CFD for Wastewater Draft Final - · PDF file• 3D Fluent CFD • 1,100,000 hexahedral...
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Transcript of CFD for Wastewater Draft Final - · PDF file• 3D Fluent CFD • 1,100,000 hexahedral...
CFD for WastewaterPresentation to the Department of Civil
and Environmental EngineeringUniversity of California, Los Angeles
19 November 2015
Randal W. Samstag, MS, PE, BCEE
Civil and Sanitary Engineer
Bainbridge Island, WA US
CFD for Wastewater
• What is it?
• How is it done?
• What is it good for?
• Who is doing it?
“If we know what is happening within the vessel,then we are able to predict the behavior of thevessel as a reactor. Though fine in principle, theattendant complexities make it impractical to usethis approach.” – Octave Levenspiel (1972)
Computational fluid dynamics (CFD) changesthis picture. Using CFD, we can compute three-dimensional velocity fields and followinteractions of reactants and products througha tank. We can use this information to optimizetank geometry.
Types of Models
Black Box Models Grey Box Models
Glass Box Models
Black Box Models
Principle:
• Output = f (Input, Volume)
Examples:
• RTD Theory
• Box and Jenkins ARIMA
These can give approximate results because outputs usually are related toinputs and volume, but can’t tell us anything about the influence of theshape of the reactor on the outputs.
Grey Box Models
Principle:
• Use knowledge about thereactor plus inputs andvolume to predict outputs.
Examples:
• Tanks in Series Models
• Axial Dispersion Models
Grey box models use macroscopic analogs of diffusion over the tank topredict outputs. The IWA ASM models are often used in this type ofmodel.
Glass Box Models
Principle:
• Use three dimensionalvelocity field model as basefor prediction of outputs.
Examples:
• CFD Models
Glass box models predict the impact of geometry on process outputsbased on the three-dimensional velocity field. This realizes Levenspiel’s“impractical” goal.
CFD: What is it?CFD Solves the Reynolds Averaged Navier-Stokes
(RANS) Equations by Numerical Schemes
• Continuity Equation: Law ofMass Conservation
• Momentum Equations:Newton’s Second Law(Incompressible Flow )
0
i
i
x
u
t
ii
t
ij
ij
i Fx
u
x
p
x
uu
t
u
j
2
21
Breakdown of the MomentumEquation
ii
t
ij
ij
i Fx
u
x
p
x
uu
t
u
j
2
21
Unsteady Term
Advective TermPressure Term
Diffusion TermSource Term
The Momentum Equations are a SpecialCase of the Generalized Transport Equation
Sxx
uxt jj
j
j
)()()(
Advection Diffusion
Unsteady
Source
Discretization Techniques
• Finite difference
• Method of weighted residuals (finite element)
• Finite volume formulation
• Grid-less methods
All of these have been used in CFD for wastewater. Finitedifference was the first technique used. Finite element has beenused for clarifier modeling. Finite volume formulation is themost common commercial CFD software approach. Grid-lessmethods have not been much used, but may be promising.
How to eliminate pressure?
• Transform the governing equations:
– Vorticity / stream function method
• Use iteration and convergence
– SIMPLE
Both of these methods have been used in CFD for wastewater.
Turbulence Modeling• Simplest model: Prandtl’s Mixing Length
Hypothesis (Plane mixing layer, width δ)
• Two Equation Models: k – epsilon
y
ulmt
2
kMbk
jk
t
j
i
i
SYPPX
k
XkU
Xk
t
)()(
S
kCPCP
kC
XXU
Xtbk
jk
t
j
i
i
2
231 )()()(
2kCt
Rodi, W. (1980) Turbulence models and their application in hydraulics: A state-of-the art review.
07.0
ml
3D transport models can be coupled to the velocitycalculations to simulate sedimentation and mixing.
• Solids Transport
• Vesilind settling
• Density couple
kCos eVV
s
ww c
1
k
s
is
t
ii
i
x
CV
x
C
xx
Cu
t
C
Samstag, et al. (1992) Prospects for Transport Modelling for Process Tanks,WST, Vol. 26. No. 5-6. pp. 1401-1410.
