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Design of asymptotic preserving schemes for the hyperbolic heat equation on unstructured meshes

Christophe Buet

, Bruno Després

& Emmanuel Franck

October 7, 2010

Abstract

The transport equation, in highly scattering regimes, has a limit in which the dominant behavior is given by the solution of a diusion equation. Angular discretization like the discrete ordinate method (SN), the truncated spherical harmonic expansion (PN) or also nonlinear moment models have the same property. For such systems it would be interesting to construct nite volume schemes on unstructured meshes which have the same dominant behavior even if the meshes are coarse. Such schemes are generally called diusion asymptotic preserving (AP) schemes and are designed presently at most on Cartesian meshes.

In this work we give some answers for unstructured meshes, when considering the lowest order possible angular discretization of the transport equation that is theP!model also refer- eed to as the hyperbolic heat equation, the Cattaneo's equation or the rst order formulation of the telegraph equation. We start from the modied upwind AP scheme proposed by Jin and Levermore [JL96] for this equation in 1-D. We show that extended in 2-D on unstructured meshes, the classical edge formulation of this scheme (and also for other AP schemes) is no longer asymptotic preserving. To solve this problem, we propose new schemes built on a node formulation of the Jin and Levermore's scheme which use the analogy betweenP1 model and acoustic equations for which schemes with corner's uxes have been built in the context of gas dynamics [Maz07,MABO07].

Contents

1 Introduction 2

2 A review of asymptotic preserving cell centered schemes in 1D 3

2.1 The classical nite volume scheme . . . 3

2.2 Jin-Levermore scheme . . . 4

2.3 Modied Jin-Levermore scheme and Gosse-Toscani scheme. . . 5

3 Design principle in dimension two 7 3.1 Denitions . . . 7

3.2 Edge formulation . . . 8

3.3 Nodal formulation . . . 10

3.4 Study of the nodal solver invertibility . . . 13

3.5 Invertibility of the nodal solver in triangular case . . . 15

3.6 Others variants . . . 17

3.7 L2 stability . . . 18

CEA, DAM, DIF, F-91297 Arpajon Cedex

Laboratoire Jacques-Louis Lions, Université Pierre et Marie Curie, 75252 Paris Cedex 05, France

CEA, DAM, DIF, F-91297 Arpajon Cedex, Laboratoire Jacques-Louis Lions, Université Pierre et Marie Curie, 75252 Paris Cedex 05, France

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4 Asymptotic preserving analysis in dimension two 20

4.1 Preliminary considerations about the convergence analysis . . . 20

4.2 Convergence of the limit semi-discrete scheme . . . 21

4.3 Asymptotic preserving schemes . . . 23

5 Details of discretization for the nodal schemes 24 5.1 Boundary conditions . . . 24

5.1.1 Neumann condition for diusion scheme . . . 24

5.1.2 Neumann condition for AP schemes applied to the telegraph equation . . . 24

5.2 Time discretization . . . 25

5.3 The limit diusion scheme on Cartesian mesh and spurious modes . . . 25

6 Numerical results 25 6.1 Numerical results for the diusion scheme . . . 25

6.1.1 Test case: Fundamental solution . . . 25

6.1.2 Test case with Neumann condition . . . 28

6.2 Numerical results in the transport regime . . . 29

6.3 The asymptotic regime . . . 29

7 Conclusion and perspectives 30

1 Introduction

The hyperbolic heat equation in dimension onex∈Ris









tp+∂xu ε = 0,

tu+∂xp ε + σ

ε2u= 0.

(1)

Throughout this work we will assume that 0 < ε≤1 and σ > 0. We will also assume that the solution(p, u)of (1) is such that for all(m1, m2)∈N2, there existsCm1,m2 >0such that

k∂xm1tm2pk≤Cm1,m2 andk∂mx1mt 2uk≤εCm1,m2.

These estimates can be proved by standard means for the solution of the Cauchy problem for (1).

The estimate for uis equivalent to say that v = uε satises k∂mx1mt 2vk ≤ Cm1,m2. It is well known that ifεgoes to 0, the system (1) can by approximated by the diusion equation

tp−∂x 1

σ∂xp

= 0. (2)

For simplicity σ is a constant in space. In this work we study asymptotic preserving numerical methods, following the seminal work [JL96], that is numerical methods such that the compatibility between (1) and (2) is true also at the discrete level. After a review of some asymptotic methods in 1D, we will consider the telegraph equation in dimension two





tp+1

ε∇ ·u= 0,

tu+1

ε∇p=−σ ε2u.

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The original contributions of our work concern the design and analysis of new asymptotic pre- serving schemes on unstructured meshes. Our motivation is to extend the domain of application of some asymptotic preserving schemes that have been published in the literature [JL96, GT01, BD06, LM07, BCLM02, DDSV09] after the seminal work of [GL96] on well-balanced schemes, which are restricted to Cartesian meshes.

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2 A review of asymptotic preserving cell centered schemes in 1D

For the three dierent schemes considered in this section, it is a simple task to check if the scheme is asymptotic preserving or not. In order to pave the way for future theoretical developments, we use a more rigorous approach where we analyze the dependence with respect to εand the mesh size∆xof the consistency error and the stability CFL condition. If the consistency error tends to zero with respect to∆x, independently ofεthe scheme is asymptotic preserving.

