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(1)

MULTIGRID METHODSFORINTERFACEPROBLEMS

LOYCE ADAMS y

AND ZHILIN LI z

Abstract. New multigridmethodsare developed forthe maximumpreservingimmersed

in-terfacemethodappliedtoellipticandparabolicinterfaceproblems. Forellipticinterfaceproblems,

the multigridsolverdevelopedinthispaperworkswhilesomeothermultigridsolversdonot. For

diusion and reaction equations, wehave developed the second ordermaximumpreservingnite

dierenceschemeinthispaper. WeusetheCrank-Nicolsonschemetodealwiththediusionpart,

andanexplicitschemeforthereactionpart.Numericalexamplesarealsopresented.

Keywords. interfaceproblems,diusionandreactionequation,multigridmethod,

discontin-uouscoeÆcients,quadraticoptimization.

AMSsubject classications.65N06,65N50

1. Introduction. In[6],themaximumprinciplepreservingschemeisproposed

for ellipticinterfaceproblems. The resultinglinearsystem ofequations from the

-nitedierence scheme haspositiveornegativedenite symmetricpartbut maynot

besymmetric. Available multigrid solversmay notwork eÆciently to solvethe

re-sultinglinearsystem. Inthispaper,weproposeamultigridmethodwhichisdesigned

particularlyforinterfaceproblems.

Inthispaper,wealsodevelopamaximumprinciplepreservingschemefordiusion

and reaction equations with a xed and closed smooth interface in the solution

domain,seeFig.1foranillustration. Thegoverningequationsare

u

t

+a(x;t)ru=r( ru)+f; x2= +

[ ; (1.1)

[u]j =w(s); [u

n

]j =v(s) (1.2)

u(x;0)=u

0

(x); u(x;t)j

@

=g(t); (1.3)

where thecoeÆcients (x;t)

min

>0, a(x;t;u) =(

1 ;

2

), f(x;t) are piecewise

continuousbut may haveanite jumpacross , ands isthearc-length

parameteri-zationoftheinterface . Thejump isdened asthedierenceof thelimitingvalues

oftwodierentsidesoftheinterface,forexample

[u]

jX2

= lim

x!X;X2 +

u(x;t) lim

x!X;X2

u(x;t)=u +

u :

For simplicity of the discussion, we assume a Dirichlet boundary condition for the

solutionandarectangulardomain. Thenaturaljumpconditionacrosstheinterface

is [u] = 0, and [u

n

] = 0 as in the example of heat conduction in a composite

materialwithoutasource/sinkalongtheinterface. However,wemakeourdiscussion

moreexiblebyallowingnon-homogeneousjump conditions.

Thesolutionto theinterface problemis in H 1

() but notin H 2

(). Formany

applications, for example, piecewisecoeÆcients, it is reasonableto assume that the

The rstauthor was supportedin part bya DOE grant DE-FG03-96ER25292. The second

authorwassupportedinpartbyanAROgrant,39676-MA,andanNSFgrant,DMS-96-26703

y

Department of Applied Mathematics, University of Washington, Seattle, WA 98195.

([email protected].)

z

Center forResearchinScienticComputation&DepartmentofMathematics, NorthCarolina

(2)

−3

−2

−1

0

1

2

3

−3

−2

−1

0

1

2

3

+

=

+

[

+

=()

Fig.1.1. (a). Adiagramof arectangulardomain = +

[ withanimmersed interface

. ThecoeÆcientssuchas(x)etc. mayhaveajumpacrosstheinterface. (b). Adiagramofthe

local coordinatesin thenormal and tangentialdirections,where is theanglebetween thex-axis

andthenormaldirection.

solutionispiecewise smoothexcludingtheinterface . Typically,there isajump in

thenormalderivativeofthesolution.

Whilea niteelementmethod withabody-tted gridcanbe usedto solvethe

problem,weproposeanumericalmethodthatusesCartesiangrids. Wereferthe

read-erstothereferencesin[6]foranincompleteoverviewofdierentnumericalmethods

forellipticinterfaceproblems. ThepotentialadvantageofCartesiangridmethodsis

toavoidthemeshgenerationprocesswithoutsacricingaccuracyand stability. Our

goalistodevelopsecondordermethodsincontrasttotherstorderghostuidsharp

interfacemethodin[7].

2. Themaximumprinciplepreservingschemefordiusionandreaction

equationswithaninterface. Themaximumprinciplepreservingschemeforelliptic

interfaceproblems isproposedin [6]and will notberepeatedhere. Wewill explain

thealgorithmforthediusion andreactionequation.

Weassumethedomainis[a; b][c; d],anduseauniformgrid

x

i

=a+ih; i=0;1;;M; y

j

=c+jh; j=0;1;;N; (2.1)

anddenotethetimestepsizebyt.