3D transport models can be implemented forwastewater quality parameters as well.
Biokinetic Models
– ASM Models
– Advanced oxidationModels
– Disinfection models
Sobremisana, Ducoste, de los Reyes III (2011)
Multi-phase models can simulatemotion of water and air.
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iciiV
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Crowe, Sommerfield, and Tusji (1998) Multiphase Flows with Droplets and Particles.
How to Do CFD?Good Modelling Practice
Wicklein et al. (in press)
Good Modelling PracticeInitial Scoping
Wicklein et al. (in press)
Good Modelling PracticeBuild Geometry and Mesh
Wicklein et al. (in press)
Good Modelling PracticeSolve
Wicklein et al. (in press)
Good Modelling PracticePost Process
Wicklein et al. (in press)
How to do CFD?Software
• Hand Coded– Fortran– C++
• Commercial platforms (Examples)– ANSYS (Fluent and CFX)– Cd-adapco– Flow-3D– Comsol– PHOENICS
• Open source platforms– OpenFOAM
Hand Coded InterfaceTANKXZ
Fluent Interface
Standard OpenFOAM Interface
Visual CFD Interface for OpenFOAM
2015 OpenFOAM WorkshopSurfers Paradise
• Presentations by IWA WGmembers
• Teaching by NelsonMarques on OpenFOAM– Modeling– Meshing– Simulation– Post-Processing
• Example cases– Parshall Flume– Flow Splitter– Clarifier– UV Channel
OpenFOAM WorkshopCase Study: Splitter Box
OpenFOAM WorkshopCase Study: Activated Sludge Clarifier
What can be done with CFD?Wastewater Treatment Examples
Case Study: WWT Hydraulics
• Adverse Hydraulics
Vortices
Pre-rotation
Turbulence
Velocity Distribution
• Leading to
Decreased capacity
Poor flow distribution
Cavitation
Excessive wear
Provided by Jim Wicks, PhDThe Fluid Group
Case Study: WWT HydraulicsDrop Shafts
To transfer flood waterand sewage rapidlydown into a main sewerwithout blockage
Multiphase flow
Velocity dependent gritdeposition
Provided by Jim Wicks, PhD
Case Study: WWT HydraulicsFlow Splits
Equal transfer ofwastewater to multipledownstream units(ensuring solidscomponent accounted forcorrectly)
Velocity dependent gritdeposition
Multiphase flow
Provided by Jim Wicks, PhD
Case Study: BiokineticsEindhoven WWTP Facility
(The Netherlands)
From Rehman (2014)Provided by Ingmar Nopens, PhDGhent University
Configuration of the Bioreactor
Geometry
Diffuserssimplification
Vector Plots
• Bad mixing zones dueto recirculation
• Averaged out insystemic modeling
• Change in aeration leads to different flow patterns
Vertical cross section inthe aerated region
Dissolved oxygen and ammonia conc. (mg/L)
Oxygen concentration at 3.45m depth Ammonia concentration at 3.45mdepth
Case Study: Jet Mixing in a sequencingbatch reactor (SBR)
Case Study: MixingCFD of Jet mixing and aeration
415,350 mixed tetrahedralcells
2,108,308 nodes
Inlet flow into jet nozzles
Outlet flow to pump suction
Air added as second phase
Solids transport, settling, anddensity impact modeled byUDF
Samstag, Wicklein, et al. (2012)
Mesh projected onto modelsurfaces.
Case Study: MixingVelocity profiles for pumped mixing and aeration
Simulated Pumped Mixing Profile Simulated Aeration Profile
Case Study: MixingComparison of pumped mix velocity profiles for increasing jet velocities
Existing(2.5m/secJet)
3.0m/secJet
3.5m/sec Jet
4.0 m/secJet
Case Study: MixingComparison of solids profiles for increasing jet velocities
Existing(2.5m/secJet)
3.0m/secJet
3.5m/sec Jet
4.0 m/secJet
Case Study: MixingComparison of density-coupled and neutral density simulations
Density-coupled
Solids transport modelcalculates the local solidsconcentration based onflow regime.
