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Licensed Unlicensed Requires Authentication Published by De Gruyter March 22, 2018

Trefftz Discontinuous Galerkin Method for Friedrichs Systems with Linear Relaxation: Application to the P1 Model

  • Guillaume Morel EMAIL logo , Christophe Buet and Bruno Despres

Abstract

This work deals with the first Trefftz Discontinuous Galerkin (TDG) scheme for a model problem of transport with relaxation. The model problem is written as a PN or SN model, and we study in more details the P1 model in dimension 1 and 2. We show that the TDG method provides natural well-balanced and asymptotic preserving discretization since exact solutions are used locally in the basis functions. High-order convergence with respect to the mesh size in two dimensions is proved together with the asymptotic property for P1 model in dimension one. Numerical results in dimensions 1 and 2 illustrate the theoretical properties.

MSC 2010: 65N30; 65N15; 35Q70

A Time-Dependent Solutions to the P1 Model in One Dimension

We give the proofs of the propositions in Section 4.1 and provide more material on how to construct the stationary and time-dependent solutions (4.3) for the one-dimensional P1 model (4.1). First we recast (4.1) as in (1.2) with d=1, n=2, which reads:

(A.1)t𝐮+A1x𝐮=-R𝐮,

with

A0=(1001),A1=(0cεcε0),R=(σa00σt).

In order to find the solutions (A.7) we search for particular solutions to (A.1) of the form

(A.2)𝐮(x,t)=𝐪(x,t)eλx

with λ and where 𝐪n is a polynomial in x and t. For example we consider

(A.3)𝐪(x,t)=𝐪0+x𝐪1+t𝐪2+xt𝐪3.

Using (A.2) in (A.1) and dropping the exponential term, one has

(t+A1x+R)𝐮=0(t+A1x+(A1λ+R))𝐪(x,t)=𝟎.

Extending 𝐪, one finds

((A1λ+R)𝐪0+A1𝐪1+𝐪2)+x((A1λ+R)𝐪1+𝐪3)+t((A1λ+R)𝐪2+A1𝐪3)+xt(A1λ+R)𝐪3=𝟎.

This equality holds for all x and t, thus one gets the system

(A.4){(A1λ+R)𝐪3=𝟎,(A1λ+R)𝐪1=-𝐪3,(A1λ+R)𝐪2=-A1𝐪3,(A1λ+R)𝐪0=-A1𝐪1-𝐪2.

Therefore the solutions to (A.1) of the form (A.2) with 𝐪 given by (A.3) satisfy the system (A.4). We can now write the conditions (A.4) for the P1 model.

Lemma A.1.

The conditions (A.4) are

(A.5){𝐪3=𝟎,(A1λ+R)𝐪2=𝟎,(A1λ+R)𝐪1=𝟎,(A1λ+R)𝐪0=-A1𝐪1-𝐪2,

with λ=±εvσaσt.

Proof.

First, a necessary condition for (A.4) to admit a solution is det(A1λ-R)=0. Since

A1λ+R=(σacελcελσt),

one deduces

det(A1λ+R)=0λ=±εcσaσt.

With this choice for λ, the matrix A1λ+R reads:

A1λ+R=(σa±σaσt±σaσtσt),

and one notices that

(A.6)(A1λ+R)2=(σa+σt)(A1λ+R).

Thanks to the first and the second equations of (A.4) one has

{(A1λ+R)𝐪3=𝟎,(A1λ+R)𝐪1=-𝐪3(A1λ+R)2𝐪1=(σa+σt)(A1λ+R)𝐪3=𝟎.

From (A.6) one gets (A1λ+R)𝐪1=𝟎, therefore 𝐪3=𝟎. ∎

Proposition A.2.

The P1 model (A.1) admits the following four solutions:

(A.7)𝐞1±(x)=(σtσa)e±εcσaσtx,𝐞2±(x)=(-cσt-σa4σaσt±εxσa+σt2σa+ctσtcσt-σa4σtσa-εxσa+σt2σtctσa)e±εcσaσtx.

Proof.