2.1 The classical nite volume scheme

In nite volume form, this method writes





pn+1j −pnj

∆t +unj+1 2 −un

j−12

ε∆x = 0, un+1j −unj

∆t +pnj+1 2 −pnj−1

2

ε∆x + σ

ε2unj = 0.

(4)

The uxes are given by the solution of the following linear system which is equivalent to writing the Riemann solver for the linear wave equation

( unj +pnj =unj+1 2+pnj+1

2

, unj+1−pnj+1=unj+1

2 −pnj+1 2

, ⇐⇒

( unj+1

2 = 12 unj +unj+1+pnj −pnj+1 , pnj+1

2 = 12 pnj +pnj+1+unj −unj+1

. (5)

Plugging these uxes in (4) we obtain an explicit formulation





pn+1j −pnj

∆t +unj+1−unj−1

2ε∆x −pnj+1−2pnj +pnj−1 2ε∆x = 0, un+1j −unj

∆t +pnj+1−pnj−1

2ε∆x −unj+1−2unj +unj−1 2ε∆x + σ

ε2unj = 0.

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Lemma 1. The classical nite volume scheme (4-6) satises the maximum principle for the Riemann invariants w=p+uandz=p−uunder CFL

∆t

ε∆x+σ∆t 2ε2 ≤1. The consistency error of both equations in (4) is O ∆xε + ∆t.

Proof. Let us dene the Riemann invariantsw=p+uandz=p−u, so that (4-5) rewrites (just compute the sum and the dierence of the equations (4))





wn+1j −wnj

∆t +wnj −wj−1n ε∆x + σ

2 wnj −zjn

= 0, zjn+1−zjn

∆t −zj+1n −znj ε∆x + σ

2 −wnj +znj= 0,

that is 





wn+1j =

1− ∆t

ε∆x−σ∆t 2ε2

wjn+ ∆t

ε∆xwj−1n +σ∆t 2ε2 znj, zn+1j =

1− ∆t

ε∆x−σ∆t 2ε2

zjn+ ∆t

ε∆xznj+1+σ∆t 2ε2 wnj.

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Under this form the stability in the maximum norm is a consequence of the non negativity of the diagonal coecient, that is1−ε∆x∆tσ∆t2 ≥0.

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The consistency error is studied with basic Taylor expansions. We use the form (6) which is well adapted for this purpose. We notexj=j∆xandtn=n∆t. The consistency errorcpfor the rst equation is

cpnj = p(xj, tn+1)−p(xj, tn)

∆t +u(xj+1, tn)−u(xj−1, tn)

2ε∆x −p(xj+1, tn)−2p(xj, tn) +p(xj−1, tn) 2ε∆x

= (∂tp(xj, tn) +O(∆t)) +

xu(xj, tn)

ε +O(∆x2)

+O ∆x

ε

=O ∆x

ε + ∆t

. The consistency errorcufor the second equation is

cunj =u(xj, tn+1)−u(xj, tn)

∆t +p(xj+1, tn)−p(xj−1, tn) 2ε∆x

−u(xj+1, tn)−2u(xj, tn) +u(xj, tn)

2ε∆x + σ

ε2u(xj, tn)

= (∂tu(xj, tn) +O(∆t)) +∂xp(xj, tn)

ε +O(∆x2 ε )

+O ∆x

ε

+ σ

ε2u(xj, tn) =O ∆x

ε + ∆t

2.2 Jin-Levermore scheme

The Jin-Levermore scheme [JL96] is a modication of the uxes used in the standard scheme (4) such that the rst equation for the unknown pis asymptotic preserving. We will prove that it is equivalent to say that the rst equation in (4) is consistent with a consistency error O(∆x) independent ofε. This is of course much better than the errorO ∆xε + ∆t

for the classical nite volume scheme when ε is small with respect to ∆x. The idea is to modify the uxes and to consider





unj +pnj =unj+1 2 +pnj+1

2 +σ∆x 2ε unj+1

2

, unj+1−pnj+1=unj+1

2 −pnj+1

2 +σ∆x 2ε unj+1

2

,

⇐⇒

( unj+1

2 =2(1+a)1 unj +unj+1+pnj −pnj+1 , pnj+1

2 =12 pnj +pnj+1+unj −unj+1 , where the coecientais (8)

a= σ∆x 2ε .

Lemma 2. The Jin-Levermore scheme (4)-(8) does not satisfy the maximum principle for the Riemann invariants w =p+u and z =p−u. The consistency error of the second equation is O ∆xε + ∆t

, and the consistency error of the rst equation is O ∆x2+ε∆x+ ∆t .

