Moving Beyond Prediction to Control

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Oct 24, 2013 (3 years and 11 months ago)

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Moving Beyond Prediction to Control

Free Surface, Turbulence, and Magnetohydrodynamics:

Interactions and effects on

flow control and interfacial transport

Mohamed Abdou

Professor, Mechanical & Aerospace Engineering, UCLA

Seminar on Science in Fusion’s Enabling R&D Program

Gaithersburg, MD, March 13, 2001



Acknowledgment:

This presentation was prepared in
collaboration with Profs. N. Morley and S. Smolentsev
and draws on the work of many scientists in the field.

TURBULENCE

FREE SURFACE
PHENOMENA

MHD

SCALAR
TRANSPORT

Liquid Wall Researchers are Advancing the
Understanding of Interacting Multi
-
Scale
Phenomena at the Frontiers of Fluid Dynamics

Fluid Out

+

-

B

r



J

r

V

r

J

r

Fluid In

Plasma

Plasma
-
Liquid
Interactions



TURBULENCE

FREE SURFACE
PHENOMENA

MHD

SCALAR
TRANSPORT

Fusion LW Researchers are Contributing to the Resolution

of

GRAND CHALLENGES in Fluid Dynamics


Turbulence redistributions

at free surface



Turbulence
-
MHD interactions



MHD effects on mean flow and
surface stability



Influence of turbulence and
surface waves on interfacial
transport and surface renewal

Teraflop Computer
Simulation


Liquid Walls:

many interacting
phenomena

Watermark
-

Shear layer instability at
water surface
-

CalTech Data


The term
free surface

is often used for any
gas/void to liquid interface, but denotes an
interface between a liquid and a second
medium that is unable to support an applied
pressure gradient or shear stress.


Formation of surface waves, a distinguishing
feature (for LW
-

Fr > 1, supercritical flow)


Interfacial flows are difficult to model
-
computational domain changes in time
making application of BCs difficult


Interfacial tension effects make equations
“stiff”
-

differing time scales for surface
wave celerity compared to liquid velocity


“Open Channel Flows
are essential to the
world as we know it”
-

Munson, Young,
Okiishi
(from their Textbook)


Free surface flow forms
:
films, droplets, jets, bubbles,
etc. Fluid regions can
coalesce, break up, and
exhibit non
-
linear behavior

CHALLENGE:
FREE SURFACE FLOW

Numerically tracking moving interfaces is
an ongoing challenge in CFD
-

Still NO IDEAL Interface Tracking Method


Volume
-
of
-
Fluid (VOF):

The method is based on the concept of advection of a
fluid volume fraction,

.I琠is瑨enpossible瑯lo瑥sr晡es,sellse瑥rminesr晡e
slopes and surface curvatures from the VOF data.







Level
-
Set Method:

The method involves advecting a continuous scalar variable. An
interface can thus be represented by a level set of the scalar variable. This is a different
approach from VOF where the discontinuity represents the interface.


OTHERS:

Lagrangian Grid Methods

Surface Height Method

Marker
-
and
-
Cell (MAC) Method

VOF

Watermark
-

milk drop splash simulation
using VOF
-

Kunugi, Kyoto Univ.

Horace

Lamb,

British

physicist
:

“I

am

an

old

man

now,

and

when

I

die

and

go

to

heaven

there

are

two

matters

on

which

I

hope

for

enlightenment
.

One

is

quantum

electrodynamics,

and

the

other

is

the

turbulent

motion

of

fluids
.

And

about

the

former

I

am

rather

optimistic
.





In Turbulent Motion the “various flow
quantities exhibit random spatial and
temporal variations” where “statistically
distinct average values can be discerned.”
-

Hinze



Turbulence is the rule, not the exception,
in most practical flows. Turbulence is not
an unfortunate phenomena. Enhancing
turbulence is often the goal.



Vastly different length and time scales
make equations stiff
-

requiring large
number of computational cycles. High
resolution required to capture all length
scales and geometrical complexities.

CHALLENGE:
TURBULENCE

Center for Computations Science and Engineering
(LBNL). LES simulation of instability in a

submerged plane jet.