2.1. The time discretization. The nite dierence scheme is based on the

prediction-correctionCrank-Nicolsondiscretization

u n+1

u n

t

+(ar

h u)

n+ 1

2

= 1

2

(r

h r

h u)

n

+(r

h r

h u)

n+1

+f n+

1

2

;

(2.2)

where

(ar

h u)

n+ 1

2

= 3

2 (ar

h u)

n 1

2 ( ar

h u)

n 1

; (2.3)

r

h

isthediscretegradient,andt n+

1

2

=t n

+t=2. Thisdiscretizationissecondorder

accurate in time. The diusion term is discretized implicitly so that we can take

largetimesteps,whilethereactiontermisdiscretizedexplicitlysothatsecondorder

(3)

i j

points in the centered ve-point stencil are on the same side of the interface, the

discreizationis thestandardone

r

h U

ij =

U

i+1;j U

i 1;j

2h ;

U

i;j+1 U

i;j 1

2h

; (2.4)

(r

h r

h )U

ij =

1

h

i+1=2;j (U

i+1;j U

ij )

h

i 1=2;j (U

i;j U

i 1;j )

h

(2.5)

+ 1

h

i;j+1=2 (U

i;j+1 U

i;j )

h

i;j 1=2 (U

i;j U

i;j 1 )

h

;

wherewehaveomittedthetimeindexforsimplicity.

At an irregular grid point where the centered ve-point stencilconsists of grid

pointsfromdierentsidesoftheinterface ,thediscretizationisdoneusingamethod

ofdeterminedcoeÆcients. Welet

(ar

h U

ij )=

n

s

2

X

k =1

k U

i+ik;j+jk Q

ij

; (2.6)

(r

h r

h )U

ij =

n

s

1

X

k =1

k U

i+ik;j+jk C

ij

; (2.7)

where n

s

1 and n

s

2

arethenumberof gridpoints in thenite dierencestencil,and

U

ij

is the approximation to the solution u(x;y) in (1.1)-(1.3) at (x

i ;y

j

). The sum

overkinvolvesanitenumberofpointsneighboring(x

i ;y

j

). Soeachi

k ;j

k

willtake

valuesinthesetf0;1;2g. ThecoeÆcients

k

andtheindicesi

k ;j

k

willdepend

on(i;j),sotheseshould reallybelabeled

ijk

;etc.,butforsimplicityofnotationwe

willconcentrateonasinglegridpoint(x

i ;y

j

)anddropthese indices.

Our criteria is to choose the coeÆcients to minimize the truncation error and

maintain the stability. The procedure to set the system of equations for the

un-determinedcoeÆcientsisdiscussedinthefollowingsubsections.

2.2.1. The local coordinates and interface relations. It is reasonableto

assume that the solution is piecewise smooth. The discontinuities in the solution

or/andthederivativesoccuralongtheinterface .

Inorder todetermine thenite dierencecoeÆcients

k , and

k

atan irregular

grid point (x

i ;y

j

), we choose the orthogonal projection (x

i ;y

j ) of (x

i ;y

j

) on the

interface ,oranypoint(x

i ;y

j

)2 that isclose to(x

i ;y

j

). Thelocal coordinates

inthenormalandthetangentialdirectionsare

= (x x

i

)cos+(y y

j )sin;

= (x x

i

)sin+(y y

j )cos:

(2.8)

Inaneighborhoodofthepoint(x

i ;y

j

),theinterface canbeparameterizedas

=(); with (0)=0; 0

(0)=0: (2.9)

Thecurvatureoftheinterfaceat(x

i ;y

j )is

00

(0).

Assume that theirregulargridpoint(x

i ;y

j

)2 . Inourmethod, the discrete

formof(2.2)-(2.3)istheapproximationtotheoriginaldierentialequationat(x

i ;y

(4)

insteadof (x

i ;y

j

). For example,f n+ 2 is ff g n+ 1 2 = lim (x;y)!(x i ;y j );(x;y)2

f(x;y;t n

+t=2):

Bydierentiating thejump conditions(1.2) along the interfacewith respect to

thearc-lengths,whichis inthelocal coordinates,togetherwith(2.9),wehavethe

followingjump relations(see[4]forthederivation),

u +

=u +w;

u +

=u

+ v + ; u + =u +w s ; (2.10) u + =u

+(1 ) 00 u 00 +

v+w

ss ;

u +

=u

+ + + u

+(1 ) 00 u + ( + ) 2 v+ 00 w s + v s + ;

where = = +

, w

s and w

ss

arethe rst and second order derivativesof w with

respecttothearc-lengthsalongtheinterface. Likewise,v

s

istherstderivativeofv

withrespectto thearclengthparameters. With the localcoordinates,the original

dierentialequationcanbewrittenas

u t +~ 1 u +~ 2 u =(u +u )+ u + u

+f; (2.11)

where ~ 1 = 1

cos+

2

sin; ~

2

=

1

sin+

2

cos; (2.12)

andu

andu

arethedirectionalderivativeofuin thenormalandtangential

direc-tions. Therefore [u t +~ 1 u +~ 2 u

]=[(u

+u )+ u + u

+f]: (2.13)

Usingthejumprelationsin (2.10)andaftersomemanipulations,weget

u +

=u

+( 1)u

+ ( 1)

00 + + +~ + 1 ~ 1 + ! u + [~ 2 ] + u + ~ + 2 + + w s w ss (2.14) + 1 + w t + 00 + + ~ + 1 + ( + ) 2 v [f] + :

Thuswehaveexpressedallthequantitiesofthesolutionuuptosecondorder

deriva-tivesfrom+sideintermsofthosefromthe sideoftheinterface .

