Hugh Stitt [1] & Peter Jackson [2]

1. What flow visualisation can teach us about reactor designWhat? Flow visualisation can teach us about reactor design? Hugh Stitt [1] & Peter Jackson [2] [1] [2]

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

3. Sensor readings reconstructred to give resistivity map 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)

4. 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)

5. Stirred Tank Tomography in 4D • 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)

6. Positron Emission Particle Tracking (PEPT) Computer Automated Radioactive Particle Tracking (CARPT ) Getting High Quality Information on Stirred Tanks • Needs a Lagrangian experimental approach • Velocimetry – or particle Tracking

7. Lagrangian Measurements on a Stirred Tank Velocity Trajectory • Loop circulation patterns are severely averaged • Actual fluid motion is far more random • Direction & velocity Fishwick, Winterbottom & Stitt

8. CARPT on 8" dia vessel PEPT on 4" vessel Rammohan, Kemoun & Dudukovic Lagrangian Measurements on a Stirred Tank Fishwick, Winterbottom & Stitt

9. Radioactive Velocimetry on a Rushton Turbine Agitated Baffled Vessel • Time-averaged velocity plots

10. 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

11. Both give recirculation loop centres at Upper loop : 0.575, 0.575 Lower loop : 0.225, 0.225 Stirred Tank Experimental vs SimulationVelocity Vectors Rammohan, Dudukovic & Ranade: IECRes 42, 2589 (2003)

12. Stirred Tank Experimental vs SimulationTurbulent Kinetic Energy • Model quality reduced for derived value Rammohan, Dudukovic, Ranade: IECRes. 42, 2589 (2003)

13. 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

14. Gas Sparging in a Stirred TankRadioactive 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

15. 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

16. Electrical Resistance Tomography Computer Tomography (g-ray) Tomography on a Bubble Column Time averaged – good spatial resolution Temporal resolution – but uncertain spatial precision Both have been done on columns  18" diameter Williams, Wang et al, Leeds Univ, UK APCI / CREL data

17. MRI – TBR Trickle-Pulse Flow Transition Trickle regime1.4 mm/s Transition regime 4.6 mm/s Pulsing regimeL = 13.3 mm/s Gas flow: 112.4 mm/sResolution: 0.7×1.4 mmAcquired at 50 f.p.s.All presented on the same intensity scale 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

18. 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 ?

19. “The bench scale results were so good that we by-passed the pilot plant”

20. 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

21. Feed Feed distributor Header Space Large dia.inert packing Smaller dia. catalyst Exit collector (porous wall) Exit flow Low Cost Radial Flow Packed BedProof 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?

22. Low Cost Radial Flow Packed BedFlow 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)

23. Low Cost Radial Flow Packed BedExperimental 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)

24. 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)

25. Velocity mapping from ER tomography CFD simulation of experiment Low Cost Radial Flow Packed BedQuantitative Validation • Qualitatively reproduces main features • Quantitation is less conclusive Bolton, Hooper, Mann & Stitt, Chem Eng Sci, 54, 1989 (2004)

26. 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 ?

27. 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

28. Reactors Behaving BadlyStirred Tank Reactors Liquid level below top impeller Impeller damage makes good mixing impossible

29. Reactor Behaving BadlyCatalytic Oxidation Reactor • Pelleted catalysts • Shallow bed (4") • Large dia (8´) • Reactor operating at reduced conversion • Observation (through spy glass) indicates “dark patches”

30. ———————————————————————————————————————————————————————————— • —————————————————————— • 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? “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?

31. Modality for “Field” Operation • Key requirements for field and research use are not the same

32. Modality for “Field” Operation • Currently - only g-ray systems meet all the requirements for field use

33. 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

34. “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!!!

35. Not too good • Not good at all Reactors Behaving BadlySteam Reformer

36. Reactors Behaving BadlySteam 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

37. Dignostics and Tomography at ScaleA Case Study • Pilot plant slurry bubble column reactor, • 18” diameter, heat exchange tube internals,

38. Base line scan - Densitometry Two successive sets of scans - Data are nearly identical showing good reproducibility

39. 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

40. Gas Outlet Detector 2 Slurry outlet • Use third detector at slurry outlet to measure gas carryover Detector 1 Gas Inlet Tracer Study - Application Example 1Slurry 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

41. Gas Outlet Slurry outlet • Use of more than one ring allows measurement of rise velocities Gas Inlet Tracer Study - Application Example 2Slurry 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

42. Install several rings of collimated detectors Use pulse injection of active particle tracers “Liquid” Catalyst Particle Tracer Studies on a SBCR - Pilot plant operated by Air Products - Tracking particles prepared by JM - Data measurement by JM-Tracerco - Data interpretation by CREL,

43. Particle Tracer Studies on a SBCR • Catalyst and “liquid follower” particles show almost identical behaviour • Assumption of pseudo-homogeneous slurry phase is valid

44. Particle Tracer Studies on a SBCR • Pulse injection of multiple particles and ring detectors used in lieu of single Lagrangian traceor 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

45. Reactor Behaving BadlyCatalytic Oxidation Reactor • 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 Hot (active) catalyst) Dark patches

46. 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

47. 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

48. Reactor Flow Distribution using Tracer • Typical test trace Inletdetectorresponse Ring detector responses – showing significant differences

49. High response at locations of persistent dark patches - Consistent with model Unexpected area of low flow Reactor Flow Distribution Using Tracer • Flow distribution by Segment • Repeat runs, and detectors at bottom of catalyst bed all gave similar results

50. 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