DTIC ADA639828: Kinetic Theories for Biofilms (Preprint)

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Kinetic Theories for Biofilms
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Institute,Columbia,SC,29208
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14. ABSTRACT
We apply the kinetic theory formulation for binary complex fluids to develop a set of hydrodynamic
models for the two-phase mixture of biofilms and solvent (water). It is aimed to model nonlinear growth
and transport of the biomass in the mixture and the biomass-flow interaction. In the kinetic theory
formulation of binary complex fluids, the biomass consisting of EPS (Extracellular Polymeric Substance)
polymer networks and bacteria is coarse-grained into an effective fluid component, termed the effective
polymer solution; while the other component, termed the effective solvent, is made up of the collective
ensemble of nutrient substrates and the solvent. The mixture is modeled as an incompressible twophase
fluid in which the presence of the effective components are quantified by their respective volume fractions.
The kinetic theory framework allows the incorporation of microscopic details of the biomass and its
interaction with the coexisting effective solvent. The relative motion of the biomass and the solvent relative
to an average velocity is described by binary mixing kinetics along with the intrinsic molecular elasticity of
the EPS network strand modeled as an elastic dumbbell. This theory is valid in both the biofilm region
which consists of the mixture of the biomass and solvent and the pure solvent region, making it convenient
in numerical simulation of the biomass-flow interaction. Steady states and their stability are discussed
under a growth condition. Nonlinear solutions of the three models developed in this study in simple shear
are calculated and compared numerically.
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Kinetic Theories for Biofilms
QiWang∗andTianyuZhang†
Abstract
Weapplythekinetictheoryformulationforbinarycomplexfluidstodevelopasetofhydrodynamic
modelsforthetwo-phasemixtureofbiofilmsandsolvent(water). Itisaimedtomodelnonlineargrowth
and transport of the biomass in the mixture and the biomass-flow interaction. In the kinetic theory
formulationofbinarycomplexfluids,thebiomassconsistingofEPS(ExtracellularPolymericSubstance)
polymernetworksandbacteriaiscoarse-grainedintoaneffectivefluidcomponent,termedtheeffective
polymersolution;whiletheothercomponent,termedtheeffectivesolvent,ismadeupofthecollective
ensemble of nutrient substrates and the solvent. The mixture is modeled as an incompressible two-
phasefluidinwhichthepresenceoftheeffectivecomponentsarequantifiedbytheirrespectivevolume
fractions. Thekinetictheoryframeworkallowstheincorporationofmicroscopicdetailsofthebiomass
and its interaction with the coexisting effective solvent. The relative motion of the biomass and the
solvent relative to an average velocity is described by binary mixing kinetics along with the intrinsic
molecularelasticityoftheEPSnetworkstrandmodeledasanelasticdumbbell. Thistheoryisvalidin
both the biofilm region which consists of the mixture of the biomass and solvent and the pure solvent
region,makingitconvenientinnumericalsimulationofthebiomass-flowinteraction. Steadystatesand
theirstabilityarediscussedunderagrowthcondition.Nonlinearsolutionsofthethreemodelsdeveloped
inthisstudyinsimplesheararecalculatedandcomparednumerically.
1 Introduction
Biofilms,consistingofmyriadmicrobes,theirexcretions,andtrappedparticles,areubiquitousinnature,
medical implants, rusty pipes, and dentistry etc., where microbes survive on wet surfaces. In principle,
a biofilm community can be formed by a single bacterial species in damp environment; but, in nature,
biofilms almost always consist of rich mixtures of multiple species of bacteria as well as fungi, algae,
yeasts, protozoa, other microorganisms, debris and corrosion products etc. Biofilms are held together by a
networkofsugarymolecularstrandsproducedbythemicrobes,collectivelytermed“extracellularpolymeric
substances” or “EPS”. In bacterial biofilms, bacterial cells are held together by the network consisting of
the EPS strands produced by the bacteria, allowing them to develop complex, three-dimensional, resilient,
attachedcommunities[10,11,13,28].