2.2.2. Determining the discretization of the diusion term using the

maximum principle preserving scheme. As we stated earlier in this paper, if

the irregular grid point (x

i ;y

j

(5)

(x

i ;y

j

)insteadof(x

i ;y

j

). Thetruncationerrorofthenitedierenceapproximation

(2.7)tothediusiontermin(1.1)is

T ij = n s 1 X k =1 k u(x i+i k ;y j+j k ;t) C

ij

( r(ru)) : (2.15)

The truncation error is evaluated at (x

i ;y

j

). The grid points involved are from

outside, +

,andinside, ,oftheclosedinterface . UsingtheTaylorexpansionat

(x i ;y j

),wecanwrite

u(x

i+ik ;y

j+jk

;t)=u(

k ;

k ;t)=u

+ k u + k u + 1 2 2 k u + k k u + 1 2 2 k u +O(h 3 );

wherethe+or signischosendependingonwhether(

k ;

k

)liesonthe+or side

of . Thereforethetruncationerrorcanbewritten as

T

ij =a

1 u +a

2 u + +a 3 u +a 4 u + +a 5 u +a 6 u + +a 7 u +a 8 u + +a 9 u +a 10 u + +a 11 u +a 12 u + C ij +

r(ru)

:

Thequantities u

,u

, , arethe limitingvaluesof thefunctions at (x i ;y j )from

+sideor sideof theinterface. ThecoeÆcientsa

j

depend onlyonthepositionof

thestencilrelativetothe interface. Theyareindependent ofthefunctions uandf.

IfwedenetheindexsetsK +

andK by

K

=fk: (

k ;

k

)isonthesideof g;

thenthea

j

aregivenby

a 1 = X k 2K k ; a 2 = X k 2K + k ; a 3 = X k 2K k k ; a 4 = X k 2K + k k ; a 5 = X k 2K k k ; a 6 = X k 2K + k k ; a 7 = 1 2 X k 2K 2 k k ; a 8 = 1 2 X k 2K + 2 k k ; a 9 = 1 2 X k 2K 2 k k ; a 10 = 1 2 X k 2K + 2 k k ; a 11 = X k 2K k k k ; a 12 = X k 2K + k k k : (2.16)

Usingthe interfacerelations(2.10) and(2.14), weeliminate thequantitiesfrom one

(6)

T ij = (a 1 +a 2 )u +

( a 3 +a 4 +a 8 ( 1) 00 + + +~ + 1 ~ 1 + ! +a 10 (1 ) 00 +a 12 + + u + a 5 +a 6 +a 8 [~ 2 ] + +a 12 (1 ) 00 u + a 7 +a 8 u + a 9 +a 10 +a 8

( 1) u

+fa 11 +a 12 gu +( ^ T ij C ij )+; (2.17) where ^ T ij =a 2 w+ a 6 +a 8 ~ + 2 + + w s +(a 10 a 8 )w ss + a 8 + w t + 1 + a 4 +a 8 00 + ~ + 1 + + a 10 00 a 12 + + v (2.18) +a 12 1 + v s a 8 [f] + :

Tominimizethemagnitudeofthetruncationerror,weshould set

a 1 +a 2 = 0 a 3 +a 4 +a 8 ( 1) 00 + + +~ + 1 ~ 1 + ! +a 10 (1 ) 00 +a 12 + + = a 5 +a 6 +a 8 [~ 2 ] + +a 12 (1 ) 00 = a 7 +a 8 = a 9 +a 10 +a 8

( 1) =

a 11 +a 12 = 0: (2.19)

If we can nd f

k

gsuch that the linear system of equations is satised,wehavea

consistentdiscretization for thediusion term but we cannotguaranteethe

stabil-ity. The stability condition can be guaranteed, however, by enforcing the discrete

maximumprinciple

k

0 if (i

k ;j

k

)6=(0;0);

k

<0 if (i

k ;j

k

)=(0;0):

(2.20)

In order to solve (2.19)-(2.20), we set-up the following quadratic optimization

problemtodeterminethediscretizationforthediusionterm

min 1 2 k gk 2 2

; s:t: (2.21)

A=b;

k

0; if (i

k ;j

k

)6=(0;0)

k

<0; if (i

k ;j

k

(7)

where g 2R 1

, and A =b is the systemoflinear equations(2.19). Naturallywe

wanttochoose

k

in asuch awaythattheybecomethecoeÆcientsofthestandard

ve-pointcentral dierencescheme if +

= is aconstant. This canbedone by

selectingthevectorg as

g

k =

i+ik;j+jk

h 2

; if (i

k ;j

k

)2f( 1;0);(1;0);(0; 1);(0;1)g;

g

k =

4

i;j

h 2

; if (i

k ;j

k

)=(0;0); g

k

=0; otherwise:

(2.23)

Wechoosen

s1

=9whichseemstoworkverywell. In[6],wenumericallydemonstrated

thatthesolutiontotheoptimizationproblemhasasolutionifhissuÆcientlysmall.

