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A Finite Element Splitting Method for a Convection-Diffusion Problem

  • Vidar Thomée EMAIL logo
Published/Copyright: September 9, 2020

Abstract

For a spatially periodic convection-diffusion problem, we analyze a time stepping method based on Lie splitting of a spatially semidiscrete finite element solution on time steps of length k, using the backward Euler method for the diffusion part and a stabilized explicit forward Euler approximation on m 1 intervals of length k / m for the convection part. This complements earlier work on time splitting of the problem in a finite difference context.

MSC 2010: 35K10; 65M15; 65M60

1 Introduction

In this paper, we shall consider a numerical method for the solution of the convection-diffusion problem in the square Ω = ( 0 , 1 ) × ( 0 , 1 ) ,

(1.1) U t = ( a U ) + b U + F in Ω , for t 0 , with u ( 0 ) = V ,

with periodic boundary conditions, where, with x = ( x 1 , x 2 ) , the initial function V = V ( x ) , the positive definite 2 × 2 matrix a = a ( x ) = ( a i j ( x ) ) , the vector b = b ( x ) = ( b 1 ( x ) , b 2 ( x ) ) and the forcing term F = F ( x , t ) are 1-periodic in x 1 and x 2 and smooth. Our method is an explicit-implicit time stepping method based on Lie splitting of a spatially discrete finite element version of (1.1).

With A U = - ( a U ) and B U = b U , the exact solution of (1.1) may be formally expressed as

U ( t ) = ( t ) V + 0 t ( t - y ) F ( y ) d y for t 0 , where ( t ) = e - t ( A - B ) .

This representation in terms of the solution operator ( t ) of the homogeneous case of (1.1) is the basis for our discretization method. Such a method was analyzed in [1] within the framework of finite differences, and here our purpose is to carry out the corresponding program with finite elements. We refer to [1] also for further references to work on splitting methods.

As a first step to define our finite element splitting method, we thus consider a spatially discrete finite element version of (1.1). Let 𝒯 h be a quasi-uniform family of triangulations of Ω, and let S h be the periodic, continuous piecewise linear functions on 𝒯 h . With ( , ) the inner product in L 2 ( Ω ) , and

A ( ψ , χ ) = ( a ψ , χ ) , B ( ψ , χ ) = ( b ψ , χ ) for all ψ , χ S h ,

the standard Galerkin spatially semidiscrete version of (1.1) is then to find u ( t ) S h for t 0 such that

( u t , χ ) + A ( u , χ ) - B ( u , χ ) = ( F , χ ) for all χ S h , t 0 , with u ( 0 ) = v V .

This equation may also be expressed in matrix form. With { Φ j } j = 1 N the pyramid function basis for S h , let

= ( m i j ) , m i j = ( Φ i , Φ j ) , 𝒜 = ( a i j ) , a i j = A ( Φ i , Φ j ) , = ( b i j ) , b i j = B ( Φ i , Φ j ) , 𝐟 = ( f j ) T , f j = ( F , Φ j ) and 𝐯 = ( v 1 , , v N ) T .

With u h ( t ) = j = 1 N 𝐮 j ( t ) Φ j and 𝐮 = ( 𝐮 1 , , 𝐮 N ) T , we have

(1.2) 𝐮 + 𝒜 𝐮 = 𝐮 + 𝐟 for t 0 , with 𝐮 ( 0 ) = 𝐯 .

For our purposes, it will be more convenient to use instead a semidiscrete method based on the lumped mass method, employing the approximate inner product on S h defined by

( ψ , χ ) h = τ 𝒯 h W τ , h ( ψ χ ) with W τ , h ( f ) = 1 3 | τ | j = 1 3 f ( P τ , j ) τ f d x ,

where, for a triangle τ of the triangulation 𝒯 h , P τ , j , j = 1 , 2 , 3 , are its vertices and where | τ | = area ( τ ) ; cf. [2, Chapter 15]. We shall then consider the semidiscrete problem, with u ( t ) S h for t 0 ,

(1.3) ( u t , χ ) h + A ( u , χ ) - B ( u , χ ) = ( F , χ ) for all χ S h , t 0 , u ( 0 ) = v .