The influence of the localsolids concentration on thelocal density is theniteratively calculated.
This approach was verified bythe field solids profile testdata.
Case Study: MixingComparison of density-coupled and neutral density simulations
Neutral Density
Solids transport model calculatesthe local solids concentrationbased on flow regime.
Influence of the local solidsconcentration on the localdensity was turned off.
This approach over-predictedmeasured solids mixing.
Case Study: Activated SludgeClarification
Case Study: Activated Sludge Clarifier
• Radial flow clarifier
• Questions:
– Optimum Depth?
– Optimum Inlet ?
– Optimum Feedwell?
– Optimum Effluent Zone?
Samstag and Wicklein(2010)
Radial Flow Clarifier CFD Model
• 3D Fluent CFD
• 1,100,000 hexahedralcells
• K-epsilon turbulencemodel
• User defined functions(UDF) to implement– Solids settling and
transport
– Density coupling
Case Study: Activated Sludge ClarifierCalibration CFD
Case Study: Activated Sludge ClarifierAlternative Inlet Configurations
Case Study: Activated Sludge ClarifierAlternative Velocity Vector Plans
Case Study: Activated Sludge ClarifierAlternative Velocity Plans
Case Study: Activated Sludge ClarifierAlternative Velocity Profiles
Case Study: Activated Sludge ClarifierComparison Solids Profiles
Case Studies: Disinfection
• Dye, disinfectant, andmicroorganismtransport in a chemicaldisinfection system
Provided by StevenSaunders, P.E.
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
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0 0.5 1 1.5
no
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zed
co
ncen
trati
on
t/TTDT
Residence Time Dstribution
T10
TTDT
T90
System Hydraulic Efficiency
The hydraulic efficiency of a contact tank systemis measured in CFD simulations with a tracer.Using a time dependent CFD model, tracer isintroduced at the point of disinfectant injection andits concentration is monitored at the model outlet.
Data gathered at the model outlet are used to plota residence time distribution (RTD) curve. Theslope and inflection points of the RTD curve areindicative of the hydraulic performance of thecontact system. Data points T10, TTDT and T90 areinputs used for accepted evaluation protocol.
T10: time at which tracer concentration hasreached 10% of the target value
TTDT: Theoretical Detention time ( Voltank/Qeffluent )
T90: time at which tracer concentration hasreached 90 % of the target value
BF: Baffle Factor – T10/TTDT Values near 1.0indicate good plug flow. Values lower than 0.3indicate some short circuiting is taking place.
MI: Morrill Index - T90/T10 Values greater than5.0 indicate some flow is getting hung up inrecirculation zones.
Streaklines colored by elapsed timenormalized against TTDT
Disinfectant Decay
The efficacy of the contact system is dependenton the time the active microorganisms in theeffluent are exposed to disinfectant at sufficientconcentration to neutralize them.
Disinfectants currently in use like sodiumhypochlorite or peracetic acid begin to decayimmediately upon introduction to the effluentstream. Their levels of concentration aremodeled by UDF based on published data.
Contours of disinfectant concentration normalized against targetconcentration level. Contour level 1.0 denotes the targetconcentration.
Log(N/N0) (bio. organisms)
Neutralization ofMicroorganisms
The rates at which microorganisms areneutralized are specific to the disinfectant in useand the target microorganism. For example,different coliforms will have differing sensitivitiesto the disinfectant in use. Their neutralization issimulated using UDF’s based on published data.
Contours of microorganism population. N is the localpopulation and N0 is the population in the effluent prior toexposure to the disinfectant.
Case Study: Dissolved Air FlotationDAF
Seawater DAF –desalination use
Prediction of absolutemaximum capacity(typically 10-20% aboveabove design max)
Comparison of nozzledesign and airintroduction
Provided by Jim Wicks,PhD
Case Study: DigestersDigesters
Non-Newtonian flow above3% DS
Rheology for all digestatesdifficult to measure.Typically we use of a libraryof values for various drysolids contents (and forvarious sludge types)
Useful for optimisingmethane gas production;reducing foaming; limitingsolids deposition andavoiding ‘dead’ volumes.