One notices Ker(A1λ+R)=Span((σt,σa)T). Thus with 𝐰=(σt,σa)T and the relations (A.5) one gets

𝐪1=α𝐰,𝐪2=β𝐰,α,β.

From the last equality of (A.5) one sees that -A1𝐪1-𝐪2(A1λ+R) which implies

-A1𝐪1-𝐪2Ker((A1λ+R)T).

Since the matrices A1 and R are symmetric, Ker((A1λ+R)T)=Ker(A1λ+R)=Span(𝐰). A necessary condition is then (-A1𝐪1-𝐪2,𝐰)=0 which is equivalent to

α=±σa+σt2σaσtεcβ.

Finally, let 𝐪0=(q01,q02)T. From the fourth equation of (A.5) one gets q01=1σa(βσa-σt2σtσaσtq02). Thus one can choose 𝐪0 of the form

𝐪0=β(-σt-σa4σaσt,σt-σa4σtσa)T+γ𝐰,

with γ. In summary, one has the following relations:

𝐪3=𝟎,
𝐪2=β(σt,σa)T,
𝐪1=-σa+σt2σaσtεcβ(σt,σa)T,
𝐪0=β(-σt-σa4σaσt,σt-σa4σtσa)T+γ(σt,±σa)T,

where β,γ. Because the solutions are of the form 𝐮(x,t)=(𝐪0+x𝐪1+t𝐪2+xt𝐪3)eλx, with λ=±εcσaσt, one finds the four basis functions (A.7). ∎

Now we construct linear combinations of the solutions (A.7) that remain stable in the case σa0. To make these solutions more convenient to read, we use the notations

zx=εcσaσtx,cosh(x)=ex+e-x2,sinh(x)=ex-e-x2.

Lemma A.3.

The following four functions are linear combinations of the solutions (A.7):

𝐞~1(x)=(σtσasinh(zx)-cosh(zx)),𝐞~2(x)=(cosh(zx)-σaσtsinh(zx)),
𝐞~3(t,x)=(-εσt+σa2σaσtxsinh(zx)-ctcosh(zx)cσt-σa2σtσaσtsinh(zx)+εσt+σa2σtxcosh(zx)+cσaσttsinh(zx)),
𝐞~4(t,x)=(cσt-σa2σaσaσtsinh(zx)-εσt+σa2σaxcosh(zx)-cσtσatsinh(zx)εσt+σa2σaσtxsinh(zx)+ctcosh(zx)).

Proof.

One defines the following linear combinations of the functions (A.7):

𝐥1±(x,t)=𝐞2±(x,t)+cσt-σa4σaσt𝐞1±(x,t),𝐥2±(x,t)=𝐞2±(x,t)-cσt-σa4σaσt𝐞1±(x,t).

Then defining the four solutions

𝐞~1(x,t)=12σa(𝐞1+(x,t)-𝐞1-(x,t)),𝐞~2(x,t)=12σt(𝐞1+(x,t)+𝐞1-(x,t)),
𝐞~3(x,t)=-12σt(𝐥1+(x,t)+𝐥1-(x,t)),𝐞~4(x,t)=-12σa(𝐥2+(x,t)-𝐥2-(x,t)),

one gets the functions given in the statement of the lemma. ∎

We show that these solutions remain stable in the limit case σa0.

Proposition A.4.

When σa0 (σtσsε2), the solutions given in Lemma A.3 tend to the following functions:

𝐞~1(x,t)σa0(εσtcx-1),𝐞~2(x,t)σa0(10),
𝐞~3(x,t)σa0(-ε2σt2cx2-ctεx),𝐞~4(x,t)σa0(-ε3σt26c2x3-εσttx-εxε2σt2cx2+ct).

Proof.

One notices that

(A.8)cosh(zx)σa01,sinh(zx)σaσtσa0εcx.

