To improve upon current capabilities to model combustion in supersonic flows Saghafian et al. conducted work
on developing an efficient flamelet-based combustion model for supersonic flows21. Combustion modeling for high-
speed flows was established on a flamelet/progress variable approach. In this methodology the temperature is
computed fromthe transported total energy and tabulated species mass fractions allowing for combustion to be
modeled by three additional scalar equations and a chemistry table that is computed froma pre-processing step21.
This approach enables the use of complexchemical mechanisms while eliminating costly iteration steps during
temperature calculation21. Also, the source termfor the progress variable is rescaled with pressure, thus accounting
for compressibility effects. This model was tested with LES and RANS for the simulation of a hydrogen jet in a
supersonic transverse flow. Comparisons were made with experimental data, LES yielded better agreement than
RANS21. The discrepancy between RANS predictions and experimental data was likely a result of deficiencies in the
mixing model implemented in RANS21.
Fromreviewing these articles it is seen that there exists multiple variables (e.g., turbulence-chemistry modeling,
equivalence ratio, modeling parameters such Prandtl number, etc.) that impact numerical predictions for the
characterization of supersonic combustion. Fromthe impact of these specific variables on supersonic combustion
stems the need not only for further investigation of the effects of these variables and the effects of their interactions
on supersonic combustion but also an optimization scheme for design purposes. It was also shown in this review that
some investigators have successfully implemented ANSYS Fluent, thus supporting its use in modeling supersonic
combustion. The following section is a portion of the validation work further supporting the use of ANSYS Fluent
12.1. It will begin by introducing the problemthat served as the basis for validating ANSYS Fluent 12.1 in scramjet
applications.
III. Validation
The problemthat was simulated was based off the work of Gruber et al.22 and Huang et al.23. Gruber et al.
conducted experimental and computational investigations for supersonic flow through scramjet combustors, each
with a geometrically different cavity. Their experimental work validated their computational work which used the
VULCAN Navier-Stokes code. In the published work fromGruber et al. only the cavity dimensions were given, not
the dimensions of the modeled scramjet engine which formed the bulk of the computational domain. Therefore the
work fromHuang et al. was used to establish the dimensions of the computational grid. Huang et al. modeled a
typical scramjet combustor with a cavity. The work fromHuang et al. was used because they referenced the
experimental work of Gruber et al. in order to validate their computational research. The following describes the
problemin more detail, beginning with boundary conditions.

15
The boundary conditions, shown in Table 1, were based on an operating pressure of 18,784 Pa. The operating
pressure was calculated using the equation for the pressure ratio frominlet to exit under isentropic conditions along
with the inlet conditions as specified by Gruber et al.22. Figure 19 shows the scramjet combustor geometry that was
used to construct the computational grid.
Table 1. Boundary Conditions.
Inlet Type Parameters Setting
Pressure-far-field Far-field gauge static pressure 671,216 Pa.
Far-field Mach number 322
Far-field static temperature 300 K
Outlet Type Parameters Setting
Pressure Gauge pressure at outflow boundary 0 Pa.
Total temperature 300 K22
Page 16
As men
appropriate
describe th
references
ratio is equ
Du/Dd). Th
Figure
normalized
the experim
Fluent 12.
Figur
ntioned, Huang
e to use their g
he cavity (e.g.
the ratio of th
ual to 5. The
he final digit in
21 shows the
d using the free
mental and co
1 follow the sa
re 19. Typic
Figu
g et al. used th
geometry of a
., LD5-01-90)
he length of the
‘01’ in LD5-0
this notation r
e normalized c
e streampressu
omputational w
ame trend as t
cal scramjet c
ure 20. Cav
he work of Gru
typical scramj
is based on t
e cavity to the
01-90 refers to
references the a
cavity wall pr
ure. Results are
work of Gruber
the experiment
ombustor geo
vity schematic
uber et al. to v
jet combustor
the schematic
e upstreamdep
the ratio of th
angle theta, as
ressure distribu
e shown for a v
r et al. As ind
tal results from
ometry23.
c for the scram
validate their s
for the compu
shown in Fig
pth (i.e., L/Du).
he upstreamde
shown in Fig.
ution for cavi
variety of turbu
dicated in Fig.
mGruber et al.
mjet combusto
simulation resu
utational grid. T
g. 20. In the c
. Therefore, L
epth to the dow
20.
ity LD5-01-90
ulence models
. 21 the predic
. There is a no
or23.
ults; therefore
The notation u
cavity notation
LD5 implies th
wnstreamdepth
0. The pressur
and are compa
ctions fromA
oticeable peak
it was
used to
n ‘LD’
hat this
h (i.e.,
re was
ared to
ANSYS
in the