Introducing the operators A h , B h : S h S h by

( A h ψ , χ ) h = A ( ψ , χ ) , ( B h ψ , χ ) h = B ( ψ , χ ) for all ψ , χ S h ,

equation (1.3) may also be written as

(1.4) u t + A h u - B h u = f for t 0 , with f = P ~ h F , u ( 0 ) = v ,

where P ~ h : L 2 S h is defined by ( P ~ h F , χ ) h = ( F , χ ) for all χ S h . In matrix form, this means that the matrix in (1.2) is replaced by the diagonal matrix 𝒟 = ( d i j ) , where d i j = ( Φ i , Φ j ) h . The solution of (1.4) satisfies

u ( t ) = E h ( t ) v + 0 t E h ( t - y ) f ( y ) d y , where E h ( t ) = e - t ( A h - B h ) , for t 0 .

We recall that E h ( t ) , the solution operator of the homogeneous case of (1.4), is stable and that the solution of (1.4) satisfies an O ( h 2 ) error estimate for suitable v.

To define our basic finite element splitting method, let k be a time step and t n = n k for n 0 . On each time interval ( t n - 1 , t n ) , we then introduce the Lie splitting E h , k = e k B h e - k A h of E h ( k ) and define a time discrete solution of (1.4) by

(1.5) u n = E h , k u n - 1 + k f n for n 1 , with u 0 = v .

We note that the two factors of E h , k are associated with the hyperbolic and parabolic parts of equation (1.1),

For a computable discretization in space and time, we then need to replace e - k A h and e k B h by rational functions of A h and B h , respectively. For the parabolic part, we shall use the implicit backward Euler operator

(1.6) Q h , k = ( I h + k A h ) - 1 e - k A h ,

where I h is the identity operator on S h . For the hyperbolic part, we define

H h , k = I h + k B h - γ k 2 L h e k B h ,

where the operator L h , defined by ( L h ψ , χ ) h = ( ψ , χ ) for all ψ , χ S h , is added to secure stability, under a mesh-ratio condition for k / h . In matrix form, the application of H h , k takes the form

𝒟 𝐰 = ( 𝒟 + k - γ k 2 ) 𝐯 , where = ( l i j ) , l i j = ( ( Φ i , Φ j ) ) ,

where the diagonal matrix on the left shows that H h , k is essentially explicit.

More generally, on each interval ( t n - 1 , t n ) , we shall allow the use m steps of the hyperbolic time stepping operator with step k m = k / m , i.e., instead of H h , k , we apply H h , k m m e k B h . This will increase the accuracy and the bound for the mesh ratio but not significantly the cost of the computation since H h , k m is explicit. We consider thus the time discrete solution defined for n 1 by

(1.7) u ~ m n = E ~ h , k , m u ~ m n - 1 + k f n , where E ~ h , k , m = H h , k m m Q h , k , with u ~ m 0 = v .

Our main result is then that, for v appropriate, the error satisfies

u ~ n - U ( t n ) C T ( U ) h + C T ′′ ( U ) k + C T ′′′ ( U ) k m for t n T .

We remark that the first term in this error bound comes from the spatial discretization, the second from the splitting and the backward Euler discretization of the parabolic part, and the third from the approximation of the hyperbolic part. In [1], numerical illustrations of these partial errors were presented in the finite difference case, in the present context essentially corresponding to uniform triangulations, and we note that the spatial discretization is then of order O ( h 2 ) . In [1], the choice of m to balance the last two terms was also discussed.

2 Splitting of the Semidiscrete Problem

In this section, we will show that the result u n in (1.5) of Lie splitting of the spatially discrete problem (1.3) differs from the exact solution U ( t n ) of (1.1) by O ( h + k ) , under the appropriate regularity assumptions and choice of v.