Proof. Let us rst analyze the stability in the maximum norm. Let us sum the two equations. We get

wjn+1−wnj

∆t +

wnj −aunj+1 2

wj−1n −aunj−1 2

ε∆x + σ

2 wnj −zjn

= 0. Sinceunj+1

2 =wjn−zj+1n

2(1 +a) , we obtain wjn+1−wnj

∆t +

1− a 2(1 +a)

wnj −wj−1n

ε∆x + a

2(1 +a)ε∆x zj+1n −zjn + σ

2 wnj −znj

= 0

that is wn+1j =

1− (2 +a)∆t

2(1 +a)ε∆x−σ∆t ε2

wjn+ σ∆t

4(1 +a)ε2wj−1n +

a∆t

2(1 +a)ε∆x+σ∆t 2ε2

zjn−a∆t ε∆xzj+1n .

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under a convenient CFL condition the diagonal coecient is positive. However it is not possible to guarantee that all non diagonal o coecients are positive. In particular σ∆t2 >0 and−ε∆xa∆t <0.

This is why the maximum principle does not hold.

Let us turn to the analysis of the consistency. Plugging the explicit form of the uxes (8) in (4) we see that the second equation is not modied therefore its consistency error is stillO ∆xε + ∆t The rst equation writes in a explicit form .

pn+1j −pnj

∆t + unj+1−unj−1

2(1 +a)ε∆x−pnj+1−2pnj +pnj−1

2(1 +a)ε∆x = 0. (9) So its consistency error is

cpnj = p(xj, tn+1)−p(xj, tn)

∆t +u(xj+1, tn)−u(xj−1, tn)

2(1 +a)ε∆x −p(xj+1, tn)−2p(xj, tn) +p(xj−1, tn) 2(1 +a)ε∆x

=∂tp(xj, tn) +O(∆t) +2∆x∂xu(xj, tn) +O(ε∆x3)

2(1 +a)ε∆x −∆x2xxp(xj, tn) +O(∆x4) 2(1 +a)ε∆x

=

tp(xj, tn) + 1

(1 +a)ε∂xu(xj, tn)− ∆x

2(1 +a)ε∂xxp(xj, tn) +O

∆x2+ ∆x3

(1 +a)ε+ ∆t

. Notice that(1 +a)ε=ε+σ∆x2 so that (1+a)ε∆x3 =O ∆x2

. Since(p, u)is the exact solution then

xxp=−σ

ε∂xu−ε∂xtu=−σ

ε∂xu+O(ε2). So the term in the rst parenthesis is also

(· · ·) =∂tp(xj, tn) + 1

(1 +a)ε∂xu(xj, tn) + ∆x 2(1 +a)ε

σ

ε∂xu(xj, tn) +O

ε2∆x 2(1 +a)ε

= 1 ε

−1 + 1

(1 +a)+ ∆x 2(1 +a)

σ ε

xu(xj, tn) +O

ε2∆x 2(1 +a)ε

.

By denition ofathe term between parenthesis is−1 + 1+a1+a = 0, and the second term is at least O(ε∆x). Thereforecp=O(∆x2+ε∆x+ ∆t).

2.3 Modied Jin-Levermore scheme and Gosse-Toscani scheme

Let us introduce what we call the modied Jin-Levermore scheme with the same uxes (8), but the sink is modied





pn+1j −pnj

∆t +unj+1 2 −un

j−12

ε∆x = 0, un+1j −unj

∆t +pnj+1 2 −pnj−1

2

ε∆x + σ 2ε2

unj+1

2 +unj−1 2

= 0.

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Lemma 3. The modied Jin-Levermore scheme is equal to the Gosse-Toscani scheme [GT01].

Proof. It is a matter of elementary manipulations. We plug the explicit uxes (8) in (10). We already know (9) that the rst equation can be rewritten as the rst equation of (3). For the second equation we check that

pnj+1 2 −pn

j−12

ε∆x + σ 2ε2

unj+1

2 +unj−1 2

= pnj+1−pnj−1

2ε∆x −unj+1−2unj +unj−1 2ε∆x

+ σ

ε24(1 +a) unj +unj+1+pnj −pnj+1+ unj−1+unj +pnj−1−pnj

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= 1

2ε∆x− σ ε24(1 +a)

pnj+1

2 −pnj−1 2

− unj+1−2unj +unj−1

+ σ

ε2(1 +a)unj. Let us dene

M = 1

1 +a = 2ε 2ε+σ∆x. One can check that

1

2ε∆x− σ

ε24(1 +a) = 1 1ε∆x

1− a

1 +a

= 1

2ε∆x× 1

1 +a = M 2ε∆x. So we obtain the important relation

pnj+1 2 −pnj−1

2

ε∆x + σ 2ε2

unj+1

2 +unj−1 2

=M

pnj+1−pnj−1

2ε∆x −unj+1−2unj +unj−1 2ε∆x + σ

ε2unj.

Therefore the modied Jin-Levermore scheme admit the explicit formulation





pn+1j −pnj

∆t +Munj+1−unj−1

2ε∆x −Mpnj+1−2pnj +pnj−1 2ε∆x = 0, un+1j −unj

∆t +Mpnj+1−pnj−1

2ε∆x −Munj+1−2unj +unj−1 2ε∆x +M σ

ε2unj = 0.

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We recognize the Gosse-Toscani scheme [GT01]. Notice also that this scheme is equal to an elementary modication of the classical explicit scheme where one has multiplied all space derivatives and sink byM.