The centerfor disease control and nationalinstitute of health estimatedthat 65% to 85%of all chronic
infections can be attributed to bacterial biofilms [11]. In human diseases, biofilm infections are some of
the most recalcitrant to treat. Even with rigorous antibiotic regimens, some biofilms, such as those within
thethickairwaymucusofcysticfibrosis(CF)patients,persistthroughoutthecourseofthediseaseprocess
[18]. One noted that the gene expression of a single bacterial (planktonic) cell differs drastically from
that of the biofilm colonies indicating environmentally induced genetic change to the bacterial cell. This
is one of the reason why antibiotics that are effective to treat single bacterium may not be effective in the
∗
DepartmentofMathematicsandNanoCenteratUSC,UniversityofSouthCarolina,Columbia,SC29208;NankaiUniversity,
Tianjin,P.R.China.Email:[email protected]
†Department of Mathematical Sciences, Montana State University, Bozeman, MT, 59717-2400. Email:
[email protected]
1
treatmentofthebacteriaencasedinbiofilms. Bacterialbiofilmscanalsobeutilizedinbio-terrorisminwhich
persistent‘bio-terroristagentbiofilms’withFrancisellatularensiscangrowonsurfaceswhereenvironmental
amoebacanphagocytosethem,allowingforgrowthoffibrosis[18]. BiofilmscosttheU.S.literallybillions
of dollars every year in energy losses, equipment damage, product contamination and medical infections.
Understandingthemechanismforthedynamicalgrowth,transport,detachmentandbreak-downofbiofilms
is important for improving water treatment, medical treatment of diseases, protecting equipment or device
from corrosion and contamination, and even preventing bio-terrorism. It can have a profound impact on
environmental sciences, medicine, civil engineering, naval sciences, military applications and homeland
security.
Modeling biofilms has been a challenge given their complex cellular structures and changing genetic
dynamics in the presence of foreign agents [10, 13, 28]. Biofilms essentially behave like biogels in which
smallsolventandnutrientmoleculecanpermeatethenetworkformedbythebacterialandtheEPSstrands. A
setofdiscreteorsemi-discretemodelsassociatedwithcellularautomatahavebeenusedtostudythevarious
aspectofthebiofilmphenomenainmultidimensionalsettings[29,30,31,32]. Recently,therehaveemerged
ahostofcontinuummodelsforbiofilmstreatingthemasmixturesofmultipleidealizedspecies[9,21,34,1,
38,39]. Inthesemodels,themixtureiseithermodeledasamulti-fluidmixture[9,21,34,1]orasinglefluid
ofmulti-components/species[38,39]. Inthemultifluidmodels[9,21,1],whichoneusesinthedevelopment
ofhydrodynamicalmodelsforhydrogels, thevelocityforeachindividualcomponentisintroducedandthe
balance laws for the mass and momentum of each species are preserved. The technical difficulty working
with these multi-fluid models is that the individual velocity fields of the species are used as primary field
variables in these theories; however they are essentially immeasurable in experiments since hydrodynamic
measurementsareoftenlimitedtothemeanoraveragequantitiesinmultiphasefluids. Moreover,theinflow
and outflow boundary conditions for the individual species are elusive when it comes to mathematically
solvingthegoverningsystemofequationswithoutadditionalsimplifications. Thesinglefluidmulti-species
model however can overcome this technical difficulty by providing explicit relative velocities in terms of
the excessive velocities generated by nonequilibrium thermodynamics (mixing dynamics) with respect to
an average bulk velocity [38, 39] and have been successfully used in modeling biofilm expansion/growth,
shedding or streaming, detachment of biofilm blobs from large colonies, and rippling phenomenon under
shear [39]. In this single fluid multi-component fluid system, the inter-penetration of different species is
carried out by their respect entropy and the mixing free energy. This molecular mechanism compensates
the so-called friction forces due to the relative motions among the various species commonly seen in the
multi-fluid theories near hydrodynamic equilibrium. By devising appropriate intermolecular potential for
themultiphasefluid,wecantailorourmodelstoaccountforthephysicsofmixingeffectively.
The mathematical models for hydrodynamics of biofilms available so far are primarily coarse-grain
models in which little cellular kinetics is incorporated. There are some common ingredients in the mul-
tiphase fluid models for biofilms (either multi-fluid or single fluid ones) [9, 1, 21, 34, 38], in which the
nutrient substrate is passively treated as a part of the solvent and the volume of the bacteria is collectively
treatedapartoftheeffectivepolymer. Theeffectivepolymeradoptedhereisalsocollectivelyidentifiedas
thebiomassintheliterature. Inthispaper,weinterchangeablyusethenameofeffectivepolymerorbiomass
inordertomakecontactwiththecomplexfluidmodelstobedevelopedaswellasthebiologicalcommunity
wherebiomassisthemorefamiliarterm.
