Clarifier Workshop Presentations - · PDF file9/18/2011 PNCWA Workshop Optimizing the...

9/18/2011

PNCWA Workshop Optimizing the Performance of Your Secondary Clarifier 1

Optimizing the Performance Optimizing the Performance and Capacity of Your and Capacity of Your Secondary ClarifierSecondary Clarifier

Ron Moeller, Kennedy Jenks (Moderator)Richard Finger, King County (retired)

Randal Samstag, P.E., Carollo EngineersEdward Wicklein, P.E., Carollo Engineers

Presented ByPNCWA Plant Operations and Maintenance Committee

Pre-Conference WorkshopSeptember 18, 2011

11

Workshop AgendaWorkshop AgendaTime Speaker Topic

1:00 pm – 1:10 pm Ron Moeller Introduction

1:10 pm – 1:20 pm Randal Samstag Clarifier Performance and Capacity Overview

1:20 pm – 1:45 pm Randal Samstag Introduction to Settleability Control

1:45 pm – 2: 15 pm Dick Finger Settleability Control – TheOperations Perspective

2:15 pm – 2:45 pm Randal / Dick Settleability Control – Case2:15 pm 2:45 pm Randal / Dick Settleability Control Case Studies

2:45 pm - 3:00 pm Break

3:00 pm – 3:15 pm Randal Samstag Introduction to Clarifier Models

3:15 pm – 3:30 pm Randal Samstag Clarifier Field Tests

3:30 pm – 4:00 pm Ed Wicklein Advanced Computational Models

4:00 pm – 4:20 pm Randal / Ed Hydraulic Control – Case Studies

4:20 pm – 4:55 pm Group Use of Capacity Tools

4:55 pm – 5:00 pm Ron Moeller Closure22

IntroductionIntroduction

Ron Moeller, Kennedy JenksRon Moeller, Kennedy Jenks

33

Performance and Capacity Performance and Capacity of Secondary Clarifiers of Secondary Clarifiers

OverviewOverview

By

Randal Samstag, P.E.Randal Samstag, P.E.

Carollo EngineersCarollo Engineers



44

Performance and Capacity of Performance and Capacity of Secondary ClarifierSecondary Clarifier

DefinitionsDefinitions

Performance IssuesPerformance Issues

Capacity IssuesCapacity Issues

Summary ofSummary of Summary of Summary of techniques for techniques for improvement of improvement of performance and performance and capacitycapacity

55

DefinitionsDefinitions

Secondary ClarifiersSecondary Clarifiers The gravity solids separator for the activated The gravity solids separator for the activated

sludge processsludge process

PerformancePerformance The ability of the secondary clarifier to meet its The ability of the secondary clarifier to meet its

effluent permit requirementseffluent permit requirements

CapacityCapacity The ability of a secondary clarifier to The ability of a secondary clarifier to

accommodate wastewater loading (while meeting accommodate wastewater loading (while meeting permit requirements!)permit requirements!)

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Clarifiers are crucial for Clarifiers are crucial for performanceperformance

Clarifiers Clarifiers Are required for solidsAre required for solids Are required for solids Are required for solids

separationseparation

Can be designed to Can be designed to improve flocculationimprove flocculation

77

Clarifiers control capacityClarifiers control capacity

Clarifiers are critical to activated sludge Clarifiers are critical to activated sludge capacitycapacity

Activated sludge process capacity Activated sludge process capacity depends on both the aeration basindepends on both the aeration basindepends on both the aeration basin depends on both the aeration basin volume and the clarifier areavolume and the clarifier area

88

Clarifier FunctionsClarifier Functions

Separate solids Separate solids (clarification function)(clarification function)

Thicken solids Thicken solids (thickening function)(thickening function)( g )( g )

Enhance flocculationEnhance flocculation

99

Activated Sludge Schematic Activated Sludge Schematic (Conventional)(Conventional)

QIN XIN

QMLSS

XMLSS

QOUT

XOUT

SINReactor Tank

Sedimentation Tank

(Clarifier)SOUT

QR XR QW XW

Aerobic

VAB VSC

1010

Activated Sludge Schematic Activated Sludge Schematic (Step Feed)(Step Feed)

QIN XIN

QMLSS

XMLSS

QOUT

XOUT

SIN

Reactor Tank Sedimentation Tank

(Clarifier)

SOUT

QR XR QW XW

Aerobic

VAB VSC

1111

Activated Sludge Schematic Activated Sludge Schematic (Selector)(Selector)

QIN XIN

QMLSS

XMLSS

QOUT

XOUT

SIN


(Clarifier)

SOUT

QR XR QW XW

AerobicSelector

VAB VSC

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Activated Sludge Schematic Activated Sludge Schematic (Contact Stabilization)(Contact Stabilization)

QIN XIN

QMLSS

XMLSS

QOUT

XOUT

SIN


(Clarifier)

SOUT

QR XR QW XW

ContactStabilization

VAB VSC

1313

Important Definitions For Secondary Important Definitions For Secondary Clarifier Performance and CapacityClarifier Performance and Capacity

)(

)/(000,000,1*)()/(

sfArea

mgalgalmgdEffluentsfgpdOFR

Overflow Rate (OFR)

Solids Loading Rate

)(

)///(34.8*)/(*)(Re)/(

sfArea

LmgmgallbLmgXmgdturnFeedsfppdSLR MLSS

g(SLR)

100*)(

)(Re(%)

mgdFeed

mgdturnRASr

Return Sludge Ratio (RASr)

Other Important Definitions For Secondary Other Important Definitions For Secondary Clarifier Performance and CapacityClarifier Performance and Capacity

)/(

)/(1000*)/()/(

LmgMLSS

gmgLmLumeSettledVolgmLSVI

Sludge Volume Index (SVI)

)/()*/(*)/()/( mgLkLmgXos

MLSSehrftVhrftV

Sludge Settling Velocity (Vs)

.Constk

trationMLSSConcenX

itytlingVelocMaximumSetV

locitySettlingVeV

MLSS

o

s

Other Important Definitions For Secondary Other Important Definitions For Secondary Clarifier Performance and CapacityClarifier Performance and Capacity

)/(

)/(1000*)/()/(

LmgMLSS

gmgLmLumeSettledVolgmLSVI

Sludge Volume Index (SVI)

)/()*/(*)/()/( mgLkLmgXos

MLSSehrftVhrftV

Sludge Settling Velocity (Vs)

.Constk

trationMLSSConcenX

itytlingVelocMaximumSetV

locitySettlingVeV

MLSS

o

s

Activated Sludge System DesignActivated Sludge System DesignFlow DiagramFlow Diagram

Flow and Load

Set SRT

Calc WAS & Inventory

S t OFRSet OFRCalc

Clarifier Area

Set SVICalc

Allowable MLSS

Calc Required

AB Volume

1717

Activated Sludge System DesignActivated Sludge System DesignAlternate Flow DiagramAlternate Flow Diagram

Flow and Load

Set SRT

Calc WAS & Inventory

S t MLSSSet MLSS

Calc Clarifier

Area

Set SVI

Calc AB Volume

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Capacity Diagram for Activated Capacity Diagram for Activated SludgeSludge

1919

How to Improve PerformanceHow to Improve Performance

Flocculation / Settleability ControlFlocculation / Settleability Control BiologicalBiological

ChemicalChemical

PhysicalPhysical PhysicalPhysical

Hydraulic Performance ImprovementHydraulic Performance Improvement Inlet energy dissipationInlet energy dissipation

Outlet configuration controlOutlet configuration control

2020

How to Improve CapacityHow to Improve Capacity

Settleability ImprovementSettleability Improvement BiologicalBiological

ChemicalChemical

H d li I tH d li I tHydraulic ImprovementHydraulic Improvement Feed variationFeed variation

Inlet energy dissipationInlet energy dissipation

Outlet configuration controlOutlet configuration control

2121

Introduction to Settleability Introduction to Settleability ControlControl

By Randal W. Samstag



2222

OutlineOutline

Why is settleability important? Why is settleability important?

Causes of poor settleabilityCauses of poor settleability

What can be done about poor settleability?What can be done about poor settleability?

A word about foamingA word about foaming

ConclusionsConclusions

2323

Why is Why is SettleabiltySettleabilty Important?Important?

Settleability of activated sludge dramatically affects both Settleability of activated sludge dramatically affects both performance and capacity!performance and capacity!

Affects effluent quality and the ability to retain biomass in Affects effluent quality and the ability to retain biomass in q y yq y ythe system.the system.

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Primary Causes of Poor Primary Causes of Poor SettleabilitySettleability

Filamentous organismsFilamentous organisms

SlimeSlime

Low Low flocfloc densitydensity

Poor flocculationPoor flocculation

Conditions Typically Associated with Conditions Typically Associated with Specific FilamentsSpecific Filaments

Low DOLow DO

Short SRT (High F/M)Short SRT (High F/M)

Long SRT (Low F/M)Long SRT (Low F/M)

Elevated VFAElevated VFA Elevated VFAElevated VFA

SepticitySepticity

Nutrient DeficiencyNutrient Deficiency

Low pHLow pH

Low DOLow DOType 1701Type 1701

Straight, smoothly curved, or Straight, smoothly curved, or bentbent

10 to 150 μm long / 1.0 μm 10 to 150 μm long / 1.0 μm widthwidth

GramGram--negativenegative NeisserNeisser--negativenegativegg Cell septaCell septa Encouraged by Encouraged by

Complete mix Complete mix Readily biodegradable Readily biodegradable

substrates (rbs)substrates (rbs) Low DO!Low DO!

