Upload
danganh
View
222
Download
3
Embed Size (px)
Citation preview
What flow visualisation can
teach us about reactor design What? Flow visualisation can
teach us about reactor design?
Hugh Stitt [1] & Peter Jackson [2]
[1] [2]
Outline
• In research
– Laboratory experiments,
– Model development
• Scale up
– Role of flow visualisation
– Measurement density
• Flow visualisation in the field
– Reactors behaving badly
– Knowledge vs. information vs. data
– Implementation
Stirred Tank Tomography in 4D
at Medium Scale • 3 m3 demonstration scale mixing tank
with 8 planes of electrical sensors
R Mann et al., Chem Eng Sci, 52, 2087-2097 (1997)
– Sensor readings reconstructred
to give resistivity map
Stirred Tank Tomography in 4D
• Video frame and tomogram showing tracer
distribution after 3 secs
R Mann et al., Chem Eng Sci, 52, 2087-2097 (1997)
Stirred Tank Tomography in 4D
• Video frame and tomogram showing tracer
distribution after 3 secs
R Mann et al., Chem Eng Sci, 52, 2087-2097 (1997)
This is great – good picture!!
– But gives little quantitative
information on mixing
UNLESS
we have a model to
compare it with
Getting High Quality Information on
Stirred Tanks • Needs a Lagrangian experimental approach
– Velocimetry – or particle Tracking
Positron Emission Particle
Tracking (PEPT)
Computer Automated
Radioactive Particle
Tracking (CARPT )
Lagrangian Measurements on a Stirred Tank
• Loop circulation patterns
are severely averaged
• Actual fluid motion is far
more random
– Direction & velocity
Velocity Trajectory
Fishwick, Winterbottom & Stitt
Lagrangian Measurements on a Stirred Tank
Fishwick, Winterbottom & Stitt
• CARPT on 8" dia vessel • PEPT on 4" vessel
Rammohan, Kemoun & Dudukovic
Radioactive Velocimetry on a
Rushton Turbine Agitated Baffled Vessel
• Time-averaged velocity
plots
Radioactive Velocimetry on a
Rushton Turbine Agitated Baffled Vessel
• Time-averaged velocity
plots
Strength of these spatial velocity data
– they can be compared directly to simulations
Great pictures!!
– But they give little quantitative
information on mixing
UNLESS
we have a model to
compare it with the data
Stirred Tank Experimental vs Simulation
Velocity Vectors
• Both give recirculation loop centres at
– Upper loop : 0.575, 0.575
– Lower loop : 0.225, 0.225
Rammohan, Dudukovic & Ranade: IECRes 42, 2589 (2003)
Stirred Tank Experimental vs Simulation
Turbulent Kinetic Energy
Rammohan, Dudukovic, Ranade: IECRes. 42, 2589 (2003)
• Model quality reduced for derived value
• Optical techniques not appropriate
– Need penetrative methods; eg. g-rays
– Flow visualisation in highly dispersed multiphase operation
• Understanding of instantaneous effects
• Valuable data for comparison to time averaged models
CREL
Velocimetry in Multiphase
Bubble Column Operation
Gas Sparging in a Stirred Tank Radioactive Techniques allow interrogation
at high hold up of dispersed phases
• Effect of gas sparging on liquid velocities
– PEPT data
• Gas hold up patterns
in a sparged stirred
tank
– g-CT data
No gas
Gas sparged Fishwick, Winterbottom & Stitt Rammohan & Dudukovic
Tomography & Velocimetry in
Multiphase Flow Reactors
• Modelling of multiphase reactors is subject to many uncertainties
– Multiphase flow regime: bubbly, unstable
– Coalescence - redispersion
• Population balance: bubble class models
– Momentum transfer
– CFD “Closures”
• Require validation of models against detailed experimental data
Tomography on a Bubble Column
• Electrical Resistance
Tomography
• Computer Tomography
(g-ray)
Williams, Wang et al, Leeds Univ, UK APCI / CREL data
Temporal resolution – but
uncertain spatial precision
Time averaged – good
spatial resolution
Both have been done on columns 18" diameter
MRI – TBR Trickle-Pulse Flow Transition
Trickle regime 1.4 mm/s
Pulsing regime L = 13.3 mm/s
Transition regime
4.6 mm/s
Gas flow: 112.4 mm/s
Resolution: 0.7×1.4 mm
Acquired at 50 f.p.s.