The limits of 𝐞~1(x,t), 𝐞~2(x,t) and 𝐞~3(x,t) are simply obtained by using the expressions (A.8) in the functions given in Lemma A.3. The limit of the second component of 𝐞~4(x,t) can be obtained in a similar way. It remains to study the first component of 𝐞~4(x,t). One has

c(σt-σa)2σaσaσtsinh(zx)-εxσt+σa2σacosh(zx)
=c(σt-σa)2σa(εcx+ε3x3σaσt3!c3+o(σa2))-εxσt+σa2σa(1+ε2σaσtx22!c2+o(σa2))
=-εx+ε3σt2x32c2(-16+12)+o(σa)=-εx-ε3σt26c2x3+o(σa).

Because

-ctσtsinh(zx)σaσtσa0-εσttx,

one gets the expression of the limit of 𝐞~4(x,t). ∎

B Proof of Proposition 7.2

Lemma B.1.

Assume that the hypotheses of Proposition 7.2 are satisfied. Then for all 0ln-2 one has the identity

p=0lxpyl-pu(𝐱0)Tlp(𝐱)+p=0l+2xpyl+2-pu(𝐱0)αl+2p(𝐱)
(B.1)=p=0lxpyl-pu(𝐱0)αlp(𝐱)+xl+2u(𝐱0)βl+2l+2(𝐱)+xl+1yu(𝐱0)βl+2l+1(𝐱).

Proof.

Let l, 0ln-2. For l1, -1l1l-1 we define the function

f(l1)=p=0l1xpyl-pu(𝐱0)αlp(𝐱)+p=l1+1lxpyl-pu(𝐱0)Tlp(𝐱)+p=l1+3l+2xpyl+2-pu(𝐱0)αl+2p(𝐱)
(B.2)+xl1+2yl-l1u(𝐱0)βl+2l1+2(𝐱)+xl1+1yl+1-l1u(𝐱0)βl+2l1+1(𝐱),

where we use the convention p=ab=0 for a,b and b<a. First we show f(l1)=f(l1+1) for -1l1l-1. Because u is solution to equation (B.1) one notices

(B.3)xl1+1yl+1-l1u(𝐱0)βl+2l1+1(𝐱)=(-xl1+3yl-l1-1+ωxl1+1yl-l1-1)u(𝐱0)βl+2l1+1(𝐱).

Now we consider the definition (B.2) of the function f and study the difference f(l1+1)-f(l1). Cancelling all elements which appear in both f(l1) and f(l1+1), one finds

f(l1+1)-f(l1)=xl1+1yl-l1-1u(𝐱0)αll1+1(𝐱)-xl1+1yl-l1-1u(𝐱0)Tll1+1(𝐱)-xl1+3yl-l1-1u(𝐱0)αl+2l1+3(𝐱)
+xl1+3yl-l1-1u(𝐱0)βl+2l1+3(𝐱)-xl1+1yl+1-l1u(𝐱0)βl+2l1+1(𝐱).

Using equality (B.3) to reformulate the fifth term on the right-hand side, one gets

f(l1+1)-f(l1)=xl1+1yl-l1-1u(𝐱0)αll1+1(𝐱)-xl1+1yl-l1-1u(𝐱0)Tll1+1(𝐱)-xl1+3yl-l1-1u(𝐱0)αl+2l1+3(𝐱)
+xl1+3yl-l1-1u(𝐱0)βl+2l1+3(𝐱)+(xl1+3yl-l1-1-ωxl1+1yl-l1-1)u(𝐱0)βl+2l1+1(𝐱).

Ordering the terms with respect to the derivatives gives

f(l1+1)-f(l1)=xl1+1yl-l1-1u(𝐱0)(αll1+1(𝐱)-Tll1+1(𝐱)-ωβl+2l1+1(𝐱))
+xl1+3yl-l1-1u(𝐱0)(-αl+2l1+3(𝐱)+βl+2l1+1(𝐱)+βl+2l1+3(𝐱)).

Using the definitions (7.3) and (7.4), one finds

αll1+1(𝐱)-Tll1+1(𝐱)-ωβl+2l1+1(𝐱)=0,
βl+2l1+3(𝐱)-αl+2l1+3(𝐱)+βl+2l1+1(𝐱)=0.