For 1-periodic functions, we define V s = V H s ( Ω ) for s 0 . Note that A V s C V s + 2 , B v s C V s + 1 and V s C ( A s / 2 V + V ) , where V = V L 2 ( Ω ) . Further, for (1.1), we recall the stability estimates

(2.1) e - t ( A - B ) V s + e - t A V s + e t B V s C T V s for s 0 , 0 t T ,

and the smoothing property

(2.2) ( t ) V j C t - ( s - j ) / 2 V s for  0 < s < j , t > 0 .

We begin the analysis with the following stability result for the operator E h , k in (1.5). Here and below, we shall use the norm χ h = ( χ , χ ) h 1 / 2 on S h , which is equivalent to χ or, more precisely, satisfies

1 4 χ h χ χ h .

Lemma 2.1.

With β 0 = 1 2 div b C , we have, for v S h and t 0 ,

(2.3) e - t ( A h - B h ) v h + e t B h v h e β 0 t v h 𝑎𝑛𝑑 e - t A h v h v h .

Further, for E h , k = e k B h e - k A h , we have

(2.4) E h , k n v h e β 0 t n v h 𝑓𝑜𝑟 v S h , n 0 .

Proof.

Since, for χ S h ,

(2.5) | B ( χ , χ ) | = | ( b χ , χ ) | = | 1 2 ( div b χ , χ ) | β 0 χ 2 β 0 χ h 2 ,

we have, for the solution u ( t ) = e - t ( A h - B h ) v of (1.4) with f = 0 ,

( u t , u ) h + A ( u , u ) = B ( u , u ) β 0 u h 2 for t 0 .

Hence ( d / d t ) u h β 0 u h , from which the first part of (2.3) follows. The other parts are shown analogously. For (2.4), we conclude

E h , k n v h = ( e k B h e - k A h ) n v h e β 0 n k v h .

We next show an error estimate for one step of the Lie splitting of ( k ) .

Lemma 2.2.

We have, for E k = e k B e - k A ,

(2.6) k V - ( k ) V C k j V 2 j , j = 1 , 2 .

Proof.

Setting G ( t ) = e t B e - t A - e - t ( A - B ) and noting that G ( 0 ) = G ( 0 ) = 0 , we have, by Taylor’s formula,

G ( k ) V = ( G ( k ) - G ( 0 ) - k G ( 0 ) ) V 1 2 k 2 sup s k G ′′ ( s ) V .

Here, for s k ,

G ′′ ( s ) V C i 1 + i 2 = 2 B i 1 e s B A i 2 e - s A v + ( A - B ) 2 e - s ( A - B ) V C V 4 ,

which by (2.1) shows (2.6) for j = 2 . In the same way, the case j = 1 follows from G ( s ) V C V 2 for s k . ∎

We shall need error bounds for the spatial discretizations of the parabolic and hyperbolic parts of E h , k . Here and below, we shall use the Ritz projection R h : H 1 S h defined by A ^ ( R h V - V , χ ) = 0 for all χ S h , where A ^ ( ψ , χ ) = A ( ψ , χ ) + ( ψ , χ ) . Recall that

(2.7) R h V - V s C h j - s V j for s = 0 , 1 , s j 2 .

We also recall that, for ε h ( ψ , χ ) = ( ψ , χ ) h - ( ψ , χ ) ,

(2.8) | ε h ( ψ , χ ) | C h 2 ψ χ C h j ψ j χ for all ψ , χ S h , j = 0 , 1 ,

where, in the last step, we have used the inverse inequality

(2.9) χ 1 ν h - 1 χ for χ S h ,

valid since the family { 𝒯 h } is quasi-uniform.

Lemma 2.3.

For any ε > 0 and for j = 0 , 1 , we have

(2.10) e - k A h R h V - R h e - k A V C ε k j h V s j , 𝑤ℎ𝑒𝑟𝑒 s 0 = 1 + ε , s 1 = 3 ,
(2.11) e k B h R h V - R h e k B V C k h j V 1 + j .

Proof.

