Turbulence and Combustion

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22 Φεβ 2014 (πριν από 3 χρόνια και 8 μήνες)

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Simulation and Modelling

of

Turbulence and Combustion

UNIVERSITY OF

CAMBRIDGE

DEPARTMENT OF

ENGINEERING

Computational Fluid Dynamics Laboratory

Stewart Cant

The CFD Lab combustion group
:


Carol Armitage, Gianluca Caretta, Nilan Chakraborty, Karen Hansen,

Karl Jenkins, Yun Kang, Michela Oliviero, Andrew Parker, Stephen Tullis, Pankaj
Vaishnavi, Saffron Wyse


plus

Daniele Baraldi, Paul Birkby, Kendal Bushe, Evatt Hawkes, Laurent Leboucher,

John Ranasinghe


and

Bill Dawes, Mark Savill; Caleb Dhanasekeran, Will Kellar, Noel Rycroft


Rob Prosser


Jackie Chen, Chris Rutland

People

Financial support for the work has been provided by:




EPSRC



Alstom Gas Turbines Ltd



Shell Global Solutions Ltd



Rolls
-
Royce plc


with high
-
performance computing and support from:




EPSRC; through EPCC, CSAR and HPCx



Cambridge
-
Cranfield High
-
Performance Computing Facility



Daresbury Laboratory (Dr. David Emerson)



CTR Stanford/NASA Ames, Sandia National Labs

Acknowledgements



RANS


Average the governing equations
-

model all scales


Modelling generally well developed


Inexpensive (relatively!)
-

remains standard for industrial problems




LES


Filter the governing equations
-

modelling required at the sub
-
grid scale


Combustion physics and chemistry tends to happen on sub
-
grid scales


Now becoming applicable to industrial problems




DNS


Solve the governing equations directly
-

no modelling of the physics


Resolution of all scales required
-

high accuracy numerical methods


Computationally very expensive


Feeds modelling data to LES and RANS

CFD
-
based Modelling Techniques


"
Structured gridding
:



-

2D Cartesian and axisymmetric


-

non
-
uniform


-

3
rd

order QUICK scheme in space


-

flux
-
limited to 2
nd

order using CCCT limiter


-

1
st

order Euler/2
nd

order Crank
-
Nicholson in time


-

turbulence modelling:
Reynolds stress or k
-
epsilon


-

combustion modelling using Bray
-
Moss
-
Libby type


laminar flamelets + partially premixed extensions




Code

TARTAN

RANS Approach
-
1

Reheat buzz combustion instability


CFD (Tartan) vs. experiment


Unstructured adaptive gridding:



-

tetrahedral cells


-

semi
-
automatic grid generation for arbitrary geometries


-

2nd order Jameson scheme in space


-

2nd order 4
-
step semi
-
implicit Runge
-
Kutta in time


-

local grid refinement on any specified quantity


-

standard turbulence modelling: k
-
epsilon


-

combustion modelling using BML
-
type laminar flamelets

"

-

parallel decomposition using standard tools




Code
McNEWT

RANS Approach
-

2

Flow with combustion past obstacles


Dynamic mesh adaption for uRANS and LES

Combustion in a vented channel


Static and dynamic mesh adaption

Oil industry case study
-

1


CAD import






via 3Dgeo

Oil industry case study
-

2


Surface mesh

Oil industry case study
-

3


Volume mesh

Oil industry case study
-

4

Flames developing from

two separate ignition sources

-

test case for HPCx


Gas turbine combustion instability


Full 3D mesh


ca. 500 000 cells


Geometrical length scales


from 0.7mm to 0.7m

Gas turbine combustion instability


Sector mesh


ca. 160 000 cells


Rising to ca. 700 000 cells


with solution adaption

Gas turbine combustion instability


Mixture fraction & pressure vs.time

Fuel injectors

time

pressure

The understanding…


CFD shows a self sustaining cycle

mixture entering combustor is richer

more heat release


pressure rises

mixture entering combustor is weaker

less heat release


pressure falls

less fuel enters


and is pushed away from combustor

more fuel enters


and is drawn into combustor

LES sub
-
grid reaction rate



Flame surface density (FSD or SDF) approach



Extension of flamelet formalism to LES sub
-
grid modelling


-

transport equation or algebraic closure



Further extension to partial premixing




Results are broadly in line with RANS experience


-

but terms depend on filter size




Applications to gas turbine combustion instability


LES modelling test case


close
-
up view

Cambridge Buzz Rig: flameholder

DNS in support of modelling




DNS involves
no

modelling


must resolve all scales



DNS remains too expensive for application to industrial systems



Run canonical cases and extract statistical data



Develop and calibrate modelling for LES




Flame propagation; FSD and transport terms




Flame kernel configuration


spherical



Inflow
-
outflow configuration


planar




Grid sizes 64
3
, 96
3
, 128
3
, 192
3
, 384
3
, (512
3
)



Requires access to world class supercomputing
-

HPCx



Flame Kernel Surface


grid size = 128
3

c = 0.5

Contours of reaction progress variable
with velocity vectors in x
-
z plane
superposed

Flame wrinkling and thickening due to turbulence


Reaction progress variable profile across the
flame brush along with the progress
variable profile of the initial laminar flame


Mean behaviour of displacement speed S
d

T
he variation of
ρS
d

0
S
L
, S
d
/S
L

and
(
S
r
+S
n
)
/S
L

across the flame brush


Variation of (1/
τ
|grad
c
|
S
L
) div
u

compared
with
ρS
d

0
S
L

plotted across the flame brush


Behaviour of the terms affecting displacement speed S
d

Reaction rate term, molecular diffusion
term, normal component of molecular
diffusion term, tangential diffusive term
and reactive
-
diffusive imbalance across
the flame brush


The variation of surface averaged SDF
across the flame brush is shown by the red
line. The scatter of SDF is shown by the
blue dots.


Budget of strain rate, curvature and propagation terms
in the transport equation for flame surface density

Budget of strain rate, curvature and propagation terms across the flame brush

Effect of tangential strain rate and curvature on

SDF strain rate term

Contours

of

joint

pdf

between

SDF

strain

rate

term

and

tangential

strain

rate

Contours

of

joint

pdf

between

SDF

strain

rate

term

and

mean

curvature

Statistics of flame normals and

flame normal interactions

Pdf of N
1

on different
c

isosurfaces


Pdf of N
2

on different
c

isosurfaces


Pdf of N
3

on different
c

isosurfaces

Mutual interactions between flame normal components

c
= 0.7

c
= 0.7

c
= 0.7

Scatter of N
1

and N
2
on
c
= 0.7 isosurface

Scatter of N
1

and N
3
on
c

= 0.7 isosurface

Scatter of N
2

and N
3
on
c

= 0.7 isosurface

Future Work in Combustion DNS



Implementation of unsteady non
-
reflecting inlet boundary condition for viscous


reacting flows



Simulation for higher turbulent Reynolds number and grid size




Effect of filter size of FSD transport equation terms




Comparative study of algebraic models for FSD and wrinkling factor




Extension of FSD based modelling in thin reaction zone regime




Modelling of surface averaged S
d

for LES combustion modelling

Test case for non
-
reflecting inlet and outlet
boundary conditions




RANS combustion modelling is highly developed


-

remains valuable for industrial applications


-

offers a high level of geometrical flexibility


-

requires desktop or PC cluster hardware




LES is the major CFD tool for the future


-

techniques are under active development


-

combustion requires high
-
level modelling


-

requires PC clusters to supercomputers




DNS is an invaluable tool for the support of modelling


-

requires top
-
end supercomputing



HPCx provides an excellent service for CFD

Conclusions