Thevolumefractionofthebiomassϕ andthatofthesolventϕ aretwobasichydrodynamicvariables
n s
along with the velocity of the biomass v and the velocity of the solvent v in multifluid models or the
n s
averagevelocityvinsinglefluidmulticomponentmodels, theconcentrationofthenutrientsubstratec, the
concentration of the bacteria B, the pressure p, and the polymeric stress for the effective polymer. The
volume fraction of the biomass and the effective solvent are assumed to obey reaction-transport equations
2
inthesemodels,
∂ϕn +∇·(ϕ v )=g ,
∂t n n n
(1.1)
∂ϕs +∇·(ϕ v )=g ,
∂t s s s
whereg andg isthepolymerproductionrateandthesolventconsumptionrate,respectively. Thebacterial
n s
productionaswellasthesubstrateconsumptionequationaregivenasfollows:
∂B+∇·(Bv )=g ,
∂t n b
(1.2)
∂(ϕ c)+∇·(cv ϕ −D ϕ ∇c)=−g ,
∂t s s s s s c
where g is the production rate for the bacteria, g is the consumption rate of the nutrient substrate in the
b c
solvent,D isthediffusionconstantforthenutrient.
s
The binary theories for biofilms differ in the formulation of various velocities in conservation of mass
andmomentumequationsandtheconstitutiverelationsforg andg . Someendupwithaquasi-compressible
n s
constraintforanaveragevelocity[9,21,1]whileothersretaintheincompressibleconstraintontheaverage
velocity field [38]. Besides these differences, the constitutive equation for the stress and reactive rates are
essentially the same when both the effective solvent and the effective polymer are treated as viscous fluids
whichisperfectlyvalidinthegrowthtimescaleofthebiofilm. Inthiscase,theextrastresstensorandsome
ofthegrowthaswellasdecayratesaregivenbythefollowingconstitutivelaws.
τ =2η D , τ =2η D ,
n n n s s s
(1.3)
g =ϕ A c , g =µϕ c ,
c n K0+c n nKc+c
where η are the viscosity of the effective polymer and the solvent, respectively, D = 1[∇v +∇vT ]
n,s n,s 2 n,s n,s
is the rate of strain tensor for the effective polymer and the solvent, respectively, A is the maximum con-
sumptionrateofthenutrientsubstrate,µisthemaximumproductionrateofthebiomass,K andK aretwo
0 c
half-saturationconstants. Wenotethatthebacterialconcentrationdecouplesfromthe restoftheequations
in the binary biofilm models. It can thus be ignored completely in the models when the focus is on the
growthofthebiomassoreffectivepolymer.
In the phase field model we developed in [38], the ensemble of the bacteria is effectively modeled as
the “viscous solvent” which blends with the EPS network to function effectively as a polymer solution. A
distribution function for the polymer network strands can then be introduced to describe the concentration
ofthepolymernetworkstrandinthe”viscoussolvent”aswellasthecoarse-grainormeso-structureofthe
polymer network. This thus motivates us to seek a kinetic formulation of biofilm theories to describe the
EPS network immersed in the viscous bacterial bath and thereby to guide the study of the biomass-flow
interaction.
In this paper, we refine our single fluid multicomponent formulation of biofilm theories by developing
aset of kinetic theory modelsfor biofilm-solventmixtures systematically [2]. This newformulation of the
biofilm models provides a well-structured theoretical framework for expanding the theory to incorporate
additionalmolecularinformationandbiochemicaldetailsofthebiofilmcomponentsintothemodelasone’s
understanding of biofilm dynamics progresses. In what follows, we treat the biomass-solvent mixture as
incompressible with a divergence-free average (bulk) velocity field and then develop a kinetic theory for
theeffectivepolymerandsolventmixturetakingintoaccountthepolymerconformationaldynamicsofthe
EPS strand, production of biomass at the microscopic level, and the biomass-solvent interaction. Within
this framework, a variety of molecular models can be crafted to account for the polymer network strand
3
(dumbbell,FENEdumbbell,Rousechain,etc.) andaspectrumofpolymerandsolventinteractiondynamics
canbeproposed(likemixingtheoryofFlory-Huggins,etc.). Asimplifiedmechanicalmodel,thedumbbell
model, for the EPS network strand and a kinetic network theory along with the Flory-Huggins mixing
dynamicsissetupto illustratetheideaanddemonstratehowconsistentstressexpressionsfortheeffective
polymer can be derived. The kinetic theories developed here are de-facto phase field models with the field
variablenaturally givenby the effectivepolymer (or biomass) volumefraction ϕ (x,t)(the zeroth moment
n
of the effective polymer distribution function), in which the biofilm-solvent interface is given by the zero-
levelsurfaceofthephasevariable: limδ→0+{x|ϕn(x,t)=δ}[35,36]. Thebiofilmregionispresentedbythe
non-vanishingbiomassvolumefractionvariableϕ . Inthisformulation,wetacitlyassumetheEPSdensity
n
is directly proportional to the bacterial density and thereby a single volume fraction can be employed to
representthebiomass. Thisphasefieldmodelprovidesalow(computational)costmathematicalformulation
ofthecomplexinterfacialproblem.