SRT 2 SRT 2 –– 20 days20 days Selectors reported effectiveSelectors reported effective

Short SRT (High F/M) Short SRT (High F/M) Type 1863Type 1863

Oval cells Oval cells

10 10 –– 50 μm long by 0.8 to 1.0 50 μm long by 0.8 to 1.0 μm diameterμm diameter

No sheathNo sheath

GramGram--negative and Neissernegative and Neisser--negative with Neissernegative with Neisser--positive positive granulesgranules

SRT < 2.5 daysSRT < 2.5 days

Like oil and greaseLike oil and grease

Selectors not effectiveSelectors not effective

Long SRT (Low F/M)Long SRT (Low F/M)Microthrix ParvicellaMicrothrix Parvicella

Coiled growthCoiled growth 50 to 200 50 to 200 m long / 0.8 m long / 0.8 m m

widewide GramGram--positivepositive NeisserNeisser--positive granulespositive granules Encouraged byEncouraged by Encouraged byEncouraged by

Alternating aerobic / anoxic Alternating aerobic / anoxic conditionsconditions

Cold temperaturesCold temperatures

Grow in Grow in unaeratedunaerated zoneszones Controlled by PAXControlled by PAX SRT 8SRT 8--50 days50 days Anoxic selectors don’t work on Anoxic selectors don’t work on

them (Can denitrify?)them (Can denitrify?)

Elevated VFAElevated VFANostacoida limicola IINostacoida limicola II

Bent and irregularly Bent and irregularly coiled filamentscoiled filaments

100 100 –– 200 μm long / 1.2 200 μm long / 1.2 ––1.4 μm diameter1.4 μm diameter

Cell septaCell septa Cell septaCell septa

Gram and Neisser Gram and Neisser variablevariable

Anaerobic selectors Anaerobic selectors effectiveeffective

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Septicity Septicity Thiothrix IIThiothrix II

SulfurSulfur--oxidizing aerobeoxidizing aerobe 50 to 200 μm in length, 50 to 200 μm in length,

0.8 0.8 –– 1.4 μm diameter 1.4 μm diameter extending from floc extending from floc surfacesurface

GramGram--negative, Neissernegative, Neisser--negativenegative

Intracellular sulfur Intracellular sulfur granulesgranules

Anaerobic selectors can Anaerobic selectors can be counterbe counter--productiveproductive

Nutrient Nutrient DeficiencyDeficiency

Type 021 NType 021 N

ThiothrixThiothrix I and III and II

N. N. limicolalimicola IIIIII

HH h d ih d i

FunghiFunghi

Low pH

H. H. hydrossishydrossis

S. S. natansnatans

Slime BulkingSlime Bulking

3232

Floc DensityFloc Density

Compact flocs settle Compact flocs settle faster than highly faster than highly filamentous sludgesfilamentous sludges

Phosphorus accumulating Phosphorus accumulating organisms (PAO) have a organisms (PAO) have a higher density than higher density than typical zoogleal or typical zoogleal or filamentous organismsfilamentous organisms

A Word about FoamingA Word about Foaming

Typically caused by Typically caused by NocardioformNocardioformss

SRT > 2 daysSRT > 2 days Aerobic selectors can Aerobic selectors can

controlcontrol Anaerobic and Anoxic Anaerobic and Anoxic

selectors may help if no selectors may help if no foam trappingfoam trapping

Selective wastingSelective wasting Chlorine not effectiveChlorine not effective Cationic polymer controls Cationic polymer controls

themthem

NocardioformsNocardioforms

Irregularly shaped trueIrregularly shaped true--branchingbranching

5 to 30 μm long and 1.0 5 to 30 μm long and 1.0 μm wideμm wide

GramGram positive andpositive and GramGram--positive and positive and NeisserNeisser--negative with negative with NeisserNeisser--positive granulespositive granules

Many genera Many genera –– Nocardia, Nocardia, Gordona, SkermaniaGordona, Skermania

Types of Control for Settleability Types of Control for Settleability ProblemsProblems

ShortShort--term Controlterm Control ChemicalsChemicals

ChlorinationChlorination PAXPAX PolymersPolymers

LongLong--term Controlterm Control SelectorsSelectors

AerobicAerobic AnoxicAnoxic AnaerobicAnaerobic PolymersPolymers

NutrientsNutrients AnaerobicAnaerobic

SRT ControlSRT Control DO ControlDO Control

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Chemical Control ExamplesChemical Control Examples

Chlorine for general filament controlChlorine for general filament control

PAX for PAX for M. M. parvicellaparvicella controlcontrol

Aluminum for general controlAluminum for general control

Polymers for Polymers for NocardioformNocardioform controlcontrol

Nutrient addition for slime bulking controlNutrient addition for slime bulking control

3737

Selector Selector –– A DefinitionA Definition

A tank upstream of the main aerobic portion of theA tank upstream of the main aerobic portion of the

Main BasinSelectorInfluent Clarifier Effluent

A tank upstream of the main aerobic portion of the A tank upstream of the main aerobic portion of the activated sludge process that is designed to control activated sludge process that is designed to control sludge settleability by metabolic or kinetic meanssludge settleability by metabolic or kinetic means Metabolic control Metabolic control –– Due to the way the organisms get food and Due to the way the organisms get food and

energyenergy

Kinetic control Kinetic control –– Due to the growth rate of the organism under Due to the growth rate of the organism under different conditions (SRT)different conditions (SRT)

Metabolic ControlMetabolic Control

Designed to encourage a Designed to encourage a certain organism by certain organism by providing the right providing the right metabolic conditions for metabolic conditions for its growthits growthgg

ExamplesExamples PAO in anaerobic selectorsPAO in anaerobic selectors

Anoxic selectors for Anoxic selectors for S. S. natansnatans controlcontrol

Kinetic Theory of Selection Kinetic Theory of Selection (Chudoba, 1973; Jenkins, 1975)(Chudoba, 1973; Jenkins, 1975)

Filaments have a competitive advantage Filaments have a competitive advantage over floc forming organisms under over floc forming organisms under conditions of low substrate (food) conditions of low substrate (food) concentration gradient (change)concentration gradient (change)concentration gradient (change). concentration gradient (change).

Selectors work by exposing treatment Selectors work by exposing treatment organisms to a high substrate organisms to a high substrate concentration gradient.concentration gradient.

4040

Comparative Growth RatesComparative Growth RatesDO 2.0 mg/L, 15 Degrees CDO 2.0 mg/L, 15 Degrees C

5

6

7

Rat

e, 1

Zooglea ramigera

0

1

2

3

4

0 10 20 30 40 50 60

Substrate, mg/L

Spe

c G

row

th R

g g

Sphaerotilus natans

Type 021N

4141

5678

Rat

e, 1

Comparative Growth Rates Comparative Growth Rates DO 2 mg/L, 25 Degrees CDO 2 mg/L, 25 Degrees C

012345

0 10 20 30 40 50 60

Substrate, mg/L

Spe

c G

row

th

Zooglea ramigera

Sphaerotilus natans

021N

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2

2.5

3

Rat

e, 1

Comparative Growth RatesComparative Growth RatesDO 0.1 mg/L, 20 Degrees CDO 0.1 mg/L, 20 Degrees C

0

0.5

1

1.5

0 10 20 30 40 50 60

Substrate, mg/L

Spe

c G

row

th

Zooglea ramigera

Sphaerotilus natans

021N

4343

Types of SelectorsTypes of Selectors

AerobicAerobic

Anoxic Anoxic

AnaerobicAnaerobic AnaerobicAnaerobic

4444

Aerobic SelectorAerobic Selector


Aerobic first stageAerobic first stage Classic kinetic mechanismClassic kinetic mechanism SRT SRT –– 3 to 5 days3 to 5 days Relies on higher substrate concentration in smaller first stage of Relies on higher substrate concentration in smaller first stage of

treatmenttreatment

Aerobic SelectorAerobic Selector

Selector

BODMain Basin

O2

CO2 + H2O

Energy

Storage BOD

O2

CO2 + H2O

Storage

Synthesis Energy

4646

Anoxic SelectorAnoxic Selector


Anoxic first stageAnoxic first stage Internal recycleInternal recycle Denitrification flow schemeDenitrification flow scheme Must nitrify! (SRT 4 to 10 days)Must nitrify! (SRT 4 to 10 days) Most filaments don’t denitrifyMost filaments don’t denitrify May not control May not control M. M. ParvicellaParvicella, which can denitrify, which can denitrify

Anoxic SelectorAnoxic Selector

Selector

BOD

Main Basin

O2

CO2 + H2O

Energy

Storage BOD

NO3

CO2 + H2O

Storage

Synthesis

Energy

N2

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Anaerobic SelectorAnaerobic Selector


Anaerobic first stageAnaerobic first stage

Encourage PAO and/or GAOEncourage PAO and/or GAO

SRT SRT -- 2.5 days to 5 days2.5 days to 5 days

No internal recycle requiredNo internal recycle required

Can encourage Can encourage Thiothrix Thiothrix if it produces Hif it produces H22SS

PAO need both anaerobic and fully aerobic conditionsPAO need both anaerobic and fully aerobic conditions

Anaerobic Selector Anaerobic Selector –– PAO PAO Phosphorus Accumulating OrganismsPhosphorus Accumulating Organisms

