Optimizing Mixing Requirements for Moving- Bed Biofilm Processes

Transcription

1 Optimizing Mixing Requirements for Moving- Bed Biofilm Processes

2 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) 9/9/2 > DEGREMONT TECHNOLOGIES - INFILCO DEGREMONT INC. 2

3 Process Description Moving-Bed Biofilm Processes IFAS (Integrated Fixed-film Activated Sludge) or MBBR (Moving-Bed Biofilm Reactor) 9/9/2 > DEGREMONT TECHNOLOGIES - INFILCO DEGREMONT INC. 3

4 Ideal Aeration Grid Design Optimizing Mixing Requirements Justification/Need for Study 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 4

5 Study Objectives. 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 9/9/2 > DEGREMONT TECHNOLOGIES - INFILCO DEGREMONT INC. 5

6 Experimental Studies Test Tank Volume = 22,5 gal L x W x D = 25 x 8 x 6 Test Tank Storage Tank 6 Pump

7 Experimental Studies Aeration Grid Made of 9 Fine Bubble Diffusers Magnum Tube Mini Panel Max Air 9 Disc

8 6 8 Aeration Grid Optimizing Mixing Requirements Experimental Studies Made of 9 Fine Bubble Diffusers Grid segregated into 9 sections Section Number

9 Experimental Studies Aeration Grid Made of 9 Fine Bubble Diffusers Grid segregated into 9 sections Sections were manually turned on/off

10 Models Applied Optimizing Mixing Requirements CFD Model Development 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 Course Bubble MaxAir: Q (SCFM/KCF) =.277 *X Size is conserved throughout simulation Fine Bubble - 9" Disc: Q (SCFM/KCF) =.782*X Bubble diameter = 2 mm Course Bubble MaxAir: Q (SCFM/KCF) =.277 *X Airflow for mixing determined using empirical correlation: Fine Bubble - Magnum Tube: Q (SCFM/KCF) =.47* X Fine Bubble - 9" Disc: Q (SCFM/KCF) =.782*X Fine Bubble - Mini Panel: Q (SCFM/KCF) =.947*X Where X = Media Fill Fraction and Q = Air flow (scfm/kcf) ine Bubble - Magnum Tube: Q (SCFM/KCF) =.47* X

11 Model Development Media Assumptions Size is conserved throughout simulation Media density = 964 kg/m 3 Media weight = 32 kg/m 3 Media porosity (ε) 88% (*ε+(- ε)*964=32) Porous media was modeled as a solid spherical particle: Real diameter = 22 mm; specific surface area= 45 m 2 /m 3 Preserving surface area, equiv. diameter =.44 mm Preserving drag forces, equiv. diameter = 3 mm Pellet diameter = 5 mm in simulation

12 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

13 Model Results Simulated Conditions From experimental study, well mixed and poorly mixed conditions were correlated with different aeration grid configurations Well Mixed Air Flow scfm/ cf Air Laterals Observatrion mixed well and Uniform roll Notice a lot of left to right movement 3.3 Small portion unmixed 6.7 Small portion unmixed 3.3 Small portion unmixed 3.3 Small portion unmixed Poorly Mixed large portion unmixed large portion unmixed

14 Model Results. Multiphase Model Results 2. DPM Results

15 Multiphase Model Results Water Velocity: Streamlines Well Mixed case shows consistent velocities with four distinct rolling patterns Well Mixed Poorly Mixed

16 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

17 Multiphase Model Results Air Volume Fraction Air is better distributed in the Well-Mixed case Well Mixed Poorly Mixed

18 Multiphase Model Results Media Volume Fraction Well Mixed: f >. = 6% f >.8 = 6% Poorly Mixed: f >. = % f >.8 = 22% Well Mixed Poorly Mixed

19 Media Volume Fraction Optimizing Mixing Requirements Multiphase Model Results Well Mixed Poorly Mixed

20 Model Results. Multiphase Model Results 2. DPM Results

21 DPM Model Results CFD Simulation Rationale/Justification for DPM approach from 28 Pilot Study Example of good mixing Multiphase Model Velocity Contours Multiphase Model DPM Simulation Media Volume Fraction Velocity Contours 2

22 DPM Model Results CFD Simulation Rationale/Justification for DPM approach from 28 Pilot Study Example of poor mixing Multiphase Model Velocity Contours Multiphase Model DPM Simulation Media Volume Fraction Velocity Contours 22

23 DPM Model Results DPM Justification f_media multiphase /ν_water multiphase /ν_water dpm Characteristics of Well Mixed case well-defined zones of high and low velocity Velocity field oriented in the vertical direction 23

24 Model Verification Media Volume Fraction Well Mixed case

25 Model Verification Media Volume Fraction Poorly Mixed case

26 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 3+ configurations in <2 months 26

27 Full-Scale Application Possible Solutions Adjust airflow to improve mixing Rearrange grid Add components to grid Change diffuser-type 27

28 Full-Scale Application Water Velocity: Centerline Vector 28

29 Full-Scale Application Water Velocity: Centerline Vector 29

30 Full-Scale Application Water Velocity: Centerline Vector 3

31 Full-Scale Application Water Velocity: Centerline Vector 3

32 Full-Scale Application Water Velocity: Centerline Vector 32

33 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

34 Conclusions. 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 9/9/2 > DEGREMONT TECHNOLOGIES - INFILCO DEGREMONT INC. 34

35 Acknowledgements ANSYS: Jaydeep, Narayana, Genong IDI: Mudit Gangal, Vishal Pandey, Amit Kaldate, Paul Lacey Questions?

36 Pellet Size Estimation Pellet has buoyancy and drag forces on it. Buoyancy force: Drag force: ( ) g F F s total l single / 2 u 3 N 6 /( d ) s F Surface volume s single 2 AC This force is always d, 2 N 3/ 4 u C / d d ratio : 6 / d s s conserved! If we want to preserve the total surface area: 6 / d 5 d 6 / / 5.44mm s If we want to preserve the total drag force: F N F d single sphere 2 / 2 u AC total, sphere sphere 6 /( d s 3/ 4 u 3/ 8 C 3 d, ), N 2 sphere d C / d, d / C cylinder s s cylinder d 4 /( d d F s 2 l) total, cylinder cylinder.6d 2 / u cylinder 2 C / d d s 3mm Upper Lower limit limit We will use d=5mm in our simulation!!