GALERKIN METHOD FOR TIME FRACTIONAL DIFFUSION EQUATIONS

HAL Id: hal-01761523

https://hal.archives-ouvertes.fr/hal-01761523

Preprint submitted on 9 Apr 2018

HAL is a multi-disciplinary open access archive for the deposit and dissemination of sci- entific research documents, whether they are pub- lished or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers.

L’archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d’enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

DIFFUSION EQUATIONS

Arnaud Rougirel, Laid Djilali

To cite this version:

Arnaud Rougirel, Laid Djilali. GALERKIN METHOD FOR TIME FRACTIONAL DIFFUSION EQUATIONS. 2018. �hal-01761523�

EQUATIONS

LAID DJILALI AND ARNAUD ROUGIREL

Abstract. We propose a Galerkin method for solving time fractional diffusion problems under quite general assumptions. Our approach relies on the theory of vector valued distributions. As an application, the “` goes to plus infinity” issue for these problems is investigated.

1. Introduction

The Galerkin approximation method in an efficient and robust tool for solving linear and nonlinear partial differential equations (see for instance [Tem88], [Lio69]).

In this paper, we implement this method for solving time fractional diffusion prob- lems. Our implementation allows non trivial initial conditions and the functional framework is quite simple.

There are two drawbacks for solving time fractional PDE’s with the Galerkin method. First, an estimate from below is needed for integrals of the form

Z T 0

Z

Ω

D^αu(t, x)u(t, x) dxdt

Here u = u(t, x) is the solution of some time fractional PDE set on [0, T]×Ω ⊂ [0,∞)× R^d, and α ∈ (0,1). The positivity of that integral can be achieved by assuming, roughly speaking, thatu(0, x) = 0(see [TM15]). However, this hypothesis is clearly too restrictive. Also, in the integer setting (i.e. when α = 1), the above integral equals

1

2ku(T)k²_L2(Ω)− 1

2ku(0)k²_L2(Ω).

Hence, it has no sign. Thus, in the fractional case, we may expect to control this integral in a similar way. This is indeed the case: in the proof of Theorem 4.1, we decompose that integral into the sum of a bad term, which turns out to be positive (by an estimate due to Nohel and Shea; see Theorem 2.1), and a quantity with no sign but controllable.

The second difficulty concerns functional spaces. In many papers, fractional Gagliardo-Sobolev spaces are used. These spaces are quite complicated to handle, and the necessity of their use in the Galerkin method, seems not obvious to the authors. Moreover, in order to have a continuation property from the time interval [0, T] into R, a trivial initial condition is needed (see [LX09], [JLPR15]).

In this paper, we use simple functional spaces which are natural generalization of the spaces involved in the integer setting (see Definition 4.1). We consider Riemann- Liouville derivatives.

Date: March 23, 2018.

Key words and phrases. Galerkin method, Time fractional diffusion equations.

In the two forcoming sections, we give the background on weak fractional deriva- tives. The Galerkin method is implemented in section 4 for solving a time fractional model problem. Finally, in Section 5, we apply our result to the “` goes to plus in- finity” issue. It is about to study the asymptotic behavior of the solutionu=u(t, x) when the domainΩ = Ω` becomes unbounded in one or several directions as`→ ∞.

2. Preliminaries

For (X,k · k) a real Banach space, let us introduce the convolution of functions and the (formal) adjoint of the convolution.

Definition 2.1. Letg ∈L¹_loc([0,∞)), T >0 and f ∈L¹(0, T;X). Then the convo- lution of g and f is the function ofL¹(0, T;X) defined by

g∗f(t) :=

Z t 0

g(t−y)f(y)dy, a.e. t∈[0, T].

Also, we define

g∗⁰f(t) :=

Z T t

g(y−t)f(y)dy, a.e. t∈[0, T].

Remark 2.1. Roughly speaking, f 7→ g ∗⁰ f is the adjoint of f 7→ g∗f. Indeed, for f,g as above and ψ ∈C([0, T]), one has, by Fubbini’s Theorem

Z T 0

g∗f(t)ψ(t) dt= Z T

0

f(t)g∗⁰ψ(t) dt.

The following kernel is of fundamental importance in the theory of fractional derivatives.

Definition 2.2. For β ∈ (0,∞), let us denote by gβ the function of L¹_loc([0,∞)) defined for a.e. t >0by

g_β(t) = 1

Γ(β)t^β−1. For each α, β ∈(0,∞), the following identity holds.

g_α∗g_β =g_α+β, in L¹_loc [0,∞)

. (2.1)

Let us recall the following well-known result: if f ∈L²(0, T;X) and g ∈ L¹(0, T) then

g∗f ∈L²(0, T;X) and kg∗fk_L²_(0,T;X) ≤ kgk_L¹_(0,T)kfk_L²_(0,T;X). (2.2) The following deep result due to Nohel and Shea ([NS76, Theorem 2 & Corollary 2.2]) is a crucial tool for estimating. That result was originally stated for scalar valued functions but can easily be extended into an hilbertian setting.

