Upload
amira-gogoanta
View
8
Download
1
Tags:
Embed Size (px)
DESCRIPTION
modelling three-phase
Citation preview
eo
ering, P
diment
ctivated sludge in an
ss models, reasonable
gen, chemical oxygen
inematics of sludge
2014 Elsevier Ltd. All rights reserved.
maintenance costs, high and flexible capacity, and low sludge
production (Hong et al., 2003). More than 10,000 oxidation
ditches are to be found in China and the USA alone. However,
land, consume sub-
osits of sludge (Yang
eing undertaken tomand and Carlsson,
reduce energy con-
sumption (see e.g. Zhou et al., 2012).
Mathematical models offer an effective means of simu-
lating the physical, chemical and biological processes in ODs
* Corresponding author. Department of Environmental Engineering, Peking University, Beijing 100871, China. Tel.: 86 10 62751185; fax:86 10 62756526.
E-mail address: [email protected] (J. Ni).
Available online at www.sciencedirect.com
ScienceDirect
.e ls
wat e r r e s e a r c h 5 3 ( 2 0 1 4 ) 2 0 0e2 1 41. Introduction
Oxidation ditches (ODs) are widely used in wastewater treat-
ment due to their simple construction, low capital and
oxidation ditches occupy large areas of
stantial energy, and produce uneven dep
et al., 2011). Much work is presently b
optimize the treatment process (see e.g. A
2012), to improve sludge deposition andPseudo-solid phase
Sedimentation
Mass transfer
Biochemical kinetics
Oxidation ditch
satisfactory agreement with laboratory data on the behavior of a
oxidation ditch. By coupling species transport and biological proce
predictions are made of: (1) the biochemical kinetics of dissolved oxy
demand (COD) and nitrogen variation, and (2) the physical k
sedimentation.Three-dimensional three-phase
model
sludge viscosity, sludge density, oxygen mass transfer rate, and carbon substrate uptake
due to adsorption onto the activated sludge. The validation test results were in veryLi Lei a,b, Jinren Ni a,b,*aDepartment of Environmental EnginebThe Key Laboratory of Water and Se
China
a r t i c l e i n f o
Article history:
Received 7 June 2013
Received in revised form
6 October 2013
Accepted 15 January 2014
Available online 23 January 2014
Keywords:0043-1354/$ e see front matter 2014 Elsevhttp://dx.doi.org/10.1016/j.watres.2014.01.021eking University, Beijing 100871, China
Sciences, Ministry of Education, Peking University, Beijing 100871,
a b s t r a c t
A three-dimensional three-phase fluid model, supplemented by laboratory data, was
developed to simulate the hydrodynamics, oxygen mass transfer, carbon oxidation, nitri-
fication and denitrification processes in an oxidation ditch. The model provided detailed
phase information on the liquid flow field, gas hold-up distribution and sludge sedimen-
tation. The three-phase model described water-gas, water-sludge and gasesludge in-
teractions. Activated sludge was taken to be in a pseudo-solid phase, comprising an
initially separated solid phase that was transported and later underwent biological re-
actions with the surrounding liquidmedia. Floc parameters were modified to improve thedenitrification in oxidation ditchan
transfer, carbon oxidation, nitrification andThree-dimensional three-phassimulation of hydrodynamics,
journal homepage: wwwier Ltd. All rights reservemodel forxygen mass
evier .com/locate /watresd.
wat e r r e s e a r c h 5 3 ( 2 0 1 4 ) 2 0 0e2 1 4 201Nomenclature
aj,i stoichiometric number of species i in the j-th
process, dimensionless1which experience complicated alternating aerobic and anoxic
conditions for nitrification and denitrification. For example,
the Activated Sludge Model (ASM) predicts the effluent water
quality and biomass production of wastewater treatment
plants (Henze et al., 2000). In ODs, the wastewater treatment
efficiency is influenced not only by the bio-reaction of acti-
vated sludge, but also by the dynamics of liquid-bubble flows
bA decay coefficient for XB,A, d
bH decay coefficient for XB,H, d1
Cs wall roughness constant, dimensionless
dG bubble diameter, m
DL diffusivity of oxygen in the liquid phase, m2 s1
dO diameter of aeration orifice, m
F!
lift; q lift force, kg m2 s2
fP fraction of biomass leading to particulate
products, dimensionless
F!
q external body force, kg m2 s2
F!
vm; q virtual mass force, kg m2 s2
g! gravitational acceleration, m s2hKs wall roughness height, m
iXB mass of nitrogen per mass of COD in biomass,
g g1
iXP mass of nitrogen per mass of COD in products
from biomass, g g1
J!
q; i diffusion flux of species i in phase q, kg m2 s1
ka ammonification rate, m3 g1 d1
kh maximum specific hydrolysis rate, d1
KLaL mass transfer coefficient, s1
KNH ammonia half-saturation coefficient for XB,A,
g m3
KNO nitrate half-saturation coefficient for XB,H, g m3
KO,A oxygen half-saturation coefficient for XB,A, g m3
KO,H oxygen half-saturation coefficient for XB,H, g m3
KS half-saturation coefficient for XB,H, g m3
KX half-saturation coefficient for hydrolysis of slowly
biodegradable substrate, g g1
mpq mass transfer from phase p to q, kg m3 s1
O2 oxygen concentration in air, g m3
OF normalized standard error, dimensionless
p pressure, N m2
Q flow rate, m3 s1
R!
pq interaction force between phase p and q,
kg m2 s2
Rq, i source term representing mass transfer of species
i from other phases to phase q, and the
production/consumption rate of the species i for
biochemical reactions, kg m3 s1
S soluble constituent concentration, g m3
SI soluble inert pollution concentration, g m3
SND soluble organic nitrogen concentration, g m3
SNH ammonium concentration, g m3
SNO nitrate and nitrite concentration, g m3
SO oxygen concentration in liquid, g m3SO(S) saturated dissolved oxygen, g m3
Sq source term of phase q, kg m3 s1
SRT sludge age, d
SS soluble biodegradable pollution concentration,(Insel et al., 2005). Carbon oxidation process was firstly
coupled in one-dimensional (1D) convectionedispersion
equation by Stamou (1994), followed by coupling more pro-
cesses such as nitrification and denitrification (Stamou, 1997;
Stamou et al., 1999; Mantziaras et al., 2011) to reveal the ef-
fects of local hydrodynamics on water quality in ODs. For
more detailed understanding of the effects of hydrodynamics,
g m3
Uslip slip velocity between a gas bubble and water,
m s1
v!pq interphase velocity from phase p to q phase, m s1v!q velocity vector of phase q, m s1X particulate component concentration, g m3
XB,A autotrophic biomass, g m3
XB,H heterotrophic biomass, g m3
xci calculated result of the i-th parameter
XI particulate inert pollution concentration, g m3
xmi measured result of the i-th parameter
XND particulate organic nitrogen concentration, g m3
XP inert biomass, g m3
XS particulate biodegradable pollution
concentration, g m3
YA yield for XB,A, g g1
YH yield for XB,H, g g1
Yq, i mass fraction of species i in phase q,
dimensionless
Greek letters
a modification coefficient for SO(S), dimensionless
adG modification coefficient for dG, dimensionless
aq volume fraction of phase q, dimensionless
b modification coefficient for KLaL, dimensionless
g modification coefficient for KLaL, dimensionless
3 dissipation rate of turbulent kinetic energy, m2 s3
hg correction factor for mH under anoxic conditions,
dimensionless
hh correction factor for hydrolysis under anoxic
conditions, dimensionless
mA maximum specific growth rate for XB,A, d1
mH maximum specific growth rate for XB,H, d1
mq shear viscosity of phase q, kg m1 s1
rj process rate of the j-th bioreaction, kg m3 s1
rq density of phase q, kg m3
s surface tension, kg s2
sq stress-strain tensor of phase q, kg m1 s2
Subscripts
G gas phase
in inflow
L liquid phase
out outflow
rec recirculation flow
S pseudo-solid phase
two-dimensional (2D) or three-dimensional (3D) models
would be preferred (Yang et al., 2011). Littleton et al. (2007)
introduced the Activated Sludge Model No. 2 (ASM2) to a 3D
fluid dynamicsmodel for elucidating the role of the bioreactor
macro-environment in simultaneous biological nutrient
removal. Other investigators also attempted to describe the
complex phenomena in OD (Zhang et al., 2010). On the other
hand, effects of hydrodynamics would be reflected bymatters
in different phases. However, most previous models have
been limited to one or two phases, although multiple-phase
phenomena and processes have been observed (e.g. Pipes,
1969; Schmid et al., 2003; Fayolle et al., 2007) in ODs.