We use the QL code developed by K. Schittkowski [8] to solve the optimization

problem.

OnceweknowthecoeÆcientsf

k

g,thecorrectiontermthenisC

ij =

^

T

ij ,where

^

T

ij

dependsonf

k

gandthejumpconditions.

2.2.3. Determinethe discretizationforthe reactionterm. Borrowingan

ideafromtheprojectionmethodfortheNavier-Stokesequations,see[3]forexample,

weuseanexplicitdiscretizationforthereactiontermsinceitinvolvesonlyrstorder

derivativesofthesolution. Thetruncationerrorofthenitedierenceapproximation

(2.6)tothereactiontermat(x

i ;y

j )is

T r

ij =

n

s

2

X

k =1

k u(x

i+i

k ;y

j+j

k ;t) Q

ij

(aru) : (2.24)

Aswementionedin[4,6],wecanrequirethetruncationerrortobeO(h)atirregular

grid pointswithout aectingsecond order accuracy. Thereforeweuse thestandard

centeredve-pointstencil(n

s

2

=5) andthelinearsystemofequationsis

a

1 +a

2 = 0

a

3 +a

4

= ~

1

a

5 +a

6

= ~

2

(2.25)

where we have neglected higher order terms of h. Note that the a

k

's are literally

dened in (2.16) with

k

being substituted with

k and n

s

1

beingsubstituted with

n

s

2

. Thesolutionto thelinear systemof equations isalso dierent. Thesystemis

anunder-determinedsystemandthesolutionisdened astheleastsquaressolution

withtheleastsquare2-norm. Thecorrectiontermthenis

Q

ij =a

2 w+a

6 w

s +

a

4

+

v; (2.26)

wherewehaveignoredhigherordertermsofh.

2.2.4. The CFL restriction. Since the reactionterm is discretized using an

explicitschemeandthemaximumdistancefrom (x

i ;y

j )to(x

i ;y

j )is

p

2h,theCFL

restrictionforthetimestepsizeis

t

h

p

2kak

2

(8)

in thissectionis consistent. Thelocaltruncation errorsareofO(h 2

)at regulargrid

points, and of O(h) at irregular grid points, or along the interface. We expect the

globalaccuracyisofO(h 2

)sincewecanallowoneorderlowerapproximationalonga

boundarywithoutaectingglobalaccuracy. Thestabilityoftheschemeisguaranteed

bythesignconstraintsofthescheme.

3. Multigrid method. In this section, we describe a multigrid method that

is appropriatefor solvingthe linear systemsthat arise from problems with internal

interfaces that have been discretized using the methods described in Section 2 for

parabolic problems from time t n

to t n+1

, and in [6] for elliptic interface problems

usingthemaximumprinciplepreservingschemes.

Wedenotethelinearsystemto besolvedonthenestgridasA h

u h

=f h

where

thelefthandsideofthisequationateachgridpointcanbepictoriallyrepresentedby

the9-pointstencilwiththenumberingschemegivenbelow:

8 5 9

o o o

1 2 3

o o o

6 4 7

o o o

Theequationfortheunknownatthecenter ofthestencilisthengivenby

1 u

1 +

2 u

2 +

3 u

3 +

4 u

4 +

5 u

5 +

6 u

6 +

7 u

7 +

8 u

8 +

9 u

9 =f

2

(3.1)

where the'sare thecoeÆcientsin therowof A h

correspondingto theunknownat

thecenterofthestencil.

Thecomponentsofthemultigridmethodare thesmoother,thechoiceof coarse

grid equations, theinterpolation operator,and therestriction operator. We discuss

eachinturnbelow.

3.1. The Smoother. A simplepointGauss-Seidel smoother isused. On each

gridlevel,thecoarsegridpointsaresmoothedrst,theverticaledgenegridpoints

aresmoothedsecond,thehorizontaledgenegridpointsaresmoothedthird,andthe

negridpointsin thecenterofacellaresmoothedlast. Thecodehastheoptionto

continuesmoothing(bothpre-andpost-smoothing)untilstallingoccursortosmooth

withaxednumberofpre-and axednumber(canbeadierentnumber)of

post-steps. For theproblems wereportin thispaper,weused 2pre-and2post-smooths.

Wefoundthepost-smoothstobecrucialtothesuccessofthemethod.

