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Advanced numerical methodsfor nonlinear advection-

diffusion-reaction equationsPeter Frolkovič, University of Heidelberg

2Kiel, 23.6.2006 peter.frolkovic@uni-hd.de

Content

Motivation and background R3T

Numerical modellingadvectionadvection + retardation + reaction advection + nonlinear retardationadvective level set equation

3Kiel, 23.6.2006 peter.frolkovic@uni-hd.de

Motivation and BackgroundUG software toolbox - Unstructured Grids

“... to simplify the implementation of parallel adaptive multigrid method on unstructured grid for complex engineering applications.”

P. Bastian et. al. 1997

4Kiel, 23.6.2006 peter.frolkovic@uni-hd.de

Motivation and BackgroundLocally adapted multilevel grid

conformingmultilevel grid structure

coarsening possible

5Kiel, 23.6.2006 peter.frolkovic@uni-hd.de

Motivation and Background

D3F application based on UG (1995-1998)

Distributed Density Driven Flownumerical modelling of gravity induced flows near saltdomes

Frolkovic, De Schepper: Numerical modeling of convection dominated transport coupled with density driven flow in porous media;Advances in Water Resources, 2001

6Kiel, 23.6.2006 peter.frolkovic@uni-hd.de

Motivation and Background

R3T application based on UG(1999-2004)

Reaction Retardation Radionuclides Transportnumerical modelling of radioactive contaminant transport

F., Lampe, Wittum: r3t - software package for numerical simulations of radioactive contaminant transport in groundwater; WiR 2005

peter.frolkovic@uni-hd.de7Kiel, 23.6.2006

R3T

234

Np U Pu238

U U

238 238

233

RRRT - Radionuclides Reactions (Decay)

∂tCi=

∑k λkiCk

− λijCi

decay chains of up to 40 nuclides

peter.frolkovic@uni-hd.de8Kiel, 23.6.2006

R3TRRRT - Transport

Nuclides in flowing groundwater

Np U Pu238

U U

238 238

233 234

convection-dispersion-diffusion PDEs (up to 40)

∂tCi + "V ·∇Ci − ∇ · Di("V )∇Ci = . . .

peter.frolkovic@uni-hd.de9Kiel, 23.6.2006

R3TRRRT - Retardation of transport

Nuclides in flowing groundwater

Np U Pu

immobilizationsorption

238

U U

238 238

233 234

up to 120 additional ordinary differential equations

∂t

(RiCi

)+ ki

(KiCi − Ci

ad

)+ . . .

10Kiel, 23.6.2006 peter.frolkovic@uni-hd.de

R3TIllustrative example (see video on my homepage)

∂t

(RiCi

)+ ki

(KiCi − Ci

ad

)+ . . .

11Kiel, 23.6.2006 peter.frolkovic@uni-hd.de

R3TLinear case

Nuclides in flowing groundwater

Np U Pu

immobilizationsorption

238

U U

238 238

233 234

∂t

(RiCi

)+ ki

(KiCi

− Ciad

)+ . . .

12Kiel, 23.6.2006 peter.frolkovic@uni-hd.de

R3T

Nuclides in flowing groundwater

Np U Pu

immobilizationsorption

U U

238

233 234

238238

Nonlinear case

∂t

(Ri(C)Ci

)+ ki

(Ki(C)Ci

− Ciad

)+ . . .

13Kiel, 23.6.2006 peter.frolkovic@uni-hd.de

R3T

∗ 0 0

0 ∗ 0

0 0 ∗

∂tU238

∂tP238

∂tU234

+

T 0 0

0 T 0

0 0 T

U238

P 238

U234

+

∗ 0 0

0 ∗ 0

∗ ∗ ∗

U238

P 238

U234

= 0

T := !u ·∇−∇ · D∇

234

U Pu

U

238 238

Sparsity of differential equations

14Kiel, 23.6.2006 peter.frolkovic@uni-hd.de

R3T

Tii Tij Tik 0 0 0 0 0 0

Tji Tjj Tjk 0 0 0 0 0 0

Tki Tkj Tkk 0 0 0 0 0 0

0 0 0 Tii Tij Tik 0 0 0

0 0 0 Tji Tjj Tjk 0 0 0

0 0 0 Tki Tkj Tkk 0 0 0

0 0 0 0 0 0 Tii Tij Tik

0 0 0 0 0 0 Tji Tjj Tjk

0 0 0 0 0 0 Tki Tkj Tkk

U238i

U238j

U238k

P 238i

P 238j

P 238k

U234i

U234j

U234k

Sparsity of discrete equations

local stiff matrix for a triangle finite element

15Kiel, 23.6.2006 peter.frolkovic@uni-hd.de

R3T

Jsparse:Daa=" *00 0*0 ***";Jsparse:Taa=" a00 0a0 00a";