Understanding of coupled physicalechemicalebiological
processes relies on accurate assessment of the transport
processes and phase interactions. There are three basic pha-
ses of the primary medias needed to be fully considered in
ODs. First, oxygen must be supplied in order to maintain the
level of dissolved oxygen (DO) during the aerobic process and
so directly affects the effluent water quality (Fayolle et al.,
2007), which implies the model that does not take gas phase
od
T d
cs;
wat e r r e s e a r c h 5 3 ( 2 0 1 4 ) 2 0 0e2 1 4202Fig. 1 e Framework of the three-dimensional three-phase m
heterotrophs; AGA denotes aerobic growth of autotrophs; OM
of heterotrophs; HEO denotes hydrolysis of entrapped organiHEON denotes hydrolysis of entrapped organics nitrogen; DH d
autotrophs).el for an oxidation ditch (AGH denotes aerobic growth of
enotes oxygenmass transfer; ANGH denotes anoxic growth
ASON denotes ammonification of soluble organic nitrogen;enotes decay of heterotrophs; DA denotes decay of
into consideration cannot reasonably simulate the oxygen
mass transfer between gas and sewage water. Second, acti-
vated sludge comprises a strongly hydrated solid phase, and
has different physical properties to those of pure water
(Schmid et al., 2003). Furthermore, sludge settling can lead to
septic sludge formation at the dead angle in OD, with associ-
ated odor (Pipes, 1969). The complicated phase interactions
and transformations in an OD system include transfer of
dissolved oxygen from the gas phase, and carbon oxidation,
nitrification and denitrification in the liquid and solid phases.
In this paper, a 3D three-phase model was developed by
between the phases is outlined. Coupled gas transport and
modified oxygen mass transfer models simulate the DO dis-
liquid, and is termed a pseudo-phase. To approximate the
pseudo-phase behavior in the model, the activated sludge is
first represented as in a separated solid phase regarding
transport and sedimentation processes, and later as in a sol-
ideliquid phase after biological changes have taken place (see
Fig. 2). The 3D three-phase model quantifies the phase-
dependent behavior of the sewage, activated sludge, and
gas, and their complicated interactions in an OD (Fig. 1). To
permit analogy between the behavior of activated sludge and
that of granular particles, the model parameters require
adjustment to account for differences between floc sludgeand
granular sludge. Floc sludge has much higher water content,
mass and momentum conservation laws. The model as-
sumptions are as follows:
wat e r r e s e a r c h 5 3 ( 2 0 1 4 ) 2 0 0e2 1 4 203tribution. Coupled species-transport and modified biological
kinetic models simulate the sludge distribution and pollutant
degradation, and include the biochemical kinetics of chemical
oxygen demand (COD) and nitrogen removal in an OD. More
specifically, the 3D and three-phase model is able to simul-
taneously describe the 3D transport of sewage water (e.g.
secondary flow, see Yang et al., 2011), bubbles and activated
sludge (settling process), in addition to the phase interactions
and the sedimentation processes related to the activated
sludge. During calibration, the input parameters are deter-
mined by iteration for target values of sludge viscosity,
settling capacity, oxygen mass transfer rate, and carbon sub-
strate uptake due to adsorption onto the pseudo-solid phase.
The sludge transport process and the effect of inclusion of the
pseudo-solid phase on mass transfer and pollutant trans-
formation are investigated through simulations of variations
in concentration of activated sludge, DO, COD, ammonia ni-
trogen and nitrate in a pilot-scale OD.
2. Methodology
2.1. Model development
A hydrated activated sludge floc is essentially a gelatinous,
coagulated material whose phase lies between solid andtaking the sewage water, air bubbles and activated sludge to
be in liquid, gas and pseudo-solid phases, respectively. The
proposed model could not only vividly describe local hydro-
dynamic structures with 3D fluid velocities but also reason-
ably simulate the interactions of sewage water, air bubbles
and activated sludge treated as pseudo-solid phase. Fig. 1
shows the proposed framework in which the relationshipFig. 2 e Dual roles of the(1) sewage water, activated sludge, and air are in liquid,
pseudo-solid, and gas phase, respectively;
(2) pollutants are divided into soluble and particulate
components regarded as species of liquid and pseudo-
solid phases, respectively;
(3) heterotrophic and autotrophic biomass are species in
the pseudo-solid phase;
(4) DO is a species in the liquid phase;
(5) oxygen mass transfer is a biological rather than a
physical process;
(6) accumulation of biomass with ammonia may be
neglected;
(7) alkalinity is not a limiting parameter;
(8) no biological reaction occurs in the secondary settling
tank.
2.1.1. Multiphase hydrodynamics modelA standard 3D steady-statemulti-phase flowmodel, described
in detail by Fluent Corporation (2006), is used to describe the
complicated hydrodynamic behavior of the sewage water,
activated sludge, and gas transportation behavior in an OD.
The steady-state equilibrium mass conservation equation is
given by:contains extracellular polymeric substances, and has a
negatively-charged surface, whereas granular sludge is more
permeable (Wang et al., 2012). To describe the transport and
evolution of the pollutants and biomass, an advection-
diffusion species transport model is coupled with the modi-
fied oxygen mass transfer model and modified biological ki-
netic process models. The governing equations are based onpseudo-solid phase.
ical
ore
iXBS
1YA
iX
fPX
fPX
wat e r r e s e a r c h 5 3 ( 2 0 1 4 ) 2 0 0e2 1 4204transport and growth/decay of activated biomass and con-
taminants in the ditch:V$aqrq v
!q
X3p1
mpq mqp
Sq (1)where aq is the volume fraction, rq is density, v
!q is velocity
vector, Sq is the source term, p and q are the different phases,
and mpq characterizes the mass transfer from phase p to q.