predicted pnumericall
model accu
of the join
Fluent 12.
stress-ome
predictions
experimen
domain us
between A
second hal
pressure at thely caused peak
urately predicte
ning of the bot
1 to model the
ega model is ap
s fromANSY
tal values from
sed by Gruber
ANSYS Fluent
f of the bottom
Americ
location of thek. The Reynold
ed the peak pre
ttomand aft c
e pressure-stra
ppropriate for
YS Fluent 12.1
mGruber et al.
et al. were un
t predictions a
mwall and alon
can Institute of
e cavity fore wads stress mode
essure, as obta
avity walls. Th
ain termin the
flows over cu
over predicte
This is likely
nknown. For s
and the experi
ng a portion of
f Aeronautics a
16
all for the stanel (RSM) whic
ained by the com
he low-Reyno
exact transpo
urved surfaces
ed the cavity w
due to the fac
some of the te
imental and co
the aft wall.
and Astronauti
ndard k-w and Sch implemente
mputational w
lds stress-ome
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and swirling f
wall pressure
ct that the exac
ested turbulenc
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SST k-w simuled the low-Re
work of Gruber
ega model is a
r the Reynolds
flows24. Major
distribution in
ct dimensions o
ce models ther
results of Gru
lation, this is liynolds stress-o
et al., at the lo
an option in A
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rity of the num
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uber et al. alon
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ANSYS
ow-Re
merical
to the
ational
eement
ng the
Page 17

The ex
scramjet co
for cavity
simulation
were plotte
fromimple
F
Figure
xperimental w
ombustor: shad
LD5-01-90. T
conducted wi
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Figure 21. C
e 22. Shadow
Americ
work by Grube
dowgraph and
The shadowgra
ith ANSYS Fl
ours showed th
RSM low-Reyn
Cavity wall no
wgraph (left)
can Institute of
er et al. includ
schlieren flow
aph image is o
luent the conto
he shockwaves
nolds stress om
ormalizedpres
andschlieren
f Aeronautics a
17
ded two metho
w visualization
on the left and
ours of the sta
s that initiated
mega model for
ssure distribu
(right) photo
and Astronauti
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n diagnostics. T
d the schlieren
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the LD5-01-90
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These images a
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ity LD5-01-90
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Fig. 22
r each
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ur plot
22.
Page 18
Figure 23. Static p pressure distr ibution in com mbustor LD5- -01-90 using t the RSMlow- -Re stress om ega

Figure
al. in their
fromANS
and the pe
correspond
angles as o
model in th
use of the
fromANSY
between th
percentage
schlieren v
in ANSYS
schielren i
ANSYS Fl
image it is
cavity wal
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model.
23 shows a sim
experimental w
YS Fluent 12.
ercent differenc
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obtained from
heir work. Sho
model resulte
YS Fluent 12.1
he ANSYS Flu
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visualization di
S Fluent and t
mage it is 0.8
luent and the c
s 0.4%. The c
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cramjets.
Americ
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1 show two sh
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ockwave angle
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uent prediction
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the correspond
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comparison be
tribution show
can Institute of
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hockwaves em
e shockwave a
the experimen
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n and the resul
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approximate p
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ximate percent
shock wave an
tween the sho
support for th
f Aeronautics a
18
anating fromt
t al. show three
manating fromt
angles fromthe
ntal work of G
shown becaus
fromthe RSM
with the smalle
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lt fromthe sha
etween the AN
percent differe
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ngle in the shad
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he use of ANS
and Astronauti
the cavity as th
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the cavity. Tab
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Gruber et al. fo
se Gruber et al
M low-Re stress
est error betwe
percentage in
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the shadowgra
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s, the images
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uent simulation
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n comparison
ve angle obser
rison to the sch
wave pattern, an
n of simulating
uber et
Results
angles
and the
kwave
ulence
ecause
values
fferent
second
omthe
served
to the
rved in
hielren
and the
g flow
Page 19
IV. Conclusion
This review concludes with summary tables, Tables 3, 4, and 5, which highlight the CFD software and
codes that have been implemented in the research of scramjet combustion. In addition the tables show the modeling
approach, grid size and the source of experimental data for the validation of the computational work. Multiple
commercial codes and in-house codes have been utilized as well as numerous sources of experimental data for
validation of CFD codes.
A variety of parametric studies and fundamental studies have been reviewed, showing the advancement in
understanding high-speed combustion. Further studies are needed in order to progress closer to the long-termgoals
pertaining to high-speed combustion in scramjets.
Table 2. Comparison of shockwave angles for combustor LD5-01-90.
Number of shockwaves
initiating from cavity
Shockwave 1
Angle
Shockwave 2
Angle
Shockwave 3
Angle
Shadowgraph 3 21° 20° 21°
Schlieren image 3 25° 24° 23°
Standardk-w 2 n/a 25°
(25%, 0.42 %)
27°
(28.6%, 17.4%)
RSM
low-Re-stress-omega
2 n/a 22°
(10%, 0.83%)
22°
(0.48%, 0.43%)
Table 3. Summary of simulation techniques.
Researchers
Code/
Software
Modeling
approach
GridSize
Source of
experimental data
for validation