234

U Pu

U

238 238

Sparse matrix storage method (Neuss, 1999)

16Kiel, 23.6.2006 peter.frolkovic@uni-hd.de

R3T - numerical modellingFinite volume methods

Grid - unstructurednumerical solution given pointwisegradient easily obtained from FE interpolation

vertex-centred finite volume method (FVM)finite volume mesh dual to finite elements

i

xx k

ijxj

i

T e

!"

"e

ik

17Kiel, 23.6.2006 peter.frolkovic@uni-hd.de

R3T - numerical modellingNumerical solution

piecewise linear, continuous

piecewise constant, discontinuous

piecewise linear reconstruction, discontinuousc(tn, x) = cn

i, x ∈ Ωi

c(tn, x) = cni + ∇|T ecn · (x − xi) , x ∈ T e

c(tn, x) = cni

+ ∇|Ωicn · (x − xi) , x ∈ Ωi

18Kiel, 23.6.2006 peter.frolkovic@uni-hd.de

Motivation and Background

Numerical modellingnumerical algorithms fit analytical model

preserving physical properties, ...stable, consistent, ...

available, simple and good in general:unstructured gridsrobust for rough data, ... (1st order schemes)

precise for smooth parts, ... (2nd order schemes)

19Kiel, 23.6.2006 peter.frolkovic@uni-hd.de

Advection-Diffusion-DispersionModel equation

∂tc +∇ · "J = 0 , "J = "V c−D∇c

20Kiel, 23.6.2006 peter.frolkovic@uni-hd.de

Advection-Diffusion-DispersionModel equation

FVM

exact integral formulation:

∂tc +∇ · "J = 0 , "J = "V c−D∇c

|Ωi|cn+1i = |Ωi|cn

i −∆tn∑

Jn+1/2ij

∫Ωi

c(tn+1) =∫

Ωi

c(tn)−tn+1∫tn

∑ ∫∂Ωi∩∂Ωj

!n · !J

21Kiel, 23.6.2006 peter.frolkovic@uni-hd.de

Advection-Diffusion-DispersionModel equation

FVM

physical property - “mass”

∂tc +∇ · "J = 0 , "J = "V c−D∇c

|Ωi|cn+1i = |Ωi|cn

i −∆tn∑

Jn+1/2ij

|Ωi|cni :≈ ∫

Ωic(tn, x) dx

22Kiel, 23.6.2006 peter.frolkovic@uni-hd.de

Advection-Diffusion-DispersionModel equation

FVM

physical property - “conservation law”

∂tc +∇ · "J = 0 , "J = "V c−D∇c

|Ωi|cn+1i = |Ωi|cn

i −∆tn∑

Jn+1/2ij

Jn+1/2ij = −Jn+1/2

ji

23Kiel, 23.6.2006 peter.frolkovic@uni-hd.de

Advection-Diffusion-DispersionModel equation

FVM

fully coupled implicit discretization

multigrid linear solver, ...

∂tc +∇ · "J = 0 , "J = "V c−D∇c

|Ωi|cn+1i = |Ωi|cn

i −∆tn∑

Jn+1/2ij

Jn+1/2ij = Jij(cn+1

i , cn+1j , · · ·)

24Kiel, 23.6.2006 peter.frolkovic@uni-hd.de

AdvectionModel equation

∂tc + ∇ ·

("V c

)= 0

25Kiel, 23.6.2006 peter.frolkovic@uni-hd.de

AdvectionMotivation - exact “simulation” (see video on my homepage)

26Kiel, 23.6.2006 peter.frolkovic@uni-hd.de

AdvectionModel equation

∂tc + ∇ ·

("V c

)= 0

27Kiel, 23.6.2006 peter.frolkovic@uni-hd.de

AdvectionModel equation

FVM∂tc + ∇ ·

("V c

)= 0

|Ωi|cn+1i = |Ωi|cn

i −∆tn∑

Vijcn+1/2ij

28Kiel, 23.6.2006 peter.frolkovic@uni-hd.de

AdvectionModel equation

FVM

physical property - “mass”