Lemma 4. The modied Jin-Levermore scheme (equal to the Gosse-Toscani scheme) satises the maximum principle for the Riemann invariants under the CFL

∆t ε∆x≤1.

The consistency error of both equations is bounded by O(∆x+ ∆t).

Proof. The stability of classical rewrites ε∆x∆t(1 +a) ≤ 1. By construction the modied Jin- Levermore scheme is a modication of all uxes and sink by M = 1+a1 . So the CFL condition is indeed ε∆x∆t ≤ 1. The consistency of the rst equation has already been established for the Jin-Levermore scheme (4)-(8). So it remains to study the consistency of the second equation. One has

cunj = u(xj, tn+1)−u(xj, tn)

∆t +M

p(xj+1, tn)−p(xj−1, tn) 2ε∆x

−u(xj+1, tn)−2u(xj, tn) +u(xj, tn)

2ε∆x + σ

ε2u(xj, tn)

=∂tu(xj, tn) +O(∆t) +M

2∆x∂xp(xj, tn) +O(∆x3) 2ε∆x +∆x

ε ∂xxu(xj, tn) + σ

ε2u(xj, tn) We known that∂xxu=−ε∂txpandk∂mx1mt 2pk≤Cm1,m2 consequently∂xxu=O(ε)

cunj = (1−M)∂tu(xj, tn) +O

∆t+M∆x2 ε + ∆x

.

By denition the coecientM satises the following properties: rstM ≤1, second M∆x

ε = 2ε∆x

(2ε+σ∆x)ε = 2∆x

(2ε+σ∆x) ≤ 2 σ =⇒O

M∆x2 ε

=O(∆x),

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and third

1−M = σ∆x

2ε+σ∆x =⇒(1−M)O

ε∆x ε+ ∆x

=O(∆x). because∂tu(xj, tn) =O(ε). It ends the proof.

Theorem 5. The modied Jin-Levermore scheme (equal to the Gosse-Toscani scheme) is con- vergent in the maximum norm under CFL with an error O(∆x+ ∆t). Therefore this scheme is AP.

Since the modied Jin-Levermore scheme satises the maximum principle for w=p+uand z=p−u, then it is stable in the maximum norm. For the unknowns(p, u)the stability constant is bounded by 2. So the result of the theorem is an immediate application of the Lax theorem.

3 Design principle in dimension two

In this section we extend in dimension two on unstructured meshes the Jin-Levermore scheme and modied Jin-Levermore scheme. We will rst show that a naive use of the Jin-Levermore procedure does not generate an asymptotic preserving scheme on unstructured meshes. Consequently we propose an alternative approach where the Jin-Levermore procedure is incorporated in a cell- centered nite volume scheme with a nodal evaluation of the uxes. The theoretical analysis of the next section will show that the resulting scheme is indeed an asymptotic preserving scheme on unstructured meshes.

3.1 Denitions

Let us consider a unstructured mesh in dimension 2. The mesh is dened by a nite number of verticesxrand cellsΩj. We denotexj a point arbitrarily chosen insideΩj. For simplicity we will call this point the center of the cell.

The common edge between the cell j and k is ∂Ωjk andxjk is the middle of∂Ωjk. The area of Ωj is |Ωj|. In the case of the edge formulation we dene the normal njk and the length ljk associate to the edge∂Ωjk.

xj xr+1

xr−1 ljk

xr

Cellj

Cellk

xk njk

Figure 1: Notation for edge formulation. The interface between cellΩj and cellΩk has a normal njk =−nkj and a lengthljk =lkj. The vertices are denoted x...,r−1,r,r+1,.... The center of the cell is an arbitrary point inside the cell.

For the node formulation the denitions are less natural. By convention the vertices are listed counterclockwisexr−1,xr,xr+1 with coordinatesxr= (xr, yr).We also dene

ljr =1

2 kxr+1−xr−1k andnjr= 1 2ljr

−yr−1+yr+1 xr−1−xr+1

. (12)

The convention is that the length of a vector x∈R2 is denoted askxk. The scalar product of two vectors is(x,y).

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Remark 6. In all this work, the lettersj andkdenote cells. The letter ris always the index on a node. This is why ljk andljr denote dierent quantities. This abuse of notations allow a easy comparison of edge and node formulations.

xj xr+1

xr−1 xr

Cellj

Cellk ljrnjr

Figure 2: Notation for node formulation. The corner length ljr and the corner normal njr are dened in equation (12). Notice that ljrnjr is equal to the the half of the vector that starts at xr−1 and nish atxr+1. The center of the cell is an arbitrary point inside the cell.