19
Ingenito and
Bruno3
Fluent 6.3TM
LES
Subgrid scale
model (SGS): ISCM
1,626,578 nodes
NASA Langley
Research Center
(SCHOLAR model)
Genin and
Menon4
n/a
LES
SGS model:
linear eddy mixing
(LEM) model
250x121x25 grid
Institute for Chemical
Propulsion of German
Aerospace Center
(DLR)
Berglund et al.5 n/a
Explicit partially stirred
finite-rate chemistry
LES model
Multiple grids tested
National Aerospace
Laboratory of Japan’s
supersonic combustor
and ONERA/LAERTE
vitiation air heater
Baurle and
Edwards7
VULCAN
RANS and
Hybrid RANS/LES
with SGS model
of Yoshizawa and
Horiuti
2D: 250,000 cells;
5 grid zones
3D: 43,285,632 cells;
1669 grid blocks
NASA Langley
Research Center
Page 20
Table 4. Continuation (1) of summary of simulation techniques.
Researchers
Code/
Software
Modeling
approach
GridSize
Source of
experimental data for
validation
Malo-Molina et al.8 HEAT3D
Steady and unsteady
RANS
First configuration:
4M points
Second
configuration:
2M points
n/a
Fulton et al.9
North
Carolina
State’s
REACTMB
flow solver
RANS and
Hybrid RANS/LES
with SGS model
of Lenormand et al.25
Nozzle grid 17.8M
Combustor grid
33M
University of Virginia
Scramjet Combustion
Facility
Ott and
Dash10
n/a
A proposed
unified k-e based
RANS turbulence
model
n/a
CRAFT Tech
Automated Validation
Environment (CRAVE)
data base and validation
tool
Milligan et al.11 n/a RANS n/a
Research cell 22
(Supersonic wind-
tunnel facility) at U.S.
Air Force Research
Laboratory
LES,
SGS model: LEM
model Research cell 19 at Air

20
Ghodke et al.13 n/a and artificial neural
network (ANN)
based
filtered chemical
rates modeling
10.2 million cells367 computational
blocks
Force Research
Laboratory, Propulsion
Directorate
Xing et al.14 ANSYS-CFX RANS Multiple grids tested
Test facility at
University of
Queensland
Potturi and
Edwards19
n/a
RANS and Hybrid
RANS/LES with
SGS model of
Lenormand et al.25
Combustor
33,141,428
interior mesh cells
and 2085 blocks
DLR
Fulton et al.20
North
Carolina
State’s
REACTMB
flow solver
RANS and Hybrid
RANS/LES with
SGS model of
Lenormand et al.25
Nozzle about 8M
cells
Combustor about
42M cells
University of Virginia
Scramjet Combustion
Facility
Saghafian et al.21 n/a
RANS and LES with
combustion model
based on a
Flamelet/Progress
Variable approach
n/a
Experimental work
fromGamba et al.26 and
Heltsley et al.27
Gruber et al.22 VULCAN RANS Mulitple grids tested
Supersonic flow facility
at AFRL, Propulsion
Directorate
Page 21
Table 5. Continuation (2) of summary of simulation techniques.
Researchers
Code/
Software
Modeling
approach
GridSize
Source of
experimental data
for validation
Huang et al.23 Fluent 6.3TM RANS
First Mesh: 36,400
cells
Second Mesh:
147,200 cells
Gruber et al.22
Schranner et al.28
ANSYS Fluent
ANSYS CFX
Navier Stokes
Multiblock solver
NSMB
RANS
Approximately 1.3
x106 elements
Standford
Expansion Tube
Facility
Brindle et al.29
General
Aerodynamic
Simulation
Program(GASP,
Aerosoft 1997);
CFD++
RANS n/a
Shock tube data
collected by United
Technologies
Research Centre
Emory et al.30
Joe (developed at
Stanford Center for
Turbulence
Research)
RANS with
Flamelet/Progress
Variable model
Mutiple
computational
domains all of
which have over a
million cells
High Enthalpy
Shock Tunnel
(HEG) of DLR
Jianwen et al.31
AHL3D code with
stretched laminar
flamelet model
RANS with
stretched laminar
flamelet model
25,000 cells DLR

21
ZhouQin et al.32
FlameMaster
Software used for
flamelet modeling
Hybrid RANS/LES n/a DLR
Oevermann33 n/a
k-ε turbulence
model with a
stretched laminar
flamelet model
n/a DLR
Page 22
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23
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