Selector

BOD

Storage

Main Basin

StorageO2

CO2 + H2O

PO4

EnergyGlycogen

Poly P

Synthesis

Energy

Poly P

Glycogen

PO4

Reducing Power

5050

Anaerobic Selector Anaerobic Selector –– GAOGAOGlycogen Accumulating OrganismsGlycogen Accumulating Organisms

Selector

BOD

Storage

Main Basin

StorageO2

CO2 + H2O

Energy

Glycogen

Synthesis

Energy

Glycogen

5151

DO ControlDO Control

Activate sludge organisms need oxygen Activate sludge organisms need oxygen for growthfor growth

Low DO can directly cause bulking Low DO can directly cause bulking

L DO di PAOL DO di PAO Low DO can discourage PAOLow DO can discourage PAO

Low DO can suppress nitrifiersLow DO can suppress nitrifiers

DO control is crucialDO control is crucial

5252

SRT ControlSRT Control

Low SRT can cause outbreaks of Type Low SRT can cause outbreaks of Type 18631863

High SRT encourages High SRT encourages NocardioformsNocardioforms and and M parvicellaM parvicellaM. parvicellaM. parvicella

Bio P organisms wash out below 2 days Bio P organisms wash out below 2 days SRTSRT

Nitrifiers wash out below 3Nitrifiers wash out below 3--4 days SRT4 days SRT

This is the primary control for microThis is the primary control for micro--organism growthorganism growth

5353

ConclusionsConclusions Settleability problems result from many different and Settleability problems result from many different and

interacting conditionsinteracting conditions

The solutions to these problems are as varied as the The solutions to these problems are as varied as the conditions that cause themconditions that cause them

No one solution will cure all problemsNo one solution will cure all problems Anaerobic selectors can can encourage PAO but alsoAnaerobic selectors can can encourage PAO but also ThiothrixThiothrix Anaerobic selectors can can encourage PAO but also Anaerobic selectors can can encourage PAO but also ThiothrixThiothrix

Anoxic selectors can control many filaments, but not Anoxic selectors can control many filaments, but not M. M. parvicella parvicella or Typeor Type 00410041

Chlorine doesn’t correct nutrient deficiencyChlorine doesn’t correct nutrient deficiency

SRT and DO control are crucialSRT and DO control are crucial

The first step in a cure is a proper diagnosisThe first step in a cure is a proper diagnosis

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Settleability Settleability Control Control The Operations PerspectiveThe Operations Perspective

By Richard Finger



5555

Presentation OutlinePresentation Outline

Long Term Approaches for Improving SettleabilityLong Term Approaches for Improving Settleability General Discussion of Activated Sludge Process ControlGeneral Discussion of Activated Sludge Process Control Biological ApproachesBiological Approaches

•• Control of Sludge AgeControl of Sludge Age•• Control of F/MControl of F/M•• Use of SelectorsUse of Selectors

Short Term Approaches to High Flow Conditions and/orShort Term Approaches to High Flow Conditions and/or Short Term Approaches to High Flow Conditions and/or Short Term Approaches to High Flow Conditions and/or High SVIHigh SVI Switching from Plug Feed to Contact StabilizationSwitching from Plug Feed to Contact Stabilization Chemical TreatmentChemical Treatment

•• Coagulant Coagulant AdditionAddition•• PolymersPolymers•• ChlorinationChlorination

Questions?Questions?

5656

Long Term Approaches for Improving Long Term Approaches for Improving Settleability Settleability

No matter how well your clarifier is No matter how well your clarifier is designed, it’s ultimate performance will be designed, it’s ultimate performance will be determined by the activated sludge determined by the activated sludge settleabilitysettleabilitysettleability.settleability.

Settleability is dependent upon a number Settleability is dependent upon a number of factors, many of which are within the of factors, many of which are within the control of the Operator.control of the Operator.

5757

General General Discussion of Activated Sludge Discussion of Activated Sludge Process ControlProcess Control

Factors Outside of the Operator’s ControlFactors Outside of the Operator’s Control Flow RateFlow Rate

Sewage StrengthSewage Strength

Aeration Tank VolumeAeration Tank Volume Aeration Tank VolumeAeration Tank Volume•• This assumes that additional tankage is not This assumes that additional tankage is not

availableavailable

Wastewater TemperatureWastewater Temperature

Number of Clarifiers Number of Clarifiers

5858

General Discussion of Activated Sludge General Discussion of Activated Sludge Process Process Control (continued)Control (continued)

Factors Within the Operator’s ControlFactors Within the Operator’s Control Aeration RatesAeration Rates

RAS Return RatesRAS Return Rates

Wasting RatesWasting Rates Wasting RatesWasting Rates

Dissolved Oxygen ConcentrationDissolved Oxygen Concentration

Aeration Tank ConfigurationAeration Tank Configuration•• Within the design limits of the tanksWithin the design limits of the tanks

5959

General Discussion of Activated Sludge General Discussion of Activated Sludge Process Control (continued)Process Control (continued)

By Adjusting the Controllable Parameters, By Adjusting the Controllable Parameters, the Operator Can Control:the Operator Can Control: The total mass of bacteria in the systemThe total mass of bacteria in the system

By Controlling the Mass of Bacteria theBy Controlling the Mass of Bacteria the By Controlling the Mass of Bacteria, the By Controlling the Mass of Bacteria, the Operator can Control:Operator can Control: The Food to Microorganism (F/M) RatioThe Food to Microorganism (F/M) Ratio

The Sludge Age (SRT) by adjusting the waste The Sludge Age (SRT) by adjusting the waste raterate

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Biological Approaches for Biological Approaches for Controlling SettleabilityControlling Settleability

Settleability in Conventional Activated Settleability in Conventional Activated Sludge Systems is a Function of:Sludge Systems is a Function of: Sludge Age or SRTSludge Age or SRT

F/M RatioF/M Ratio F/M RatioF/M Ratio

Aeration TimeAeration Time

Dissolved Oxygen ConcentrationDissolved Oxygen Concentration

6161

Biological Approaches for Controlling Biological Approaches for Controlling Settleability (continued)Settleability (continued)

Sludge Age or SRTSludge Age or SRT Young sludges tend to settle more slowly than Young sludges tend to settle more slowly than

older sludgesolder sludges

Long SRT sludges tend to settle rapidly butLong SRT sludges tend to settle rapidly but Long SRT sludges tend to settle rapidly, but Long SRT sludges tend to settle rapidly, but may leave fine particles in solutionmay leave fine particles in solution

SRT does not change instantaneously with SRT does not change instantaneously with changes in wasting rates. Once a change is changes in wasting rates. Once a change is made, it takes up to 3 SRT’s to see the full made, it takes up to 3 SRT’s to see the full effect.effect.

6262

Effect of Sludge Age on Effect of Sludge Age on SettleabilitySettleability

6363


F/M RatioF/M Ratio

6464


Low F/M can result in filament growthLow F/M can result in filament growth

At low substrate concentrations, filaments At low substrate concentrations, filaments are more effective at capturing BOD than are more effective at capturing BOD than the floc forming organisms and thus canthe floc forming organisms and thus canthe floc forming organisms and thus can the floc forming organisms and thus can grow fastergrow faster

6565


Aeration TimeAeration Time Bacteria need sufficient time in an aerobic Bacteria need sufficient time in an aerobic

environment to metabolize what they have environment to metabolize what they have removed.removed.

•• The time required is a function of both the F/M The time required is a function of both the F/M ratio and the temperature. Higher F/M requires ratio and the temperature. Higher F/M requires longer aeration times while higher temperatures longer aeration times while higher temperatures allow faster metabolism and thus shorter aeration allow faster metabolism and thus shorter aeration times.times.

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Dissolved OxygenDissolved Oxygen DO should normally be maintained in the 2 DO should normally be maintained in the 2

mg/l rangemg/l range

DO’s below 2 mg/l can lead to filament growthDO’s below 2 mg/l can lead to filament growth DO s below 2 mg/l can lead to filament growth DO s below 2 mg/l can lead to filament growth and can limit the ability of microorganisms to and can limit the ability of microorganisms to metabolize organic materialmetabolize organic material

DO’s significantly above 2 mg/l wastes energyDO’s significantly above 2 mg/l wastes energy

6767


SelectorsSelectors Poor settling conditions resulting from Poor settling conditions resulting from

filaments can be addressed by changing the filaments can be addressed by changing the operating configuration to create conditions operating configuration to create conditions p g gp g gthat favor the growth of nonthat favor the growth of non--filamentous filamentous organismsorganisms

Originally developed for biological nutrient Originally developed for biological nutrient removalremoval

Most common are either anoxic selectors or Most common are either anoxic selectors or anaerobic selectorsanaerobic selectors

6868


Basic Selector ConfigurationsBasic Selector ConfigurationsAnaerobic Selector

Anoxic Selector

6969

Short Term ApproachesShort Term Approaches

Switching from Plug Flow to Contact Switching from Plug Flow to Contact StabilizationStabilization High flows can result in excessive solids High flows can result in excessive solids

loading on the clarifiersloading on the clarifiersloading on the clarifiersloading on the clarifiers

High flows can result in inadequate aeration High flows can result in inadequate aeration detention timedetention time

7070

Plug Flow vs Contact StabilizationPlug Flow vs Contact StabilizationPlug Flow

Contact Stabilization

7171

Plug Flow vs Contact Stabilization : Plug Flow vs Contact Stabilization : Clarifier Solids Clarifier Solids LoadingLoading

At the point the feed is switched to contact, At the point the feed is switched to contact, mixed liquor entering the contact zone is diluted mixed liquor entering the contact zone is diluted by the relocated feed. This results in a period of by the relocated feed. This results in a period of

d d lid l di t i th l ifid d lid l di t i th l ifireduced solids loading entering the clarifiers.reduced solids loading entering the clarifiers.