3.2 Edge formulation

We consider the telegraph model in dimension two (3). The purpose of this subsection is to incorporate the Jin-Levermore procedure in a standard nite volume discretization of (3). The starting point is the standard nite volume scheme





|Ωj|∂tpj(t) +1 ε

X

k

ljk(ujk,njk) = 0,

|Ωj|∂tuj(t) +1 ε

X

k

ljkpjknjk=− |Ωj| σ ε2unj,

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where the uxes associated to the edge∂Ωjk common to the cellsj andkare dened by





pjk= 1

2(pj+pk) +1

2(uj−uk,njk) (ujk,njk) = 1

2(uj+uk,njk) +12(pj−pk) It will appear that it is more convenient to rewrite these formulas as

pjk−pj+ (ujk−uj,njk) = 0,

pjk−pk−(ujk−uk,njk) = 0. (14) The Jin-Levermore method in dimension one results in the incorporation of the source term in the uxes, in order to have a more accurate approximation of stationary solution. It is easy to use the same method in dimension two. Consider a stationary solution such that

∇p=−σ εu.

A Taylor expansion shows that

p(xjk)−p(xj) =σε(u(xjk),xj−xjk) +O(h2),

p(xjk)−p(xk) = σε(u(xjk),xk−xjk) +O(h2) (15)

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withxj, (resp. xk) the center of the cellj and (resp. k),xjk the middle and hthe local charac- teristic length of the mesh.

Following the interpretation of Jin-Levermore we interpret (14) and (15) as linear relations between dierences. The idea is to mix these relations and to get

pjk−pj+ (ujk−uj,njk) =σε(ujk,xj−xjk),

pjk−pk−(ujk−uk,njk) = σε(ujk,xk−xjk). (16) This is a linear system of two equations and three unknownspjk andujk which is not solvable in general. In dimension one, there is no such problem. At this point it is natural but restrictive to assume that the mesh satises the Delaunay condition which is equivalent to(xjk−xj) =djknjk and(xjk−xj) =−dkjnjk, withdjk=d(xj,xjk)>0and dkj=d(xk,xjk)>0. The linear system

becomes

pjk−pj+ (ujk−uj,njk) =−σεdjk(ujk,njk),

pjk−pk−(ujk−uk,njk) =σεdkj(ujk,njk). (17) This is a linear system of two equations and two unknownspjk and(ujk,njk). The solution is





(ujk,njk) =(uj+uk).njk+ (pj−pk) 2 + (σ/ε)(djk+dkj)

pjk=((uj,njk) +pj)(1 +dkj(σ/ε))−((uk,njk)−pk)(1 +djk(σ/ε)) 2 + (σ/ε)(djk+dkj)

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The result of this construction is the scheme (13) with the uxes (18).

Proposition 7. If the mesh satisfy the Delaunay condition, the asymptotic limit of the scheme (13) with the ux (18) is the diusion scheme VF4

|Ωj|∂tpj(t)−X

k

ljk pk−pj djk+dkj

= 0, withdjk+dkj=d(xj,xk). (19)

Proof. We rst multiply the second equation byε2 ε2|Ωj|∂tuj(t) +εX

k

ljkpjknjk=− |Ωj|σunj (20) By factoring the denominator by1/ε we obtain the following formulation

εpjk= ((uj,njk) +pj)(ε2+dkj(σε))−((uk,njk)−pk)(ε2+djk(σε))

(2ε+σ(djk+dkj)) (21) Whenεtends to zero, the right inside of (21) tends to zero. Plugging in (20) it shows thatunj = 0.

We plug this result in the formula of(ujk,njk)(18) and obtain at the limit the scheme (19).

Since the mesh satises the Delaunay condition then(xj−xk)⊥∂Ωjkanddjk+dkj=d(xj,xk).

we obtain the VF4 scheme.

Even if the mesh does not satisfy the Delaunay condition the scheme (13)-(18) is well dened.

Further it is known that the VF4 scheme doesn't converge for meshes that do not fullled the Delaunay condition. The explanation is that the reconstruction of the gradient in the normal direction imposes a strong geometrical restriction. Consequently the scheme (13)-(18) is not asymptotic preserving on all unstructured meshes.

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3.3 Nodal formulation

In this section we propose a new scheme for the telegraph equation which is based on a nodal formulation in order to solve the problem perceived in the previous subsection. We use the analogy between the telegraph equation and the linearized Euler equations. B. Després and C. Mazeran in [Maz07] constructed a nodal scheme named GLACE for Euler equation [Des09, CDDL09].

Consequently we want to use this scheme with the Jin-Levermore method. We begin by writing the GLACE scheme for the telegraph equation (3)





|Ωj|∂tpj(t) +1 ε

X

r

ljr(ur.njr) = 0

|Ωj|∂tuj(t) +1 ε

X

r

ljrpjrnjr =− |Ωj| σ

ε2uj (22)

with the uxes dened by

pjr=pj+ (uj−ur,njr), X

j

ljrpjrnjr= 0. (23)

The formulas (23) are a nodal generalization of the edge formulas (14). The solution of this linear system is easily computed by elimination ofpjr

 X

j

(ljrnjr⊗njr)

ur=X

j

ljr(pjnjr+njr⊗njruj). (24) The matrix of the left hand side is always invertible for non-degenerate unstructured meshes.

As before we incorporate the source term in the uxes. Plugging the source term in the Riemann invariant as (17) we obtain









pjr=pj+ (uj−ur,njr)−σ

ε(ur,xr−xj),

 X

j

ljr(njr⊗njr

εnjr⊗(xr−xj))

ur=X

j

ljr(pjnjr+njr⊗njruj). (25) Denition 8. The scheme (22)-(25) will be referred to as the JL-(a) scheme.