∂tc + ∇ ·

("V c

)= 0

|Ωi|cn+1i = |Ωi|cn

i −∆tn∑

Vijcn+1/2ij

|Ωi|cni :≈ ∫

Ωic(tn, x) dx

29Kiel, 23.6.2006 peter.frolkovic@uni-hd.de

AdvectionModel equation

FVM

physical property - “conservation law”

∂tc + ∇ ·

("V c

)= 0

Vij = −Vji , cn+1/2ij = cn+1/2

ji

|Ωi|cn+1i = |Ωi|cn

i −∆tn∑

Vijcn+1/2ij

30Kiel, 23.6.2006 peter.frolkovic@uni-hd.de

AdvectionModel equation

FVM

physical property - “characteristic curves”

cn+1/2ij :=?

|Ωi|cn+1i = |Ωi|cn

i −∆tn∑

Vijcn+1/2ij

∂tc + ∇ ·

("V c

)= 0

31Kiel, 23.6.2006 peter.frolkovic@uni-hd.de

Advection - 1st order schemeModel equation

FVM

Piecewise constant numerical solution

cn+1/2ij =

cni Vij > 0

cnj Vij < 0

|Ωi|cn+1i = |Ωi|cn

i −∆tn∑

Vijcn+1/2ij

∂tc + ∇ ·

("V c

)= 0

32Kiel, 23.6.2006 peter.frolkovic@uni-hd.de

Advection - 1st order schemeModel equation

FVM

physical property - “residence time”

∂tc + ∇ ·

("V c

)= 0

|Ωi|cn+1i = |Ωi|cn

i −∆tn∑

Vijcn+1/2ij

0 = |Ωi|− τi∑

max0, Vij

33Kiel, 23.6.2006 peter.frolkovic@uni-hd.de

Advection - 1st order schemeModel equation

FVM

physical property - “CFL condition”

∂tc + ∇ ·

("V c

)= 0

|Ωi|cn+1i = |Ωi|cn

i −∆tn∑

Vijcn+1/2ij

∆tn ≤ τi

34Kiel, 23.6.2006 peter.frolkovic@uni-hd.de

Advection - 1st order schemeCourant number = 1

Courant number > 1

Courant number < 1

35Kiel, 23.6.2006 peter.frolkovic@uni-hd.de

Advection - 1st order schemeFlux-based method of characteristicsDistributeMass(j, t0, τ , q)

t0 = t0 + τj ;if (t0 ≥ tn+1) then

bj = bj + τ q ;return;

if (t0 + τ > tn+1) then

bj = bj + (τ − (tn+1 − t0)) q ;τ = tn+1 − t0 ;

jm−1 = j ;for (jm−2 ∈ Λout

jm−1)

DistributeMass(jm−2, t0, τ ,vjm−1jm−2

vjm−1q) ;

return ;

F.: Flux-based method of characteristics for transport in porous media; CVS, 2002

36Kiel, 23.6.2006 peter.frolkovic@uni-hd.de

Advection and Reaction and Retardation

Courant number

Computation time

≈ 5

≈ 2.5 hours

37Kiel, 23.6.2006 peter.frolkovic@uni-hd.de

Advection and Reaction and Retardation

Courant number

Computation time ≈ 1.7 hours

≈ 15

38Kiel, 23.6.2006 peter.frolkovic@uni-hd.de

Advection and Reaction and RetardationExample of 3 radionuclides

R1=1, R2=3, R3=9, small physical dispersion

V = (1,0), small dispersion, linear decay chaininitially only 1st component non-zero

39Kiel, 23.6.2006 peter.frolkovic@uni-hd.de

Advection and Reaction and RetardationExample of 3 radionuclides

R1=1, R2=3, R3=9, small physical dispersion

2nd order Godunov method with many time steps

40Kiel, 23.6.2006 peter.frolkovic@uni-hd.de

Advection and Reaction and RetardationExample of 3 radionuclides

R1=1, R2=3, R3=9, small physical dispersion

standard operator splitting method, 2 time steps

2nd order Godunov method with many time steps

41Kiel, 23.6.2006 peter.frolkovic@uni-hd.de

Advection and Reaction and RetardationExample of 3 radionuclides

R1=1, R2=3, R3=9, small physical dispersion

flux-based method of characteristics

F.: Flux-based method of characteristics for coupled system of transport equations in in porous media; CVS, 2002

42Kiel, 23.6.2006 peter.frolkovic@uni-hd.de

AdvectionGodunov method

use exact solution of related simpler problem1D Riemann’s problem

justified by numerical hyperbolic equationse.g., 1D advection => 1st order upwind m.