Solids concentration in the reaeration zone Solids concentration in the reaeration zone increases to the RAS concentration as mixed increases to the RAS concentration as mixed liquor is displaced.liquor is displaced.

Sludge blanket in the clarifier is reduced as the Sludge blanket in the clarifier is reduced as the solids loading drops.solids loading drops.

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Plug Flow vs Contact Stabilization : Plug Flow vs Contact Stabilization : Clarifier Solids LoadingClarifier Solids Loading

Once flows moderate, the feed should be Once flows moderate, the feed should be returned to the original configurationreturned to the original configuration

To the extent possible, transfer of feed To the extent possible, transfer of feed back to the head of the aeration tankback to the head of the aeration tankback to the head of the aeration tank back to the head of the aeration tank should be done gradually to avoid short should be done gradually to avoid short term clarifier solids overloading as the term clarifier solids overloading as the RAS enters the clarifiers.RAS enters the clarifiers.

7373

Plug Flow vs Contact Plug Flow vs Contact Stabilization : Stabilization : Aeration TimeAeration Time

Assumptions:Assumptions:

Aeration Tank Volume = 2 MGAeration Tank Volume = 2 MG

Return Rate = 35%Return Rate = 35%

Contact Volume = 1 MGContact Volume = 1 MG

Reaeration Volume = 1 MGReaeration Volume = 1 MG

Aeration Detention Time at 10 MGD FlowAeration Detention Time at 10 MGD Flow

Plug Flow: 2 MG x 24/10 mgd x 1.35 = 3.6 hrPlug Flow: 2 MG x 24/10 mgd x 1.35 = 3.6 hr

Aeration Detention Time at Aeration Detention Time at 30 30 MGD FlowMGD Flow

Plug Flow: 2 MG x Plug Flow: 2 MG x 24/30 24/30 mgd x 1.35 = 1mgd x 1.35 = 1.2 hr.2 hr

Contact StabilizationContact Stabilization

•• Aeration Time: 1 x 24/Aeration Time: 1 x 24/ 24/30 mgd x 1.35 24/30 mgd x 1.35 = 0.6 hr= 0.6 hr

•• Reaeration Time: 1 x 24/30 x .35 = 2.3 hrReaeration Time: 1 x 24/30 x .35 = 2.3 hr

•• Total Time for aeration: 0.6 + 2.3 = 2.9 hrTotal Time for aeration: 0.6 + 2.3 = 2.9 hr

7474

Short Term Short Term Approaches Approaches (continued)(continued)

Chemical TreatmentChemical Treatment Coagulant AdditionCoagulant Addition

•• May be used to improve poor settleability due to May be used to improve poor settleability due to filamentous conditions or nonfilamentous conditions or non--filamentous filamentous conditionsconditionsconditionsconditions

•• Acts both as a bulking agent to increase floc mass Acts both as a bulking agent to increase floc mass and as a flocculating agent to help compact the and as a flocculating agent to help compact the floc and reduce settling resistancefloc and reduce settling resistance

•• Most commonly used chemicals are iron and Most commonly used chemicals are iron and aluminum saltsaluminum salts

•• Not recommended for long term use both due to Not recommended for long term use both due to chemical costs and increased mass of inorganic chemical costs and increased mass of inorganic flocfloc 7575

Short Term Approaches Short Term Approaches (Coagulant Addition)(Coagulant Addition)

Chemical addition should be upstream of Chemical addition should be upstream of clarifiers in an area where there is good clarifiers in an area where there is good mixing and with sufficient detention time to mixing and with sufficient detention time to facilitate flocculationfacilitate flocculationfacilitate flocculationfacilitate flocculation

The feed rate should be proportional to the The feed rate should be proportional to the mixed liquor flow ratemixed liquor flow rate

Alum and iron salts can depress the pH, Alum and iron salts can depress the pH, thus feed rates should be limited so as to thus feed rates should be limited so as to maintain the pH at 6.5 or abovemaintain the pH at 6.5 or above

7676


Poly aluminum chloride (PAX) Poly aluminum chloride (PAX) formulations are available which formulations are available which significantly reduce pH depression. Thus, significantly reduce pH depression. Thus, they can be fed at a higher rate so as to they can be fed at a higher rate so as to y gy gachieve the desired results more rapidlyachieve the desired results more rapidly

Feed rate adjustments Feed rate adjustments sshould be made hould be made based on observation of actual based on observation of actual performanceperformance

7777

Alum Addition and SVIAlum Addition and SVI

7878

9/18/2011


Alum Addition and SVIAlum Addition and SVI

7979


Coagulant feed should be closely Coagulant feed should be closely monitored and stopped once the desired monitored and stopped once the desired level of settling is achievedlevel of settling is achieved

As shown in the previous slide theAs shown in the previous slide the As shown in the previous slide, the As shown in the previous slide, the settleability reduction lasts for a period of settleability reduction lasts for a period of time after coagulant feed is stopped. Feed time after coagulant feed is stopped. Feed can be resumed when settleability starts to can be resumed when settleability starts to increase and/or when an increase in increase and/or when an increase in filaments is observed under the filaments is observed under the microscopemicroscope

8080

Short Term Approaches Short Term Approaches (Polymer addition)(Polymer addition)

Polymer AdditionPolymer Addition Polymers perform similarly to coagulants by Polymers perform similarly to coagulants by

enhancing flocculationenhancing flocculation

Unlike coagulants polymers to not increaseUnlike coagulants polymers to not increase Unlike coagulants, polymers to not increase Unlike coagulants, polymers to not increase density by incorporating mass within the flocdensity by incorporating mass within the floc

The use of polymers does not significantly The use of polymers does not significantly increase the total mass of sludgeincrease the total mass of sludge

Jar tests can be used to identify the most Jar tests can be used to identify the most effective polymer additive and doseeffective polymer additive and dose

8181

Short Term Approaches Short Term Approaches (Polymer addition)(Polymer addition)

As with coagulants, the polymer As with coagulants, the polymer should be should be added upstream added upstream of clarifiers in an area of clarifiers in an area where there is good mixing and with where there is good mixing and with sufficient detention time to facilitatesufficient detention time to facilitatesufficient detention time to facilitate sufficient detention time to facilitate flocculationflocculation

The feed rate should be proportional to the The feed rate should be proportional to the mixed liquor flow mixed liquor flow rate based on the rate based on the dosage determined in the jar testsdosage determined in the jar tests

8282

Short Term Short Term Approaches Approaches (Continued)(Continued)

RAS ChlorinationRAS Chlorination RAS chlorination is used to control poor RAS chlorination is used to control poor

settleability due to filamentssettleability due to filaments

Chlorine is applied to the RAS ahead of theChlorine is applied to the RAS ahead of theChlorine is applied to the RAS ahead of the Chlorine is applied to the RAS ahead of the aeration tankaeration tank

The normal dosage rate is 3 The normal dosage rate is 3 –– 6 lb. chlorine 6 lb. chlorine per 1000 pounds of VSSper 1000 pounds of VSS

Start at the lower rate and closely monitor the Start at the lower rate and closely monitor the activated sludge under the microscopeactivated sludge under the microscope

8383

Short Term Approaches Short Term Approaches (RAS Chlorination)(RAS Chlorination)

Chlorine feed should be controlled proportional Chlorine feed should be controlled proportional to the RAS flow rate to achieve the desired to the RAS flow rate to achieve the desired dosage ratiodosage ratio

Care Care must be taken not to overdose must be taken not to overdose

Continue chlorination until filaments are no Continue chlorination until filaments are no longer prevalent and/or settling improveslonger prevalent and/or settling improves

8484

9/18/2011


Effect of RAS ChlorinationEffect of RAS Chlorination

Before Chlorination After Chlorination

8585

Settleability Control Settleability Control –– Case Case StudiesStudies

By Dick Finger / Randal Samstag



8686

Settleability Control Case Settleability Control Case StudiesStudies

Nationwide plant surveyNationwide plant survey

King County South Plant King County South Plant –– Anaerobic Anaerobic selector successselector success

W t P i t HPO Pil tW t P i t HPO Pil t A bi l tA bi l tWest Point HPO Pilot West Point HPO Pilot –– Anaerobic selector Anaerobic selector failure failure

Bellingham Bellingham –– Anaerobic selector success Anaerobic selector success for low DO bulking and high VFAfor low DO bulking and high VFA

Aberdeen Aberdeen –– Anoxic/anaerobic selector Anoxic/anaerobic selector successsuccess

8787

Performance of Activated Sludge Performance of Activated Sludge Plants with Plants with Anoxic Anoxic SelectorsSelectors

8888

Performance of Activated Sludge Performance of Activated Sludge Plants with Anaerobic SelectorsPlants with Anaerobic Selectors

8989

Impact of Anaerobic Selector at Impact of Anaerobic Selector at King County South PlantKing County South Plant

9090

9/18/2011


West Point HPO Test FacilityWest Point HPO Test Facility 44--stage HPO pilot facility stage HPO pilot facility