This scheme is a valid one provided the linear system in the second equation of (25) is invertible.

We will show that this scheme is asymptotic preserving on unstructured meshes.

Another problem that needs to be studied is the well posedness of the asymptotic limit of the JL-(a) scheme.

Proposition 9. If the matrix of (25) is invertible ,the asymptotic limit of the JL-(a) scheme is









|Ωj|∂tpj(t) +X

r

ljr(ur,njr) = 0,

σ

 X

j

ljrnjr⊗(xr−xj)

ur=X

j

ljrpjnjr.

(26)

Proof. : To demonstrate this result we use a Hilbert expansion as in [BCLM02]. We write the following expansion

pj=pj,0+εpj,12pj,2+....

pjr=pjr,0+εpjr,12pjr,2+....

(11)

We do the same for all other variables. Plugging this expansion in the rst equation of (22) one gets

tpj,0(t) +1 ε

X

r

ljr(ur,1,njr) +X

r

ljr(ur,0,njr) =O(ε). The term proportional to 1ε is

X

r

ljr(ur,0,njr) = 0. (27) The term proportional toO(1)is

tpj,0(t) +X

r

ljr(ur,1,njr) = 0. (28) Using the same method for the second equation we obtain three terms

1

ε2 : uj,0= 0 (29)

1

ε : X

r

ljrpjr,0njr=−σuj,1 (30) 1

ε0 : ∂tuj,0(t) +X

r

ljrpjr,1njr =−σuj,2 (31) Doing the same in (25) we obtain

1

ε : σ

 X

j

ljrnjr⊗(xr−xj))

ur,0= 0 (32) and

1 ε0 :

 X

j

ljr(njr⊗njr)

ur,0

 X

j

ljrnjr⊗(xr−xj)

ur,1 (33)

=X

j

ljrpj,0njr+ljr(njr⊗njr)uj,0.

Assuming that the matrix in (32) is invertible, (32) implies that ur,0 = 0. Since we have (29), (33) yields

σ

 X

j

ljrnjr⊗(xr−xj)

ur,1=X

j

pj,0njr. (34)

This equality and (28) give the result (26).

Now we propose a variant of (22)-(25) based on another discretization of the source term. This scheme is the dimension two extension of the modied Jin-Levermore scheme (10)-(8)





|Ωj|∂tpj(t) +1 ε

X

r

ljr(ur,njr) = 0,

|Ωj|∂tuj(t) +1 ε

X

r

ljrpjrnjr=−σ ε2

X

r

ljrnjr⊗(xr−xj)ur.

(35)

This variant can also be seen as the two dimensional extension of the Gosse-Toscani scheme.

Denition 10. The scheme (35)-(25) will be referred to as the JL-(b) scheme.

Proposition 11. If the matrix of (25) is invertible, the schemes JL-(b) and JL-(a) have the same asymptotic limit (26).

(12)

Proof. The scheme (35) can be written as





|Ωj|∂tpj(t) +1 ε

X

r

ljr(ur,njr) = 0,

|Ωj|∂tuj(t) +1 ε

X

r

ljrpjrnjr = 0,

(36)

with the ux





pjr=pj+ (uj−ur,njr),

 X

j

ljr(njr⊗njr

εnjr⊗(xr−xj))

ur=X

j

ljr(pjnjr+njr⊗njruj). (37) Using the method of the Hilbert expansion one gets

1

ε : X

r

ljr(ur,0,njr) = 0, (38) 1

ε0 : ∂tpj,0(t) +X

r

ljr(ur,0,njr) = 0. (39) For the second equation we obtain

1

ε : X

r

ljrpjr,0njr= 0 (40)

1

ε0 : ∂tuj,0(t) +X

r

ljrpjr,1njr= 0. (41) Now we use the denition of the uxpjr

X

r

ljrpjr,0njr =X

r

ljrpj,0njr+X

r

ljrnjr⊗njr(uj,0−ur,0) = 0. (42) The rst term is zero because we haveP

rljrnjr= 0, consequently when we use (42) we obtain X

r

ljrnjr⊗njr(uj,0−ur,0) = 0. (43) Using the Hilbert expansion in the nodal solver and assuming the same invertibility condition on the matrixP

jβbjr, we obtain the two following relations

 X

j

ljrnjr⊗njr

ur,0

 X

j

ljrnjr⊗(xr−xj)

ur,1=X

j

ljrpj,0njr+X

j

ljrnjr⊗njruj,0

andur,0= 0. (44)

As ur,0 = 0, so (43) is equivalent to P

rljr(njr⊗njr)uj,0 = 0. It is immediate to show that P

rljrnjr⊗njris symmetric positive for a non-degenerated mesh, see [Maz07]. Souj,0= 0. This result associates with (43) and (39) ends the demonstration.

The previous demonstrations require that the matrixP

jljrnjr⊗(xr−xj)is invertible. This is the subject of the next section.