3.2. The Coarse Grid Problem. Let u~ h

be the approximation to u h

after

pre-smoothing the problem A h

u h

= f h

. Then the error equation is A h

e h

= r h

,

wheretheresidualr h

=f h

A h

~ u h

mustbeapproximatedonagridof size2h. The

correspondingcoarsegridequationisA 2h

e 2h

=r 2h

wherethecoarsegridoperatoris

givenbytheusualGalerkinchoice,

A 2h

=R A h

I h

2h

(9)

where R isthe restrictionoperator,andI

2h

is theinterpolation operator. Likewise,

the righthand side of the coarse grid equation is givenby restrictingthe ne grid

residualtothecoarsegridby

r 2h

=R r h

: (3.3)

3.3. TheInterpolationOperator. Weusetwodierentinterpolationschemes.

Oneisfortheregulargridpointsandonefortheirregularpoints. Recallagridpoint

is termed irregular ifits nine point stencilrepresents connections to grid points on

dierentsidesoftheinternalinterface.

3.3.1. Interpolation at Regular Points. Many authors, (see for example

Dendy, [2], and Briggs, et.al. [1] and the references therein), have developed an

operatorinducedinterpolationscheme. Fortwodimensionalproblems,giventhe

val-ues of the error e 2h

at coarse grid points, we need to interpolate I h

2h e

2h

to nd an

approximationtoe h

atallnegridpoints. Forcoarsegridpoints(thecornersofgrid

cells), the value of e 2h

is simply copied to be the value of e h

. Forne grid points

that are on a vertical cell edge, the operator induced scheme would start with the

error-residualequationassociatedwith(3.1),

1 e

1 +

2 e

2 +

3 e

3 +

4 e

4 +

5 e

5 +

6 e

6 +

7 e

7 +

8 e

8 +

9 e

9 =r

2

0; (3.4)

wheretheresidual,r

2

,forthispurposeis assumedsmallrelativeto theerrorsin the

equation. This is avalidassumption for smootherror after thepre-relaxation step.

An equation for e

2

in terms ofe

4 and e

5

is desired if weare interpolating to e

2 by

using thecoarsegriderrorvaluesat e

4 ande

5

. Now,equation(3.4)could givesuch

anapproximationif alltheerrorson theleft handside couldbeestimated in terms

ofe

4 and e

5

. Ataregularpoint, alltheseneighborgridpointsare onthesameside

oftheinternalinterface,soitmakessensetouseTaylorapproximationstoexpresse

1

ande

3

intermsofe

2

,toexpresse

6 ande

7

intermsofe

4

,andtoexpresse

8 ande

9 in

termsofe

5

. Thisleadstothefollowingequationfore

2

in termsofe

4 ande

5 :

e

2 =c

4 e

4 +c

5 e

5

(3.5)

where

c

4

= (

6 +

4 +

7 )=(

1 +

2 +

3

) (3.6)

and

c

5

= (

8 +

5 +

9 )=(

1 +

2 +

3

): (3.7)

Thesamestrategyleadstoaninterpolationformulafortheerroratthecenterof

ahorizontal edgeintermsofthecoarsegridpointsoneitherside. Weuse

e

2 =c

1 e

1 +c

3 e

3

(3.8)

where

c

1

= (

6 +

1 +

8 )=(

4 +

2 +

5

(10)

0

10

20

30

40

50

60

70

0

20

40

60

80

−30

−25

−20

−15

−10

−5

0

0

10

20

30

40

50

60

70

0

20

40

60

80

0

0.5

1

1.5

2

2.5

Fig.3.1. (a). Thediscreteerror afterpre-relaxin V-cycle1. (b). Thediscrete errorafter

pre-relaxation inV-cycle2. ThePDEis giveninSection4.1with b=:1and C =0. Noticethe

jumpinthenormal derivativeof theerrorattheinterface.

and

c

3

= (

7 +

3 +

9 )=(

4 +

2 +

5

): (3.10)

Now, with the values determined at the coarse grid points (via copy) and the

centersofverticalandhorizontaledgesbytheformulasgivenabove,theerrorsatthe

centers ofeachcell canbefound bysimplysolvingequation (3.4)fore

2

in termsof

the other interpolatedvalues. This can be written like aninterpolation formula by

castingtheresultfore

2

intermsofthefourcoarsegriderrorvaluesat thecornersof

thecell.

3.3.2. Interpolation atIrregularPoints. Atirregulargridpoints,the

inter-polation formulas given in (3.5) and (3.8) are no longer valid since the error after

thepre-relaxation stepcanalso havealargejump in itsnormalderivative,and the

approximations that were made in goingfrom (3.4)to these formulasare not

suÆ-cient. This has been veried in practice for the test problems used in Section 4.1

whereweknowtheexactsolutions. InFigures3.1and3.2,weplotthediscreteerror

rightafter thepre-relax smoothingstepis completed in therst, second,and tenth

V-cycles. Theoriginalerrorhasbeensmoothedbut alargejump stillremainsatthe

interfaceandthiscontinuesthroughoutthecomputation. InFigure3.2, wealsoplot

the negativeof the nal discrete solution u h

which also has a jump in the normal

derivativeattheinterface,ajump in attheinterface, butnojump in thevalueof

u

n .