Teraflop Computers

are Making TURBULENCE Accessible

Averaged Models:

Some or all
fluctuation scales
are modeled in an
average sense

LES

Super
-

DNS

length ratio:
l
/

Re

3/4

grid number: N

(3Re

)
9/4

For Re

=10
4

,
N

10
10

Teraflop computing

computers

RANS

Turbulence Structure Simulated

Turbulence / free surface interaction produces new
phenomena
-

anisotropic near
-
surface turbulence

Watermark
-

Vortex structure and free surface
deformation
(DNS calculation)


Turbulent production
dominated by the
generation of wall ejections,
formation of spanwise
“upsurging vortices”



Upsurging vortices reach
free surface, form surface
deformation patches, roll
back in form of spanwise
“downswinging vortices”,
with inflow into the bulk.



The ejection
-

inflow events
are associated with the
deformation of the free
surface and a redistribution
of near surface vorticity and
velocity fields
.

Conceptual illustration of experimental observation of burst
-
interface
interactions
-

From Rashidi, Physics of Fluids, No.9, November 1997
.

CHALLENGE:
MAGNETOHYDRODYNAMICS


Complex non
-
linear interactions between
fluid dynamics and electrodynamics



Powerful mechanism to “influence” fluids



Strong drag effects, thin active boundary
layers, large (possibly reversed) velocity
jets are characteristic MHD phenomena



Large currents with joule dissipation and
even self
-
sustaining dynamo effects add to
computational complexity

Free surface flow velocity jets produced from
MHD interaction
-

UCLA calculation

Computational Challenge Li flow in a chute
in a transverse field with: b=0.1 m (half
-
width); B
0
=12 T (field)

Ha = B
0
b


Each cross
-
section requires

MANY uniform grids, or special
non
-
uniform meshes.

MHD interactions can change the nature of
turbulence
-

providing a lever of CONTROL

From Dresden University of Technology


Experimental control of flow separation by a
magnetic field:



fully developed von Kármán vortex street without
a magnetic field (upper)


with a magnetic field (right)


Applied Lorentz forces act mainly in the
fluid regions near the walls where they can
prevent flow separation or reduce friction
drag by changing the flow structure.


Because heat and mass transfer rely
strongly on the flow structure, they can in
turn be controlled in such fashion.


Flow direction

Liquid Wall Science is important in many
scientific pursuits and applications


Liquid Jet and Film Stability and Dynamics:

fuel injection,
combustion processes, water jet cutting, ink jet printers, continuous
rod/sheet/ribbon/sphere casting, flood/jet soldering, ocean waves, hull design,
ocean/river hydraulic engineering, surfing, liquid walls for fusion reactors


Liquid MHD / free surface interactions:

melt/mold stirring
and heating, liquid jet/flow control and shaping, crystal growth, astrophysical
phenomena, liquid metal walls for particle accelerators and fusion reactors


Liquid MHD / turbulence interactions:
microstructure control
in casting, boundary layer control, astrophysical dynamos and plasmas, liquid
walls for particle accelerators and fusion reactors


Free surface heat and mass transfer:

oceanography,
meteorology, global climate change, wetted
-
wall absorbers/chemical reactor,
condensers, vertical tube evaporator, film cooling of turbine blades, impurity
control in casting, liquid walls for particle accelerators and fusion reactors



Watermark: Turbulent flow effect on dendrite formation in casting
-

LANL simulation

NSTX Li module


HYLIFE
-
II

Liquid Wall Science is being Advanced in Several

MFE & IFE Research Programs

IFMIF

KOH
Jacket

KOH

Twisted
-
Tape

3D Laser

Beams

Thin

Plastic

JUPITER
-
II

APEX CLiFF

MODELING FREE
-
SURFACE MHD TURBULENCE

(from limited DNS/experimental data to real applications)

EXPERIMENTS

underway at UCLA for near
surface turbulence and
interfacial transport
measurements


Statistical description of bulk and
free surface TURBULENCE


D N S

for free surface MHD flows
developed as a part of collab
-
oration between UCLA and
Japanese Profs Kunugi

and Satake

RANS
TURBULENCE
MODELS


K
-
epsilon


RST model


DNS and
Experimental data are
used at UCLA for
characterizing
turbulence phenomena
and developing
closures in RANS
models

Turbulent Prandtl
Number

Joule Dissipation


Strong

redistribution

of

turbulence

by

a

magnetic

field

is

seen
.