Therefore one has f(l1+1)-f(l1)=0 for all -1l1l-1. One deduces f(-1)=f(l) which can be written as

p=0lxpyl-pu(𝐱0)Tlp(𝐱)+p=2l+2xpyl+2-pu(𝐱0)αl+2p(𝐱)+yl+2u(𝐱0)βl+20(𝐱)+xyl+1u(𝐱0)βl+21(𝐱)
=p=0lxpyl-pu(𝐱0)αlp(𝐱)+xl+2u(𝐱0)βl+2l+2(𝐱)+xl+1yu(𝐱0)βl+2l+1(𝐱).

Noticing from (7.5) that αl+20(𝐱)=βl+20(𝐱) and αl+21(𝐱)=βl+21(𝐱), one incorporates the two corresponding terms in the second sum. So one finds equality (B.1). ∎

Proof of Proposition 7.2.

Start from the Taylor expansion (7.2). From definition (7.3) one has αnp(𝐱)=Tnp(𝐱) and αn-1p(𝐱)=Tn-1p(𝐱). Therefore

u(𝐱)=k=0n-2p=0kxpyk-pu(𝐱0)Tkp(𝐱)+p=0n-1xpyn-1-pu(𝐱0)αn-1p(𝐱)
+p=0nxpyn-pu(𝐱0)αnp(𝐱)+p=0n+1xpyn+1-pu(𝐱s)Tn+1p(𝐱).

One can recursively use equality (B.1) from l=n-2 to l=0. More precisely, rearranging the first sum, one has

u(𝐱)=k=0n-3p=0kxpyk-pu(𝐱0)Tkp(𝐱)+p=0n-1xpyn-1-pu(𝐱0)αn-1p(𝐱)
+(p=0n-2xpyn-2-pu(𝐱0)Tn-2p(𝐱)+p=0nxpyn-pu(𝐱0)αnp(𝐱))+p=0n+1xpyn+1-pu(𝐱s)Tn+1p(𝐱).

One can reformulate the terms between brackets using (B.1) with the index correspondence n-2=l. One finds

u(𝐱)=k=0n-3p=0kxpyk-pu(𝐱0)Tkp(𝐱)+p=0n-1xpyn-1-pu(𝐱0)αn-1p(𝐱)+p=0n-2xpyn-2-pu(𝐱0)αn-2p(𝐱)
(B.4)+[xnu(𝐱0)βnn(𝐱)+xn-1yu(𝐱0)βnn-1(𝐱)]+p=0n+1xpyn+1-pu(𝐱s)Tn+1p(𝐱).

One can now recursively repeat this simple operation using equality (B.1) for l=n-3 to l=0. One finally gets formula (B.4) where the first line is written for n=2, the term [] becomes a sum and the last term remains unchanged:

u(𝐱)=0+p=01xpy1-pu(𝐱0)α1p(𝐱)+u(𝐱0)α00(𝐱)
+k=2n[xku(𝐱0)βkk(𝐱)+xk-1yu(𝐱0)βkk-1(𝐱)]+p=0n+1xpyn+1-pu(𝐱s)Tn+1p(𝐱).

That is,

u(𝐱)=u(𝐱0)α00(𝐱)+xu(𝐱0)α11(𝐱)+yu(𝐱0)α10(𝐱)
+k=2n[xku(𝐱0)βkk(𝐱)+xk-1yu(𝐱0)βkk-1(𝐱)]+p=0n+1xpyn+1-pu(𝐱s)Tn+1p(𝐱).

Noticing from (7.5) that α00(𝐱)=β00(𝐱),α10(𝐱)=β10(𝐱),α11(𝐱)=β11(𝐱), one finds the expression (7.6). ∎

C Interpretation of the One-Dimensional TDG Method as a Finite Difference Scheme

The goal of this section is to obtain the FD scheme (4.6) based on the Trefftz discontinuous Galerkin method (2.10) for the one-dimensional hyperbolic heat equation

(C.1){tp+cεxv=0,tv+cεxp=-σsε2v,

ε*+, σs,c+. For the sake of simplicity we assume that σs is constant in the domain. This model can be written in the form of the Friedrichs system (1.2) with

A0=(1001),A1=cε(0110),R=(000-σsε2).