(Lotepro)(Lotepro) 2020--30 gpm30 gpm

SRT: 1SRT: 1--2 days2 days

MarMar -- Dec 1988Dec 1988 Mar Mar Dec 1988Dec 1988

3 modes evaluated:3 modes evaluated: Plug FlowPlug Flow

Contact/ReaerationContact/Reaeration

Anaerobic Selector w/ Anaerobic Selector w/ Plug FlowPlug Flow

HPO Test Facility SchematicHPO Test Facility Schematic

9292

Settleability Data from HPO Settleability Data from HPO Test FacilityTest Facility

400500600700800900

, mL

/g Min

Ave

0100200300400

Plug F

low

Plug F

low

Plug F

low

Plug F

low

Plug F

low

Plug F

low

Conta

ct / R

eaer

ation

Conta

ct / R

eaer

ation

Selecto

r

Conta

ct / R

eaer

ation

Conta

ct / R

eaer

ation

SV

I,

Max

9393

The CulpritsThe Culprits

Microscopic evaluation of Microscopic evaluation of both the pilot test facility both the pilot test facility and the UW bench scale and the UW bench scale foundfoundThiothrix IIThiothrix II

Type 021NType 021N

Sulfur oxidizing aerobesSulfur oxidizing aerobes

Predicted BioWinPredicted BioWin P04 ProfileP04 Profile

Primary Influent EffluentHPO Cell 2 HPO Cell 3 HPO Cell 4 ML ChannelHPO Cell 1

Waste

Selector

2.5 Primary Influent2.669 Selector2.403 HPO Cell 12.287 HPO Cell 22.26 HPO Cell 32.265 HPO Cell 42.275 ML Channel2.273 Secondary Clarifier2.273 Ef fluent2.275 Waste

BioWin Chart

TIMEPrimary Influent HPO Cell 2 HPO Cell 4 Effluent

CO

NC

EN

TR

ATIO

N (m

g/L

)

2

1

0

9595

Predicted Biomass Distribution: Predicted Biomass Distribution: No PAONo PAO

ZbhZbaZbpZbpaZbamZbhmZe

BioWin Chart

N (

mg

/L) 600

500

ML Channel

TIMEML Channel

CO

NC

EN

TR

AT

ION

400

300

200

100

0

ML ChannelML ChannelML ChannelML ChannelML ChannelML Channel

9696

9/18/2011


The Bellingham Post Point PlantThe Bellingham Post Point Plant

20 mgd capacity high purity 20 mgd capacity high purity oxygen (HPO) activated oxygen (HPO) activated sludge plantsludge plant

Average SVI of 170 mL/g over Average SVI of 170 mL/g over period from 1999 to 2004period from 1999 to 2004

Typical filaments causingTypical filaments causing Typical filaments causing Typical filaments causing settleability problems: Type settleability problems: Type 1701 (Low DO) and Type 1863 1701 (Low DO) and Type 1863 (Low SRT)(Low SRT)

Periodically high VFA feed Periodically high VFA feed from influent sewer and from from influent sewer and from solids dewatering operation 3solids dewatering operation 3--4 days per week leading to 4 days per week leading to slime bulkingslime bulking

Idea for Improvement Idea for Improvement ––Anaerobic SelectorAnaerobic Selector

Provide zone for uptake of VFA Provide zone for uptake of VFA

Encourage growth of phosphorus accumulating Encourage growth of phosphorus accumulating organisms (PAO)organisms (PAO)

Increasing population distribution of PAO increases floc Increasing population distribution of PAO increases floc densitydensitydensitydensity

PAO have a compact morphology and higher density PAO have a compact morphology and higher density than other typical activated sludge bacteria (Schuler and than other typical activated sludge bacteria (Schuler and Jenkins)Jenkins)

Experience at three other HPO plants (SE Essex SD, Experience at three other HPO plants (SE Essex SD, Hyperion, SE San Francisco)Hyperion, SE San Francisco)

9898

Simulation of Anaerobic First Simulation of Anaerobic First StageStage

Primary Effluent Secondary Clarifiers OutfallCl2 ContactAerobic AerobicAnaerobic

WAS

Simulations of Population Simulations of Population DistributionsDistributions

Impact of Anaerobic SelectorImpact of Anaerobic SelectorSVI ProbabilitySVI Probability

101101

Impact of Anaerobic SelectorImpact of Anaerobic SelectorSVI Probability SRT > 2.3 DaysSVI Probability SRT > 2.3 Days

102102

9/18/2011


Impact on CapacityImpact on Capacity

103103

Aberdeen Anoxic / Anaerobic Aberdeen Anoxic / Anaerobic SelectorSelector

Mechanically mixed Mechanically mixed activated sludge aeration activated sludge aeration tankstanks

Upgraded in 2002 for fine Upgraded in 2002 for fine bubble aeration withbubble aeration withbubble aeration with bubble aeration with anoxic/anaerobic anoxic/anaerobic selectorsselectors

Aberdeen WWTP SchematicAberdeen WWTP Schematic

From Influent Pumps Primary Sed Anaerobic AerobicAnoxic Secondary Sed

Gravity Thickener

Grit Cyclone

Screens

Screenings

Chlorine Con

Main Digester

Gravity Thickener

Secondary Digesters

Return Flows

Grit

Rotary Thickener

Biosolids

Screw Press

105105

Selector Operation Has Selector Operation Has Improved SVIImproved SVI

Influence of Selector Operation on SVI and SRT

12

14

L)

350

400

SRT (days) NH3 Removal (mg/L) SVI (mL/g)

Selector Implemented

0

2

4

6

8

10

2002 2003 2004 2005 2006

SR

T (

day

s) a

nd

NH

3r (

mg

/L

0

50

100

150

200

250

300

SV

I (m

L/g

)

106106

Introduction to Clarifier Introduction to Clarifier ModelsModels

By Randal Samstag, Carollo Engineers



107107

Why do Modeling?Why do Modeling?

No matter what you do you can’t avoid No matter what you do you can’t avoid using a model of some kind.using a model of some kind.

Every system is differentEvery system is different

I i it li it i tI i it li it i t Increasing permit limit requirementsIncreasing permit limit requirements

Increasing Need to reduce safety factors Increasing Need to reduce safety factors to reduce costto reduce cost

Increasing need to maximize capacity of Increasing need to maximize capacity of existing facilitiesexisting facilities

108108

9/18/2011


Types of Sedimentation ModelsTypes of Sedimentation Models

Solids flux models (state point analysis)Solids flux models (state point analysis)

OneOne--dimensional dynamic models (Biowin, dimensional dynamic models (Biowin, SedtankSedtank, Takacs, , Takacs, VitasovicVitasovic, Stenstrom), Stenstrom)

TT di i l d i d l (UNOdi i l d i d l (UNO TwoTwo--dimensional dynamic models (UNO, dimensional dynamic models (UNO, TANKXZ, Carollo Fluent UDF)TANKXZ, Carollo Fluent UDF)

ThreeThree--dimensional dynamic models dimensional dynamic models (Zhou/McCorquodale, Carollo Fluent UDF)(Zhou/McCorquodale, Carollo Fluent UDF)

109109

State Point Analysis (State Point Analysis (ClarifluxClariflux®)®)

Developed by Developed by VesilindVesilind. . Implemented by Carollo Implemented by Carollo Engineers (among Engineers (among others)others)

Solves solids flux Solves solids flux equations based on equations based on qqmeasured settling velocity measured settling velocity coefficients (or SVI)coefficients (or SVI)

Calculates state point for Calculates state point for steady state operationsteady state operation SOR LineSOR Line MLSS LineMLSS Line RAS lineRAS line

110110

OneOne--dimensional (1D) Dynamic Modelsdimensional (1D) Dynamic Models

Developed by Developed by Stenstrom, Tracy, Stenstrom, Tracy, VitasovicVitasovic, Takacs, , Takacs, SedtankSedtank, Biowin, Biowin

Simulate average Simulate average upward velocity versusupward velocity versusupward velocity versus upward velocity versus downward settling downward settling velocityvelocity

Solved dynamicallySolved dynamically Layered modelLayered model Used for longUsed for long--term term

dynamic simulationsdynamic simulations

111111

Why do CFD Modeling?Why do CFD Modeling?

CFD based on prediction of two or three CFD based on prediction of two or three dimensional velocity profilesdimensional velocity profiles

Thirty years of development using Thirty years of development using computational fluid dynamics (CFD) for computational fluid dynamics (CFD) for analysis of sedimentation has proven that analysis of sedimentation has proven that CFD can CFD can 1) Capture the main features of clarifier behavior1) Capture the main features of clarifier behavior2) Predict detailed features of hydraulic behavior2) Predict detailed features of hydraulic behavior3) Efficiently predict performance of novel designs3) Efficiently predict performance of novel designs4) Be more cost effective than full4) Be more cost effective than full--scale prototypesscale prototypes

112112

TwoTwo--dimensional (2D) Modelsdimensional (2D) Models

Incorporate 2D tank Incorporate 2D tank hydraulicshydraulics Boundary effectsBoundary effects TurbulenceTurbulence Density effectsDensity effectsyy

Used for geometric Used for geometric optimization of optimization of symmetrical elementssymmetrical elements

Proprietary codes or Proprietary codes or public domain public domain programsprograms

113113

ThreeThree--dimensional (3D) Modelsdimensional (3D) Models

Resolution and detail Resolution and detail limited only by computing limited only by computing powerpower

Very detailed grids can Very detailed grids can be used to capture be used to capture geometric features as geometric features as ggsmall as several inchessmall as several inches

Crucial for modeling of Crucial for modeling of nonnon--symmetric featuressymmetric features

Implemented in Implemented in proprietary code or proprietary code or commercial CFD commercial CFD packages with special packages with special addadd--ons ons

114114

9/18/2011


Each Type of Model Has its Each Type of Model Has its PlacePlace

State Point Analysis State Point Analysis –– Steady State Steady State Capacity AnalysisCapacity Analysis

1D Dynamic Models 1D Dynamic Models –– LongLong--term term Dynamic simulationsDynamic simulationsDynamic simulationsDynamic simulations

2D Models 2D Models –– Simple design evaluationsSimple design evaluations

3D Models 3D Models –– For design problems that are For design problems that are not simplenot simple

115115

Clarifier Field TestsClarifier Field Tests

By Randal Samstag, Carollo Engineers



116116

OutlineOutline

Limitations of field tests

What are field tests good for?