Subscripts q W, G and S denote water, gas and active sludge,respectively. The steady-state equilibrium momentum equa-
tion is:
V$aqrq v
!q v!
q
aqVp V$sq aqrq g!
Xnp1
R!
pqmpq v!
pq
mqp v!qp
Fq! F!lift; q F!vm; q (2)
where p is the pressure shared by all phases, g! is gravitationalacceleration, R
!pq is the interaction force between phases, v
!pq
is the inter-phase velocity from phase p to q, mpq v!
pq mqp v!qpdenotes themomentum change due tomass transfer between
the p-th and the q-th phases, F!
q is an external body force,
F!
lift;q is a lift force, F!
vm;q is a virtual mass force and sq is the
stress-strain tensor for the q-th phase. The multi-phase flow
model is closed using a steady-state k- 3turbulencemodel (see
e.g. Fluent Corporation, 2006).
2.1.2. Species transport modelThe following 3D steady-state advection-dispersion species
transport equation with source term is used to describe the
Table 1 e Quantifications of the major chemical and biolog
No. Process Bi
1 Aerobic growth of heterotrophs 1YHSS 1YHYH SO
2 Aerobic growth of autotrophs 4:57YAYA
SO iXB
3 Oxygen mass transfer O2/SO4 Anoxic growth of heterotrophs 1
YHSS 1YH2:86YH SNO
5 Hydrolysis of particulate organics XS/SS6 Ammonification SND/SNH7 Hydrolysis of particulate organics nitrogen XND/SND8 Decay of heterotrophs XB, H/(1fP)XS9 Decay of autotrophs XB, A/(1fP)XSV$aqrq v
!qYq; i
V$aq J!q; i Rq; i (3)
where Yq,i is the mass fraction of species i in phase q, Rq, i is a
source term representingmass transfer of species i from other
phases to phase q, and the production/consumption rate of
the species i for biochemical reactions, J!
q; i is the diffusion
flux of species i in phase q.
2.1.3. Biochemical kinetics modelThe source term Rq, i in Equation (3) is given by the modified
Activated Sludge Model No.1 (ASM1) (Henze et al., 2000).
Biochemical processes, such as carbon oxidation, nitrification
and denitrification, are described by considering thirteen
components (Fig. 1). Autotrophic, heterotrophic and inert
biomass is regarded as particulate matter. Fig. 1 and Table 1
summarize the detailed biological interactions among thethree phases and corresponding kinetic processes. The source
term Rq, i is expressed by
Rq; i X9j1
aj; irj
(4)
where j is the number of the process in Table 1, aj,i is the
stoichiometric number of species i in the j-th process, and rj is
the process rate. In Equation (4), if species i is produced, istaken positive; whereas if species i is consumed, is takennegative.
Carbon substrate removal from storage always occurs in an
activated sludge system, because activated sludge is in the
separated phase (Carucci et al., 2001). COD then accumulates
in sludge (Beccari et al., 2002), leading to the heterotrophs
having a competitive growth advantage (Cggn et al., 2011).
Hence, certain stoichiometric and kinetic parameters (such as
mH, YH, KS and bH) are modified herein, given that activated
sludge is treated as in the separated pseudo-solid phase. Table
2 lists the proposed parameters used by ASM1 and the modi-
fied input parameters used in the present work.
2.1.4. Oxygen mass transfer modelThe oxygen mass transfer rate r3 (see Table 1) from the gas to
the liquid phase is determined by Kulkarni (2007)
r3 KLaL wastewateraSOS SO
(5)
in which KLaL wasterwater is the mass transfer coefficient, SO(S) is
saturated DO concentration in clean water, SO is oxygen con-
centration in the liquid phase, and a expresses the propor-
processes.
action Process rate
NH/XB; H r1 mH SSKSSSSO
KO; HSO XB; HSNH/XB; A 1YA SNO r2 mA
SNHKNHSNH
SOKO; ASO XB; A
r3(KLaL)wastewater(aSO(S)SO)BSNH/XB; H r4 mH SSKSSS
KO; HKO; HSO
SNOKNOSNO hgXB; H
r5 kh XS=XB; HKXXS=XB; Hh
SOKO; HSO hh
KO; HKO; HSO
SNOKNOSNO
iXB; H
r6kaSNDXB, Hr7 r5XND=XS
P(iXBfPi)XPXND r8 bHXB,HP(iXBfPi)XPXND r9 bAXB,Ationality between saturated DO in wastewater and its clean
water value. For bottom aeration, the oxygen mass transfer
coefficient for sewage water is expressed as:
KLaL wastewater gb12aGdG
DLUslippdG
s(6)
where g is introduced to consider the pseudo solid-effect, b is
the ratio of wastewater to clean water mass transfer co-
efficients, aG is the volume fraction occupied by the gas phase,
dG is the Sauter mean diameter of the bubbles, DL is diffusivity
of oxygen in the liquid phase, and Uslip is the slip velocity
between a gas bubble and water, and can be estimated by
evaluating jvL-vGj. For surface aeration, the oxygen masstransfer correlates directly with the dissipation rate of energy
(Kumar and Rao, 2009) such that
Table 2 e Summary of parameters used in modeling of biological processes.
Parameter Unit ASM1 Su and Yu (2006) Present
Stoichiometric YA g(COD) g(COD)1 0.24 0.24 0.24
YH g(COD) g(COD)1 0.67 0.58 0.63e0.67
fP Dimensionless 0.08 0.08 0.08
iXB g(N) g(COD)1 0.086 0.086 0.086
iXP g(N) g(COD)1 0.06 0.06 0.06
Kinetic mH d1 6.00 4.98 5.50e6.00
KS g(COD) m3 20.0 26.1 20.0e23.0
KO,H g(O2) m3 0.20 0.20 0.20
KNO g(N) m3 0.50 0.50 0.50
bH d1 0.62 0.92 0.62e0.77
hg Dimensionless 0.8 0.8 0.8
hh Dimensionless 0.40 0.44 0.44
kh d1 3.0 3.0 3.0
KX g(COD) g(COD)1 0.03 0.03 0.03
mA d1 0.80 0.80 0.80
KNH g(N) m3 1.0 1.0 1.0
KO,A g(O2) m3 0.4 0.4 0.4
ka m3 g(COD)1 d1 0.08 0.08 0.08
bA d1 0.15 0.15 0.15
wat e r r e s e a r c h 5 3 ( 2 0 1 4 ) 2 0 0e2 1 4 205equations governing the interaction force R!
pq are listed byKLaL3
p 0:64 exp0:29 30:98 1:6 106 exph0:72 3 3:912:0i(7)
where 3is the dissipation rate of the turbulent kinetic energy.
Hence, the oxygenmass transfers due to the surface impellers
and bottom aeration system can be evaluated by using Equa-
tions (5)e(7).