Theorem 2.1. Let (H,(·,·))be a real Hilbert space, f ∈L²(0, T;H) and α∈(0,1).

Then

Z T 0

f(t), g_α∗f(t)

dt≥0.

3. Riemann fractional derivatives

We will introduce fractional derivatives and weak fractional derivatives, that is, fractional derivatives in the sense of distributions. Let us start with the well-known fractional forward and backward derivatives of a function in the sense of Riemann and Liouville. We refer to [Pod99] for more details on fractional derivatives.

Definition 3.1. Letα∈(0,1), T >0 and f ∈L²(0, T;X). We say that f admits a (forward) derivative of order α in L²(0, T;X) if

g_1−α∗f ∈H¹(0, T;X).

In this case, its (forward) derivative of order αis the function ofL²(0, T;X)defined by

RD^α_0,tf := d dt

g1−α∗f .

Definition 3.2. Let α ∈ (0,1), T > 0 and f ∈ W^1,1(0, T;X). Then we say that f admits a backward derivative of order α in L²(0, T;X) if

g1−α∗⁰ d

dtf ∈L²(0, T;X).

In this case, its backward derivative of order α is the function of L²(0, T;X)defined by

RD^α_t,Tf :=g1−α∗⁰ d dtf.

Remark 3.1. If f ∈ H¹(0, T;X) then g1−α ∗⁰ _dt^df lies in L²(0, T;X), according to (2.2). Hence f admits a fractional backward derivative of orderα in L²(0, T;X).

Proposition 3.1. Let α∈(0,1), f ∈L²(0, T;X) andψ ∈H¹(0, T). Assume that f admits a derivative of order α in L²(0, T;X). Then

Z T 0

D^α_0,tf(t)ψ(t) dt=− Z T

0

f(t)^RD^α_t,Tψ(t) dt+

g1−α∗f ψT

0. (3.1) Moreover, if, in addition, ψ ∈ D(0, T) then

Z T 0

f(t)D^α_t,Tψ(t) dt ≤√

T g2−α(T)kfk_L²_(0,T;X)kψ⁰k∞,[0,T]. (3.2) Proof. Starting to integrate by part, we obtain

Z T 0

D^α_0,tf(t)ψ(t) dt=− Z T

0

g_1−α∗f(t)d

dtψ(t) dt+

g_1−α∗f ψT 0

=− Z T

0

f(t)g1−α∗⁰ d

dtψ(t) dt+

g1−α∗f ψT

0 (by Rem. 2.1)

=− Z T

0

f(t)^RD^α_t,Tψ(t) dt+

g1−α∗f ψT

0 (by Def. 3.2).

In order to prove (3.2), we use Cauchy-Schwarz inequality and the estimate kD^α_t,Tψk_L^∞_(0,T) ≤g_2−α(T)kψ⁰k_L^∞_(0,T).

That property allows us to define fractional derivative in the sense of distributions.

Indeed, (3.2) shows that the linear map D(0, T)→X, ϕ7→ −

Z T 0

f(t)^RD^α_t,Tϕ(t) dt

is a distribution, whose order is (at most) 1. The set of distributions with values in X is denoted byD⁰(0, T;X). That allows us to set the following definition.

Definition 3.3. Let α ∈ (0,1) and f ∈ L²(0, T;X). Then the weak derivative of order α of f is the vector valued distribution, denoted by ^RD^α_0,tf, and defined, for all ϕ∈ D(0, T), by

h^RD^α_0,tf, ϕi=− Z T

0

f(t)^RD^α_t,Tϕ(t) dt.

If we want to highlight the duality taking place in the above bracket, we will write h^RD^α_0,tf, ϕi_D⁰_{(0,T;X),D(0,T)}

instead of h^RD^α_0,tf, ϕi. The following result states that weak derivative extend frac- tional derivatives in L²(0, T;X). That justifies the use of the same notation in definitions 3.1 and 3.3.

Proposition 3.2. Let α ∈(0,1) and f ∈L²(0, T;X).

(i) If f admits a derivative of order α in L²(0, T;X) (in the sense of Definition 3.1) then that derivative is equal to the weak derivative of f.

(ii) If the weak derivative of f belongs to L²(0, T;X) then f admits a derivative in L²(0, T;X) and these two derivatives are equal.