Model calibration and validation Model calibration and validation

Input tests

Output tests

117117

Limitations of Field TestsLimitations of Field Tests

Limited to one geometryLimited to one geometry We can only test an existing tank at fullWe can only test an existing tank at full--scalescale

Tests don’t tell us how to improve Tests don’t tell us how to improve performance or capacityperformance or capacityperformance or capacityperformance or capacity

Limited to one point in time Limited to one point in time Characteristics of feed sludge changeCharacteristics of feed sludge change

•• Flocculation characteristicsFlocculation characteristics

•• Particle size distributionsParticle size distributions

•• Settling velocitySettling velocity

•• TemperatureTemperature

•• Wind speedsWind speeds118118

What are field tests good What are field tests good for?for?

Calibration and Validation of Calibration and Validation of Models!Models!

119119

Calibration or Validation?Calibration or Validation?DefinitionsDefinitions

Calibration: Initial trials to Calibration: Initial trials to dj t d l tdj t d l t

Validation: Tests to Validation: Tests to fi th t d l ifi th t d l iadjust model parameters adjust model parameters

to reproduce field to reproduce field conditions (either long conditions (either long term data or field testing term data or field testing data).data).

confirm that a model is confirm that a model is representing field representing field conditions. For example by conditions. For example by independent stress tests independent stress tests with different flow or settling with different flow or settling conditions or operating dataconditions or operating data

120120

9/18/2011


Input and Output Parameters for Input and Output Parameters for Model Calibration and ValidationModel Calibration and ValidationInput parameters:Input parameters:

•• Settling velocity test Settling velocity test

Output parameters:Output parameters:

•• ESSESSparametersparameters

•• Flow measurementsFlow measurements

•• MLSS testsMLSS tests

•• Flocculation parametersFlocculation parameters

•• FractionationFractionation

•• Simulation parametersSimulation parameters

•• Others like temperature, dry Others like temperature, dry floc density, atmospheric floc density, atmospheric parameters, etc. parameters, etc.

•• Solids profileSolids profile

•• Velocity profileVelocity profile

•• Dye behaviorDye behavior

•• RAS SSRAS SS

•• Blanket depthBlanket depth

•• Solids fraction Solids fraction distributiondistribution

121121

Input Parameter TestsInput Parameter Tests

Settling velocity testingSettling velocity testing

Flow measurementFlow measurement

MLSS measurementMLSS measurement

Density measurement: lock exchangeDensity measurement: lock exchange

Dispersed solids / flocculation tests Dispersed solids / flocculation tests

Particle size distributionsParticle size distributions

TemperatureTemperature

122122

The McCorquodale Settling The McCorquodale Settling ModelModel

Total Suspended Solids Concentration (TSS)

Settling Domain Settling Model

TSS < 5-15 mg/L Non-settleable VS = 0

5-15 mg/L < TSS < 600 mg/L Discrete Settling VS1 < 1.5 m/hr (“small”)1.5 m/hr < VS2 < 6 m/hr (“medium”)

VS3 > 6 m/hr (“large”)VSD = ∑ fi VSi

600 mg/L < TSS < 1200 mg/L Flocculent Settling

Vs = fH*VO*e(-k1*TSS) + (1-fH)*VSD

TSS > 1200 mg/L Hindered Settling

VS = VO * exp (-kH * TSS)

TSS > 6,000 mg/L Compressive Settling

VS = VC * exp (-kC * TSS)

123123

Discrete SettlingDiscrete Settling

The settling velocities of large The settling velocities of large and medium and medium flocsflocs are found by are found by di ( i ldi ( i ldirect measurement (visual direct measurement (visual inspection) in a column batch inspection) in a column batch test using a light source, a test using a light source, a scale and a stopwatch scale and a stopwatch

124124

Sludge Settling Velocity TestsSludge Settling Velocity Tests

Goal: Goal: •• Establish settling Establish settling

velocity at the time of velocity at the time of field testsfield testsfield testsfield tests

Sensitive to:Sensitive to:•• Column shape (Dick Column shape (Dick

1975)1975)

•• Mixing intensityMixing intensity

•• TemperatureTemperature

125125

Settling Velocity Data FitsSettling Velocity Data Fits

126126

9/18/2011


Hindered and compressive settling Hindered and compressive settling coefficients from the same data set.coefficients from the same data set.

10

0.1

1

0 1000 2000 3000 4000 5000

MLSS mg/L

Vs

m/h

127127

Output Validation TestsOutput Validation Tests

Sludge blanket monitoringSludge blanket monitoring

Solids profile testingSolids profile testing

Velocity profile testingVelocity profile testing

Dye transport testingDye transport testing RTD RTD

Continuous dye snapshotContinuous dye snapshot

128128

Sludge Blanket Monitoring Sludge Blanket Monitoring

Dynamic monitoring of sludge blanket Dynamic monitoring of sludge blanket using a sludge judgeusing a sludge judge

Difficulties: What is the threshold Difficulties: What is the threshold concentration of the “sludge blanket”?concentration of the “sludge blanket”?

129129

Solids Profile MeasurementSolids Profile Measurement

Sampling MethodSampling Method•• Larsen:Larsen:

•• KemmererKemmerer

•• Crosby:Crosby:•• Solids Distribution Test Solids Distribution Test

-- Sample pumpsSample pumps

•• Current use:Current use:•• Portable optical probePortable optical probe

130130

Solids Profile VisualizationSolids Profile Visualization

131131

Solids Profile Comparison to SimulationSolids Profile Comparison to SimulationField Test (Crosby SD test)Field Test (Crosby SD test) Simulation (2DC)Simulation (2DC)

132132

9/18/2011


Velocity Profile MeasurementVelocity Profile Measurement

Larsen built his own Larsen built his own ultrasonic velocity probeultrasonic velocity probe

Commercial probes: ADVCommercial probes: ADV

DroguesDrogues

CCConcerns:Concerns:•• Low velocitiesLow velocities

•• Probe sensitivityProbe sensitivity

•• Difficult to hold still!Difficult to hold still!

133133

Velocity Profile VisualizationsVelocity Profile Visualizations

134134

Dye Tests: Residence Time Dye Tests: Residence Time Distribution TestsDistribution Tests

1.2

1.4

1.6

N = 2.3West SideSouth SideEast SideNorth SideAverage

0

0.2

0.4

0.6

0.8

1

0.00 0.50 1.00 1.50 2.00 2.50

C/C

o

135135

Dye Tests: Flow Pattern Distribution Dye Tests: Flow Pattern Distribution Test (Crosby and Bender 1984)Test (Crosby and Bender 1984)

136136

Conclusions: Output validation testsConclusions: Output validation tests

•• Dynamic blanket monitoringDynamic blanket monitoring•• Useful for rough monitoring of test conditionsUseful for rough monitoring of test conditions

•• Not as quantitative as solids profilesNot as quantitative as solids profiles

Solids profilesSolids profiles•• Relatively easy to measureRelatively easy to measure

Directly comparable to model resultsDirectly comparable to model results•• Directly comparable to model resultsDirectly comparable to model results

Velocity profilesVelocity profiles•• More difficult to measure directlyMore difficult to measure directly

Dye testsDye tests•• Useful for flow distribution issuesUseful for flow distribution issues

•• Continuous test not commonly usedContinuous test not commonly used

137137

Advanced Computational Advanced Computational ModelsModels

ByEdward Wicklein, P.E.



138138

9/18/2011


CFDCFD ModelingModelingComputational Fluid Dynamics is the Computational Fluid Dynamics is the

Numerical Solution of:Numerical Solution of: Turbulent Fluid Motion, Energy, Reactions, Turbulent Fluid Motion, Energy, Reactions,

Process Equations, etcProcess Equations, etc. .