2.2. Phase interaction
2.2.1. Liquidegas interactionAir bubbles introduced into OD experience a drag force due to
the different velocities in the liquid and gas phases. The
Fluent Corporation (2006). Liquid-gas interaction directly in-fluences both physical and mass transfer processes, with the
Fig. 3 e Plan view sketch of the pilot-scale oxidation ditch (aeffect of the latter incorporated via the source term in Equa-
tion (3).
2.2.2. Liquid-solid interactionThe density of activated sludge density ranges from 1010 to
1060 kg/m3 (Dammel and Schroeder, 1991), and so sludge
settling always occurs. Flow turbulence influences sludge
settling, resulting in intensive interaction between sewage
water and activated sludge floc. The interaction force R!
pq
between pseudo-solid and liquid phases is also described
using interaction equations listed by Fluent Corporation
(2006).
In activated sludge systems, intensive interaction occurs
between different species in the sewage and activated sludge.
To sustain growth, heterotrophs and autotrophs biomassutilize ammonium and nitrate species in sewage (Table 1).
) and monitoring points of liquid velocity (b) (Unit: mm).
Meanwhile, heterotrophs and autotrophs decompose to par-
ticulate biodegradable organic nitrogen and slowly biode-
gradable substrate, which are further hydrolyzed respectively
to soluble biodegradable organic nitrogen and readily biode-
particulate components Xi in Table 1) is initially also pre-
scribed. At steady state, when the internal condition of the OD
is balanced after sludge return, Xin is assumed to be the same
as the sludge concentration at the outlet (Xout) provided the
average sludge concentration (Xaverage) in OD is less than a
pre-set value (Xset). For Xaverage > Xset, the surplus sludge
(Xsurplus) is removed from the OD by pumping in order to
maintain the sludge concentration at a desired level. Full de-
tails about the surplus sludge pumping model and the inlet
sludge concentration condition are given by Stamou (1997).
The recirculation flow recycles water to the inlet. If Sin and Srecdenote the soluble constituents (e.g. ammonium and nitrate)
of wastewater and recirculation flow, the inlet value of the
soluble constituent variable is:
S QinSin QrecSrec=Qin Qrec (8)
where Qout is the outflow rate, Qin is the inflow rate, and Qrec is
Table 3 e Operation modes of impellers and stirrers.
Movingpart
Case I Case II
Speed (rpm) Direction Speed (rpm) Direction
Impeller 1 80 a 40 Impeller 2 80 40 Stirrer 1 90 b 70 eStirrer 2 90 70 Stirrer 3 90 70 Stirrer 4 70 50 a rotation in clockwise direction.b - rotation in anticlockwise direction.
ria
O
wat e r r e s e a r c h 5 3 ( 2 0 1 4 ) 2 0 0e2 1 4206activated sludge floc has properties different from pure water,
it is better to treat the floc as in a separated pseudo-solid
phase, with oxygen mass transfer between gas and liquid
phases modified accordingly in terms of solid concentration
(Mena et al., 2011). For this purpose, the parameter g is
introduced in Equation (6).
2.3. Boundary conditions
For the OD (Fig. 3), open boundary conditions are applied at
the influent inlet and effluent outlet. The walls are treated as
fixed, impermeable boundaries. At the inlet, the velocity is
prescribed (according to the inflow rate), and the inlet sludge
concentration (Xin, the sum of the concentrations of all
Table 4 e Experimental conditions and range of primary va
Variablesgradable substrate. The present model describes the in-
teractions between species in liquid and pseudo-solid phases,
unlike traditional models that neglect the pseudo-solid
phase.
2.2.3. Gasesolid interactionMany models, such as ASM-series models, consider activated
sludge to be perfectly soluble in the liquid phase. Given that anRotation mod
Model Calibration Liquid velocity Case I
MLSS Case I
DO Case I
COD Case I
Ammonium Case I
Nitrate Case I
Model Verification Liquid velocity Case II
MLSS Case II
DO Case II
COD Case II
Ammonium Case II
Nitrate Case IIthe recirculation flow rate. The wastewater constituents are
determined from experiments, following Henze et al. (2000).
At the OD outlet, the boundary pressure is atmospheric.
For bottom aeration, the introduction of gas can be treated
as source term in the Equations (1)e(3), and the oxygen con-
centration in the pumped air is evaluated using an equation
provided by Fayolle et al. (2007). Surface aeration refers to
rotation of the impellers which aerated the water in their vi-
cinity. The oxygen mass transfer rate due to surface aeration
is obtained by solving Equations (5) and (7).
A rigid-lid, slip wall boundary condition (see e.g. Yang
et al., 2011) is applied to the liquid and pseudo-solid phases
at the water surface. Injected air from bottom aeration es-
capes the OD at the gaseliquid surface, and so a degasification
condition (Le Moullec et al., 2011) is applied to the gas phase at
the water surface.
No-slip boundary conditions are assigned for all other
walls, including the bottom surface, the side and central walls
of the ditch. The roughness constant and the roughness
height at the no-slip boundaries are calibrated to the
measured data, using the Fluent values of 1 and 0.02 m,
respectively following Yang et al. (2011).
bles for model calibration and verification.
peration conditions Range of variables
e Aeration rate (m3/h)
2.2 ux: 0.000e0.155 m/s
uy: 0.000e0.044 m/s
uz: 0.000e0.116 m/s
2.2 3.80e4.16 g/L
2.2 0.32e1.66 mg/L
2.2 12.8e14.0 mg/L
2.2 0.33e0.90 mg/L
2.2 16.6e17.5 mg/L
2.2 ux: 0.000e0.132 m/s
uy: 0.000e0.031 m/s
uz: 0.000e0.101 m/s
2.2 3.42e4.55 g/L
2.2 0.28e1.07 mg/L
2.2 14.7e15.8 mg/L2.2 3.04e3.91 mg/L
2.2 11.78e14.01 mg/L
wat e r r e s e a r c h 5 3 ( 2 0 1 4 ) 2 0 0e2 1 4 207Table 5 e Description of the parameters used in themodel.
Parameter Notation Unit Value
Sewage water density rL kg/m3 1000
Sewage water viscosity mL kg/m/s 0.0010
Dissolved oxygen of
synthetic wastewater
SO mg/L 0.20
Soluble inert organic SI mg/L 10.0The multiphase flow in OD is agitated by the moving parts
such as rotating blades, disc aerators and submerged impellers.
Here, the rotation of the rotating blades and disc aerators is
simulated by a moving wall model and the submerged impeller
describedbya fanmodel.For furtherdetails seeYangetal. (2011).