The rest of the paper is organized as follows. First we develop a set of kinetic theories for biofilms by
accounting for transport of polymer network strands and their conformational changes as well as nutrient
substrates, and the response of the polymer network in flow in three plausible ways within the theoretical
framework of network theories for one fluid multi-component mixtures. We then analyze the stability of
steady states to identify the unstable modes in long wave regimes. Finally, we study the biofilm expan-
sion/growthinonespacedimensionnumericallyandcomparethepredictionsmadewiththethreedifferent
kinetictheories.
2 Kinetic Theories for Biofilms
We model the biofilm as a fluid mixture of two effective components: the biomass as the effective
polymersolutionincludingboththeviscoelasticEPSpolymernetworkandtheviscousbacterial”solution”,
and the effective solvent consisting of the solvent and the dissolved nutrient substrate. In this theory, we
neglect the mass of the nutrient and instead only account for its reactive effect. The EPS polymer network
is described by network strands connected at junction points. The dynamics of the network consist of
the dynamics of the center of mass of the polymer strand and the dynamics for the center of mass. This
description clearly cast a two-scale view on the nature of the polymer network dynamics. The dynamics
for the center of mass of the polymer strand can be described at the macroscopic or the continuum level;
whereasthedynamicsofthepolymerstrandrelativetothecenterofmassbelongstothemesoscale. Based
on this, we develop a kinetic theory for the fluid mixture accounting for the microstructure conformation
of the polymer network strand as well as the interaction between the effective components, in which we
modelthestrandintheEPSnetworkusinganelasticdumbbellmodelandbacteriaasviscousfluids. Inthis
setting,theeffectivepolymeriseffectivelytreatedasapolymericsolution,wheretheEPSpolymernetwork
is“immersed”inthe“bacterialsolution.”
Wedenotethestatisticalweightofapolymernetworkstrandwithitscenterofmasslocatedatxandthe
end-to-endvectorqattimet asψ(x,q,t)suchthatthepolymernetworkvolumefractionϕ isdefinedasthe
n
zerothmomentofthestatisticalweightψwithrespecttotheconfigurationvariableq,
∫
ϕ (x,t)= ψdq=⟨1⟩, (2.1)
n
R3
where
∫
⟨(•)⟩= (•)ψdq. (2.2)
R3
Notice that wherever the region is filled with pure solvent, i.e., ϕ (x,t) = 0, ψ(x,q,t) = 0. Wherever
n
ϕ (x,t)̸=0, however, a probability density function ψ(x,q,t) can be identified and a probability ensemble
n ϕn(x,t)
4
averagewithrespecttotheconformationvariableqcanbedefinedby
1
⟨(•)⟩ = ⟨(•)⟩. (2.3)
q ϕ (x,t)
n
Tomakeadistinctionbetweenthetwoensembleaveragesdefinedabove,weremarkthat⟨⟩ isaprobability
q
ensemble average while ⟨⟩ is an ensemble proportional to the volume fraction ϕ. Apparently, the effective
polymervolumefractionϕ (x,t)playstheroleofaphasefieldvariableinthetheory. I.e.,whenϕ (x,t)=0,
n n
the fluid consists of entirely the solvent; otherwise, it is a true binary mixture. Therefore, the resulting
theoryservesasaneffectivephasefieldmodel. Thetwodistinctivephasesaredifferentiatedbyϕ (x,t)=0
n
(solvent) and ϕ (x,t)>0 (biofilm mixture), respectively. For biofilms, ϕ (x,t)<1 is normally assumed,
n n
excludingtheveryunlikelysituationwherethebiofilmiscompletelydrywithoutanysolvent.
