Optimizing Mixing Requirements for Moving-Bed Biofilm Processes
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Optimizing Mixing Requirements
Discussion Outline
Process Description
Justification/Need for Study
Objectives
Experimental Approach (Pilot-scale)
CFD Model Creation and Verification of pilot-scale results
Example of Model Application (Full-scale)
09/09/2011 > DEGREMONT TECHNOLOGIES - INFILCO DEGREMONT INC. 2
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Optimizing Mixing Requirements
Process Description
09/09/2011 > DEGREMONT TECHNOLOGIES - INFILCO DEGREMONT INC. 3
Moving-Bed Biofilm Processes
IFAS (Integrated Fixed-film Activated Sludge) or
MBBR (Moving-Bed Biofilm Reactor)
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Optimizing Mixing Requirements
Justification/Need for Study
4
Ideal Aeration Grid Design
Create upwelling and downwelling zones for good mixing of media
Minimize energy demand without sacrificing oxygenation or mixing
Problem
Aeration grids do not create ideal mixing• Media floats on surface: “rafting”
• Media bunches in corners and deadzones
Interaction between grid configuration and mixing is complex• Difficult to improve upon grid design due to complex physics involved in mixing
Need
Develop a CFD model that can:• Simulate a three phase system (solid, liquid, and air) over a large computational domain
• Represent the macroscale mixing tendencies IFAS/MBBR systems at various configs.
Goal
Improve understanding of mixing
Guide the selection and arrangement of aeration grids
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Optimizing Mixing Requirements
Study Objectives
09/09/2011 > DEGREMONT TECHNOLOGIES - INFILCO DEGREMONT INC. 5
1. Create a model capable of simulating the movement of media
2. Verify the simulated results with empirical observations from a pilot-scale system
3. Apply model to full-scale application
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Optimizing Mixing Requirements
Experimental Studies
Test Tank
Volume = 22,500 gal
L x W x D = 25’ x 8’ x 16’
Storage TankTest Tank
6” Pump
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Optimizing Mixing Requirements
Experimental Studies
Aeration Grid
Made of 9” Fine Bubble Diffusers
Magnum Tube Mini Panel
Max Air 9” Disc
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Optimizing Mixing Requirements
Section Number
Experimental Studies
Aeration Grid
Made of 9” Fine Bubble Diffusers
Grid segregated into 9 sections
25’
23’15.5”
8’
6’
9”
13”
1 2 3 4 5 6 7 8 9
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Optimizing Mixing Requirements
Experimental Studies
Aeration Grid
Made of 9” Fine Bubble Diffusers
Grid segregated into 9 sections
Sections were manually turned on/off
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Optimizing Mixing Requirements
CFD Model Development
Models Applied
Eulerian Multiphase model
• Water: Continuous phase
• Air bubble: Secondary Phase
• Solid Phase: Secondary Phase (Granular Model)
Discrete Phase Model (DPM)
Model Closures
Standard k-ε turbulence model was used
Phase Interactions are handled through the “drag” term
Air Assumptions
Size is conserved throughout simulation
Bubble diameter = 2 mm
Airflow for mixing determined using empirical correlation: Course Bubble – MaxAir: Q (SCFM/KCF) = 0.2771 *X + 9.6386
Fine Bubble - 9" Disc: Q (SCFM/KCF) = 0.0782*X + 8.917
Fine Bubble - Magnum Tube: Q (SCFM/KCF) = 0.047* X + 9.6121
Fine Bubble - Mini Panel: Q (SCFM/KCF) = 0.0947*X + 7.0615
Where X = Media Fill Fraction and Q = Air flow (scfm/kcf)
Course Bubble – MaxAir: Q (SCFM/KCF) = 0.2771 *X + 9.6386
Fine Bubble - 9" Disc: Q (SCFM/KCF) = 0.0782*X + 8.917
Fine Bubble - Magnum Tube: Q (SCFM/KCF) = 0.047* X + 9.6121
Fine Bubble - Mini Panel: Q (SCFM/KCF) = 0.0947*X + 7.0615
Where X = Media Fill Fraction and Q = Air flow (scfm/kcf)
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Optimizing Mixing Requirements
Model Development
Media Assumptions
Size is conserved throughout simulation
Media density = 964 kg/m3
Media weight = 132 kg/m3
Media porosity (ε) ≈ 88% (1*ε+(1- ε)*964=132)
Porous media was modeled as a solid spherical particle:
• Real diameter = 22 mm; specific surface area= 450 m2/m3
• Preserving surface area, equiv. diameter = 1.44 mm
• Preserving drag forces, equiv. diameter = 13 mm
• Pellet diameter = 5 mm in simulation
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Optimizing Mixing Requirements
Model Development
Geometry and Meshing Assumptions
For pilot-scale study, tank was symmetrical
• Simulated ¼ of domain
For full-scale study, tank was not symmetrical
Hybrid mesh was used in both pilot- and full-scale simulations
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Optimizing Mixing Requirements
Model Results
Simulated Conditions
From experimental study, well mixed and poorly mixed conditions were correlated with different aeration grid configurations
large portion unmixed10001000113.3
large portion unmixed00100100116.7
Small portion unmixed01010101013.3
Small portion unmixed10101010113.3
Small portion unmixed11100011116.7
Small portion unmixed11000001113.3
Notice a lot of left to
right movement11111111111.7
mixed well and
Uniform roll01100011011.7
987654321
ObservatrionAir LateralsAir Flow
scfm/1000 cf
large portion unmixed10001000113.3
large portion unmixed00100100116.7
Small portion unmixed01010101013.3
Small portion unmixed10101010113.3
Small portion unmixed11100011116.7