Proof. (i) Let ^RD^α_0,tf be the derivative of f in L²(0, T;X). Then, for each ϕ ∈ D(0, T), Proposition 3.1 leads to

Z T 0

RD^α_0,tf(t)ϕ(t) dt=− Z T

0

f(t)^RD^α_t,Tϕ(t) dt.

Then Definition 3.3 tells us that ^RD^α_0,tf is the weak derivative of f.

(ii) Let ^RD^α_0,tf denote the weak derivative of f (in the sense of Definition 3.3).

Then

h^RD^α_0,tf, ϕiD⁰(0,T;X),D(0,T)=− Z T

0

f(t)g1−α∗⁰ d

dtϕ(t) dt

=− Z T

0

g1−α∗f(t)d

dtϕ(t) dt,

by Remark 2.1. Since, by assumption, ^RD^α_0,tf lies in L²(0, T;X) we deduce that g1−α∗f is in H¹(0, T;X) and

d dt

g1−α∗f = ^RD^α_0,tf, in L²(0, T;X).

Proposition 3.3. Let α ∈ (0,1), V be a real Banach space and f ∈ L²(0, T;V⁰).

We assume that f admits a derivative of order α in L²(0, T;V⁰). Then, for each v in V, hf, vi_V⁰_,V admits a derivative of order α in L²(0, T) and

h^RD^α_0,tf(·), vi_V⁰_,V = ^RD^α_0,t

hf, vi_V⁰_,V , in L²(0, T). (3.3) Above V⁰ denotes the dual space of V and h·,·i_V⁰_,V, the duality between V⁰ and V.

Proof. Let ϕ∈ D(0, T). Since, for each v ∈ V, the linear map h·, vi_V⁰_,V is bounded on V⁰, we have (see for instance [ABHN11, Proposition 1.1.6])

I :=

Z T 0

h^RD^α_0,tf(t), vi_V⁰_,Vϕ(t) dt = Z T

0

RD^α_0,tf(t)ϕ(t) dt, v

V⁰,V. Then, with Proposition 3.1,

I =

− Z T

0

f(t)^RD^α_t,Tϕ(t) dt, v

V⁰,V

=− Z T

0

hf(t), vi_V⁰_,V^RD^α_t,Tϕ(t) dt.

Then, we infer from Definition 3.3 that I =_R

D^α_0,thf(·), vi_V⁰_,V, ϕ

D⁰(0,T),D(0,T). Hence

h^RD^α_0,tf, vi_V⁰_,V =^RD^α_0,thf(·), vi_V⁰_,V, in D⁰(0, T).

By assumption, ^RD^α_0,tf belongs to L²(0, T;V⁰), thus that identity holds in L²(0, T).

By Proposition 3.2 (ii), we deduce that hf(t), viV⁰,V admits a derivative of order α

in L²(0, T). That completes the proof.

Proposition 3.4. Let α ∈ (0,1) and u ∈ L²(0, T;X). If u admits a derivative of order α in L²(0, T;X), then

u= (g1−α∗u)(0)g_α+g_α∗^RD^α_0,tu in L¹(0, T;X). (3.4) Proof. The proof is rather standard; we just emphasize the functional spaces involved.

By integration, we have

g1−α∗u= (g1−α∗u)(0) +g₁∗^RD^α_0,tu in H¹(0, T;X).

By [ER18, Proposition 2.6] or [ABHN11, Proposition 1.3.6], we know that U ∈H¹(0, T;X) =⇒g_α∗U ∈W^1,1(0, T;X).

Thus, with (2.1)

g₁∗u= (g1−α∗u)(0)g_1+α+g_1+α∗^RD^α_0,tu in W^1,1(0, T;X).

By differentiation and using a slight variant of [ER18, Proposition 2.6], we get (3.4).

Proposition 3.5. Let α ∈ (0,1) and u ∈ C([0, T];X) be such that ^RD^α_0,tu lies in C([0, T];X). Then u(0) = 0.

Proof. Sinceuis continuous on[0, T], there holds(g1−α∗u)(0) = 0. Thus, with (3.4), u=g_α∗^RD^α_0,tu.

By continuity of ^RD^α_0,tu, we get u(0) = 0.

4. Galerkin method for a time fractional PDE

Let d ≥ 1 and Ω be an open bounded subset of R^d. We refer to [Chi00] for the definition of the standard Sobolev spaces H₀¹(Ω) and H⁻¹(Ω).

Definition 4.1. Let α∈(0,1) and T >0. Then we denote by H^α 0, T;H₀¹(Ω), H⁻¹(Ω)

,

the set of all functions in L²(0, T;H₀¹(Ω)) whose weak fractional derivative belongs to L²(0, T;H⁻¹(Ω)).