Solution Visualization Aided By GraphicsSolution Visualization Aided By Graphics Solution Visualization Aided By GraphicsSolution Visualization Aided By Graphics

139139

2

2

2

2

2

22 1)()()(

z

u

y

u

x

u

x

p

z

wu

y

vu

x

u

t

u t

Fundamental Fluid EquationsFundamental Fluid Equations

140140

Transport modeling treats solids Transport modeling treats solids concentration as a passive scalar quantity concentration as a passive scalar quantity that is transported through a discrete gridthat is transported through a discrete grid

User defined functions (UDF) to implementUser defined functions (UDF) to implement Solids transportSolids transport

Density couplingDensity coupling

S lid ttli l itS lid ttli l it Solids settling velocitySolids settling velocity

z

CV

z

C

zx

C

xz

CV

x

CV

t

Csszsx

zx

141141

Solids Solids Settling Velocity is Settling Velocity is Empirical, Using Empirical, Using Latest Research and Is Easily Calibrated to Latest Research and Is Easily Calibrated to

Field ConditionsField Conditions

kCs eVV 0

(Vesilind Equation)

Model SelectionModel SelectionCommercial Commercial Software PackagesSoftware Packages

Extensive validationExtensive validation

CurrentCurrent

Ease of grid development Ease of grid development g pg p

Some customization capabilitiesSome customization capabilities

Open Source and Proprietary/CustomOpen Source and Proprietary/Custom Complete ability to customizeComplete ability to customize

Significant work to develop and maintainSignificant work to develop and maintain

143143

Computational Grid Developed for Key Computational Grid Developed for Key Features of the Model DomainFeatures of the Model Domain

Cell shape/mesh type:Cell shape/mesh type: HexahedralHexahedral

TetrahedralTetrahedral

HybridHybrid HybridHybrid

PolyhedralPolyhedral

Cell quality:Cell quality: Aspect ratioAspect ratio

Length ratioLength ratio

Grid Grid refinementrefinement144144

9/18/2011


Flow Solver and Solution Flow Solver and Solution ConvergenceConvergence

Fluid Flow Solver:Fluid Flow Solver: Finite volume numerical methodsFinite volume numerical methods

Second order discratezationSecond order discratezation

22 C 0 001 f l b l id lC 0 001 f l b l id l2.2. Convergence = 0.001 for global residual Convergence = 0.001 for global residual and turbulent viscosity ratioand turbulent viscosity ratio

3.3. UnderelaxationUnderelaxation

145145

Results Show Details of Flow FieldResults Show Details of Flow Field

Density CurrentDensity Current

RecirculationRecirculation

SedimentationSedimentation

Velocity GradientsVelocity Gradients Velocity GradientsVelocity Gradients

Short CircuitingShort Circuiting

146146

Poor PerformancePoor PerformanceExisting inlet ports act as nozzles leading Existing inlet ports act as nozzles leading

to stagnation areas within to stagnation areas within flocfloc wellwell

147147

Initial Inlet Spreadsheet Model Initial Inlet Spreadsheet Model Geometry Optimized with Geometry Optimized with 3D3D ModelModel

Spreadsheet InletSpreadsheet Inlet Optimized InletOptimized Inlet

148148

Optimized Inlet has Improved Optimized Inlet has Improved Energy DissipationEnergy Dissipation

Spreadsheet InletSpreadsheet Inlet Optimized InletOptimized Inlet

149149

Other Geometries Readily ModeledOther Geometries Readily ModeledSquare Peripheral Feed / Withdrawal TankSquare Peripheral Feed / Withdrawal Tank

Overall Geometry and GridOverall Geometry and Grid

150150

9/18/2011


Square Peripheral Feed / WithdrawalSquare Peripheral Feed / WithdrawalSolids ProfilesSolids Profiles

151151

Square Peripheral Feed / WithdrawalSquare Peripheral Feed / WithdrawalSludge Blanket Level TopographySludge Blanket Level Topography

152152

Rectangular Lamella ClarifierRectangular Lamella Clarifier

Carollo Fluent UDF Carollo Fluent UDF ModelModel

2D and 3D flow in and 2D and 3D flow in and around the lamella around the lamella plate modulesplate modulesA ti t d l dA ti t d l d Activated sludge Activated sludge clarifiersclarifiers

Two different settling Two different settling models:models: VesilindVesilind VesilindVesilind with Boycott in with Boycott in

lamella zonelamella zone

153153

Detailed Grid CapabilityDetailed Grid Capability

154154

3D3D Model Allows for Detailed Model Allows for Detailed Flow InvestigationFlow Investigation

Flow goes different Flow goes different directions across directions across width and verticallywidth and vertically

155155

Baffling Easy to EvaluateBaffling Easy to Evaluate

Initial DesignInitial Design Baffled DesignBaffled Design

156156

9/18/2011


High Velocity at Mid Depth High Velocity at Mid Depth Better Distributed with BaffleBetter Distributed with Baffle

Initial DesignInitial Design Baffled DesignBaffled Design

157157

VesilindVesilind Model with Moderate SVIModel with Moderate SVI

158158

VesilindVesilind Model of Inlet BaffleModel of Inlet Baffle

159159

VesilindVesilind Model with No LamellasModel with No Lamellas

160160

VesilindVesilind/Boycott Model of Moderate SVI/Boycott Model of Moderate SVI

161161

Different Different 3D3D Improvements Improvements Easily ComparedEasily Compared

Current ConfigurationCurrent Configuration Potential ModificationsPotential Modifications

162162

9/18/2011


Modifications Generally Modifications Generally Increase Velocity GradientIncrease Velocity Gradient


163163

Modifications Have Little Impact Modifications Have Little Impact on Sedimentationon Sedimentation


164164

ConclusionsConclusionsCFD models are well developed for CFD models are well developed for

evaluation of sedimentation tanksevaluation of sedimentation tanks

Some important problems can only be Some important problems can only be adequately evaluated using 3D modelsadequately evaluated using 3D models Inlet designInlet design

Radial flow / square shapeRadial flow / square shape

NonNon--symmetrical elementssymmetrical elements

Commercial 3D CFD codes can be Commercial 3D CFD codes can be productively used with custom addproductively used with custom add--onsons

165165

Secondary Clarifier Secondary Clarifier Hydraulic Control Hydraulic Control

Case StudiesCase Studies

By Randal Samstag / Ed Wicklein



166166

Hydraulic Control Case StudiesHydraulic Control Case Studies

Reno / Truckee Meadows Reno / Truckee Meadows RAS controlRAS control

Olympus Terrace Sewer DistrictOlympus Terrace Sewer DistrictO tl t t l (St f d B ffl )O tl t t l (St f d B ffl ) Outlet control (Stamford Baffle)Outlet control (Stamford Baffle)

Denver Metro, Las Vegas, Daly CityDenver Metro, Las Vegas, Daly City Inlet control (MEDIC)Inlet control (MEDIC)

Dallas Dallas Inlet control (Modified Inlet)Inlet control (Modified Inlet)

167167

TMWRF SST MODELING Base Simulation - Existing Conditions

BASE SIMULATION

FLOW FIELD

Flow = 7.2 mgd

MLSS = 1,500 mg/L

SVI = 125 mL/g

RAS Rate = 40%

SOLIDS FIELD

ESS = 18.5 mg/L

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TMWRF SST MODELING Impact of RAS Flow Reduction

FLOW FIELD

SIMULATION 1

Flow = 7.2 mgd

MLSS = 1,500 mg/L

SVI = 125 mL/g

RAS Rate = 20%

SOLIDS FIELD

ESS = 15.3 mg/L ( = 3.2 mg/L)

169169

TMWRF SST MODELING Impact of Influent Distribution Changes

FLOW FIELD

SIMULATION 2

Flow = 7.2 mgd

MLSS = 1,500 mg/L

SVI = 125 mL/g

RAS Rate = 20%

SOLIDS FIELD

ESS = 11.5 mg/L ( = 3.8 mg/L)

170170

TMWRF SST MODELING Impact of Density Current Baffle

FLOW FIELD

SIMULATION 3

Flow = 7.2 mgd

MLSS = 1,500 mg/L

SVI = 125 mL/g

RAS Rate = 20%

SOLIDS FIELD

ESS = 10.5 mg/L ( = 1.0 mg/L)

171171

TMWRF SST MODELING Impact of Floc Well Optimization

FLOW FIELD

SIMULATION 4

Flow = 7.2 mgd

MLSS = 1,500 mg/L

SVI = 125 mL/g

RAS Rate = 20%

SOLIDS FIELD

ESS = 8.0 mg/L ( = 2.5 mg/L)

172172

TMWRF SST MODELING Impact of Improved Settling Characteristics

FLOW FIELD

SIMULATION 5

Flow = 7.2 mgd

MLSS = 1,500 mg/L

SVI = 125 mL/g

RAS Rate = 40%

SOLIDS FIELD

ESS = 12.5 mg/L ( = 6.0 mg/L)

3.0 cm/s

30

130230

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TMWRF SST MODELING Summary Comparison

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TMWRF SST MODELING Impact of Process Change

30

35

40

ESS = 19.2 5.6 mg/L

BEFORE AFTER

ESS = 12.0 3.9 mg/L

0

5

10

15

20

25

1/1/

99

3/1/

99

5/1/

99

7/1/

99

9/1/

99

11/1

/99

1/1/

00

3/1/

00

5/1/

00

7/1/

00

9/1/

00

11/1

/00

1/1/

01

3/1/

01

ES

S,

mg

/l

ESS 19.2 5.6 mg/L g

175175

Olympus Terrace Sewer DistrictOlympus Terrace Sewer District

TABLE 3. EFFLUENT CONCENTRATIONS (MG/L) FROM CLARIFIER NUMBER 2 FOR DIFFERENT

OVERFLOW AND BAFFLE ARRANGEMENTS

Overflow Rate (gallons/square feet day) Configuration 300 600 1200

Large Feedwell w/o Stamford Baffle

7.94 12.00 26.4

Large Feedwell with Stamford Baffle

6.38 9.21 19.3

Small Feedwell w/o Stamford Baffle

6.40 10.10 139.0

Small Feedwell with Stamford Baffle

5.88 7.97 96.9

176176

Olympus Terrace Sewer DistrictOlympus Terrace Sewer DistrictClarity 2D CFD ModelClarity 2D CFD Model