Provided by Jim Wicks,PhD
Case Study: DigestersDigesters
Structurally quite simpleand can compare differentmixers, baffles around theouter wall, distribution ofgas lances at the base etc
Dynamic modelling ispractical, with changes togas flow rate and locationover time to shift material
Velocity and (virtual)tracer measurementspractical (Volume withvelocity > 0.1 m/s used asa coarse measure inliterature)
Case Study: DigestersPitfalls
High levels of mixing donot equate linearly tomethane gas production
Density impact ofdigester solidsconcentration
Changes to dry solidscontent over time asdigestion processcontinues
Potential loss of activevolume around the basedue to solids deposition
Ongoing work
CFD plus “ADM1”
Who is Doing CFD?
• IWA CFD Working Group
“The WG intends to solve shortcomings arising fromlack of knowledge of CFD in the water andwastewater community in the short term byproducing papers and books as well as hands-ontraining for the IWA MIA members (and beyond).Furthermore, a book dedicated for training newpeople in the water/wastewater field will beproduced.”
IWA CFD Working GroupManagement Team
IWA CFD Working GroupWork Products
• Published Papers– Good Modelling Practice in Applying Computational Fluid Dynamics for WWTP Modelling, WEFTEC
2012– A protocol for the use of computational fluid dynamics as a supportive tool for wastewater treatment
plant modelling, WST– Computational Fluid Dynamics: an important modelling tool for the water sector, IWC Conference
• Submitted Papers– Good Modelling Practice in Applying Computational Fluid Dynamics for WWTP Modelling, WST– CFD for Wastewater: State of the Art, WST
• Workshops– WEFTEC 2012 (Fluent)– WWTMod 2012– Watermatex 2015 (OpenFOAM)– WWTMod 2016 (Proposed: Flow-3D)– IWA Biennium 2016 (Proposed)
• Book Plans– IWA Scientific and Technical Report– CFD for Water Book for Students and Practitioners
There is also a LinkedIn GroupCFD for Wastewater
The Momentum Equations are a SpecialCase of the Generalized Transport Equation
Sxx
uxt jj
j
j
)()()(
)()()()(
w
zv
yu
xu
xj
j
)()()()(zzyyxxxx jj
Advection
Diffusion
z,w
y,v
x,u
The RANS Equations in RectangularCartesian Coordinates
0)()()(
w
zv
yu
x
)(1
2
2
2
2
2
2
z
u
y
u
x
u
x
p
z
uw
y
uv
x
uu
t
ut
)(1
2
2
2
2
2
2
z
v
y
v
x
v
y
p
z
vw
y
vv
x
vu
t
vt
z
w
wt g
z
w
y
w
x
w
z
p
z
ww
y
wv
x
wu
t
w
)()(
12
2
2
2
2
2
z,w
x,u
y,v
McCorquodaleComposite Settling Model
Settling Zones
1) Non-settleables (C<CN)
2) Discrete (CN<C<CD)
3) Transition (CD<C<CH)
4) Hindered (CH<C<CC)
5) Compressive (C>CC)
Formula
1) Vs = 0.0
2) Vsd = � � �
3) Vs = ζ �� +(1-ζ)Vsd
=
4) Vs = Vo�
5) Vs = VC
Bürger-DiehlComposite Settling Model
Settling Zones
1) Clarification (X<XTC)
2) Compression (X>XTC)
Formula
1) Vs = Vo�
2) Vs = VT(1-Dcomp )
VT = Vo�
Dcomp = �
� � � �
= ( �
� � � �
)bcomp
McCorquodale Rheology Model
1) X < 1 g/L
2) X >1 g/L
1) νb=νoe1.386 X
2) νb=2.9νoe0.322X
McCorquodale Flocculation Model
Shear induced
/ = KB*X*Gm- KA*X*G
Differential settling
1/ = −9/4 � � 1 2/ρ1ρ2(1+2 1/ 2) 1/ 1( � 2− � 1)