Let f ∈ L²(0, T;H⁻¹(Ω)) and v ∈ L²(Ω). We will focus on the following model problem.







Find u∈ H^α 0, T;H₀¹(Ω), H⁻¹(Ω)

such that

RD^α_0,tu−∆u=f in L²(0, T;H⁻¹(Ω)) (g1−α∗u)(0) =v in L²(Ω).

(4.1) In (4.1), the initial condition means that

(g1−α∗u)(t)−−−→

t→0⁺ v in L²(Ω).

4.1. Well posedness.

Theorem 4.1. Let f ∈L²(0, T;H⁻¹(Ω)) and v ∈H₀¹(Ω).

(i) If α∈(¹₂,1)then (4.1) has a unique solution.

(ii) If α∈(0,¹₂] then

(a) if v 6= 0 then (4.1) has no solution.

(b) if v = 0 then (4.1) has a unique solution.

Proof. Combining (3.4) and (2.2), we derive that (4.1) has no solution if α ≤ 1/2 and v 6= 0. On the other hand, ifv = 0 then the solvability of (4.1) can be achieved as in the case where α ∈(¹₂,1). Thus we will assume in the sequel that α >1/2.

Existence of a solution. We will implement the Galerkin approximation method.

For, let us introduce some notation. Let V :=H₀¹(Ω) and A:H₀¹(Ω)→H⁻¹(Ω), u7→ −∆u.

Fork = 1,2, . . ., let(w_k, λ_k)∈H₀¹(Ω)×(0,∞)be ak^th mode ofA such that(w_k)k≥1

forms an hilbertian basis of L²(Ω).

For n = 1,2, . . ., we denote by F_n the vector space generated by w₁, . . . , w_n. Finally, we decompose the initial condition v, by writing

v =X

k≥1

b_kw_k in H₀¹(Ω), and we set

v_n:=

n

X

k=1

b_kw_k. (4.2)

Whence v_n ∈F_n and v_n →v in H₀¹(Ω).

For each integer n ≥1, our approximated problem takes the form







Findu_n ∈L²(0, T;F_n) such that ^RD^α_0,tu_n∈L² 0, T;H⁻¹(Ω)

h^RD^α_0,tun, wiV⁰,V +hAun, wiV⁰,V =hf, wiV⁰,V in L²(0, T),∀w∈Fn

(g1−α∗u_n)(0) =v_n.

(4.3)

(i) Solvability of the approximated problem. The decomposition and notation u_n(t) =

n

X

k=1

x_k(t)w_k, f_k(t) := hf(t), w_ki_V⁰_,V,

lead to the equivalent system:

( _R

D^α_0,tx_k+λ_kx_k =f_k in L²(0, T)

(g1−α∗x_k)(0) =b_k , ∀k = 1, . . . , n. (4.4) Surprisingly, we have not found a well-posedness result for (4.4) in the literature.

However, the local well-posedness in L²(0, τ), for small positive τ can be obtained by standard fix point method (see [Die10, Chap 5] where another functional setting is used).

Regarding global well-posedness i.e. well-posedness on[0, T]for allT > 0, adapting to our framework, Lemma 4.2 in [ZPAA17] and Theorem 10 of [dCNFJ18], we may obtain ablow-up alternative. Namely, if the maximal existence timeT_m is finite then the corresponding maximal solution u to (4.4), fulfills

kuk_L²_(0,τ) → ∞, as τ →T_m⁻. (4.5) Let us notice that

sup

τ∈(0,Tm)

kuk_L²_(0,τ) <∞

implies by the monotone convergence theorem, that ulies in L²(0, T_m).

So, in order to get global well-posedness, we assume that T_m is finite. Then, for each τ ∈(0, T_m), we have by (4.4), Proposition 3.4 and (2.2),

x_k+λ_kg_α∗x_k=b_kg_α+g_α∗f_k, in L²(0, τ).

We multiply that equation by x_k and integrate on [0, τ]. By Theorem 2.1, Z τ

0

x_k(t)g_α∗x_k(t) dt≥0.

Thus since λ_k ≥0 and α >1/2, we get

kxkk²_L2(0,τ)≤ |bk|kgαk_L²_(0,Tm)kxkk_L²_(0,τ)+kgα∗fkk_L²_(0,Tm)kxkk_L²_(0,τ).

Then kx_kk_L²_(0,τ) remains bounded as τ approaches T_m. That contradicts (4.5), so that T_m =∞. Thus (4.3) admits an unique solution for all positive time T.

(ii) Estimates. Using g_α ∈L²(0, T)and taking w=v_n in (4.3), we derive Z T

0

h^RD^α_0,tu_n, u_n−g_αv_ni_V⁰_,V dt+

Z T 0

hAu_n, u_n−g_αv_ni_V⁰_,V dt = Z T

0

hf, u_n−g_αv_ni_V⁰_,V dt.