High-resolution FVMpiecewise linear numerical solutionstructured grid - Leveque 2002unstructured grid? (e.g., Sonar 1993)

43Kiel, 23.6.2006 peter.frolkovic@uni-hd.de

Advection and retardationModel equation

Fast sorption (equilibrium)

linear case

R := 1 + 1−φφ ρK

R = R(x)

∂t (Rφc) +∇ ·(

#V c)

= 0

44Kiel, 23.6.2006 peter.frolkovic@uni-hd.de

Advection and retardationExample - Henry isotherm (see video on my homepage)

R = 2

45Kiel, 23.6.2006 peter.frolkovic@uni-hd.de

Advection and retardationModel equation

Fast sorption

nonlinear case

R := 1 + 1−φφ ρK

R = R(x, c)

∂t (Rφc) +∇ ·(

#V c)

= 0

46Kiel, 23.6.2006 peter.frolkovic@uni-hd.de

Advection and retardationExample - Freundlich isotherm (see video on my homepage)

R = 1 + up−1

47Kiel, 23.6.2006 peter.frolkovic@uni-hd.de

Advection and retardationNonlinear hyperbolic equation

shocks

correct speedsharp also with diffusion

rarefaction waves0

0.2

0.4

0.6

0.8

1

0.5 1 1.5 2 2.5 3 3.5

x

∂tθ + ∇ ·

(#V c

)= 0

θ = θ(c), c = θ−1(c)

F., Kačur: Semi-analytical solutions of contaminant transport equation with nonlinear sorption in 1D; Comp. Geosciences, 2006, to appear

48Kiel, 23.6.2006 peter.frolkovic@uni-hd.de

Advection and retardationImplementation (see video on my homepage)

linear sorption nonlinear sorption

49Kiel, 23.6.2006 peter.frolkovic@uni-hd.de

Advection - 1st order methodTrivial example∂tc + "V ·∇c = 0 , "V ·∇c(0, x) ≡ const

cn+1i = cn

i −∆tnconst

50Kiel, 23.6.2006 peter.frolkovic@uni-hd.de

Advection - 1st order methodConsistent for structured grid?∂tc + "V ·∇c = 0 , "V ·∇c(0, x) ≡ const

|Ωi|cn+1i = |Ωi|cn

i −∆tn∑

Vijcn+1/2ij

51Kiel, 23.6.2006 peter.frolkovic@uni-hd.de

Advection - 1st order methodConsistent for structured grid!∂tc + "V ·∇c = 0 , "V ·∇c(0, x) ≡ const

|Ωi|cn+1i = |Ωi|cn

i −∆tn∑

Vijcn+1/2ij

52Kiel, 23.6.2006 peter.frolkovic@uni-hd.de

Advection - 1st order methodNonconsistent for unstructured grid!∂tc + "V ·∇c = 0 , "V ·∇c(0, x) ≡ const

|Ωi|cn+1i = |Ωi|cn

i −∆tn∑

Vijcn+1/2ij

53Kiel, 23.6.2006 peter.frolkovic@uni-hd.de

Advection - 1st order method (200x200)t = 0

0 0.5 10

0.5

1

t = 0.19635

0 0.5 10

0.5

1t = 0.3927

0 0.5 10

0.5

1

t = 0.58905

0 0.5 10

0.5

1t = 0.7854

0 0.5 10

0.5

1t = 0.98175

0 0.5 10

0.5

1

t = 1.1781

0 0.5 10

0.5

1t = 1.3744

0 0.5 10

0.5

1t = 1.5708

0 0.5 10

0.5

1

54Kiel, 23.6.2006 peter.frolkovic@uni-hd.de

AdvectionLevel set equation

∂tc + "V ·∇c = 0 , ∇ · "V = 0

55Kiel, 23.6.2006 peter.frolkovic@uni-hd.de

AdvectionLevel set equation

FVM

|Ωi|cn+1i = |Ωi|cn

i −∆tn∑

Vijcn+1/2ij

∂tc + "V ·∇c = 0 , ∇ · "V = 0

56Kiel, 23.6.2006 peter.frolkovic@uni-hd.de

AdvectionLevel set equation

FVM

physical property - “value”

|Ωi|cn+1i = |Ωi|cn

i −∆tn∑

Vijcn+1/2ij

cni :≈ c(tn, xi)