Frequency of vortex structures
decreases, but vortex size increases.



Stronger

suppresion

effect

occurs

in

a

spanwise

magnetic

field



Free

surface

approximated

as

a

free

slip

boundary
.

Work

proceeding

on

a

deformable

free

surface

solution
.








A BIG STEP FORWARD

-


(1st FREE SURFACE, MHD TURBULENT DNS)

“DNS of turbulent free surface flow with MHD at
Ret = 150”

-

Satake,

Kunugi,
and
Smolentsev,
Computational Fluid Dynamics Conf., Tokyo, 2000

Ha=20, Streamwise

Ha=0

Ha=10, Spanwise

PUTTING DATA TO WORK

RANS EQUATIONS:
“K
-

” model

1

2

Comparison of UCLA model

to experimental data

Experimental measurements of

Turbulent Prandl number

MHD DEPENDENT TURBULENCE CLOSURES

Magnetic field

direction

K

em







em

3

C

4

C

Streamwise

K

B

C

2

0

3











2

0

4

B

C

0.02

0.015

Wall
-
normal

K

B

C

2

0

3











2

0

4

B

C

}

0

.

1

exp{

9

.

1

N

-

}

0

.

2

exp{

9

.

1

N

-

Spanwise

K

B

C

2

0

3











2

0

4

B

C

}

0

.

1

exp{

9

.

1

N

-

}

0

.

2

exp{

9

.

1

N

-

K
-



呕R䉕䱅LC䔠佄䕌





Interfacial Transport Experiments in FLIHY

Visualization of sinking and
dispersing milk drop in water


2 cm


Large scale test section with
water/electrolyte flow will
generate LW relevant flow


Tracer dye and IR camera
techniques will be used to
measure interfacial transport
at free surface


PIV and LDA systems for
quantitative turbulence
comparison to DNS

FLIHY Experiment at UCLA
-

Test section length = 4 m

Dye Diagnostics for Interfacial
Mass Transport Measurements

Profile of dye penetration (
red dots
)

Local free surface (
blue dots
)

flow direction ~2 m/s

Water jet

hot droplets

Hot droplet penetrating jet

Dynamic Infrared
measurements of jet
surface temperature


Impact of hot droplets on cold
water jet (~8 m/s) thermally
imaged in SNL/UCLA test


NEW PHENOMENA IN LM
-
MHD FLOW

2D Turbulence












LM free surface images with motion from left to right
-


Riga Data

3D fluctuations on
free surface

N=0

Surface fluctuations
become nearly 2D
along field

N=6


Surface fluctuations
are nearly suppressed

N=10


B

SOME PROPERTIES OF

2
-
D MHD TURBULENCE:



Inverse energy cascade;


Large energy containing
vortices;


Low Joule and Viscous
dissipation;


Insignificant effect on the
hydraulic drag.


2
-
D turbulence could be
very useful as a mean of
intensifying heat transfer.

Isolated

walls
:

In

the

near
-
surface

jet

the

velocity

is

about

2

times

higher

than

the

mean

velocity

Conducting

walls
:

In the near
-
surface jet
the velocity is about
10
times
higher than the
mean velocity

Electromagnetic Control of Heat Transfer


Velocity profiles with favorable features could be formed by making
the side
-
walls slightly electrically conducting.


Simulations of Flowing Lithium in
NSTX

Upper
-

“Center Stack +Inboard Divertor”, 2.5
-
D model;

Lower


“Inboard Divertor”, Flow3D
-
M

MHD and Heat Transfer Conclusions:


Stable Li film flow can be established
over the Center Stack;


The

Center

Stack

projected

heat

load

can

be

removed

by

a

4

mm

film

ejected

at

2

m/s
.