(4.6)

Let us show that the first integral above is non negative; this is the key point of our proof. For, in view of Proposition 3.4, there holds

u_n−g_αv_n=g_α∗^RD^α_0,tu_n in L²(0, T;H₀¹(Ω)). (4.7) Thus, setting for simplicity D^α instead of ^RD^α_0,t,

Z T 0

hD^αu_n, u_n−g_αv_ni_V⁰_,V dt

= Z T

0

hD^αu_n, g_α∗D^αu_ni_V⁰_,V dt

= Z T

0

dt Z t

0

g_α(t−y)

D^αu_n(t),(D^αu_n)(t−y)

V⁰,Vdy

=

n

X

k=1

Z T 0

dt Z t

0

g_α(t−y)D^αx_k(t)(D^αx_k)(t−y)dy,

since hw_k, w_ji_V⁰_,V = δ_k,j. By Theorem 2.1, the latter right hand side is the sum of non-negative numbers. Hence

Z T 0

h^RD^α_0,tu_n, u_n−g_αv_ni_V⁰_,V dt≥0.

Going back to (4.6), we derive Z T

0

hAu_n, u_ni_V⁰_,V dt ≤ Z T

0

|hAu_n, v_ni_V⁰_,V|g_α(t) dt

+ Z T

0

|hf, u_ni_V⁰_,V|dt+ Z T

0

|hf, v_ni_V⁰_,V|g_α(t) dt.

Since

Z T 0

hAu_n, u_ni_V⁰_,V dt=ku_nk²_L2(0,T;H₀¹(Ω))

and v_n→v in H₀¹(Ω), we derive in a standard way that ku_nk_L2(0,T;H₀¹(Ω)) ≤C,

where the constantCis independent ofn. Then there exists someu∈L²(0, T;H₀¹(Ω)) such that , up to a subsequence,

u_n* u in L²(0, T;H₀¹(Ω))-weak. (4.8) (iii) Equation of (4.1). Let k ≥ 1 be fixed and n ≥ k. For each ϕ ∈ D(0, T), we derive from (4.3) and Proposition 3.1 that

Z T

0

−u_n(t)^RD^α_t,Tϕ(t) + Au_n−f(t)

ϕ(t) dt, w_k

V⁰,V = 0.

Passing to the limit in n and using Definition 3.3, we get

D^αu+Au−f = 0 in D⁰(0, T;H⁻¹(Ω)).

SinceAu andf belong toL²(0, T;H⁻¹(Ω)), we derive from Proposition 3.2 (ii), that u lies in H^α 0, T;H₀¹(Ω), H⁻¹(Ω)

and

D^αu+Au=f in L²(0, T;H⁻¹(Ω)).

(iv) Initial condition. Let k, n ≥ 1 and ϕ∈ D(0, T) with ϕ(T) = 0. Then, due to Proposition 3.3 and Proposition 3.1,

Z T 0

hD^αu_n(t), w_ki_V⁰_,Vϕ(t) dt

=− Z T

0

hu_n(t), w_ki_V⁰_,V^RD^α_t,Tϕ(t) dt− hg1−α∗u_n(0), w_ki_V⁰_,Vϕ(0)

−−−→n→∞ − Z T

0

hu(t), w_ki_V⁰_,V^RD_t,T^α ϕ(t) dt− hv, w_ki_V⁰_,Vϕ(0),

by (4.8) and (4.2). Moreover, using Proposition 3.1 and Proposition 3.3 once again, the latter limit is equal to

Z T 0

hD^αu(t), wkiV⁰,V dt+hg1−α∗u(0), wkiV⁰,Vϕ(0)− hv, wkiV⁰,Vϕ(0).

Then, we get in a usual way (see for instance [Chi00, Chap 11]) that g1−α∗u(0) =v.

That completes the proof of the existence part.

Uniqueness of the solution. By linearity, it is enough to prove that any functionuin H^α 0, T;H₀¹(Ω), H⁻¹(Ω)

, solution to

RD^α_0,tu−∆u= 0 in L²(0, T;H⁻¹(Ω)) (g1−α∗u)(0) = 0 in L²(Ω),

is trivial. For, testing the above equation with

u_α :=g1−α∗u∈L² 0, T;H₀¹(Ω) , we get

Z T 0

hd

dtu_α, u_αi_V⁰_,V dt+ Z T

0

Z

Ω

∇u∇u_αdxdt= 0.

