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 4 D at Medium Scale • 3 m 3 demonstration scale mixing tank with 8 planes of electrical sensors – Sensor readings reconstructred to give resistivity map R Mann et al. , Chem Eng Sci, 52, 2087 -2097 (1997)
Stirred Tank Tomography in 4 D • 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 4 D • Video frame and tomogram showing tracer distribution after 3 secs This is great – good picture!! – But gives little quantitative information on mixing UNLESS we have a model to compare it with R Mann et al. , Chem Eng Sci, 52, 2087 -2097 (1997)
Getting High Quality Information on Stirred Tanks • Needs a Lagrangian experimental approach – Velocimetry – or particle Tracking Computer Automated Radioactive Particle Tracking (CARPT ) Positron Emission Particle Tracking (PEPT)
Lagrangian Measurements on a Stirred Tank Trajectory Velocity • Loop circulation patterns are severely averaged • Actual fluid motion is far more random – Direction & velocity Fishwick, Winterbottom & Stitt
Lagrangian Measurements on a Stirred Tank • PEPT on 4" vessel Fishwick, Winterbottom & Stitt • CARPT on 8" dia 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 Great pictures!! – But they give little quantitative information on mixing UNLESS we have a model to compare it with the data Strength of these spatial velocity data – they can be compared directly to simulations
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 • Model quality reduced for derived value Rammohan, Dudukovic, Ranade: IECRes. 42, 2589 (2003)
Velocimetry in Multiphase Bubble Column Operation • 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
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 Temporal resolution – but uncertain spatial precision • Computer Tomography (g-ray) Time averaged – good spatial resolution Both have been done on columns 18" diameter Williams, Wang et al, Leeds Univ, UK APCI / CREL data
MRI – TBR Trickle-Pulse Flow Transition Trickle regime 1. 4 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 Pulsing regime L = 13. 3 mm/s Flow transition is a local phenomenon. Specific information on pulsing, its origin and the bed structures that promote it Lim, Sederman, Gladden, Stitt, Chem Eng Sci, in press
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 Feed – Low DP at a premium Header Space • Radial flow benefits Large dia. inert packing – High cost engineering retrofits available – But a very cost sensitive industry Smaller dia. catalyst • Can radial flow be induced by directed packing? Feed distributor 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 – 4 D 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 • Reconstructed conductivity maps at single horizontal plane for 8 different times ERT provides demonstration of overall axial / radial flow profile Bolton, Hooper, Mann & Stitt, Chem Eng Sci, 54, 1989 (2004)
Low Cost Radial Flow Packed Bed Quantitative Validation • Velocity mapping from ER tomography • CFD simulation of experiment • Qualitatively reproduces main features – Quantitation is less conclusive Bolton, Hooper, Mann & Stitt, Chem Eng Sci, 54, 1989 (2004)
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 ?
Tomography & Velocimetry in the Field Large Scale Particle Tracking : An old technology • 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
Reactors Behaving Badly Stirred Tank Reactors Impeller damage makes good mixing impossible Liquid level below top impeller
Reactor Behaving Badly Catalytic Oxidation Reactor • Pelleted catalysts – Shallow bed (4") – Large dia (8´) • Reactor operating at reduced conversion • Observation (through spy glass) indicates “dark patches”
“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
Modality for “Field” Operation • Currently - only g-ray systems meet all the requirements for field use
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 BUT : Cost vs. Information is exponential
“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 1 D, 1 m 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 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
Tracer Study - Application Example 1 Slurry Bubble Column • Open Tracer Studies Detector 2 Gas Outlet – For axial mixing and entrainment measurements • Inject gas tracer at gas inlet. – Responses from detectors 1 & 2 gives mean residence time, Slurry outlet • Axial mixing information – Use third detector at slurry outlet to measure gas carryover Detector 1 Gas Inlet
Tracer Study - Application Example 2 Slurry Bubble Column • Open tracer studies with ring Gas Outlet detectors – Investigate phase distribution and mixing – Tracers • Catalyst particles – doped with Mn 562 O 3 • “Liquid follower” : – Slurry outlet powdered Mn 562 O 3 • Open gas tracer : Ar 41 – Use of more than one ring allows measurement of rise velocities Gas Inlet
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
Reactor Behaving Badly Catalytic Oxidation Reactor • Pelleted catalysts – Shallow bed (4“) – Large dia (8´) • Reactor operating at reduced conversion • Observation through (spy glass) indicates “dark patches” • Modelling Hot (active) catalyst) Dark patches – Local extinction of catalyst and stable “cold channels” with steep thermal gradients • With very high mass flow
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) …. . Hot (active) catalyst) – Would expect massive mal-distribution of gas flow • Significantly higher flow though cold zones Dark patches
Evaluation of Flow (mal)Distribution Through a Packed Bed Reactor • Flow distribution study using – Open 85 Kr 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 : 137 Cs : 662 ke. V – Use of Phantoms • Steel bar, tube and plate, Hollow polystyrene block – Ab initio reconstructions • From calculated line densities Darwood et al. , WCIPT 3, Sept 2003
Densitometry : Results for Dual Phantoms Steel Pipe Steel Plate 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
Fan-beam Tomograms of Phantoms Drilled polystyrene block 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 • 6. 2 m dia. packed column – 32 source locations – 6 scans per position Use multiple source positions “Fan beam” arrangement of sensors
Tomography of Commercial Units 6. 2 m dia fractionation column 1 m dia FCC Riser • 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
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
Скачать презентацию What flow visualisation can teach us about reactor
929498163f9cba14e21774a8bb6f1ed5.ppt