Development of an Innovative Methodology
for Hydraulic Residence Time Distribution
Analysis – Virtual E-Curve Method
November 17, 2015
Don Lee, Ph.D., P.E.
Senior Wastewater Process Engineer
Project Manager
AECOM, Greenville SC
Tom Leland P.E.
Ovivo USA, Salt Lake City, UT
Steven A. Yeats, P.E.
Jones Edmunds & Associates, Gainesville FL
Ben Koopman, Ph.D.
University of Florida, Gainesville FL
Virtual E-Curve Method
OUTLINE
Introduction
Virtual E-Curve Method
Application to Full-Scale Tracer Study
Summary and Conclusions
OUTLINE
Introduction
Virtual E-Curve Method
Application to Full-Scale Tracer Study
Summary and Conclusions
Introduction: Mixing Performance Evaluation
Completely Stirred Tank Reactor
(CSTR) Conditions
Wastewater-mixed liquor contact
Mixed liquor suspension
Dead zone and short-circuiting
minimization
Assumption for most BNR modeling
(ASMs and simulation programs)
Ease of Reactor Characterization
Hydraulic Residence Time
Distribution (HRT) Analysis with
Tracer Study
Lee et al., Virtual E-Curve Method
4
HRT Analysis with influent interferences
Ideal CSTR
Q
C
Q
with slug load
tracer input
t
t
Two Ideal CSTRs in series with recirculation flow
QR
Q
Q
Q + QR
t ??
C
t
Lee et al., Virtual E-Curve Method
5
Live Oak WWTF Carrousel® denitIR® System, Live Oak, FL
Reclaimed Water
IR flow w/o influent
Aeration Basin
(0.834 MG)
Anoxic Basin
(0.34 MG)
Aerators
Influent (Q)
Mixer
RAS (QR=Q)
denitIR® Gate
Mixed
Liquor to
Clarifier
(QR+Q=2Q)
Internal Recirculation
Combined
Influent 5Q
(Q
IR = 3Q)
IR
Anoxic
Basin
RAS
Lee et al., Virtual E-Curve Method
MLE Process
INF
6
Aeration
Basin
EFF
Clarifier
WAS
OUTLINE
Introduction
Virtual E-Curve Method
Application to Full-Scale Tracer Study
Summary and Conclusions
Virtual E-Curve Method
(adapted from “Virtual Batch Curve” of Lee et al., 2008)
Q
t ??
C
Q
V1 C1
dC1,12
dt
C1,12
t
V2 C2
C
Q
Q
 C 2  C1
V
V