All presented on the
same intensity scale
Lim, Sederman, Gladden, Stitt, Chem Eng Sci, in press
Flow transition
is a local
phenomenon.
Specific information on pulsing, its origin and
the bed structures that promote it
Flow Visualisation in the Laboratory
• Range of techniques available for use with
multiphase systems
– g-ray, X-ray, Electrical, MRI
• Varying cost, spatial and temporal resolution
• Important role in building models and
fundamental understanding
– Specific information on flow regimes
– Model discrimination and validation
• Next question
– How do we exploit these techniques in
scale up and design ?
“The bench scale results were so good
that we by-passed the pilot plant”
Design and Scale up
Role of Flow Visualisation
• Experimental tomography and velocimetry
have a clear role in reactor design and
development
– Quantitative information for model validation
– Qualitative role in understanding flow
behaviour and phase interactions
– Quantitative evaluation of changes in mixing /
hydrodynamics behaviour with changes in
scale
Low Cost Radial Flow Packed Bed
Proof of Concept
• High pressure processes • Ammonia synthesis
– Low DP at a premium
• Radial flow benefits
– High cost engineering retrofits available
– But a very cost sensitive industry
• Can radial flow be induced by directed packing?
Header Space
Feed Feed
distributor
Large dia.
inert packing
Smaller dia.
catalyst
Exit collector
(porous wall)
Exit flow
Low Cost Radial Flow Packed Bed
Flow Modelling
• Radial flow patterns
predicted using CFD
• Process gas
conditions and flow
– Based on assumptions
of global packed bed
permeabilities
• But are these
predictions correct
and realistic ?
– Use Electrical Resistance Tomography
Bolton, Hooper, Mann & Stitt:, Chem Eng Sci, 59, 1989-1997 (2004)
Low Cost Radial Flow Packed Bed
Experimental Validation with ERT • Electrical Resistance tomography
– 4D resolution
• Low spatial resolution
• Use 36" diameter vessel
– Packed aspect ratio 1:1
– Annular configuration,
• 2 particle diameters
• Central collector
– 8 planes of 32 electrodes
• Injection of concentrated brine tracer and monitor conductivity
– Reconstruct conductivity maps
Bolton, Hooper, Mann & Stitt, Chem Eng Sci, 54, 1989 (2004)
Radial Flow Packed Bed ERT Flow Pattern
ERT provides demonstration of
overall axial / radial flow profile Bolton, Hooper, Mann & Stitt, Chem Eng Sci, 54, 1989 (2004)
• Reconstructed conductivity maps at single
horizontal plane for 8 different times
Low Cost Radial Flow Packed Bed
Quantitative Validation • Velocity mapping from
ER tomography
• CFD simulation
of experiment
Bolton, Hooper, Mann & Stitt, Chem Eng Sci, 54, 1989 (2004)
• Qualitatively reproduces main features
– Quantitation is less conclusive
What? Flow visualisation can teach us
about larger scale operation? • Scale up
– Use measurement system and measurement
density appropriate to validation of design
concept and models
• Does not need same precision as lab scale.
• Objective different
– Justification of scale up protocol
– Testing of models at increased scale
– NOT fundamental understanding and
derivation of models per se
• But what about manufacturing scale ?
• Tracking of fluid movement
– within and between oil and gas
reservoir wells
• during drilling and production.
• Examination of transfer pipelines
to and from processing facilities
– for slugging effects, phase flow
rates, solids build-up or blockage,
pigging operation monitoring.
It’s only one dimensional and single
pass but ……….. it is an invaluable technique
Priority list : 1) Is there a blockage?
2) If yes, then where is it?
3) Then characterise the blockage
Tomography & Velocimetry in the Field Large Scale Particle Tracking : An old technology
Reactors Behaving Badly
Stirred Tank Reactors
Liquid level below
top impeller Impeller damage makes
good mixing impossible
• Pelleted catalysts
– Shallow bed (4")
– Large dia (8´)
• Reactor operating at
reduced conversion
• Observation (through
spy glass) indicates
“dark patches”
Reactor Behaving Badly
Catalytic Oxidation Reactor
“Field” Particle Tracking Technology?
• What are the objectives ?
– Detailed diagnosis of flow patterns with high
spatial resolution ?