2.4. Parameter estimation
Activated sludge flocs are considered to be in a pseudo-solid
phase, whose density ranges from 1010 to 1060 g/mL
maximum specific storage rate and size of floc-like sludge
particles are both less than for granular sludge, and their
substrate of synthetic
wastewater
Readily biodegradable
substrate
synthetic wastewater
SS mg/L 80.0
Particulate inert organic of
synthetic wastewater
XI mg/L 0.0
Slowly biodegradable
substrate of synthetic
wastewater
XS mg/L 160.0
Nitrate and nitrite
of synthetic wastewater
SNO mg/L 0.0
Ammonium of synthetic
wastewater
SNH mg/L 50.0
Soluble biodegradable
organic nitrogen of
synthetic
wastewater
SND mg/L 0.0
Particulate biodegradable
organic nitrogen of
synthetic wastewater
XND mg/L 0.0
Sludge floc density rs kg/m3 1010
Sludge floc viscosity ms kg/m/s 0.0046
Sludge floc diameter ds mm 0.40
Pre-set average sludge
concentration
Xset g/L 3.8
Sludge age SRT d 25
Air density rG kg/m3 1.225
Air viscosity mG kg/m/s 1.8 105Air bubble diameter dG mm 2.60
Air bubble diameter
modification coefficient
adG Dimensionless 0.58
Wall roughness constant Cs Dimensionless 1
Wall roughness height hKs m 0.02
Modification coefficient a a Dimensionless 0.92
Modification coefficient b b Dimensionless 0.44
Modification coefficient g g Dimensionless 0.75
Yield for heterotrophic
biomass
YH g/g 0.64
Maximum specific growth
rate for heterotrophic
biomass
mH 1/d 5.80
Half-saturation coefficient
for heterotrophic
biomass
KS g/m3 22.0
Decay coefficient for
heterotrophic biomass
bH 1/d 0.70physical properties (e.g. moisture content and negative sur-
face charge) are also different (Grijspeerdt and Verstraete,
1997; Liu et al., 2005; Wang et al., 2012). In general, the pa-
rameters in the present model lie between those of ASM1 and
the granular sludge system (Su and Yu, 2006).
3. Experimental measurements in pilot-scale oxidation ditch
Fig. 3 depicts a plan view of the pilot-scale carrousel-type
oxidation ditch. The ditch was fabricated from plexiglass, and
comprised four straight 1.15 m lengths of channel each with
semi-circular end channels, the smaller semi-circles having
radius 0.35 m, the larger semi-circles having radius 0.7 m. The
total working volume was 1.4 m3. The channels had rectan-
gular cross-section of width 0.35 m and still depth 0.5 m. Two
surface impellers (Impeller 1 and Impeller 2) and four sub-
merged stirrers (Stirrer 1, Stirrer 2, Stirrer 3 and Stirrer 4)
located in the curved channels drove the recirculating flow in
the oxidation ditch. Each spindle-like impeller consisted of 18
steel strips; each stirrer comprised an S-shape blade of
diameter 0.2 m Table 3 lists the operating rotational speeds
and angular directions of the impellers and stirrers for the
calibration Case I and validation Case II. Air was introduced
from a series of 1 m long gas distributors located at the base of
the second and third channels, and also from the surface
entrainment effect of the impellers. Each orifice of the gas
distributorswas of diameter 0.1mm. The overall aeration rate,
controlled by a rotameter, was 2.2 m3/h. Synthetic waste-
water, originally stored in a tank of volume 1.8 m3, was(Dammel and Schroeder, 1991) and dynamic viscosity ranges
from 3.8 to 11.0 mPa S (Jin et al., 2004), andmean floc diameter
from 0.05 to 0.5 mm (Grijspeerdt and Verstraete, 1997).
The interaction force between the gas and liquid phases is
closely related to the bubble diameter, and is given by:
dG 2:9adGsdogrL
1=3(9)
where do is diameter of the aeration orifice, s is surface tension
of liquid phase, g is the acceleration due to gravity, rL is den-
sity of the liquid phase, and adG is a coefficient allowing for the
aeration orifice configuration and the presence of pseudo-
solid phase.
The mass transfer rate corresponding to the pseudo solid-
phase is greatly dependent on the coefficients a[0.92,1.0](Stenstrom and Gilbert, 1981), b[0.44,0.98] (Gillot and Heduit,2008), and g (to be calibrated experimentally).
Table 2 lists the major stoichiometric and kinetic param-
eters (after eliminating the pseudo-solid phase effect). Pa-
rameters related to heterotrophs growth and decay processes
(such as mH, YH, KS and bH) are modified in the present model
compared to ASM1 reflecting an improved understanding of
biodegradable material storage (see e.g. Gujer et al., 1999;
Krishna and Van Loosdrecht, 1999; Su and Yu, 2006). Thepumped into the ditch at a flow rate of 0.1 m3/h, and this flow
rate then maintained for a hydraulic residence time of 14 h.
The composition of synthetic wastewater was as follows:
1000 L of tap water, 250.0 g of sugar (approximately 250 mg/L
COD), 107.2 g of ammonium chloride (50 mg/L total nitrogen
concentration), 61.3 g of Na3PO4,12H2O, 500.0 g of NaHCO3,
3.0 g of FeSO4,7H2O, 10.0 g of CaCl2, 12.0 g of MgSO4, and 50mL
of trace element solution. The trace element solution con-
tained (per liter of tap water): 3.5 g of ethylene diamine tet-
raacetic acid, 2.0 g of ZnSO4,7H2O, 1.0 g of CuSO4,5H2O, 1.0 g of
MnSO4,7H2O, 1.0 g of Na2MoO4,2H2O, 1.0 g of H3BO3 and 0.2 g
of CoCl2,6H2O. A settling tank of volume 0.15m3 separated the
sludge which is recycled at the ditch inlet. The sludge recycle
ratio was 100%, and the average activated sludge concentra-
tion in the ditch was maintained at about 3.8 g/L. The sludge
retention time was 25 d. All experiments were performed at
atmospheric pressure and room temperature.
A High-resolution Acoustic Doppler Velocimeter for the
Laboratory (Vectrino II, developed by Nortek AS, Vangkro-
ken, Norway) was used to measure 3D liquid velocities at the
Sections 1-1, 2-2 and 3-3 as shown in Fig. 3. Twice a week,
activated sludge was sampled 0.1 m from the bed at M1, M2,
M3, M4, M5 and M6 (Fig. 3). The mixed liquor suspended
solid (MLSS) of each sample was determined using Method
2540 D (APHA, 1998). Twice daily, water samples for were
obtained 25 cm above the bed at W1, W2, W3, outlet, W4 and
W5 (Fig. 3). Each water sample was immediately filtered
using a 0.45 mm filter, and then stored at 4 C in refrigerator.Soluble COD was determined by the closed reflux titrimetric
method 5220C (APHA, 1998). Ammonia nitrogen and nitrate
concentrations were measured by Nesslers reagent spec-
trophotometry HJ 535-2009 (Environmental Protection
Agency of China, 2009) and ultraviolet spectrophotometric
screening 4500-NO3 B (APHA, 1998), respectively. DO con-
centrations were also monitored twice daily by an oxygen
probe (YSI-550A, YSI, Yellow Springs, Ohio, USA) located
0.25 m above the bed at W1, W2, W3, outlet, W4 and W5.
Ranges of primary variables experimental conditions are
listed in Table 4.