For (2.10), we set W ( t ) = e - t A V and w ( t ) = e - t A h R h V . We want to bound θ ( k ) , where θ = w - R h W . With ρ = R h W - W , we have

( θ t , χ ) h + A ( θ , χ ) = - ( ρ t , χ ) + ( ρ , χ ) - ε h ( R h W t , χ ) for all χ S h , for t 0 .

Choosing χ = θ , we find, using (2.7) and (2.8), for t 0 ,

d d t θ h C ( ρ t + ρ + h R h W t 1 ) C h W 3 C h t - 1 2 ( 3 - s j ) V s j .

Since θ ( 0 ) = 0 , this shows θ ( k ) C h k 1 2 ( s j - 1 ) V s j and thus (2.10).

For (2.11), we set W ( t ) = e t B V and w ( t ) = e t B h R h V . In this case, again with θ = w - R h W , ρ = R h W - W , we have

( θ t , χ ) h = B ( θ , χ ) - ( ρ t , χ ) + B ( ρ , χ ) - ε h ( R h W t , χ ) for all χ S h , for t 0 .

Choosing χ = θ and using (2.5), (2.7) and (2.8), we find

d d t θ h β 0 θ + C ( ρ t + ρ 1 + h j R h W t j ) β 0 θ h + C h j V 1 + j ,

which implies (2.11) since θ ( 0 ) = 0 . ∎

This shows the following error estimate for the operator E h , k .

Lemma 2.4.

For any ε > 0 , we have, for j = 0 , 1 , with s 0 = 1 + ε , s 1 = 3 ,

(2.12) E h , k R h V - R h ( k ) V C ε k j h V s j + C k 1 + j V 2 + 2 j .

Proof.

Recalling k = e k B e - k A , we have

E h , k R h - R h k = e k B h ( e - k A h R h - R h e - k A ) + ( e k B h R h - R h e k B ) e - k A .

Hence, by Lemmas 2.1 and 2.3, E h , k R h V - R h k V is bounded as in (2.12). By Lemma 2.2 and the boundedness of R h , we also find R h ( k - ( k ) ) V C k 1 + j V 2 + 2 j , j = 0 , 1 . Together, these estimates show the lemma. ∎

We now show a global error estimate for the homogeneous equation.

Lemma 2.5.

We have, for any ε > 0 , if v - V C h V 1 ,

(2.13) E h , k n v - ( t n ) V C ε , T h V 1 + ε + C ε , T ′′ k V 2 + ε 𝑓𝑜𝑟 t n T .

Proof.

We find, using (2.4), and Lemma 2.4 with j = 0 for the first term on the right below and with j = 1 for the terms in the sum, and then the smoothing estimate (2.2),

( E h , k n R h - R h ( t n ) ) V = j = 0 n - 1 E h , k n - j - 1 ( E h , k R h - R h ( k ) ) ( t j ) V C ( E h , k R h - R h ( k ) ) V + C j = 1 n - 1 ( E h , k R h - R h ( k ) ) ( t j ) V C ε h V 1 + ε + C k V 2 + C k j = 1 n - 1 ( h ( t j ) V 3 + k ( t j ) V 4 ) C ε ( 1 + k j = 1 n - 1 t j - 1 + ε / 2 ) ( h V 1 + ε + k V 2 + ε ) .

Since E h , k n ( v - R h V ) + ( R h - I ) ( t n ) V C h V 1 , (2.13) follows. ∎

One possible choice for v with v - V C h V 1 which will be used below is v = P ~ h V . In fact, since

( P ~ h V - P h V , χ ) h = - ε h ( P h V , χ ) ,

we find P ~ h V - P h V h C h P h V 1 C h V 1 , from which our claim follows.

We now show a complete error estimate for our basic splitting method.

Theorem 2.1.

Let u n be the solution of (1.5) with v - V C h V 1 and U ( t n ) that of (1.1). Then we have, for any ε > 0 , t n T ,

u n - U ( t n ) C ε , T h Z 1 + ε ( U , t n ) + C ε , T ′′ k Z ^ 2 + ε ( U , t n ) ,

where

Z s ( U , t ) = V s + 0 t F ( y ) s d y , Z ^ s ( U , t ) = Z s ( U , t ) + 0 t F ( y ) d y .