Moreover, since u_α(0) = 0, Z T 0

hd

dtu_α, u_αi_V⁰_,V dt= 1

2ku_α(T)k²_L2(Ω)

and, by Theorem 2.1, Z T

0

Z

Ω

∇u∇u_αdxdt=

n

X

k=1

Z

Ω

Z T 0

∂_xku(t, x)g_1−α∗∂_xku(·, x)(t) dtdx≥0.

Then, for all t∈[0, T], we deduce g1−α∗u(t) = 0. Thus, with (2.1) u(t) = d

dt{gα∗g1−α∗u}(t) = 0.

That completes the proof of the theorem.

4.2. Regularity. Similarly to the case α = 1, regularity of the solution to (4.1) is obtained assuming some smoothness conditions on the data. However, no additional assumption is made on the domain Ω. Let us recall that the operator A is defined by

A:H₀¹(Ω)→H⁻¹(Ω), u7→ −∆u.

Theorem 4.2. Letα ∈(0,1),Ωbe an open bounded subset ofR^d,f be inL²(0, T;L²(Ω)), and v belong to H₀¹(Ω).

(i) If α∈(¹₂,1)then assume that Av lies in L²(Ω);

(ii) If α∈(0,¹₂] then assume that v = 0.

Then the solution u to (4.1) satisfies

Au, ^RD^α_0,tu∈L²(0, T;L²(Ω))

RD^α_0,tu+Au=f in L²(0, T;L²(Ω)).

Remark 4.1. Theorem 4.2 is not a regularity result in H²(Ω). Indeed, we do not claim that u belongs to L²(0, T;H²(Ω)). Moreover, since Ω is only assumed to be a bounded open set, the eigenfuntion w_k does not belong to H²(Ω), in general.

H²(Ω)-regularity results may be obtained by assuming for instance, that Ω is convex (see [Gri85, Theorem 3.2.1.2]).

Proof. Arguing as in the proof of Theorem 4.1, we will focus on the case α > ¹₂. Let us recall that (w_k, λ_k) ∈ H₀¹(Ω)×(0,∞) denotes a k^th mode of A and that v_n is defined by (4.2). Let u_n be the solution to (4.3). Since Aw_k =λ_kw_k, it is clear that A(u_n(t)−g_α(t)v_n)belongs to F_n for all t∈(0, T). Thus (4.3) leads to

h^RD^α_0,tun, A(un−gαvn)iV⁰,V +hAun, A(un−gαvn)iV⁰,V =hf, A(un−gαvn)iV⁰,V. In view of (4.7), we derive

h^RD^α_0,tu_n(t), A(u_n(t)−g_α(t)v_n)i_V⁰_,V =

n

X

k=1

λ_kD^αx_k(t)g_α∗D^αx_k(t).

Then, Theorem 2.1 leads to Z T

0

h^RD^α_0,tu_n, A(u_n−g_αv_n)i_V⁰_,V dt ≥0.

In order to estimate hf, g_αAv_ni_V⁰_,V, we recall that hf, hi_V⁰_,V =

Z

Ω

f(x)h(x) dx, ∀f ∈L²(Ω), ∀h∈H₀¹(Ω).

Thus

hf(t), g_α(t)Av_ni_V⁰_,V

≤g_α(t)kf(t)k_L²_(Ω)kAv_nk_L²_(Ω). Moreover, Av_n =Pn

k=1λ_kb_kw_k and Av∈L²(Ω), thus Lemma 4.3 below implies that kAv_nk_L²_(Ω) is bounded.

Thus, estimating in a standard way, we obtain that a subsequence of (Au_n) con- verges weakly in L²(0, T;L²(Ω)). Hence, by the uniqueness of the limit, Au belongs

to L²(0, T;L²(Ω)).

The following lemma is used is the proof of Theorem 4.2.

Lemma 4.3. Let Ω be an open bounded subset of R^d. For each v ∈ H₀¹(Ω) with v =P

b_kw_k in H₀¹(Ω), one has

Av∈L²(Ω)⇔X

(b_kλ_k)² <∞.

Proof. Let us assume that Av lies in L²(Ω). Since (w_k) is an hilbertian basis of L²(Ω), there exists a sequence(c_k)_k≥0 ⊂R such that

Av=X

k≥1

c_kw_k, X

(c_k)² <∞, c_k = Z

Ω

Av(x)w_k(x) dx.

Moreover,

Z

Ω

Av(x)w_k(x) dx= Z

Ω

∇v(x)∇w_k(x) dx=b_kλ_k.

Hence, P

(bkλk)² <∞.

Conversely, let vn := Pn

k≥1bkwk. Since Awk = λkwk, we know that Awk is in L²(Ω). Thus, for1≤m < n,

kAv_n−Av_mk²_L2(Ω) =

n

X

k=m+1

(b_kλ_k)².