Thestrategyweemployistodevelopaninterpolationformulaforthemidpoints

ofverticalandhorizontaledgesbyusinginformationabouttheinterfaceandmaking

thefollowingassumptionsaboutthediscreteerror.

1. The jump in the discrete errorat the internal interfaceafter pre-relaxation

is 0. That is [e h

] =0. This is reasonablesince the relaxationwill smooth

enoughforthis tobetrue. This givestherelationshipe +

=e .

2. [e h

n

]=0attheinternalinterface. Intheproblemswearesolving,thevalue

of[u

n

]isgiven,andthisinformationisbuiltintotheequationsforu h

,soas

theiterationproceedsthediscretesolutionwillbeanorderh 2

approximation

to u and will approximate this jump as well. This gives the relationship

e +

=

+

e

(11)

0

10

20

30

40

50

60

70

0

20

40

60

80

0

1

2

3

4

5

x 10

−4

0

10

20

30

40

50

60

70

0

20

40

60

80

−40

−35

−30

−25

−20

−15

−10

−5

0

Fig.3.2. (a). Thediscreteerror afterpre-relaxin V-cycle10. (b). Thevalue of ~

u h

after

V-cycle10.ThePDEisgiveninSection4.1withb=:1andC=0. Noticethejumpinthenormal

derivativeoftheerrorattheinterfaceandthejumpinthesolutionattheinterface.

3. [e h

]=0. Thisisalsoobservedinpractice,andthecorrespondingjumpinthe

solutionofthePDE,[u

]isalso0.

4. Wecannotassumethat e h

n

willbesmoothacrosstheinterface.

Wenowderivetheinterpolationformulaforthemidpointofaverticaledgethat

cutsthroughthe interface. Welook for aformulafor e

2

of theform (3.5). We rst

expand each sideof (3.5)aboutapoint(x

;y

)on theinterface, takingcare to use

thevaluesontheappropriatesideof theinterface. Wecenterthecoordinatesystem

atthisexpansionpoint,andusethenormalandtangentialcoordinates andgiven

by(2.8). Thisleadsto

e +

2

2 e

+

2 e

=c

4 (e +

4

4 e

+

4 e

)+c

5 (e +

5

5 e

+

5 e

) (3.11)

toO(h 2

),where

i

=1ifthegridpointisinsideorontheinterfaceand

i =

+

ifthe

gridpointisoutsidetheinterface. A similarequationholdsforhorizontal midpoints

withthesubscripts4and5replacedby1and3. Sincethejumpconditionshavebeen

applied,wenowconvertbacktoxandycoordinatesusing(2.8)andtherelationships

e

=e

x

cos()+e

y

sin() (3.12)

and

e

= e

x

sin()+e

y

cos(): (3.13)

Afterdoingthis,wewouldliketobeabletosetthecoeÆcientsofe ,e

x ,ande

y

tozero. Thiswouldgive3equationsbutweonlyhavethe2unknowns(c

4 andc

5 for

verticalmidpoints, orc

1 and c

3

for horizontal midpoints). Before goingfurther, we

writedownthesethreeequations.

e :c

4 +c

5 =1

e

x :c

4 (

4

4

c

4 s)+c

5 (

5

5

c

5 s)=(

2

2

c

2 s)

e

y :c

4 (

4

4 s+

4 c)+c

5 (

5

5 s+

5 c)=(

2

2 s+

2

(12)

For midpoints of vertical edges, we use the rst and third equations; thereby

forcing the coeÆcients of e and e

y

to vanish. Note that we are hoping for the

secondequationto benearlysatisedwithoutitsenforcement. Thisisdenitely the

casewhen nointerfaceis present(all

i

=1). This givesthefollowingvaluesforc

4

andc

5 :

c

5 =

(

4 s

2

+c 2

)(y

y

4 )+(

2 s

2

+c 2

)(y

2 y

)

(

4 s

2

+c 2

)(y

y

4 )+(

5 s

2

+c 2

)(y

5 y

)

(3.15)

andc

4

=1 c

5

. Thevaluess 2

andc 2

aresin 2

()andcos 2

(),respectively.

Formidpointsofhorizontaledges,weusetherstandsecondequations;thereby

forcingthecoeÆcientsofe ande

x

tovanish. Notethat wearehopingforthethird

equation to be nearlysatised without its enforcement. This is denitely the case

whennointerfaceis present. Thevaluesobtainedforc

1 andc

3 are:

c

1 =

(

3 c

2

+s 2

)(x

x

3 )+(

2 c

2

+s 2

)(x

2 x

)

(

3 c

2

+s 2

)(x

x

3 )+(

1 c

2

+s 2

)(x

1 x

)

(3.16)

andc

3

=1 c

1

. Thevaluess 2

andc 2

aresin 2

()andcos 2

(),respectively.

Thisinterpolationschemeallowstheerrortohavejumpsinthedirectionnormal

totheinterface. Theerrorisnotassumedtovarystrictlywithy(forvertical

interpo-lation)orstrictly withx(forhorizontalinterpolation). Thejump conditionsrelative

to and areimposed.