Proof.

In view of Lemma 2.5, it suffices to consider the case v = 0 . Recalling that f = P ~ h F , we may write the error e n = u n - U ( t n ) as

e n = k j = 1 n E h , k n - j f j - 0 t n ( t n - y ) F ( y ) d y = k j = 1 n ( E h , k n - j P ~ h - ( t n - j ) ) F j + j = 1 n ( k ( t n - j ) F j - I j ( t n - y ) F ( y ) d y ) = J + J ′′ , I j = ( t j - 1 , t j ) .

To bound J , we set h , k , j = E h , k j P ~ h - ( t j ) and write

k ( E h , k n - j P ~ h - ( t n - j ) ) F j = I j h , k , n - j F ( y ) d y + I J y t j h , k , n - j F ( σ ) d σ d y .

By Lemma 2.5, we find

j = 1 n I j h , k , n - j F ( y ) d y C ε , T 0 t n ( h F ( y ) 1 + ε + k F ( y ) 2 + ε ) d y

and, since h , k , j is bounded,

j = 1 n I j y t j h , k , n - j F ( σ ) d σ d y C ε , T k 0 t n F ( y ) d y .

Thus J is bounded as claimed. Similarly, J ′′ = j = 1 n J j ′′ , where

J j ′′ = I j ( ( t n - j ) F j - ( t n - y ) F ( y ) ) d y = I j y t j d d σ ( ( t n - σ ) F ( σ ) ) d σ d y = I j y t j ( t n - σ ) ( ( 𝒜 - ) F ( σ ) + F ( σ ) ) d σ d y .

Thus, using the stability of ( t ) ,

J ′′ j = 1 n J j ′′ C T k 0 t n ( F ( σ ) 2 + F ( σ ) ) d σ for t n T .

Adding these estimates completes the proof. ∎

3 Complete Discretization in Time and Space

We now turn to the analysis of the complete discretization using the operators Q h , k and H h , k m m in (1.6) and (1.7) for the parabolic and hyperbolic factors of E h , k = e k B h e - k A h . We note that, since

| ( B h ψ , χ ) h | b ψ χ β 1 ψ χ for ψ , χ S h , where β 1 = sup Ω | b ( x ) | ,

we have B h ψ h β 1 ψ for ψ S h . Further, by (2.9), L h ψ h ν h - 1 ψ .

We shall first consider the stability of E ~ h , k , m .

Lemma 3.1.

We have Q h , k v h v h for v S h . Let β 0 = 1 2 div b C and β 1 and ν as above. Then, if γ > β 1 2 , we have

H h , k m m v h ( 1 + β 0 k ) v h 𝑓𝑜𝑟 k m / h λ 0 = ( γ - β 1 2 ) / ( γ ν ) 2 .

The time stepping operator E ~ h k , m = H h , k m m Q h , k is stable and

(3.1) E ~ h , k , m n v h e β 0 t n v h 𝑓𝑜𝑟 t n 0 .

Proof.

The first inequality is obvious by the definition of Q h , k . For the hyperbolic part, we begin with m = 1 . Setting w 1 = H h , k v , w 0 = v , we have ¯ t w 1 + γ k L h v = B h v , where ¯ t w 1 = ( w 1 - w 0 ) / k . Recalling (2.5), we have

( ¯ t w 1 , v ) h + γ k v 2 = B ( v , v ) β 0 v 2 β 0 v h 2

or, writing v = 1 2 ( w 1 + v ) - 1 2 ( w 1 - v ) ,

(3.2) 1 2 ( w 1 h 2 - v h 2 ) - 1 2 w 1 - v h 2 + γ k 2 v 2 β 0 k v h 2 .