We consider basis functions 𝐞i,l where i is the global number of the cell and l the local number of the basis function in the cell i. We denote by xi-12 and xi+12 the edges of the spatial cell ΩS,i, i.e. ΩS,i=[xi-12,xi+12] and xi the midpoint. We use two stationary basis functions defined as

(C.2)𝐞k,1(t,x)={(10)if (t,x)Ωk,(00)otherwise,𝐞k,2(t,x)={(-σscε(x-xk)1)if (t,x)Ωk,(00)otherwise.

We use the notation 𝐞i,1n,𝐞i,2n when designing the basis functions from the spatial cell ΩS,i at the time step n. Consider the bilinear and linear forms obtained from the decoupled formulation (2.11):

aTn(𝐮,𝐯)=-kj<kΣknjn(Mknjn-𝐯kn+Mknjn+𝐯jn)T(𝐮kn-𝐮jn)-kΩSΩkn(𝐯kn)TMkn-𝐮kn
-kΣknkn-1(𝐯kn)TMknkn-1-𝐮kn,𝐮,𝐯V(𝒯h),
(C.3)ln(𝐯)=-kΩSΩkn(𝐯kn)T𝐠S-kΣknkn-1(𝐯kn)TMknkn-1-𝐮kn-1,𝐯V(𝒯h).

In the following, we will write explicitly the equality

(C.4)aTn(𝐮,𝐞l,in)=ln(𝐞l,in),l=1,2,

for any time step n and any spatial cell ΩS,i. For simplicity we will consider periodic boundary conditions, a uniform space step h and a uniform time step Δt. Let us introduce some notation.

Definition C.1.

Define

(C.5)CS,i,ln=-kjΣknjn(Mknjn-𝐞i,ln)T(𝐮kn-𝐮jn),
CT,i,ln-1=-kΣknkn-1(𝐞i,ln)TMknkn-1-𝐮kn-1,
CT,i,ln=-kΣknkn-1(𝐞i,ln)TMknkn-1-𝐮kn.

Since 𝐮k is a combination of the basis functions in each cell, one can make the following assumption.

Assumption C.2.

Assume that 𝐮k admits the following decomposition in each cell Ωk:

𝐮k=αk𝐞k,1+βk𝐞k,2,αk,βk,

or, in an identical way, when considering the time step n and the spatial cell ΩS,i:

(C.6)𝐮in=αin𝐞i,1n+βin𝐞i,2n,αin,βin.

We can now write equality (C.4) using Definition C.1.

Proposition C.3.

Consider the model (C.1) and the basis functions (C.2). Equality (C.4) with periodic boundary conditions at the time step n in any spatial cell ΩS,i reads:

(C.7)CT,i,1n-CT,i,1n-1+CS,i,1n=0,CT,i,2n-CT,i,2n-1+CS,i,2n=0.

Proof.

Since we consider periodic boundary conditions, the term

ΩSΩkn(𝐯kn)TMkn-𝐮kn

in the bilinear form and the term

ΩSΩkn(𝐯kn)T𝐠S

in the linear form of (C.3) are equal to zero. One notices that

-kj<kΣknjn(Mknjn-𝐯kn-Mknjn+𝐯jn)T(𝐮kn-𝐮jn)=-kjΣknjn(Mknjn-𝐯kn)T(𝐮kn-𝐮jn).

Therefore one has aT(𝐮,𝐞l,in)=CT,i,ln+CS,i,ln and l(𝐞l,in)=CT,i,ln-1. Equality (C.4) gives for l=1 and l=2 the first and second equation of (C.7), respectively. ∎

Now we can study the values of the coefficients CS,i,l and CT,i,l.

Proposition C.4.

One has

(C.8)CS,i,1n=cΔt2ε(-αi-1+2αi-αi+1+(1-σsh2cε)(βi+1-βi-1))n,
(C.9)CS,i,2n=cΔt2ε((σsh2cε)2(βi+1+2βi+βi-1)+σsh2cεβi+(-βi-1+2βi-βi+1)+(1+σsh2cε)(αi+1-αi-1))n.