Theonlyremainingissueishowtointerpolatethecentersofthecells. Sincewe

nowhaveaformulafor thecellcorners(copythecoarsevalue)and theverticaland

horizontalmidpoints,wecansolve(3.4)tondthevalueofe

2

forcellcenters. Thisis

thesamestrategyadoptedforcellcentersforregularpoints. Hencetheoverallscheme

takesadvantageoftheinterfaceinformationaswellasthat ofthePDEoperator.

3.4. The Restriction Operator. By discretizing the PDEs as described in

Section2,weguaranteethattheproblemA h

onthenestgridisdiagonallydominant.

This does not however, guarantee that A 2h

is diagonally dominant. For problems

withlargejumps attheinternalinterface,thechoiceofR=(I h

2h )

T

willnotleadtoa

diagonallydominantproblem ortoaproblem that is solvedquickly withmultigrid.

Whatistrue,however,isthat simpleinjectionwillledtoadiagonallydominantA 2h

matrix. Theproofisverysimpleandwill notbepresentedhere. Wehavefoundthis

choice for R , combined with ourinterpolation scheme to be very eectivefor these

interfaceproblems.

4. Numericalresults. Wehaveperformedanumberofnumericalexperiments.

ThecomputationsaredoneusingeitheraSun'sUltra-1oraDecAlphaworkstation.

Thelinearsystemofequationsissolvedusingthemultigridmethod. Theinterfaceis

aclosed curvein thesolutiondomainandisexpressedin termsoftheperiodiccubic

splineinterpolationdevelopedin[5]. Theimplementationofthemethodsissequential

and not optimized. In this section, the following notations are used: m = n is the

numberof grid lines in thex- andy- directions; n

1

is the number ofcontrol points

used in thespline interpolationto representthe interface ; n

coarse and n

(13)

isused;n

l

isthenumberoflevelsusedforthemultigridmethod.

4.1. Numericalresultsforellipticproblems. Firstwepresentourmultigrid

resultsforellipticinterfaceproblems. Weconsidertheellipticequation

r((x;y)ru(x;y)) = f(x;y): (4.1)

Inthis example,the interfaceis the circlex 2

+y 2

= 1

4

within thecomputation

domain 1x;y1. Thevalueof is

(x;y)= (

x 2

+y 2

+1; ifx 2

+y 2

1

4 ,

b; ifx

2

+y 2

> 1

4 .

(4.2)

Thesourcetermis

f(x;y)=8(x 2

+y 2

)+4: (4.3)

Thetruesolutionis

u(x;y)= (

r 2

; ifr

1

2 ,

(1 1

8b 1

b )=4+(

r 4

2 +r

2

)=b+C log(2r)=b; ifr> 1

2 :

(4.4)

Inthisexample,wehavevariableanddiscontinuouscoeÆcients. Thejumpconditions

are

[u]=0; [u

n

]= 2C ; []=5=4 b; [f]=0: (4.5)

ThediÆcultyoftheproblemcanbecontrolledbydecreasingthevalueofbsincethe

jump inthenormalderivativeofthesolutionisgivenby

[u

n

]=(2C+5=4)=b 1: (4.6)

WeuseDirichletboundaryconditions.

Tables4.1,4.2,and4.3 showtheresultsofthemultigridsolverforvarious levels

n

l

and valuesofb. Notethat in Table4.2 whereb =0:1, boththesolutionand the

uxarecontinuous,buthasanitejump. Themaximumerroroverallgridpoints,

kE

n k

1 =max

i;j ju(x

i ;y

j ) U

ij j;

ispresented. Theorder ofconvergenceiscomputedfrom

order=

log( kE

n1 k

1 =kE

n2 k

1 )

log (n

1 =n

2 )

;

whichisthesolutionoftheequation

kE

n k

1 =Ch

order

with two dierent n's. The fourth column in the Tables gives the number of

V-cyclesto reachthe convergence criteria,and the fthcolumn givesthe average rate

ofmultigridconvergencecalculatedas

rate(k)=e log(jjr

k

jj

2 =jjr

0

jj

2 )

k

(14)

Multigridresults. Theparameters aren

coarse

=8, C =0:0, b=1:25. Thediscrete system

wassolved toa 2-normresidualtoleranceof10 6

. Constantnumberofiterationswithgridsizeis

conrmed.

n

finest n

1 n

l

V's Rate kE

n k

1

Order

32 40 3 4 .02 6:042010

3

64 80 4 5 .02 1:455410

3

2:0536

128 160 5 5 .02 3:559810

4

2:0315

256 320 6 5 .02 8:770710

5

2:0210

512 640 7 5 .02 2:220410

5

1:9819

Table4.2

Multigridresults. Theparameters arencoarse =8, C =0:0, b=0:10. Thediscrete system

wassolved toa 2-normresidualtoleranceof10 6

. Constantnumberofiterationswithgridsizeis

conrmed.