Small portion unmixed11000001113.3
Notice a lot of left to
right movement11111111111.7
mixed well and
Uniform roll01100011011.7
987654321
ObservatrionAir LateralsAir Flow
scfm/1000 cf
Well Mixed
Poorly Mixed
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Optimizing Mixing Requirements
Model Results
1. Multiphase Model Results
2. DPM Results
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Optimizing Mixing Requirements
Multiphase Model Results
Water Velocity: Streamlines
Well Mixed case shows consistent velocities with four distinct rolling patterns
Well Mixed Poorly Mixed
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Optimizing Mixing Requirements
Multiphase Model Results
Water Velocity: Centerline Contour
Low velocity and high velocity zones are critical to create upwelling and downwelling zones
Well Mixed Poorly Mixed
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Optimizing Mixing Requirements
Multiphase Model Results
Air Volume Fraction
Air is better distributed in the Well-Mixed case
Well Mixed Poorly Mixed
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Optimizing Mixing Requirements
Multiphase Model Results
Media Volume Fraction
Well Mixed: f > 0.1 = 6% f > 0.08 = 16%
Poorly Mixed: f > 0.1 = 11% f > 0.08 = 22%
Well Mixed Poorly Mixed
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Optimizing Mixing Requirements
Multiphase Model Results
Media Volume Fraction
Well Mixed Poorly Mixed
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Optimizing Mixing Requirements
Model Results
1. Multiphase Model Results
2. DPM Results
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Optimizing Mixing Requirements
DPM Model ResultsCFD Simulation
Rationale/Justification for DPM approach from 2008 Pilot Study
Example of “good” mixing
21
Multiphase Model
Media Volume Fraction
Multiphase Model
Velocity Contours
DPM Simulation
Velocity Contours
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Optimizing Mixing Requirements
DPM Model ResultsCFD Simulation
Rationale/Justification for DPM approach from 2008 Pilot Study
Example of “poor” mixing
22
Multiphase Model
Media Volume Fraction
Multiphase Model
Velocity Contours
DPM Simulation
Velocity Contours
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Optimizing Mixing Requirements
DPM Model Results
DPM Justification
f_mediamultiphase 1/ν_watermultiphase ≈ 1/ν_waterdpm
Characteristics of Well Mixed case • well-defined zones of high and low velocity
• Velocity field oriented in the vertical direction
23
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Optimizing Mixing Requirements
Model Verification
Media Volume Fraction
Well Mixed case
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Optimizing Mixing Requirements
Model Verification
Media Volume Fraction
Poorly Mixed case
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Optimizing Mixing Requirements
Full-Scale Application
Optimize Air Grid to Minimize “Rafting”
Large Municipal Wastewater Treatment Plant• 35 MGD
• Impending nutrient regulations
Used DPM Model for Evaluating Grid Configurations • Need for rapid evaluation
• Evaluated 30+ configurations in <2 months
26
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Optimizing Mixing Requirements
Full-Scale Application
27
Possible Solutions
Adjust airflow to improve mixing
Rearrange grid
Add components to grid
Change diffuser-type
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Optimizing Mixing Requirements
Full-Scale Application
28
Water Velocity: Centerline Vector
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Optimizing Mixing Requirements
Full-Scale Application
29
Water Velocity: Centerline Vector
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Optimizing Mixing Requirements
Full-Scale Application
30
Water Velocity: Centerline Vector
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Optimizing Mixing Requirements
Full-Scale Application
31
Water Velocity: Centerline Vector
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Optimizing Mixing Requirements
Full-Scale Application
32
Water Velocity: Centerline Vector
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Optimizing Mixing Requirements
Full-Scale Application
Applied Solution
Using the CFD model simulations as guides, an optimal solution was found that minimized “rafting”
Solution did not add significant cost to project
Solution did not delay project
33
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Optimizing Mixing Requirements
Conclusions
09/09/2011 > DEGREMONT TECHNOLOGIES - INFILCO DEGREMONT INC. 34
1. CFD model mimicked mixing tendencies of pilot-scale tank
2. DPM simulations provided a time-saving computational method that correlated well with multiphase simulations
3. For full-scale application, multiple scenarios were investigated in a short period
4. Optimal solution applied for full-scale application
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Optimizing Mixing Requirements
Questions?
Acknowledgements
ANSYS: Jaydeep, Narayana, Genong
IDI: Mudit Gangal, Vishal Pandey, Amit Kaldate, Paul Lacey
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Optimizing Mixing RequirementsPellet Size Estimation
Pellet has buoyancy and drag forces on it.
Buoyancy force:
Drag force:
If we want to preserve the total surface area:
If we want to preserve the total drag force:
We will use d=5mm in our simulation!!
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