(13)

3.4 Study of the nodal solver invertibility

In this section we study the invertibility of the matrix X

j

ljr(njr⊗njr

εnjr⊗(xr−xj)). (45) This is essential to guarantee the well posedness of the nodal ux solver. This matrix is the sum of two matrices. The rst one

X

j

ljr(njr⊗njr) (46)

is positive denite for all non-degenerated meshes [Maz07]. The second matrix is Ar=X

j

ljrnjr⊗(xr−xj). (47) Notice hasAr has no reason to be symmetric. We will study conditions such thatAr is positive, that is

(y, Ary)>0 ∀y∈R2, y6= 0.

Remark 12. For triangular meshes, there is an elegant possibility to guarantee thatAr=Atr>

0.Let us assume that the orthocenter of the triangle is inside the triangle. We choose x equal to the orthocenter. In this casexr−xj =djrnjr withdjr>0.Then

Ar=X

j

ljrdjr(njr⊗njr) =Atr.

For a non-degenerated mesh, the sum overj contains more than two independent directions. So The matrix is positive. There is an important restriction. All angles must be strictly less than π/2, in order that the orthocenters are inside the cells.

Currently we fail to prove a complete result such as that of C. Mazeran. However we can show that if we do not distort the mesh too much, then the matrix is invertible. The idea is to note T r(Ar) = 2VrwithVrthe control volume around the verticesxr.

Denition 13. With a slight abuse of notation, the control volume Vr is dened by the closed loop

. . . ,xj−1

2,xj,xj+1 2, . . . . Here the xj's are the center of the cells, and the xj+1

2's are the middle of the edges around the verticesxr. A typical example is depicted in gure3.

The idea is to compare Ar with VrcIdand look which are the conditions for the matrix stay positive denite.We introduce the following denitions.

Proposition 14. Arsatises:

Ar=VrIdc+1 2

X

j

(wj+1/2 ⊗wj+1/2−vj+1/2 ⊗vj+1/2) =VrcId+P (48) withwj+1/2= (xj+1−xj+1/2) andvj+1/2= (xj+1/2−xj).

T r(Ar) = 2Vr. (49)

Proof. For the polygon dened by all the pointsxj andxj+1/2 around the vertexxr, we have the identity which is a consequence of the Stokes theorem

VrcId=X

j

(xj+1/2−xj)⊗(1

2(xj+1/2+xj)−xr) + (xj−xj−1/2)⊗(1

2(xj−1/2+xj)−xr) (50)

(14)

xj x1

2

xr

xj−1 2

Vr

Figure 3: Denition of the control volumeVr around vertexxr. The control volume is dened by the close loop that joins the center of the cells (xr's) and the middle of the edges (xj+1

2's) around the vertex.

=X

j

(xj+1/2−xj)⊗(1

2(xj+1/2−xj)+xj−xr)+(xj−xj−1/2)⊗(1

2(xj−1/2−xj)+xj−xr) (51) Sinceljrnjr =−(xj+1/2−xj)−(xj−xj−1/2) we have

VrcId=Ar+1 2

X

j

(xj+1/2−xj)⊗(xj+1/2−xj)−(xj−xj−1/2)⊗(xj−xj−1/2) (52)

which reads also, using the denition of the matrixP,Ar=VrcId+P. The second point is then evident since for any vectorv we haveT r(v⊗v) = 0.

Introducing the polygon Tjr dened by (xr,xj,xj+1/2,xj+1)we can also write Ar=X

j

|Tjr|cId+1

2(wj+1/2⊗wj+1/2−vj+1/2⊗vj+1/2)

=X

j

|Tjr|Idc+Pj

(53)

or ifTejr is dened by(xr,xj−1/2,xj,xj+1/2) Ar=X

j

|Tejr|cId+1

2(wj−1/2⊗wj−1/2−vj+1/2⊗vj+1/2)

=X

j

|Tejr|Idc+Pj

. (54) Using these decompositions we have the following result

Proposition 15. The matrix Ar is positive under the sucient condition that for all j

|Tjr|> 1

2 kxj+1−xjkkxj+1/2−1

2(xj+1+xj)k (55) or that for allj

|Tejr|> 1

2 kxj+1/2−xj−1/2kkxj−1

2(xj+1/2+xj−1/2)k (56)

Proof. For the two decompositions (53) and (54) we have xtArx=X

j

|Tjr|||x||2+xtPjsx≥X

j

(|Tjr| −ρ(Pjs)||x||2

(15)

wherePjs= 12(Pj+Pjt)is the symmetric part ofPj. For any matrix M,ρ(M)stands for its spectral radius. Thus if for anyj |Tjr| −ρ(Pjs)>0 thenAr is positive. Set nowC =w⊗w−v⊗v withv= (a, b)∈R2 and f andw= (˜a,˜b)∈R2 then

Cs=

ab−a˜˜b −a2+ ˜a2+b2−˜b2

−a2+ ˜a2+b2−˜b2 2

2 ˜a˜b−ab

We notex= (a−˜a),y= (b−˜b),α=12(b+ ˜b)andβ =12(a+ ˜a). We have evidentlyT r(Cs) = 0.