By assumption P

(b_kλ_k)² converges; so that there exists some f ∈L²(Ω) such that Av_n→f in L²(Ω).

However,v_n→vinH₀¹(Ω)and the operatorAis continuous fromH₀¹(Ω)intoH⁻¹(Ω).

Thus Av_n →Av inH⁻¹(Ω). WhenceAv lies in L²(Ω).

5. The “` goes to plus infinity” issue

In many physical situations, three dimensional problems are sometimes approxi- mated by two dimensional problems. That procedure simplifies the mathematical analysis and decreases the computational cost of discretisation algorithms.

The issue is then to estimate the error made by replacing the solution of the 3D problem by the solution of some 2D problem. We refer to the books [Chi02], [Chi16]

for more informations on that subject. Basically, if the 3D problem is set on a cylinder with large height, then the solution will be locally well approximated by the solution of the “same problem” set on the section of the cylinder.

Regarding fractional derivatives, the paper [CR17] is concerns with the fractional Laplacian. Here, we will look at linear time fractional diffusion problems. More precisely, let p < dbe positive integers, ω be an open bounded subset of R^d−p and

Ω<sub>`</sub>:= (−`, `)^p×ω ⊂R^p×R^d−p.

We write any x∈Ω_` asx= (X₁, X₂), whereX₁ ∈R^p and X₂ ∈R^d−p. For f inL²(0, T;L²(ω)) and v ∈H₀¹(ω), we consider the problem







Findu_{`</sub> ∈ H<sup>α</sup> 0, T;H<sub>0</sub><sup>1</sup>(Ω<sub>`}), H⁻¹(Ω_`)

such that

RD^α_0,tu_{`</sub>−∆u<sub>`} =f in L²(0, T;H⁻¹(Ω_{`</sub>)) (g1−α∗u<sub>`})(0) =v in L²(Ω_`).

(5.1)

Then the problem set on the section ω is







Find u∞∈ H^α 0, T;H₀¹(ω), H⁻¹(ω)

such that

RD^α_0,tu∞−∆u∞ =f in L²(0, T;H⁻¹(ω)) (g_1−α∗u_∞)(0) =v in L²(ω).

(5.2)

Theorem 5.1. Let ω and Ω_` as above, α ∈ (0,1), f belong to L²(0, T;L²(ω)) and v ∈H₀¹(ω).

(i) If α∈(¹₂,1)then assume that Av lies in L²(Ω);

(ii) If α∈(0,¹₂] then assume that v = 0.

Then there exists two positive constantsε andC such that, for all` >0, the solutions u<sub>`</sub> and u_∞ to (5.1) and (5.2) satisfy

Z T 0

Z

Ω_`/2

|∇(u<sub>`</sub>−u∞)|<sup>2</sup>dxdt≤Ce<sup>−ε`</sup>. (5.3) Of course, we deduce from the above result (using also Poincaré inequality) that, for any fixed `₀ >0,

u_` −−−→

`→∞ u∞ in L<sup>2</sup> 0, T;H<sup>1</sup>(Ω<sub>`0</sub>) ,

with exponential convergence rate. Let us recall that the Poincaré constant is inde- pendent of `: see for instance [CR02, Lemma 2.1].

Proof. As in the previous section, we will only study the case where α > 1/2. For

` ≥1 and `₁ ≤`−1, consider a functionρ=ρ<sub>`1</sub> :R^p →[0,∞) such that

ρ_{`1</sub> = 1 on Ω<sub>`1}, ρ_{`1</sub> = 0 on R<sup>p</sup>\Ω<sub>`1+1} (5.4) ∇ρ_`1(X₁)

≤C, ∀X₁ ∈R^p, (5.5)

where C is independent of X₁ and `₁. Also, by Theorem 4.2, one has

RD^α_0,t(u`−u∞) +A(u`−u∞) = 0 in L²(0, T;L²(Ω`)). (5.6) Moreover, (u<sub>`</sub> −u∞)ρ is in L²(0, T;H₀¹(Ω_`)) by (5.4). Thus testing (5.6) with this function, we get

Z

Ω`

ρ(X1) dx Z T

0

D^α(u`−u∞) (u`−u∞) dt+ Z T

0

Z

Ω`

|∇(u`−u∞)|²ρ(X1) dxdt

=− Z T

0

Z

Ω`1+1\Ω<sub>`</sub>

1

∇(u_{`</sub>−u<sub>∞</sub>)∇ρ(X<sub>1</sub>) (u<sub>`}−u_∞) dxdt.