• But how high a spatial resolution is required?
• Customer requirement
– Measuring the degree of mixing with sufficient resolution to establish:
• overall quality of mixing and
• any severe maloperation
• at minimum cost
– Do mixing and flow patterns adversely affect production and profits?
– —————————————————————
—————————
• ——————————————————————
Modality for “Field” Operation
• Key requirements for field and research
use are not the same
Research Priorities Field Priorities
Resolution Tomography Technique
Spatial Temporal
Transp- ortable
Sees through
Metal
g-ray Good None Yes Yes
e+ emission Good Moderate No Yes
X-ray Good Some Moderate Moderate
Electrical Moderate Excellent Yes No
Optical Good Good Yes No
MRI Good Good No No
Modality for “Field” Operation
• Currently - only g-ray systems meet all the
requirements for field use
Research Priorities Field Priorities
Resolution Tomography Technique
Spatial Temporal
Transp- ortable
Sees through
Metal
g-ray Good None Yes Yes
e+ emission Good Moderate No Yes
X-ray Good Some Moderate Moderate
Electrical Moderate Excellent Yes No
Optical Good Good Yes No
MRI Good Good No No
10
100
1000
80 90 100
Information Obtained (%)
Co
st
(Arb
itra
ry)
BUT :
Cost vs. Information
is exponential
The 80 : 20 Rule
• 80% of the information is only 20% of the cost
– And that 80% is normally sufficient to make an
educated decision or diagnosis
• Corollary : the remaining 20% of information
requires an additional 80% of the total effort
• Cost vs number of data points may be linear
“Field” Tomography Technology?
• What information are we trying to obtain ?
– And at what level ?
• High levels of information cost money & time
• Diagnosis of good, adequate or poor operation can often be done with little measurement and information
– Provided you know what information or data to measure ……. & how to interpret it
• Detailed measurement will only be done in the field where it is essential
– Where it adds value
• Hence - if an operator can get enough information to understand what he critically needs to know by a 1D, 1m measurement
– Then he won’t pay for more!!!
Reactors Behaving Badly
Steam Reformer
• Not too good
• Not good at all
Reactors Behaving Badly
Steam Reformer
• Tube wall temperature surveys can be used
routinely to identify zones of misbehaviour
– Use Gold Cup Pyrometry
• Zone of hot tubes
– Operator needs
to trim burners to
avoid premature
tube failure
• And the resulting
cost penalty
But here we’re lucky. We have observation
windows to look through
Dignostics and Tomography at Scale
A Case Study • Pilot plant slurry bubble column reactor,
– 18” diameter, heat exchange tube internals,
Base line scan - Densitometry
1.0E+03
1.0E+04
1.0E+05
1.0E+06
0 10 20 30 40 50 60
Pin Number
Co
un
ts
Two successive sets of scans - Data are nearly
identical showing good reproducibility
Field Measurements on a
Slurry Bubble Column Reactor
– 18” diameter, heat exchange tube internals
• High number of detectors / scans required to
achieve spatial resolution
– Very long time (thus high cost) to collect
statistically significant data set
• Internals effect “lines of sight”
• Very complex reconstruction
• Calibration during operation?
• Questionable value proposition
– Consider an alternative approach
Gas Inlet
Slurry
outlet
Gas Outlet Detector 2
Detector 1
Tracer Study - Application Example 1
Slurry Bubble Column
• Open Tracer Studies
– For axial mixing and entrainment measurements
• Inject gas tracer at gas inlet.