Proof.

For simplicity we will use the notation

M±1-=M-((0,±1)T),M±1+=M+((0,±1)T),(λk,jm,l)±=(M±1+𝐞j,l)T𝐞k,m.

Since the function 𝐞i,l is only non-zero in the cell Ωi, one can write CS,i,l from (C.5) as

(C.10)CS,i,l=tn-1tn(-(M-1-𝐞i,l)T(𝐮i-𝐮i-1)(xi-12)-(M1-𝐞i,l)T(𝐮i-𝐮i+1)(xi+12)).

Using M±1-=-M1+, the decomposition (C.6) of 𝐮in and the fact that the basis (C.2) does not depend on time, we deduce that (C.10) reads:

CS,i,ln=Δt(αi(λi,i1l)+(xi-12)+βi(λi,i2l)+(xi-12)-αi-1(λi,i-1l1)+(xi-12)-βi-1(λi,i-1l2)+(xi-12)
(C.11)+αi(λi,i1l)-(xi+12)+βi(λi,i2l)+(xi+12)-αi+1(λi,i+1l1)-(xi+12)-βi+1(λi,i+1l2)-(xi+12))n.

For nt=0, one has

M(𝐧)=M(0,nx)=cε(0nxnx0),M+(0,nx)=c2ε(1nxnx1),M-(0,nx)=c2ε(-1nxnx-1),

and one notices that

(C.12){(λji11)±(x)=c2ε,(λji12)±(x)=c2ε(-σscε(x-xi)±1),(λji22)±(x)=c2ε(1σscε((x-xi)+(x-xj))+(σscε)2(x-xi)(x-xj)).

Recalling that for simplicity h=xi+12-xi-12 for all i and inserting (C.12) into (C.11), one finds (C.8) and (C.9) for l=1 and l=2, respectively. ∎

Proposition C.5.

One has

(C.13)CT,i,1n=h,CT,i,2n=h(1+σs2h248c2ε2).

Proof.

Since -Mknkn-1-=Im, we have

CT,i,ln=-kΣknkn-1(𝐞i,ln)TMknkn-1-𝐮kn=xi-12xi+12(𝐞i,ln)T𝐮in.

One notices that

xi-12xi+12(𝐞i,1n)T𝐞i,2n=0.

Therefore, using the decomposition (C.6) of 𝐮in, one finds

CT,i,1n=αinxi-12xi+12(𝐞i,1n)T𝐞i,1n=hαin,CT,i,2n=βinxi-12xi+12(𝐞i,2n)T𝐞i,2n=h(1+σs2h248c2ε2)βin.

Proposition C.6.

The scheme (C.7) reads:

(C.14){pin-pin-1Δt+c2εh[-pi+1+2pi-pi-1+(1-a)(vi+1-vi-1)]n=0,(1+a23)vin-vin-1Δt+c2εh[a2(vi+1+2vi+vi-1)+(-vi+1+2vi-vi-1)+(1+a)(pi+1-pi-1)]n=-σsε2vin,

Proof.

Starting from (C.7), one has

CT,i,1n-CT,i,1n-1+CS,i,1n=0,CT,i,2n-CT,i,2n-1+CS,i,2n=0.

We recall the decomposition (C.6):

𝐮in(x)=αinei,1n(x)+βinei,2(x)=(pin,vin)T(x).

In particular, considering the center of the cell, one finds αin=pin(xi) and βin=vin(xi). Therefore, using (C.8), (C.9) and (C.13) in (C.7) and making the simplification αin=pin and βin=vin, one finally gets the scheme (C.14). ∎

Acknowledgements

The authors thank the referees for their comments and remarks which helped to improve the quality of this work.

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Received: 2017-05-29
Revised: 2017-12-02
Accepted: 2018-02-27
Published Online: 2018-03-22
Published in Print: 2018-07-01

© 2018 Walter de Gruyter GmbH, Berlin/Boston

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