State
-
of
-
the
-
Art Computational Techniques

are Required for Intensive LW Simulation

Lithium Jet start
-
up without and with grid adaption
-

HyperComp Simulation


Grid adaption or

multi
-
resolution


Parallel Algorithm
Implementation


Unstructured Meshes


High
-
order advection
and free surface
tracking algorithms

USING MHD FORCES TO CONTROL FLOW

Soaker Hose Concept



Leak liquid radially inward from supply
tubes


Stagnate inward flow and drive liquid
radially over short path with applied poloidal
current


Complex interaction with other field
components seen in simulations

UCLA Simulation

u

u

u


J
a

Poloidal


J
a



䈠††BR慤i慬


B Toroidal

Exploring Free Surface LM
-
MHD
in MTOR Experiment


Study toroidal field and gradient effects:

Free surface flows are very sensitive to drag from
toroidal field 1/R gradient, and surface
-
normal fields




3
-
component field effects on drag and
stability
:
Complex stability issues arise with field
gradients, 3
-
component magnetic fields, and applied
electric currents





Effect of applied electric currents
:
Magnetic
Propulsion and other active electromagnetic restraint
and pumping ideas





Geometric Effects
:
axisymmetry, expanding /
contacting flow areas, inverted flows, penetrations




NSTX Environment simulation:

module
testing and design

MTOR Magnetic Torus and LM Flowloop:

Designed in collaboration between UCLA, PPPL and ORNL

Timeof
-
flight

Liquid Jet Research for IFE Chambers

High
-
velocity, oscillating

jets for liquid “pocket”


flow trajectory and jet deformation


primary breakup / droplet formation


dissembly processes


liquid debris interaction / clearance


partial head recovery


High
-
velocity, low surface
-
ripple
jets for liquid “grid”


surface smoothness control


pointing accuracy / vibration


primary breakup / droplet ejection


Graphics from UCB


Single jet water experiments
and numerical simulations
demonstrate control of jet
trajectory and liquid pocket
formation at near prototypic
Re

Oscillating IFE jet

experiments

and simulations

Experimental Data
from UCB

Flow

Direction

Regions flattened by
interaction with
neighboring jet

Simulations from
UCLA

Flow

Direction

Understanding mechanisms of flow
instability leads to improved control of

jet surface smoothness for IFE


Upstream turbulence
and nozzle boundary
layer thickness
heavily influence
downstream jet
stability


Turbulence
conditioning and
boundary layer
trimming in nozzle
dramatically improves
jet quality


UC Berkeley data

Re = 100,000

L/D = 44

Re = 75,000

L/D = 44

w/ conditioning

w/o conditioning

Modeling of Stationary
Jet Deformation


Initially rectangular jets deform
due to
surface tension

and

corner

pressurization

in nozzle


Capillary waves from corner
regions fan across jet face
-

largest
source of surface roughness!

LIF measurement of surface topology at

Georgia Tech

Modeling
UCLA
Experiment


Numerical simulations and
quantitative surface topology
measurements are critical
tools for
understanding jet
deformation,

and
controlling jet behavior
with nozzle shaping

Watermark: Turbulent flow effect on dendrite formation in casting
-

Juric simulation

Liquid Wall Science is important in many
scientific pursuits and applications


Liquid Jet and Film Stability and Dynamics:

fuel injection,
combustion processes, water jet cutting, ink jet printers, continuous
rod/sheet/ribbon/sphere casting, flood/jet soldering, ocean waves, hull design,
ocean/river hydraulic engineering, surfing, liquid walls for fusion reactors


Liquid MHD / free surface interactions:

melt/mold stirring
and heating, liquid jet/flow control and shaping, crystal growth, astrophysical
phenomena, liquid metal walls for particle accelerators and fusion reactors


Liquid MHD / turbulence interactions:
microstructure control
in casting, boundary layer control, astrophysical dynamos and plasmas, liquid
walls for particle accelerators and fusion reactors


Free surface heat and mass transfer:

oceanography,
meteorology, global climate change, wetted
-
wall absorbers/chemical reactor,
condensers, vertical tube evaporator, film cooling of turbine blades, impurity
control in casting, liquid walls for particle accelerators and fusion reactors




Increasing Green House Gases:


Humidity,
CO
2
, Methane, NOx,


Sox etc.


Infra Red Absorption into


Green House Gases and


on the Earth surface

Preserving Heat in the Air

Temperature Rise

in the Air

Earth

I
.
R
.:
Infra

Red

I
.
R
.

Absorption

Sun

Air

I
.
R
.

Radiatio
n

Temperature Rise (K)

Year

What is Global Warming?