C1, 2  C1,1
C1,12Virtual
t
t 2  t1

C1, 2V  C1,1 
C1, 23Virtual
t
t
t


C1,12
t
dC1,12

Q
C 2,1
V
C1,12Virtual
t
C1, 23
C1,3V  C1, 2V 
t
 t
 t
Lee et al., Virtual E-Curve Method
t
Re-integrate a virtual C-curve
using adjusted rates of changes
as if there were NO influent interferences.
 Q / V (C1, 2  C1, 2V )  Q / V (C 2, 2 )
C1, 23Virtual
t
t
dt
8
Virtual E-Curve Method: applied to theoretical
reactor behaviors simulated with programming
1
Tracer concentration in an influenced CSTR
0.8
Tracer concentration in the influent
0.6
C
0.4
0.2
1.4
0
0
1
2
Time (hours)
3
4
E Curve of non-influenced CSTR
1.2
1
E Curve of influenced CSTR from Virtual
E-Curve Method
E
0.8
0.6
0.4
0.2
0
0
Lee et al., Virtual E-Curve Method
2
4
6
Time (hours)
9
8
10
Verification of Virtual E-Curve Method
Q
Q + QR
1.4
t ??
C
1.2
Q
E Curve of non-influenced CSTR
1
0.8
E Curve of influenced CSTR from Virtual
E-Curve Method
E
t
0.6
0.4
0.2
Sensitivity analyses:
0
0
2
4
6
8
10
Initial (theoretical) vs actual volume
Time (hours)
Numerical methods
Integration step-size
Sampling intervals
Tested various types of influent
interferences with additional simulations:
Recycle flows
Continuous or Sudden influent
concentration changes
Varying influent flowrate
Lee et al., Virtual E-Curve Method
10
OUTLINE
Introduction
Virtual E-Curve Method
Application to Full-Scale Tracer Study
Summary and Conclusions
Full Scale Tracer Study
EFF
Sampling
Aeration Basin
(0.834 MG)
EFF
Anoxic Basin
(0.34 MG)
Aerators
Mixer
INF
INF
Sampling
Slug Load
Tracer Input
Lee et al., Virtual E-Curve Method
12
Sampling and Onsite Measurement
Lee et al., Virtual E-Curve Method
13
Full Scale Test Results
EFF
Anoxic Basin
(0.34 MG)
with a Mixer
Aerators
Aeration Basin
(0.834 MG)
INF
Slug Load
Tracer Input
t ??
C
Q
Q
Q
t
Lee et al., Virtual E-Curve Method
14
Full Scale Test Results
300
Anoxic
Anoxic
Anoxic
Anoxic
Rhodamine WT (ppb)
250
200
Basin Influent (theoretical)
Basin Effluent (theoretical)
Basin Influent (test result)
Basin Effluent (test result)
150
100
50
0
0.0
0.5
1.0
Lee et al., Virtual E-Curve Method
1.5
2.0
Time (hours)
15
2.5
3.0
3.5
4.0
Application of Virtual E-Curve Method to Test Results
4
3.5
E Curve from Ideal CSTR
3
E Curve from Virtual E-Curve Method
E
2.5
2
44 min average (115% theoretical HRT)
1.5
2.5 CSTRs in series – NOT an ideal CSTR
1
0.5
0
0.0
0.5
1.0
Lee et al., Virtual E-Curve Method
1.5
2.0
Time (hours)
16
2.5
3.0
3.5
4.0
Virtual E-Curve Method
Error Estimations with Uniform Tanks-in-Series
Modeling
% Error of Virtual E-Curve Method
60
50
250% Anoxic Volume
40
100% Anoxic Volume
80% Anoxic Volume
30% Anoxic Volume
30
20
10
0
0
5
10
15
Number of Ideal CSTR in Series
Lee et al., Virtual E-Curve Method
17
20
25
Virtual E-Curve Method
Error Adjustment with Non-Uniform Tanks-in-Series Modeling
Outlet
Slowly Mixed Zone
(12.5-25%)
Outlet PFR –
tanks in series
(25%)
Center
Rapidly Mixed
Zone (50-75%)
Center CSTR (50%)
Inlet PFR
tanks in series
(25%)
Tracer
Injection
Location
Inlet
Slowly Mixed Zone
(12.5-25%)
Lee et al., Virtual E-Curve Method
18
Virtual E-Curve Method
Error Adjustment with Non-Uniform Tanks-in-Series Modeling
4
3.5
E Curve from Ideal CSTR
3
E Curve from Virtual E-Curve Method
E
2.5
E Curve from Non-Uniform
Tanks-in-Series Modeling
2
1.5
Percent Error = 23%
1
0.5
0
0.0
0.5
1.0
1.5
2.0
Time (hours)
2.5
3.0
3.5
4.0
91% theoretical HRT (reactor volume utilization)
Lee et al., Virtual E-Curve Method
19
OUTLINE
Introduction
Virtual E-Curve Method
Application to Full-Scale Tracer Study
Summary and Conclusions
Summary and Conclusions
Virtual E-Curve method allows hydraulic residence time distribution
analysis of ideal CSTRs with influent interferences.
Integration methodologies, step-sizes and sampling intervals affect the
accuracy of Virtual E-Curve method.
Errors associated with non-ideal reactor behaviors could be adjusted using
advanced reactor modeling.
Lee et al., Virtual E-Curve Method
21
Questions?
Don Lee, Ph.D., P.E.
Senior Wastewater Process Engineer/Project Manager
AECOM, Greenville SC
864-234-3583
don.lee02@aecom.com
Virtual E-Curve Method