– Responses from detectors 1 & 2 gives mean residence time,
• Axial mixing information
– Use third detector at
slurry outlet to measure
gas carryover
Tracer Study - Application Example 2
Slurry Bubble Column
• Open tracer studies with ring detectors
– Investigate phase distribution and mixing
– Tracers
• Catalyst particles
– doped with Mn562O3
• “Liquid follower” :
– powdered Mn562O3
• Open gas tracer : Ar41
Gas Inlet
Slurry
outlet
Gas Outlet
– Use of more than one ring allows
measurement of rise velocities
Particle Tracer Studies on a SBCR
• Install several rings of
collimated detectors
• Use pulse injection of
active particle tracers
– “Liquid”
– Catalyst
- Pilot plant operated by Air Products
- Tracking particles prepared by JM
- Data measurement by JM-Tracerco
- Data interpretation by CREL,
Particle Tracer Studies on a SBCR • Catalyst and “liquid follower” particles show
almost identical behaviour
– Assumption of pseudo-homogeneous
slurry phase is valid
Particle Tracer Studies on a SBCR
• Pulse injection of multiple particles and ring
detectors used in lieu of single Lagrangian trace
or tomography
– Simpler to install, calibrate and use
• Ring detector responses compared to model
predictions
– In general - good comparability
– Demonstrates model validity
OR....If we have a model that predicts behaviour
then we can assess any deviation from that
ideal using simpler (tracing) techniques
• Pelleted catalysts
– Shallow bed (4“)
– Large dia (8´)
• Reactor operating at reduced conversion
• Observation through (spy glass) indicates “dark patches”
• Modelling
– Local extinction of catalyst and stable “cold channels” with steep thermal gradients
• With very high mass flow
Reactor Behaving Badly
Catalytic Oxidation Reactor
Hot (active) catalyst)
Dark
patches
Catalytic Oxidation Reactor
• CFD modelling of gas
distribution system
and head space
indicated no problem
• If modelling is correct
(catalyst extinction and
cold flow channels) …..
– Would expect massive
mal-distribution of gas flow
• Significantly higher flow
though cold zones
Hot (active) catalyst)
Dark
patches
Evaluation of Flow (mal)Distribution
Through a Packed Bed Reactor
• Flow distribution study using
– Open 85Kr tracer
– Ring of detectors just above catalyst bed
Detectors
were not
colliimated
Reactor Flow Distribution using Tracer
• Typical test trace
Inlet
detector
response
Ring detector responses
– showing significant
differences
Reactor Flow Distribution Using Tracer
• Flow distribution by Segment
High response
at locations of
persistent
dark patches
- Consistent
with model
Unexpected
area of low flow
• Repeat runs, and detectors at bottom of
catalyst bed all gave similar results
Flow Visualisation in the field
• High measurement density not appropriate
– Financial considerations
• Information rich data, with few
measurements feasible based on
– Selecting appropriate measurements
• Not necessarily the same as in the lab
– Open tracers, chordal scans, ………
– A priori knowledge of what results represent
poor / bad behaviour
– Availability of models to interpret data and
relate to lab-based understanding
• Validation of model scalability
But sometimes we need a “map”
Development of Tomography for Field Use
• A portable g-ray tomographic toolkit • For process diagnostic application on steel vessels
– Robust & portable. Accurate, repeatable & quick to analyse, Non-intrusive and non-invasive, Easy to install & remove. Economic
• Experimental & Methods
– Steel vessel, thin walled, 40 cm diameter
• Source : 137Cs : 662 keV
– Use of Phantoms
• Steel bar, tube and plate, Hollow polystyrene block
– Ab initio reconstructions
• From calculated line densities
Darwood et al., WCIPT3, Sept 2003
Densitometry : Results for Dual Phantoms
Experimental
20 x 8 grid
Theoretical
40 x 4 grid
• Ghost images on both experimental and
theoretical reconstructions
– Grid scanning not able to discriminate multiple
features at low numbers of scans
Steel
Pipe
Steel
Plate
Fan-beam Tomograms of Phantoms
Drilled polystyrene block 32 nodes x 6 scans
Pipe & plate dual phantom 32 nodes x 6 scans
• Tomograms show good representation
– Note absence of ghost images on
tomogram of dual phantom
g-ray Computed Tomography Scanning
Imaging of Process Vessels & Reactors
“Fan beam”
arrangement
of sensors
Use multiple
source
positions
• 6.2 m dia. packed column
– 32 source locations
– 6 scans per position
Tomography of Commercial Units
• Tomography can be done on commercial units with reduced number of scans
– Scale limited by g-ray attenuation
• Particle tracking also feasible but issues on tracer retrieval
6.2 m dia fractionation column 1m dia FCC Riser
What? Flow Visualisation Can Teach us
about Reactor Design and Operation ? • Research
– Building fundamental understanding
• Model building, discrimination and validation
• Requires high density of measurements
• Scale up and Design
– Objective to test the model at the larger scale
• Lower measurement density probably adequate
• Manufacturing scale
– Objective is diagnostic
• Good operation or not: is it a financial burden?
• Even lower (single point?)
measurement may suffice
What?
Flow visualisation can
teach us about reactor
design and operation