4. Results and discussion
4.1. Numerical model calibration
A 3D unstructured tetrahedral mesh was created for the OD
system using GAMBIT (Fluent Corporation, 2005) with mesh
refinement in the rotating and aerator zones. The governing
equations at steady state were solved using the finite volume
computer code, FLUENT. The grid independent analysis was
done, in which the liquid velocity was selected to conduct the
mesh test. Three different sets of meshes with cells of 55946,
161987 and 367881 respectively, were chosen to simulate the
liquid velocity field in the OD. As a result, the second set was
selected for all computations, considering the low difference
(less than 5%) of liquid velocities simulated with the optimal
mesh (161987 cells) and the refined mesh (36788 cells). The
segregated solver of Fluent 6.3 was used, with default
wat e r r e s e a r c h 5 3 ( 2 0 1 4 ) 2 0 0e2 1 4208Fig. 4 e Comparison between measured and simulated concent
nitrogen, and (e) nitrate, at the sampling locations for Case I.rations of: (a) MLSS, (b) DO, (c) soluble COD, (d) ammonia
Fig. 5 e Comparisons of simulated and measured liquid velocity components at different layers over cross-section 1-1:
surface (a), top (b), middle (c) and bottom (d) for Case II.
wat e r r e s e a r c h 5 3 ( 2 0 1 4 ) 2 0 0e2 1 4 209
parameter settings applied. All simulationswere computed on
a workstation equipped with two Intel Xeon 2.93 GHz pro-
cessors and 24 GB RAM. Each run took about 24 h of CPU time
to reach steady state condition.
The inlet boundary conditions in the numerical model of
the pilot-scale OD utilized measured parameters relating to
the liquid and pseudo-solid phases. The inlet had a rectan-
gular cross-section of breadth 0.15 m, depth 0.05 m, and area
0.0075 m2. At the inlet, the flow speeds of the combined liquid
and pseudo-solid phases were kept at 0.0074 m/s. The syn-
theticwastewaterwas composed of SNO 0mg/L, SNH 50mg/L, SND 0 mg/L and XND 0 mg/L. The quantity of slowlybiodegradable substrate was about twice that of readily
biodegradable substrate (Henze et al., 2000; Orhon et al., 1997).
Sugar provided the carbon source for the synthetic waste-
water. The particulate inert organic concentration was
assumed zero, following Le Moullec et al. (2011). Hence, the
COD compositionwas: SI 10mg/L, SS 80mg/L,XS 160mg/L and XI 0 mg/L.
In order to calibrate the numerical model, the input pa-
rameters were adjusted iteratively in order to minimize the
following objective function (Squires, 2001):
OF
1nn1
Pni1 xci xmi2
q1n
Pni1 xci
(10)
where OF was the normalized standard error; xmi and xci were
themeasured and the calculated results of the i-th parameter,
and nwas the number of monitored samples. Table 5 lists the
input parameters determined by minimizing the objective
function for MLSS, DO, COD, ammonia nitrogen and nitrate
concentration, where the corresponding errors were 2.7%,
12.7%, 2.8%, 6.7% and 6.6%, respectively. Fig. 4 shows the close
agreement between the simulated and measured variables
after calibration, Case I.
4.2. Activated sludge distribution
The model was calibrated using one group of data at Case I
and further verified using another group of data obtained
under Cases II. In Fig. 5, comparison of the simulated and
measured 3D liquid velocities at Section 1-1 demonstrated
reasonable agreements between them with normalized stan-
dard error less than 9.6% at Case II.
Fig. 6 shows the numerically predicted horizontal velocity
component field 0.1 m from the bed and the simulated
streamwise-vertical velocity component field at longitudinal
sections taken along the and third channel in the carrousel
oxidation ditch for Case II. In Fig. 6a, vectors of the horizontal
velocity components are superimposed on contours of
magnitude of the horizontal velocity components. Strong
wat e r r e s e a r c h 5 3 ( 2 0 1 4 ) 2 0 0e2 1 4210Fig. 6 e Case II: (a) predicted horizontal velocity component distr
velocity component distributions along the third channel.ibution, 0.1 m above bed; (b) predicted stream-wise-vertical
clockwise-rotating forced vortices are evident at Stirrers 2, 3,
and 4, and a weaker anti-clockwise flow deflection can be seen
at Stirrer 1. The surface impellers help direct flow from thewall
to the interior of the OD. The gas distributors cause an up-
welling effect driving a ring vortex (which appears like two
counter-rotating vortices in the two-dimensional plane view)
throughwhich a vertical flow passes, later radiating away from
a stagnation point close to the free surface, as shown in Fig. 6b.
From the inlet onwards, the overall horizontal plane flow
conditions in Fig. 6a are as follows: the flow spreads out to
move along Channel 1; it then runs into the opposing flow from
Impeller 1 and enters a strong mixing zone towards the end of
the straight portion of Channel 1. It appears that somematerial
can remain trapped for considerable time in Channel 1. On
entering Channel 2, the flow is essentially uniform across the
breadth of the ditch, but runs into the opposing flow generated
by Stirrer 1 and is driven upwards by the air bubbles at the
bottom aerator, causing a persistent horizontal eddy-like
feature to form about halfway along Channel 2, perhaps
linked to the ring vortex generated by the bottom aeration
system. Stirrer 1 rotates in the anti-clockwise direction, and
this causes a weakly deflected flow into Channel 3. This flow
meets the rotating flow from Impeller 2 and the vertical upflow
from the bottom aerators (Fig. 6b), and again an eddy-like
feature forms in the mixing region towards the middle of
Channel 3. The flow in Channel 4 is partly driven by Impeller 2
and is initially fairly uniform, but appears to separate at a
stagnation point about 0.25 m along the internal wall, after
which a recirculation zone develops. The flow then meets the
strongly rotating vortex associated with Stirrer 2, and stag-
nates. A free anti-clockwise rotating eddy occupies the final
quarter of Channel 4, and is divided from the forced vortex of
Stirrer 2 by a transverse flow towards another stagnation point
at the external wall. Strong forced clockwise rotating vortices
can be seen at Stirrers 1, 2, and 3.Mixing regions and stagnation
points are evident between the stirrers.
Figs. 7 and 8 present the results obtained for the water
quality parameters for Case II. Fig. 7a shows the predicted
MLSS distribution, where the liquid sludge was taken to be in
the pseudo-solid phase closely coupled with liquid and gas
phases. Superimposed on Fig. 7a are six experimental mea-
surements of MLSS taken from the pilot-scale laboratory test
samples. It can be seen that the 3D three-phase model suc-
cessfully predicted the observed processes, i.e. activated
sludge tended to settle out where the liquid velocity was
small, especially in the nearly stagnant zones and slowly
rotating free eddies. Fig. 8a presents a comparison of the
modeled andmeasuredMLSS concentrations. The normalized
standard error between the numerically predicted and labo-
ratory measured MLSS concentration is less than 2.8%,
demonstrating that the proposed model usefully described
the interaction between liquid and pseudo-solid phases in the
wat e r r e s e a r c h 5 3 ( 2 0 1 4 ) 2 0 0e2 1 4 211Fig. 7 e Case II: (a) MLSS concentration distribution, 0.1 m above
nitrate distribution, 0.25 above the bed (where D indicates meathe bed; (b), (c), (d) and (e) DO, COD, ammonia nitrogen and
sured data values at the sampling points in Fig. 3).
wat e r r e s e a r c h 5 3 ( 2 0 1 4 ) 2 0 0e2 1 4212OD in reproducing the transport and sedimentation of acti-
vated sludge.