Here, since w 1 - v = k B h v - k 2 γ L h v and using (2.9), we have, for k / h λ 0 ,

1 2 w 1 - v h 2 k 2 B h v h 2 + γ 2 k 4 L h v h 2 k 2 ( β 1 2 + γ 2 ν 2 λ 0 2 ) v 2 = γ k 2 v 2 .

Hence, by (3.2), w 1 h 2 ( 1 + 2 β 0 k ) v h 2 , which shows our claim for m = 1 .

For m > 1 , we have

(3.3) H h , k m m v h ( 1 + β 0 k m ) m v h e β 0 k v h for k m / h λ 0 ,

and (3.1) now follows at once. ∎

For our analysis, we shall need norms on S h which are analogues of s . We introduce A ¯ h : S h S h by ( A ¯ h ψ , χ ) = A ( ψ , χ ) for all χ S h . Noting that A ¯ h is positive semidefinite, we set A ^ h = A ¯ h + I h and define

ψ h , s = A ^ h s / 2 ψ = ( A ^ h s ψ , ψ ) 1 / 2 for all ψ S h , for s 0 .

For s = 1 , we have the obvious norm equivalence c ψ 1 ψ h , 1 C ψ 1 for ψ S h , with c > 0 , and, by the inverse inequality (2.9),

(3.4) ψ h , s ( ρ / h ) s - j ψ h , j for ψ S h , 0 j s .

We shall need the following lemma.

Lemma 3.2.

We have

(3.5) e t B h v h , 2 C v h , 2 𝑓𝑜𝑟 v S h , 0 t C h .

Proof.

We first show

(3.6) B h ψ h , 1 C ψ h , 2 for ψ S h .

We see at once that P ~ h is bounded on L 2 and, using (2.9),

P ~ h ψ 1 R h ψ 1 + C h - 1 P ~ h ψ - ψ h + C h - 1 R h ψ - ψ C ψ 1 .

Inequality (3.6) may also be formulated as B h T h ψ 1 C ψ for ψ S h , where T h = A ^ h - 1 . To show this inequality, we have, with T = ( A + I ) - 1 ,

B h T h ψ 1 P ~ h ( b T ) ψ 1 + C h - 1 P ~ h ( b ( T h - T ) ) ψ h C T ψ 1 + C h - 1 ( T h - T ) ψ 1 C T ψ 2 C ψ .

With w ( t ) = e t B h v and ( ψ , χ ) h , 2 = ( A ^ h ψ , A ^ h χ ) for ψ , χ S h , we have, using (3.4) and (3.6),

1 2 d d t w h , 2 2 = ( w t , w ) h , 2 = ( B h w , w ) h , 2 C h - 1 B h w h , 1 w h , 2 C h - 1 w h , 2 2 .

Hence, by integration, w ( t ) h , 2 C e C t h - 1 v h , 2 , which shows (3.5). ∎

We have the following error estimates for one step of the parabolic and hyperbolic approximations.

Lemma 3.3.

We have, for v S h ,

(3.7) ( Q h , k - e - k A h ) v C k h j v h , 2 + j + C k 1 + j v h , 2 + 2 j , j = 0 , 1 .

With β 1 , γ, λ 0 as in Lemma 3.1, we have, for k m / h λ 0 ,

(3.8) ( H h , k m m - e k B h ) v C m - 1 k 2 v h , 2 𝑓𝑜𝑟 v S h .

Proof.

We first note that, with Q ¯ h , k = ( I h + k A ¯ h ) - 1 ,

( Q ¯ h , k - e - k A ¯ h ) v C k 1 + j A ¯ h 1 + j v C k 1 + j v h , 2 + 2 j for all v S h .

Estimate (3.7) will now follow from

(3.9) Q h , k - Q ¯ h , k ) v + ( e k A h - e - k A ¯ h ) v C k h j v h , 2 + j for all v S h .