Free surface mass transport is
affecting CO
2

concentrations

Missing Sink Problem over past 30 years


Measured atmospheric CO2 increase (34 ppm)

-

Spent Fossile Fuel emissions (61 ppm)

=
Missing Sink(
-
27 ppm)



Turbulent Heat and Mass transfer across Free Surface ?


CO2 absorption at the turbulent
free
-
surface

deformed by the
shear wind, by means of direct
numerical solution procedure for
a coupled gas
-
liquid flow

Wind flow

Free surface contour
-

wind
-
driven calculation

?

Coherent

Structures

in

Wind
-
driven

Turbulent

Free

Surface

Flow



Water

Wind

Atmospheric Pressure Contour Surface (Green)

High Speed Gas Side Regions (Brown)

High Speed Water
-
Side Regions (Blue)

Streamwise Instantaneous Velocity (Color Section)

DNS

Some Common Aspects between Global Warming
and Fusion Science Thermofluid Research

Similar Phenomena


High Pr flow with radiation heating at free surface from plasma


High Sc flow with CO2 absorption at free surface of sea


Similar Flow Characteristics


Re is high, both have the similar turbulence characteristics.


MHD (fusion) and Coriollis (global warming) forces can influence
the average velocity


Heat and Mass Transfer Similarity


High Pr, very low thermal diffusivity
-
>very thin thermal boundary
layer
-
>large temperature gradient at interface


High Sc, very low molecular diffusivity
-
>very thin concentration
boundary layer
-
>large concentration gradient at interface

.

Simulation of commercial inkjet


by Rider, Kothe, et al.
-

LANL

Liquid Jet Stability and Breakup

Inkjet Printer quality is
hampered by formation
of “satellite” droplets

Data from Ho
-

UCLA

Micro
-
injector increases relative importance
of surface tension by decreasing size
-

eliminates satellite droplets and improves
precision

Vertical B field effects on

Liquid Metal Film Flows

Continuous sheet casting
can produce smooth free
surfaces and film thickness
control via MHD forces

Film thickness profiles for

various Hartmann Numbers

Simulation by Lofgren, et al.


Reflections on 19th & 20th Centuries


1850:

Navier
-
Stokes Equation


1873:

Maxwell’s Equations


1895:

Reynolds Averaging



1900
-
1960’s:


-
Averaging techniques, Semi
-
empirical approach. Heavy reliance on Prototype
Testing (e.g. wind tunnels for aerodynamics).


1960’s
-

1970’s:


-
Supercomputers allow direct solution of N
-
S for simple problems. Advances in
Computational Fluid Dynamics (CFD), e.g. utilization of LES technique.


1980’s
-

1990’s:

-
Rapid advances to Teraflop Computers

-
Rapid advances in CFD and in experimental techniques

-
Turbulence structure “simulated” and “observed” for key problems

-
Better understanding of fluid physics and advanced “Prediction” tools

-
Paradigm Shift:

-

From

“mostly experimental for empirical global parameters”
to

“larger share
for CFD: simulation first followed by smaller number of carefully planned
experiments aimed at understanding specific physics issues and verifying
simulation.”


21st Century Frontiers

Moving Beyond “Prediction” of Fluid Physics

To “Control” of Fluid Dynamics




With the rapid advances in teraflop computers, fluid dynamicists are increasingly able to
move beyond predicting the effects of fluid behavior to actually controlling them;
with
enormous benefits to mankind!

Examples



Reduction in the Drag of Aircraft

The surface of a wing would be moved slightly in response to fluctuations in the
turbulence of the fluid flowing over it. The wings surface would have millions of
embedded sensors and actuators that respond to fluctuations in the fluids, P, V as to
control eddies and turbulence drag. DNS shows scientific feasibility and MEMS can
fabricate integrated circuits with the necessary microsensors, control logic and actuators



Fusion Liquid Walls

Control of “free surface
-
turbulence
-
MHD” interactions to achieve fast interfacial
transport and “guided motion” in complex geometries (“smart
-
liquids”)



Nano Fluidics: Pathway to Bio
-
Technologies

Appropriately controlled fluid molecules moving through nano/micro passages can
efficiently manipulate the evolution of the embedded macro DNA molecules or affect the
physiology of cells through gene expression.