4.3. Modified oxygen mass transfer
Fig. 7b shows the predicted DO distribution, on which are
superimposed five experimental measurements of DO taken
from the pilot-scale laboratory test samples. The DO content
rises in a fairly uniform fashion from aminimumat Impeller 1
to a maximum in Channel 3, after which DO content reduces
along Channel 4. Fig. 8b also shows the predicted DO con-
centrations for the validation Case II without and with the
pseudo-solid phase (based on the mass transfer model pre-
and post-modification) for Case II. It is obvious that the
modified model (with pseudo-solid phase) provides a much
closer fit to the measurements. This is further verified by
calculating the normalized standard errors obtained by
comparing the two sets of predicted values against the
experimental data. Here, the normalized standard error is
24.6% using the unmodified model for a 0.92 and b 0.44.The normalized standard error is reduced to 9.9% by modi-
fying the pseudo-solid phase effect through the parameter g
in Equation (6) (Mena et al., 2011; Su and Yu, 2006). The very
satisfactory agreement between the simulated and measured
DO concentrations confirms that the proposed model is
capable of providing an accurate description of the liquid-
egasesolid interaction in terms of oxygen mass transfer.
Fig. 8 e Comparison between measured and simulated concent
nitrogen, and (e) nitrate, at the sampling locations for Case II.4.4. Water quality
In predicting the water quality, the stoichiometric and kinetic
parameters in ASM1 were modified along with the oxygen
mass transfer model. Fig. 7cee show the predicted soluble
COD, ammonia nitrogen, and nitrate distributions. In each
plot, the five experimental measurements are superimposed.
For the COD and ammonia nitrogen, both contour plots tell a
similar story: a contaminant hot spot can be seen immediately
downstream of the inlet, and a further high concentration
zone at the end of Channel 1. The water quality then consis-
tently improves throughout Channels 2, 3, and 4. Fig. 7e shows
that the nitrate distribution follows an almost inverse trend to
the ammonia nitrogen, as would be expected. Fig. 8cee show
the close agreement between the numerically predicted and
measured values of soluble COD, ammonia nitrogen, and ni-
trate respectively at different locations in the OD for Case II. In
general, both soluble COD (Figs. 7c and 8c) and ammonia ni-
trogen (Figs. 7d and 8d) decline in the OD from a peak at the
inlet to a low values of about 16 mg/L and 4 mg/L respectively
at W2, after which there is little further change. The nitrate
concentration (Figs. 7e and 8e) increases substantially from
the inlet to W2, and seems to saturate at about 13 mg/L
beyond. The normalized standard errors between the simu-
lated and measured soluble COD, ammonia nitrogen and ni-
trate concentrations are 1.5%, 1.5% and 3.3%, respectively.
Hence, it can be concluded that the present model provides a
rations of: (a) MLSS, (b) DO, (c) soluble COD, (d) ammonia
dynamics was developed that satisfactorily represents phase
Amand, L., Carlsson, B., 2012. Optimal aeration control in anitrifying activated sludge process. Water Res. 46 (7),
wat e r r e s e a r c h 5 3 ( 2 0 1 4 ) 2 0 0e2 1 4 2132101e2110.APHA, 1998. Standard Methods for the Examination of Water and
Wastewater, 20th ed. American Public Health Association,Washington, DC.
Beccari, M., Dionisi, D., Giuliani, A., Majone, M., Ramadori, R.,motion and phase interactions in an oxidation ditch. Acti-
vated sludge flocs were interpreted as having pseudo-solid
phase, and the related parameters modified by calibrating
the sludge viscosity, settling capacity, oxygen mass transfer
rate, and carbon substrate uptake due to adsorption on acti-
vated sludge. The assumption that activated sludge was in a
pseudo-solid phase made it possible to describe its transport
and sedimentation. By modifying the oxygen mass transfer
model, and the stoichiometric and kinetic parameters, the
numerical model was able to represent biochemical trans-
formation of sludge. Experimental data on mixed liquor sus-
pended solid (MLSS), DO concentration, soluble COD,
ammonia nitrogen, and nitrate were obtained from a pilot-
scale carrousel oxidation ditch. The numerical predictions of
flow field in the OD showed the great importance of the im-
pellers and stirrers in promoting mixing. The excellent
agreement obtained between the numerical simulations and
sampled data measurements for water quality parameters
indicated that the numerical model accurately simulated the
kinematics of the multi-phase flow and the carbon oxidation,
nitrification and denitrification processes in the OD. The pre-
sent paper has focused on model calibration and verification,
and used the results to provide some insights into the
behavior of an oxidation ditch. In future, it is recommended
that the model be used for parameter studies as a design tool
in helping to select optimal arrangements of impellers, stir-
rers, and aeration zones in planned oxidation ditches.
Acknowledgments
Financial support from National Natural Science Foundation
of China (Grant No. 21261140336/B070302) is very much
appreciated. Sincere thanks are also to Professor Alistair G.L.
Borthwick at Department of Engineering Science, Oxford
University for his careful editing on the manuscript.
r e f e r e n c e sreasonable description of the interactions between species in
liquid and pseudo-solid phases. The modified stoichiometric
and kinetic parameters in presence of solid phase lie between
those of ASM and granular sludge system (Su and Yu, 2006).
5. Conclusions
A 3D three-phase fluid model based on computational fluid2002. Effect of different carbon sources on aerobic storage byactivated sludge. Water Sci. Technol. 45 (6), 157e168.Carucci, A., Dionisi, D., Majone, M., Rolle, E., Smurra, P., 2001.Aerobic storage by activated sludge on real wastewater. WaterRes. 35 (16), 3833e3844.
Cggn, A.S., Orhon, D., Rossetti, S., Majone, M., 2011. Short-termand long-term effects on carbon storage of pulse feeding onacclimated or unacclimated activated sludge. Water Res. 45(10), 3119e3128.
Dammel, E.E., Schroeder, E.D., 1991. Density of activated sludgesolids. Water Res. 25 (7), 841e846.
Environmental Protection Agency of China, 2009. Water quality-Determination of ammonia nitrogen-Nesslers reagentspectrophotometry (HJ 535-2009). China EnvironmentalScience Press, Beijing.
Fayolle, Y., Cockx, A., Gillot, S., Roustan, M., Heduit, A., 2007.Oxygen transfer prediction in aeration tanks using CFD.Chem. Eng. Sci. 62 (24), 7163e7171.
Fluent Corporation, 2005. Gambit 2.2 Users Guide, Lebanon, NH,USA.