Setting w 1 = Q h , k v , w ¯ 1 = Q ¯ h , k v , w 0 = w ¯ 0 = v and ω j = w j - w ¯ j , we have

( ¯ t ω 1 , χ ) h + A ( ω 1 , χ ) = ε h ( ¯ t w ¯ 1 , χ ) for χ S h

or, with χ = ω 1 , since ω 0 = 0 , and using (2.8),

Q h , k - Q ¯ h , k ) v = ω 1 C k h j ¯ t w ¯ 1 j C k h j A ¯ h w ¯ 1 j C k h j v h , 2 + j .

Now, let w ( t ) = e - t A h v , w ¯ ( t ) = e - t A ¯ h v , and set θ ( t ) = w ( t ) - w ¯ ( t ) . Then

( θ t , χ ) h + A ( θ , χ ) = ε h ( w ¯ t , χ ) for χ S h , t 0 , with θ ( 0 ) = 0 .

Setting χ = θ and using (2.8), we obtain

θ ( k ) h C h j 0 k w ¯ t ( s ) j d s C h j 0 k A ¯ h w ¯ ( s ) j d s C k h j v h , 2 + j ,

which completes the proof of (3.9).

We turn to (3.8) and begin with m = 1 . We have

( H h , k - e k B h ) v ( I h + k B h - e k B h ) v + γ k 2 L h v

Using (3.6) and (3.5), we obtain

( H h , k - e k B h ) v C k 2 sup s k B h 2 e s B h v C k 2 v h , 2 .

To complete the proof, we show L h v C v h , 2 or, equivalently, with T h as in Lemma 3.2, L h T h v C v . For this, we use the Ritz projection defined by ( R ~ h w , χ ) + ( R ~ h w , χ ) = ( w , χ ) + ( w , χ ) for all χ S h . We find ( L h R ~ h w , χ ) h = ( R ~ h w , χ ) = ( w , χ ) - ( R ~ h w - w , χ ) = - ( Δ w , χ ) - ( R ~ h w - w , χ ) and hence L h R ~ h w C w 2 . Using also L h χ C h - 2 χ , the proof is completed by

L h T h w L h R ~ h T w + C h - 2 ( R ~ h T w - T w + T h w - T w ) C w .

To show (3.8) for m > 1 , we write

(3.10) H h , k m m v - e k B h v = j = 0 m - 1 H h , k m m - j - 1 ( H h , k m - e k m B h ) e j k m B h v .

By Lemma 3.2 with t = j k m k λ 0 h , we have e j k m B h v h , 2 C v h , 2 . Using (3.10), (3.3) and the already proven case of (3.8), with k replaced by k m , we find

H h , k m m v - e k B h v h e β 0 k j = 0 m - 1 ( H h , k m - e k m B h ) e j k m B h v h C k m 2 j = 0 m - 1 e j k m B h v h , 2 C m k m 2 v h , 2 = C m - 1 k 2 v h , 2 .

As a result, we have the following error estimate for the completely discrete time stepping operator.

Lemma 3.4.

If γ > β 1 2 and k m / h λ 0 , we have, with s 0 = 1 + ε , s 1 = 3 ,

E ~ h , k , m R h V - R h ( k ) V C k h j V s j + C ′′ k 1 + j V 2 + 2 j + C ′′′ m - 1 k 2 V 2 𝑓𝑜𝑟 j = 0 , 1 .

Proof.

In view of Lemma 2.4, it remains to bound ( E ~ h , k , m - E h , k ) R h V . We have, for v S h , by Lemmas 3.1 and 3.3,

( E ~ h , k , m - E h , k ) v H h , k m m ( Q h , k - e - k A h ) v + ( H h , k m m - e k B h ) e - k t A h v C k h j v h , 1 + 2 j + C ′′ k 1 + j v h , 2 + 2 j + C ′′′ m - 1 k 2 v h , 2 .

For v = R h V , we find v h , 2 C V 2 , and since A ^ h R h = P h A ^ ,

v h , 4 = A ^ h 2 R h V = A ^ h P h A V A ^ h R h A V + A ^ h ( P h - R h ) A ^ V P h A ^ 2 V + C h - 2 h 2 A ^ V 2 C V 4 ,

and similarly, v h , 3 C V 3 , which completes the proof of the lemma. ∎

This implies the following result for the homogeneous equation.