In this model, we treat the entire material system as an incompressible single fluid mixture of two
effective components, in which an average velocity v is assumed to exist and divergence free. We propose
thatthefreeenergydensityofthemixturesystemiscomposedofthemixingfreeenergyforthesolventand
the polymer network, elastic energy for the polymer network, self-energy of the polymer and the solvent
respectively,andtheconformationalentropyforthepolymernetworkstrand(elasticdumbbell):
F = f + f + f + f , (2.4)
int ec es sol
where f is the extended Flory-Huggins mixing free energy density, f is the entropic and the elastic
int ec
energydensityfortheconformationofthepolymerstrand, f istheelasticenergyforthepolymernetwork,
es
and f istheself-energyforthesolvent. Specifically,
sol
∫
ψ
f =νk T [ln( )+ξ∥q∥2]ψ(x,q,t)dq, (2.5)
ec B ϕ
R3 n
whereξνk T isthestiffnessofthepolymerchain,νisthenumberdensityofthepolymerchainand(ln ψ)ψ
B ϕ
n
corresponds to the entropic contribution of the polymer chain, which is understood to be possibly nonzero
onlyintheregionwhereϕ ̸=0andzeroelsewhere;theextendedFlory-Hugginsmixingfreeenergydensity
n
f asafunctionofϕ isgivenby
int n
[ ( )]
γ ϕ
f =k T 1∥∇ϕ ∥2+γ nln(ϕ )+(1−ϕ )ln(1−ϕ )+χϕ (1−ϕ ) , (2.6)
int B n 2 n n n n n
2 N
whereγ andγ measuresthestrengthoftheentropicconformationalandbulkmixingfreeenergy, respec-
1 2
tively,χistheFlory-Huggin’smixingparameter,N isthegeneralizedpolymerizationindexforthepolymer
strand;
f =ϕ f(B), (2.7)
es n
where f isaprescribedfunctionoftheFingertensorBwhosetransportequationisgivenby
es
∂B B 2η
+∇·(v B)+W ·B−B·W −a [D ·B+B·D ]+ = bD =2GD , (2.8)
∂t n n n 1 n n λ λ n i n
2 2
where λ is the relaxation time, −1 ≤ a ≤ 1 is a model parameter, v is the network velocity (defined
2 1 n
below), W and D are the vorticity and rate of deformation tensor associated to the network deformation,
n n
respectively, a is a parameter between -1 and 1, η is a viscosity parameter and G = ηb is the elastic
1 b i λ
2
modulus;
f =(1−ϕ )C , (2.9)
sol n sol
5
whereC istheself-energyofthesolventwhichisaconstant. Since f isalinearfunctionofthevolume
sol sol
fraction, its contribution to the chemical potential is merely a constant and therefore can be neglected. We
willtherebydroptheself-energyofthesolventfromthefreeenergyfunctionaltosimplifythepresentation.
Wenotethatγ =νN isproportionaltothereciprocalofthevolumeofthesolventmoleculeand∥·∥denotes
2
the l norm of a vector. The entropic conformational free energy is included in the Flory-Huggins mixing
2
freeenergytominimizethespatialinhomogeneityinthebiomass.
One choice of the nonlinear elastic energy for the deformation of the center of mass of the polymer
strandinthenetworkisgivenby
f(B)=ξ tr(B)+ξ lndet(B), (2.10)
2 3
whereξ andξ aretwomodelparameters. Then,
2 3
∂f(B)
=ξ I+ξ B−1. (2.11)
∂B 2 3
Given the free density functional, we can calculate the chemical potential of the polymer system as
follows
δF δf δf δf
int ec es
µ= = + + , (2.12)
δψ δψ δψ δψ
where
δfec =νξk T∥q∥2+νk T[ln ψ],
δψ B B ϕ
n
[ ]
δfint = δfint =−k Tγ ∆ϕ −γ k T −1(1+ln(ϕ ))+ln(1−ϕ )+1−χ+2χϕ , (2.13)
δψ δϕn B 1 n 2 B N n n n
δfes = f(B).
δψ
δϕ
Wenotethattheidentity: n =1isusedintheabovederivation. So,
δψ
[ ]
ψ −1
µ=k T νξ∥q∥2+ν(ln )−γ ∆ϕ −γ [ (ln(ϕ ))+ln(1−ϕ )+2χϕ ] + f(B)+const. (2.14)
B ϕ 1 n 2 N n n n
n
Withthechemicalpotential,wenextderiveasetofkineticmodelsforthebiofilmfluid. Wewillpresentthree
distinctversionsbypostulatingthreeplausiblewaysthattheconservativeforceintranslationaldiffusionof
theEPSnetworkcanbeapproximatedinthemean-field.