Solids ProfileSolids Profile

Small FeedSmall Feed--wellwell

Stamford BaffleStamford Baffle

Solids ProfileSolids Profile

Large FeedLarge Feed--well well

Stamford BaffleStamford Baffle

177177

Upgrade in OperationUpgrade in Operation

178178

Daly City, CaliforniaDaly City, CaliforniaCenterCenter--feed, Radialfeed, Radial--flow Square Clarifiersflow Square Clarifiers

Case study for use of Case study for use of modelsmodels State Point AnalysisState Point Analysisyy

2D Model2D Model

3D Model3D Model

179179

State Point ComparisonState Point Comparison

33% RAS 33% RAS 66% RAS66% RAS

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2D Model 2D Model –– UNO ModelUNO Model

Developed by J. A. Developed by J. A. McCorquodale and McCorquodale and associates at the associates at the University of New University of New Orleans for EPAOrleans for EPA

TwoTwo--dimensional model dimensional model based onbased onbased onbased on VorticityVorticity / stream function / stream function

model (2D only)model (2D only) Turbulent hydraulicsTurbulent hydraulics Radial flow coordinates Radial flow coordinates

((axiaxi--symmetric)symmetric) Solids transportSolids transport Composite settling modelComposite settling model FlocculationFlocculation

181181

2D Model Results2D Model ResultsTest Calibration ResultsTest Calibration Results

FieldUNO Model

182182

2D Model Results2D Model ResultsSummary of Model RunsSummary of Model Runs

183183

ThreeThree--dimensional Modelingdimensional ModelingEffluent LaundersEffluent Launders

Comparison Existing Versus Stamford BaffleComparison Existing Versus Stamford Baffle

10

12

14

g/L

)

Existing Clarifier (Normal Flow of2.5 MGD, SVI of 110 and RAS of33.3%)

Existing Clarifier (High Flow of 3 5

0

2

4

6

8

0 100 200 300 400 500

Integration Time (minute)

Eff

luen

t T

SS

(m

g Existing Clarifier (High Flow of 3.5MGD, SVI of 110 and RAS of33.3%)

Effluent Weir (Normal Flow of 2.5MGD, SVI of 110 and RAS of33.3%)

Effluent Weir (High Flow of 3.5MGD, SVI of 110 and RAS of33.3%)

184184

Inlet ComparisonInlet Comparison

ExistingExisting

Multilayer Energy Multilayer Energy Dissipating Inlet Colum Dissipating Inlet Colum (MEDIC)(MEDIC)

185185

3D Model (Zhou CFD)3D Model (Zhou CFD)

Developed by Siping Developed by Siping Zhou and J. A. Zhou and J. A. McCorquodaleMcCorquodale

ThreeThree--dimensional dimensional solution based onsolution based onsolution based on solution based on Control volume modelControl volume model Turbulent hydraulicsTurbulent hydraulics Generalized coordinatesGeneralized coordinates Solids settlingSolids settling Solids transportSolids transport No flocculation or No flocculation or

compression modelingcompression modeling

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ThreeThree--dimensional Modelingdimensional ModelingInlet Optimization + Higher RAS at SVI 126Inlet Optimization + Higher RAS at SVI 126

Existing InletExisting Inlet Optimized InletOptimized Inlet

MLSS = 3,250 mg/LOFR = 714 gpd/sfRAS = 100%

187187

ThreeThree--dimensional Modelingdimensional ModelingInlet Optimization at SVI 190Inlet Optimization at SVI 190



188188

ThreeThree--dimensional Modelingdimensional ModelingInlet Optimization at SVI = 110 mL/gInlet Optimization at SVI = 110 mL/g



189189

Upgraded Clarifier InletsUpgraded Clarifier Inlets

Estimated increase in Estimated increase in performance (lower performance (lower ESS) by 25%ESS) by 25%

Estimated increase in Estimated increase in capacity (higher flow capacity (higher flow at same SVI) by 40%at same SVI) by 40%

190190

CenterCenter--feed Circular Radial Flow Tankfeed Circular Radial Flow TankComparison of Tangential to Puzzled InletsComparison of Tangential to Puzzled Inlets

Denver Metro and Clark County (Las Vegas)Denver Metro and Clark County (Las Vegas)

Tangential InletTangential Inlet Puzzled InletPuzzled Inlet

191191

Comparison of Tangential to Puzzled InletsComparison of Tangential to Puzzled InletsInlet VelocitiesInlet Velocities


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Comparison of Tangential to Puzzled Inlets (3D Model)Comparison of Tangential to Puzzled Inlets (3D Model)Inlet Velocity IntensityInlet Velocity Intensity

Clark County (Las Vegas)Clark County (Las Vegas)


193193

Denver Metro Denver Metro Upgraded ClarifiersUpgraded Clarifiers

194194

Current Dallas Clarifiers had Current Dallas Clarifiers had Poor Inlet Energy Poor Inlet Energy DissapationDissapation

195195

Dallas Proposed Inlet Dallas Proposed Inlet Evaluated and ImprovedEvaluated and Improved

Proposed InletProposed Inlet Optimized InletOptimized Inlet

196196

Dallas Inlet EvaluationDallas Inlet Evaluation

Initial InletInitial Inlet Optimized InletOptimized Inlet

197197

Upgraded UnitsUpgraded Units

New Inlet InstalledNew Inlet Installed New Inlet in OperationNew Inlet in Operation

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Dallas Dallas -- Modified Inlet Improved Modified Inlet Improved PerformancePerformance

199199

Use of Capacity ToolsUse of Capacity Tools

By Randal Samstag and All



200200

Use of Capacity ToolsUse of Capacity ToolsState Point AnalysisState Point Analysis

201201

State Point AnalysisState Point AnalysisHistoryHistory

Based on theory by Coe and Clevenger Based on theory by Coe and Clevenger (1916) and subsequently advanced by (1916) and subsequently advanced by Dick (1967), Yoshioka (1957) and Dick (1967), Yoshioka (1957) and VesilindVesilind(1968)(1968)(1968)(1968)

First Proposed by First Proposed by McHargMcHarg (1973)(1973)

Systematically developed by Systematically developed by KeinathKeinath(1979)(1979)

More recent paper by Narayanan (2000)More recent paper by Narayanan (2000)

202202

Elements of State Point AnalysisElements of State Point AnalysisFlux LineFlux Line

Gx = XVoe-XMLSSk

203203

Elements of State Point AnalysisElements of State Point AnalysisOverflow Rate LineOverflow Rate Line

OFR = Gx / XMLSS

Slope = Q / A

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Elements of State Point AnalysisElements of State Point AnalysisMLSS LineMLSS Line

XMLSS

205205

Elements of State Point AnalysisElements of State Point AnalysisRAS LineRAS Line

RAS = -GR / XRAS

Slope = -QR / A

XRAS

206206

Interpreting SPAInterpreting SPAFlux FailureFlux Failure

207207

Interpreting SPAInterpreting SPARAS FailureRAS Failure

208208

State Point Analysis ExampleState Point Analysis Example

Parameter Value Parameter Value

Flow (mgd) 3.5 Type Rectangular

MLSS (mg/L) 3,250 Length (ft) 70

SVI (mg/L) 190 (Daigger)

Width (ft) 70

RASr (%) 33 Safety Factor 1.0

Vo (ft/hr) 21.3

k (L/g) 0.466

209209

State Point ExampleState Point Example33% Return Rate33% Return Rate

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State Point ExampleState Point Example100% Return Rate100% Return Rate

211211

Results of 3D ModelingResults of 3D ModelingHigh SVI ConditionHigh SVI Condition

Configuration OFR(gpd/sf)

SVI (mL/g)

MLSS (mg/L)

RASr(%)

ESS (mg/L)

Existing 714 190 3,250 33 >100

Existing 714 190 3,250 100 >1,000g , ,

Optimized 714 190 3,250 33 <10

Optimized 714 190 3,250 100 <10

212212

State Point ExampleState Point Example100% Return Rate w/ SF = 1.3100% Return Rate w/ SF = 1.3

213213

Inlet ConfigurationsInlet Configurations

ExistingExisting OptimizedOptimized

214214

State Point Analysis ExampleState Point Analysis ExampleIncrease Flow to 5 mgdIncrease Flow to 5 mgd

Parameter Value Parameter Value

Flow (mgd) 5.0 Type Rectangular

MLSS (mg/L) 3,250 Length (ft) 70

SVI (mg/L) 190 (Daigger)

Width (ft) 70

RASr (%) 100 Safety Factor 1.3

Vo (ft/hr) 21.3

k (L/g) 0.466

215215

State Point Example State Point Example –– 5 mgd5 mgd3,250 mg/L MLSS3,250 mg/L MLSS

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State Point Example State Point Example –– 5 mgd5 mgd1,500 mg/L MLSS1,500 mg/L MLSS

217217

ConclusionsConclusions

State Point Analysis is a valuable toolState Point Analysis is a valuable tool

But it needs to be used with a generous But it needs to be used with a generous safety factor in practice due to hydraulic safety factor in practice due to hydraulic inefficienciesinefficienciesinefficienciesinefficiencies

To adequately evaluate hydraulic To adequately evaluate hydraulic inefficiencies a two or three dimensional inefficiencies a two or three dimensional CFD model is requiredCFD model is required

218218

ClosureClosure

Ron Moeller, Kennedy JenksRon Moeller, Kennedy Jenks

219219

Clarifier Workshop Presentations - · PDF file9/18/2011 PNCWA Workshop Optimizing the...

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