Lemma 3.5.

Let ε > 0 and γ > β 1 2 . Then, if v - V C h V 1 , we have, for k m / h λ 0 , t n T ,

E ~ h , k , m n v - ( t n ) V C ε , T h V 1 + ε + C ε , T ′′ k V 2 + ε + C T m - 1 k V ε .

Proof.

Using the stability of E ~ h , k , m and Lemma 2.4 instead of Lemma 3.4, the result follows as that in Lemma 2.5. ∎

We are now ready to formulate our main result.

Theorem 3.1.

Assume that γ > β 1 2 . Then, for the solutions u ~ n of (1.7) with v - V h V 1 and U ( t n ) of (1.1), we have, with Z s ( U , t ) and Z ^ s ( U , t ) as in Theorem 2.1, for any ε > 0 and k m / h λ 0 ,

u ~ n - U ( t n ) C ε , T h Z 1 + ε ( U , t n ) + C ε , T ′′ k Z ^ 2 + ε ( U , t n ) + C ε , T ′′′ m - 1 k Z ε ( U , t n ) .

Proof.

The proof is analogous to that of Theorem 2.1, with E h , k replaced by E ~ h , k , m , the stability property (2.4) by (3.1), and Lemma 2.5 by Lemma 3.5. ∎


Dedicated to the memory of Alexander Andreevich Samarskii


References

[1] A. K. Pani, V. Thomeée and A. S. Vasudeva Murthy, A first order explicit-implicit splitting method for a convection-diffusion problem, Comput. Methods Appl. Math. (2020), 10.1515/cmam-2020-0009. 10.1515/cmam-2020-0009Search in Google Scholar

[2] V. Thomée, Galerkin Finite Element Methods for Parabolic Problems, 2nd ed., Springer, Berlin, 2006. Search in Google Scholar

Received: 2020-08-17
Accepted: 2020-08-27
Published Online: 2020-09-09
Published in Print: 2020-10-01

© 2021 Walter de Gruyter GmbH, Berlin/Boston

This work is licensed under the Creative Commons Attribution 4.0 International License.

Articles in the same Issue

  1. Frontmatter
  2. Editorial
  3. Modern Problems of Numerical Analysis. On the Centenary of the Birth of Alexander Andreevich Samarskii
  4. Special Issue Articles
  5. Finite Difference Approximation of a Generalized Time-Fractional Telegraph Equation
  6. Weighted Estimates for Boundary Value Problems with Fractional Derivatives
  7. Lagrangian Mixed Finite Element Methods for Nonlinear Thin Shell Problems
  8. Reliable Computer Simulation Methods for Electrostatic Biomolecular Models Based on the Poisson–Boltzmann Equation
  9. Adaptive Space-Time Finite Element Methods for Non-autonomous Parabolic Problems with Distributional Sources
  10. On Convergence of Difference Schemes for Dirichlet IBVP for Two-Dimensional Quasilinear Parabolic Equations with Mixed Derivatives and Generalized Solutions
  11. Difference Schemes on Uniform Grids for an Initial-Boundary Value Problem for a Singularly Perturbed Parabolic Convection-Diffusion Equation
  12. A Finite Element Splitting Method for a Convection-Diffusion Problem
  13. Incomplete Iterative Implicit Schemes
  14. Explicit Runge–Kutta Methods Combined with Advanced Versions of the Richardson Extrapolation
  15. Regular Research Articles
  16. A General Superapproximation Result
  17. A First-Order Explicit-Implicit Splitting Method for a Convection-Diffusion Problem
  18. A Factorization of Least-Squares Projection Schemes for Ill-Posed Problems
  19. A New Mixed Functional-probabilistic Approach for Finite Element Accuracy
  20. Error Analysis of a Finite Difference Method on Graded Meshes for a Multiterm Time-Fractional Initial-Boundary Value Problem
  21. A Finite Element Method for Elliptic Dirichlet Boundary Control Problems
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