FluentCorporation, 2006. Fluent6.3UsersGuide, Lebanon,NH,USA.Gillot, S., Heduit, A., 2008. Prediction of alpha factor values for
fine pore aeration systems. Water Sci. Technol. 57 (8),1265e1269.
Grijspeerdt, K., Verstraete, W., 1997. Image analysis to estimatethe settleability and concentration of activated sludge. WaterRes. 31 (5), 1126e1134.
Gujer, W., Henze, M., Mino, T., van Loosdrecht, M., 1999. Activatedsludge model No. 3. Water Sci. Technol. 39 (1), 183e193.
Henze, M., Gujer, W., Mino, T., van Loosdrecht, M., 2000. ActivatedSludge Models ASM1, ASM2, ASM2d and ASM3. Scientific andTechnical Report 9, IWA Task Group on MathematicalModelling for Design and Operation of Biological WastewaterTreatment. IWA Publishing, London.
Hong, K.H., Chang, D., Hur, J.M., Han, S.B., 2003. Novel phasedisolation ditch system for enhanced nutrient removal and itsoptimal operating strategy. J. Environ. Sci. Health Part A-Toxic/Hazard. Subst. Environ. Eng. 38 (10), 2179e2189.
Insel, G., Artan, N., Orhon, D., 2005. Effect of aeration on nutrientremoval performance of oxidation ditch systems. Environ.Eng. Sci. 22 (6), 802e815.
Jin, B., Wilen, B., Lant, P., 2004. Impacts of morphological, physicaland chemical properties of sludge flocs on dewaterability ofactivated sludge. Chem. Eng. J. 98 (1e2), 115e126.
Krishna, C., Van Loosdrecht, M.C.M., 1999. Substrate flux intostorage and growth in relation to activated sludge modeling.Water Res. 33 (14), 3149e3161.
Kulkarni, A.A., 2007. Mass transfer in bubble column reactors:effect of bubble size distribution. Industrial Eng. Chem. Res. 46(7), 2205e2211.
Kumar, B., Rao, A.R., 2009. Oxygen transfer and energy dissipationrate in surface aerator. Bioresour. Technol. 100 (11), 2886e2888.
Le Moullec, Y., Potier, O., Gentric, C., Leclerc, J.P., 2011. Activatedsludge pilot plant: comparison between experimental andpredicted concentration profiles using three differentmodelling approaches. Water Res. 45 (10), 3085e3097.
Littleton, H.X., Daigger, G.T., Strom, P.F., 2007. Application ofcomputational fluid dynamics to closed-loop bioreactors: II.Simulation of biological phosphorus removal usingcomputational fluid dynamics. Water Environ. Res. 79 (6),613e624.
Liu, Y., Liu, Y., Wang, Z., Yang, S., Tay, J., 2005. Influence ofsubstrate surface loading on the kinetic behaviour of aerobicgranules. Appl. Microbiol. Biotechnol. 67 (4), 484e488.
Mantziaras, I.D., Stamou, A., Katsiri, A., 2011. Effect of operationalcycletime length on nitrogen removal in an alternatingoxidation ditch system. Bioprocess Biosyst. Eng. 34 (5), 597e606.
Mena, P., Ferreira, A., Teixeira, J.A., Rocha, F., 2011. Effect of somesolid properties on gas-liquid mass transfer in a bubble
column. Chem. Eng. Process. 50 (2), 181e188.
Orhon, D., Ates , E., Sozen, S., Cokgor, E.U., 1997. Characterizationand COD fractionation of domestic wastewaters. Environ.Pollut. 95 (2), 191e204.
Pipes, W.O., 1969. Types of activated sludge which separatepoorly. J. Water Pollut. Control Fed. 41 (5), 714e724.
Schmid, M., Thill, A., Purkhold, U., Walcher, M., Bottero, J.Y.,Ginestet, P., Nielsen, P.H., Wuertz, S., Wagner, M., 2003.Characterization of activated sludge flocs by confocal laserscanning microscopy and image analysis. Water Res. 37 (9),2043e2052.
Squires, G.L., 2001. Practical Physics. Cambridge University Press,Cambridge, UK.
Stamou, A.I., 1994. Modelling oxidation ditches using the IAWPRCactivated sludge model with hydrodynamic effects. Water Sci.Technol. 30 (2), 185e192.
Stamou, A.I., 1997. Modelling of oxidation ditches using anopen channel flow 1-D advection-dispersion equation andASM1 process description. Water Sci. Technol. 36 (5),269e276.
Stamou, A.I., Katsiri, A., Mantziaras, I., Boshnakov, K.,Koumanova, B., Stoyanov, S., 1999. Modelling of analternating oxidation ditch system. Water Sci. Technol. 39(4), 169e176.
Stenstrom, M.K., Gilbert, R.G., 1981. Effects of alpha-factor, beta-factor and theta-factor upon the design, specification andoperation of aeration systems. Water Res. 15 (6), 643e654.
Su, K.Z., Yu, H.Q., 2006. A generalized model for aerobic granule-based sequencing batch reactor. 1. Model development.Environ. Sci. Technol. 40 (15), 4703e4708.
Wang, J., Qiu, Z., Chen, Z., Li, J., Zhang, Y., Wang, X., Zhang, B.,2012. Comparison and analysis of membrane fouling betweenflocculent sludge membrane bioreactor and granular sludgemembrane bioreactor. PLoS One 7 (7).
Yang, Y., Yang, J., Zuo, J., Li, Y., He, S., Yang, X., Zhang, K., 2011.Study on two operating conditions of a full-scale oxidationditch for optimization of energy consumption and effluentquality by using CFD model. Water Res. 45 (11), 3439e3452.
Zhang, D., Guo, L., Xu, D., Chen, Y., 2010. Simulation ofcomponent distributions in a full-scale carrousel oxidationditch: a model coupling sludge-wastewater two-phaseturbulent hydrodynamics with bioreaction kinetics. Environ.Eng. Sci. 27 (2), 159e168.
Zhou, X., Guo, X., Han, Y., 2012. Enhancing nitrogen removal in anOrbal oxidation ditch by optimization of oxygen supply:practice in a full-scale municipal wastewater treatment plant.Bioprocess Biosyst. Eng. 35 (7), 1097e1105.
wat e r r e s e a r c h 5 3 ( 2 0 1 4 ) 2 0 0e2 1 4214
Three-dimensional three-phase model for simulation of hydrodynamics, oxygen mass transfer, carbon oxidation, nitrification ...1 Introduction2 Methodology2.1 Model development2.1.1 Multiphase hydrodynamics model2.1.2 Species transport model2.1.3 Biochemical kinetics model2.1.4 Oxygen mass transfer model
2.2 Phase interaction2.2.1 Liquidgas interaction2.2.2 Liquid-solid interaction2.2.3 Gassolid interaction
2.3 Boundary conditions2.4 Parameter estimation
3 Experimental measurements in pilot-scale oxidation ditch4 Results and discussion4.1 Numerical model calibration4.2 Activated sludge distribution4.3 Modified oxygen mass transfer4.4 Water quality
5 ConclusionsAcknowledgmentsReferences