∂tc + "V ·∇c = 0 , ∇ · "V = 0

∂tc + "V ·∇c = 0 , ∇ · "V = 0

57Kiel, 23.6.2006 peter.frolkovic@uni-hd.de

AdvectionLevel set equation

FVM

physical property - “characteristic curves”

|Ωi|cn+1i = |Ωi|cn

i −∆tn∑

Vijcn+1/2ij

cn+1/2ij := c(tn,Xij(tn))

∂tc + "V ·∇c = 0 , ∇ · "V = 0

58Kiel, 23.6.2006 peter.frolkovic@uni-hd.de

Advection - 2nd order schemeLevel set equation

FVM

physical property - “characteristic curves”

|Ωi|cn+1i = |Ωi|cn

i −∆tn∑

Vijcn+1/2ij

cn+1/2ij := c(tn,Xij(tn))

cn+1/2ij := cn

ij − ∆tn

2!Vi ·∇cn

i

59Kiel, 23.6.2006 peter.frolkovic@uni-hd.de

Advection - 1st versus 2nd order method

0,20 0,8

X

Y

0,4

0,6

0,8

0

1

0,2

10,60,4

t = 0

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 10

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

60Kiel, 23.6.2006 peter.frolkovic@uni-hd.de

Advection - 1st order method (200x200)t = 0

0 0.5 10

0.5

1

t = 0.19635

0 0.5 10

0.5

1t = 0.3927

0 0.5 10

0.5

1

t = 0.58905

0 0.5 10

0.5

1t = 0.7854

0 0.5 10

0.5

1t = 0.98175

0 0.5 10

0.5

1

t = 1.1781

0 0.5 10

0.5

1t = 1.3744

0 0.5 10

0.5

1t = 1.5708

0 0.5 10

0.5

1

61Kiel, 23.6.2006 peter.frolkovic@uni-hd.de

Advection - 2nd order method (200x200)t = 0

0 0.5 10

0.5

1

t = 0.19635

0 0.5 10

0.5

1t = 0.3927

0 0.5 10

0.5

1

t = 0.58905

0 0.5 10

0.5

1t = 0.7854

0 0.5 10

0.5

1t = 0.98175

0 0.5 10

0.5

1

t = 1.1781

0 0.5 10

0.5

1t = 1.3744

0 0.5 10

0.5

1t = 1.5708

0 0.5 10

0.5

1

62Kiel, 23.6.2006 peter.frolkovic@uni-hd.de

Advection - 2nd order method (200x200)t = 0

0 0.5 10

0.5

1

t = 0.3927

0 0.5 10

0.5

1t = 0.7854

0 0.5 10

0.5

1

t = 1.1781

0 0.5 10

0.5

1t = 1.5708

0 0.5 10

0.5

1t = 1.9635

0 0.5 10

0.5

1

t = 2.3562

0 0.5 10

0.5

1t = 2.7489

0 0.5 10

0.5

1t = 3.1416

0 0.5 10

0.5

1

63Kiel, 23.6.2006 peter.frolkovic@uni-hd.de

Advection

Flux-based level set method (see video on my homepage)

F., Mikula: High resolution flux-based level set method; 2005

64Kiel, 23.6.2006 peter.frolkovic@uni-hd.de

Nonlinear advective level set equation

Example with topological changes (see video on my homepage)

F., Mikula: Flux-based level set method: finite volume emthod for evolving interfaces; 2002

65Kiel, 23.6.2006 peter.frolkovic@uni-hd.de

ConclusionsNumerical modelling

numerical algorithms fit analytical model preserving physical properties, ...stable, consistent, ...

available, simple and good in generalunstructured gridsrobust for rough data, ... (1st order schemes)

precise for smooth parts, ... (2nd order schemes)