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