2.1 SeparableModel1forBiofilms
Inthebiomass,weassume(1). thecreationrateandtheannihilationrateofpolymernetworkstrandsis
balancedbyagrowth/productionrate,(2). thetranslationaldiffusioniscarriedoutthroughaconfigurational
spaceaveragedchemicalpotential, (3). thedeformationoftheEPSstrand(elasticdumbbell)intheconfig-
urationalspace(q)isduetothepolymervelocitygradient∇v tobederivedbelow. Thetransportequation
n
forthestatisticalweightψisthengivenbythefollowingSmoluchowskiequation[3,15]
∂ψ+∇·(vψ)=∇·(λ∇⟨µ⟩ ψ)+∇ ·1(∇ µψ)−∇ ·((∇v +(a−1)D )·qψ)+G ,
∂t q q ζ q q n n n
(2.15)
G =µ ψc ,
n rKc+c
6
whereλisthemobilitycoefficient,ζisthefrictioncoefficientfortherotationalmotionofthepolymerchain,
a is a slip parameter between -1 and 1 accounting for slippage between the polymer and the solvent, ∇v
n
isthevelocitygradienttensorwithrespecttothepolymervelocity, D = 1[∇v +∇vT]istherateofstrain
n 2 n n
tensorwithrespecttothepolymervelocity,G isthepolymernetworkstrandproductionrateinunitvolume
n
inphasespace(x,q),µ isthemaximumgrowthrateofthebiomassandK isahalf-saturationconstantfor
r c
thenutrientconsumptionkineticsviaaMichaelis-Mentonmodel. Wenotethatbothλandζcanbesecond
order tensors when the diffusion is anisotropic. In this paper, we adopt an isotropic diffusion coefficient
tensorforillustrationpurposesthough. Tosimplifythepresentation,westipulatethattheensembleaverage
⟨(•)⟩ =0wheneverϕ =0throughoutthepaper.
q n
2.1.1 TransportEquationsForVolumeFractionsAndStructureTensors: LowOrderMomentEqua-
tions
Sincepolymervolumefractionϕ isthezerothmomentofψ,weobtainthetransportequationofϕ by
n n
integratingtheSmoluchowskiequationovertheconfigurationalspace(q-space),
∂ϕn +∇·(ϕ v)=∇·[λϕ ∇⟨µ⟩ ]+g ,
∂t n n q n
g =µ ϕnc ,
n rKc+c
[ ] (2.16)
⟨µ⟩ =−k Tγ ∆ϕ −γ k T −lnϕn +ln(1−ϕ )+2χϕ +
q B 1 n 2 B N n n
νξk T⟨∥q∥2⟩ +νk T⟨ln(ψ)⟩ + f(B)+const, inbiofilm.
B q B ϕ q
n
We remark that the mobility vanishes in pure solvent and so does ϕ ⟨µ⟩ = 0. So, this is a singular or
n q
modifiedCahn-Hilliardequation[4,5].
From the transport equation for the volume fraction, the local instantaneous velocity can be identified
as consisting of twoparts: the average velocity v and the excessivevelocity due to the binary mixing. The
lattercontributiontotheflux,whichcanbereadofffromthetransportequation,isassumedproportionalto
themixingforcegivenbythegradientoftheensembleaverageofthechemicalpotential
ve =−λ∇⟨µ⟩ . (2.17)
n q
Itiscalledtheexcessivepolymervelocitythatisonlydefinedinthebiofilmregion. Thepolymervelocityis
thenidentifiedas
v =v+ve. (2.18)
n n
This polymer velocity is not a divergence-free vector although the average velocity v may be. In fact, this
velocitycoincideswiththeaveragevelocityoutsidethebiofilmregion; soitisagloballydefinedhydrody-
namicvariable. Usingthisnotation,thetransportequationforϕ simplifiesto
n
∂ϕ
n +∇·(ϕ v )=g . (2.19)
∂t n n n
With this polymer velocity, we can define the rate of strain tensor and vorticity tensor associated with the
velocityfield:
1 1
D = (∇v +∇vT),W = (∇v −∇vT). (2.20)
n 2 n n n 2 n n
7