n

finest n

1 n

l

V's Rate kE

n k

1

Order

64 80 4 12 .21 2:596010

2

128 160 5 12 .21 6:398110 3

2:0206

256 320 6 13 .21 1:632210 3

1:9708

512 640 7 14 .21 4:268110 4

1:9352

Table4.3

Multigridresults. Theparametersaren

coarse

=16,C =0:0, b=:005. Thediscretesystem

wassolved toa 2-normresidualtoleranceof10 6

. Constantnumberofiterationswithgridsizeis

conrmed.

n

finest n

1 n

l

V's Rate kE

n k

1

Order

64 80 3 17 .29 6:06310

1

128 160 4 21 .36 1:44910 1

2:065

256 320 5 32 .47 3:61910 2

2:002

512 640 6 42 .54 9:14810 3

(15)

usedanincompleteCholeskysmoother. Thenumberofiterationsrequiredtosolvethe

problemwasaround275forallthelevels,muchworsethantheresultsweobtained.

Also,ourmultigridsolverwasabletosolvetheproblemwhenb=10 6

in32iterations

with arate of :43 on a gridof size 256256and in 36 iterationson agrid of size

256256; whereas, the algebraic multigrid solver failed for this value of b. For a

given value of (x;y), the V-cycle ratesare constantas theproblem size increases.

OurexperimentsshowthenumberofV-cyclesisnotquiteconstantastheratio = +

increases,buttendstovarylinearlywiththelogarithmoftheratio. Thatis,V-cycles

=c

1 log

10

( =

+

)+c

2 .

4.2. Numerical results for diusion and reaction equations. Inthis

ex-ample, theinterfaceis againthe circlex 2

+y 2

= 1

4

within the computationdomain

1 x;y 1. The heat conductivity is the same as (4.2). Let g(x;y) be the

piecewisefunctiondened in(4.4)and

f(x;y)=h(t)

1 @g

@x +

2 @g

@y 8(x

2

+y 2

) 4

+h 0

(t)g; (4.8)

whereh(t)isafunction ofourchoice. Thejump conditionsare

[u]=0; [u

n

]=h(t)2C : (4.9)

Thesolutiontothediusion andreactionequations(1.1)-(1.3)is

u(x;y)=h(t)g(x;y): (4.10)

WeuseDirichletboundaryconditionsandtheinitialconditionfromtheexactsolution.

Table4.4showstheresultsofthegridrenementanalysisofourmethodfordierent

gridsizes. Thelinear systemateach timestep wassolvedusing boththemultigrid

method describedin Section 3and analgebraicmultigrid method that uses

incom-pleteCholesky smoothing. Both multigrid methods solvedthe systemsequallywell

(requiringbetween3and5V-cycles). Thesesystemsweremorediagonallydominant

thattheellipticproblemsreportedin Section4.1.

Table4.4

Thegridrenementanalysis. Theparametersareh(t)=cost, 1=100,2=1,ncoarse=9,

C=0:1,b=10,thenaltimeist=1:0. Secondorderconvergenceisconrmed.

n

finest n

1 n

l

kE

n k

1

order

32 40 3 7:560210 4

64 80 4 1:379210 4

5:48216

128 160 5 2:849610 5

2:2750

256 320 6 6:578810 6

2:1147

A remark. ThemethodhereisrecommendedformodestconvectioncoeÆcient

kak since this term was treated explicitly. If kak is very large, then the time step

is small. In this case, some may prefer to use a upwind scheme to deal with the

(16)

preservesthediscretemaximumprincipleforadiusionandreactionequation

involv-ingaxedinterfaceandpresentedamultigridmethodforsolvingthediscretesystem

ofequationsobtainedfromthemaximumprinciplepreservingschemebothforelliptic

andparabolicpartialdierentialequations.

REFERENCES

[1] W.L.Briggs,V.E.Henson,andS.F.McCormick. AMultigridTutorial. SIAMPublication,

2000.

[2] Jr.J.E.Dendy.Blackboxmultigrid.J.Comput.Phys.,48:336{386,1982.

[3] M-C.LaiandZ.Li.Theimmersedinterfacemethodforthenavier-stokesequationswithsingular

forces. J.Comput.Phys.,inpress,2001.

[4] R.J.LeVequeandZ.Li.Theimmersedinterfacemethodforellipticequationswithdiscontinuous

coeÆcientsandsingularsources. SIAMJ.Numer.Anal.,31:1019{1044,1994.

[5] Z.Li.TheImmersedInterfaceMethod|ANumericalApproachforPartialDierential

Equa-tionswithInterfaces. PhDthesis,UniversityofWashington,1994.

[6] Z.LiandK.Ito. Maximumprinciplepreservingschemesforinterfaceproblemswith

discontin-uouscoeÆcients.SIAMJ.Sci.Comput.,inpress.

[7] X.Liu,R.Fedkiw,andM.Kang.AboundaryconditioncapturingmethodforPoisson'sequation

onirregulardomain. J.Comput.Phys.,160:151{178,2000.

[8] K. Schittkowski. QL-quadratic Programming, version 1.5, 1991.

References

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