Using the factorizationab−˜a˜b=xα+yβ, we obtain easily

Det(Cs) =−(x2+y2)(α22) =− kv−wk2k 1

2(v+w)k2. SinceCsis a traceless two dimensional matrix one gets

ρ(Cs) =λmax=1

2(T r(Cs) +p

T r(Cs)2−4Det(Cs)) =kw−vk k 1

2(v+w)k. Specifyingvandw for the decompositions (53) and (54) ofAr gives us (55) and (56).

Remark 16. For meshes made with equilateral triangles or made with squares, it is easy to check that Ar>0 becausexj+1/2= 12(xj+1+xj) so that (55) is veried.

3.5 Invertibility of the nodal solver in triangular case

In this section we study the invertibility of the nodal solver in the case of a general triangular mesh and xj is equal to the barycenter of the cell. The case of equilateral triangles has been treated in remark16. The case where xj is the orthocenter of the triangle has been treated in remark12 with the restriction that the angles of the triangles must be strictly less thanπ/2.

The method consists in the characterization of the three local inequalities (56) (one per corner).

for the generic triangle depicted in gure4

Figure 4: A generic triangle. The barycenter isG= 13(A+B+C). The middle of the edge BC isI=12(B+C), and so on.

We dene three angles. The rst one is θA the angle between AG and KJ, the second one is θB the angle between BG and KI and the third one is θC the angle between CG and IJ.

(16)

Proposition 17. The three local inequalities (56) are veried if

|sin(θA,B,C)|> 1

4. (57)

Proof. By symmetry it is sucient to study the corner condition for vertex A which correspond to

xr=A, xj+1/2=J =A+C

2 , xj−1/2=K=A+B

2 , xj =G= A+B+C

3 .

The quadrangleTejr in inequality (56) corresponds toTejr= (A, K, G, J). One as

|Tejr|= 1

2 kAGkkJ K k|sin(θA)|. We see thatkxj+1/2−xx−1/2k=kJ Kk. One also has

kxj−1

2(xj+1/2+xj−1/2)k=

A+B+C

3 −2A+B+C 4

=k −−2A+B+C

12 k=k B+C

2 −Ak. As G is the barycenter we can saykAGk=2

3 kAIk. We will also needD=K+J

2 , so that kADk=kA−2A+B+C

4 k=1

2 kAIk SokADk= 1

2 kAIkandkDGk= 1

6 kAIk.

Consequently (56) is equivalent to 1

2 kAGkkJ Kk|sin(θA)|> 1

2 kJ KkkDGk. Using the previous results we obtain|sin(θA)|>14.

In order to get a more useful interpretation of the previous proposition, we deneAˆ,Bˆ andCˆ the angles associate to the vertex A,B and C.

Proposition 18. One has the correspondence

|sin(θA)|= 1

q1 +4 sinsin22( ˆBB−ˆsinC)ˆ2Cˆ

. (58)

Similar formulas hold for the two other angles.

Proof. To simplify the proof we choose the vertex : A = (x, y), B = (0,0), C = (1,0) and D= (0.5,0). We known thatx= cot( ˆB)y and1−x= cot( ˆC)y. Consequently

y= 1

cot( ˆB) + cot( ˆC) andy= cot( ˆB) cot( ˆB) + cot( ˆC) Now we remark thatx−1/2 = cot(θA)y, socot(θA) = 1

2(cot( ˆB)−cot( ˆC)). This is also equivalent to

cot(θA) = sin( ˆC−Bˆ) 2 sin( ˆC) sin( ˆB) To conclude we use1 + cot2A) = 1

sin2A).

(17)

Finally we desire to characterize all triangles such that the sucient conditions of positivity (57) with (58) are satised. We dene the functiong such that

g( ˆB,Cˆ) = 1

q1 +4 sinsin22( ˆBB−ˆsinC)ˆ2Cˆ

.

SinceAb+Bb+Cb=π, the sucient conditions of positivity rewrites f( ˆB,Cˆ)> 1

4, f( ˆB,Cˆ) = min(g( ˆB,Cˆ), g(π−Cˆ−B,ˆ Cˆ), g( ˆB, π−Cˆ−Bˆ)).

0 0.5 1 1.5 2 2.5 3

0 0.5 1 1.5 2 2.5 3 0.5 0.25 0.125

x

y

Figure 5: Plot of the function f in function of x ∈ [0, π] and y ∈ [0, π].. The interesting part corresponds tox≥0,y≥0andx+y≤π. The positivity domainf(x, y)> 14 is delimited by the blue isoline between the two others.

We observe on gure5that if all angles are strictly greater than 0.2 radian,that is 11 degrees, then the positivity criterion f(x, y)> 14 is fullled. In consequence the angle restriction is much weaker than with the orthocenter. At least angles more than π2 are possible in the mesh, provided there is no angle less than0.2 radian. We believe that sharper positivity estimates are possible.

Since the analysis is tricky we leave this issue for further studies.

3.6 Others variants

In this section we dene others variants. These variants are based on a tensor formulation that we borrow from [Klu08]. It allows to propose other discretization for the acoustic part and for the part associate to the source term in the uxes. We rewrite the scheme in the following form

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