The first integral above is positive due to Theorem 2.1, sinceu_{`</sub>−u∞=g<sub>α</sub>∗D<sup>α</sup>(u<sub>`}− u_∞), by Proposition 3.4. Next, using|∇ρ

≤C, Young and Poincaré inequalities, we get in a standard way, the following bound of the latter integral:

C Z T

0

Z

Ω`1+1\Ω`1

|∇(u_`−u∞)|²dxdt.

Thus, sinceρ= 1 onΩ`1, we derive Z T

0

Z

Ω_`1

|∇(u_`−u∞)|²dxdt ≤ C 1 +C

Z T 0

Z

Ω_`1+1

|∇(u_`−u∞)|²dxdt.

There results (see [Chi16] Section 1.7) that Z T

0

Z

Ω_`/2

|∇(u<sub>`</sub>−u∞)|<sup>2</sup>dxdt≤Ce<sup>−2ε`</sup>

Z T 0

Z

Ω_`

|∇(u_`−u∞)|²dxdt.

There remains to estimate the latter integral. For, using the regularity result of Theorem 4.2 and testing (5.1) with u_`−g_α(t)v, we get

Z T 0

Z

Ω_`

D^αu_{`</sub>(u<sub>`}−g_α(t)v) dxdt+ Z T

0

Z

Ω_`

|∇u_`|²dxdt

= Z T

0

Z

Ω`

f(t, X₂)(u_`−g_α(t)v) dxdt+ Z T

0

g_α(t) dt Z

Ω`

∇u_`∇vdx.

The first term is positive by Theorem 2.1 and Proposition 3.4. Moreover, Young and Poincaré inequalities yield

Z T 0

Z

Ω_`

f(t, X₂)(u_`−g_α(t)v) dxdt

≤C_ε⁰(2`)^pkfk²_L2(0,T;L²(ω))

+ε⁰C Z T

0

Z

Ω`

|∇u<sub>`</sub>|<sup>2</sup>dxdt+ (2`)^p

2 kg_αk²_L2(0,T)kvk²_L2(ω). Choosing the positive constant ε⁰ sufficiently small, there results that

Z T 0

Z

Ω`

|∇u<sub>`</sub>|<sup>2</sup>dxdt ≤C`^p, ∀`≥1.

Performing the same computation with u_∞, we obtain (5.3). That completes the

proof of the Theorem.

References

[ABHN11] Wolfgang Arendt, Charles J. K. Batty, Matthias Hieber, and Frank Neubrander.Vector- valued Laplace transforms and Cauchy problems, volume 96 of Monographs in Mathe- matics. Birkhäuser/Springer Basel AG, Basel, second edition, 2011.

[Chi00] Michel Chipot.Elements of nonlinear analysis. Birkhäuser Advanced Texts. Birkhäuser Verlag, Basel, 2000.

[Chi02] Michel Chipot.`goes to plus infinity. Birkhäuser Advanced Texts: Basler Lehrbücher.

[Birkhäuser Advanced Texts: Basel Textbooks]. Birkhäuser Verlag, Basel, 2002.

[Chi16] Michel Marie Chipot.Asymptotic issues for some partial differential equations. Imperial College Press, London, 2016.

[CR02] M. Chipot and A. Rougirel. On the asymptotic behaviour of the solution of ellip- tic problems in cylindrical domains becoming unbounded.Commun. Contemp. Math., 4(1):15–44, 2002.

[CR17] Indranil Chowdhury and Prosenjit Roy. On the asymptotic analysis of problems involv- ing fractional Laplacian in cylindrical domains tending to infinity.Commun. Contemp.

Math., 19(5):1650035, 21, 2017.

[dCNFJ18] Paulo M. de Carvalho-Neto and Renato Fehlberg Júnior. Conditions for the absence of blowing up solutions to fractional differential equations.Acta Applicandae Mathemati- cae, 154(1):15–29, Apr 2018.

[Die10] Kai Diethelm.The analysis of fractional differential equations, volume 2004 ofLecture Notes in Mathematics. Springer-Verlag, Berlin, 2010. An application-oriented exposi- tion using differential operators of Caputo type.

[ER18] Hassan Emamirad and Arnaud Rougirel. Time fractional linear problems onl²(r^d).to appear, 2018.

[Gri85] P. Grisvard. Elliptic problems in nonsmooth domains, volume 24 of Monographs and Studies in Mathematics. Pitman (Advanced Publishing Program), Boston, MA, 1985.

[JLPR15] Bangti Jin, Raytcho Lazarov, Joseph Pasciak, and William Rundell. Variational for- mulation of problems involving fractional order differential operators. Math. Comp., 84(296):2665–2700, 2015.

[Lio69] J.-L. Lions. Quelques méthodes de résolution des problèmes aux limites non linéaires.

Dunod; Gauthier-Villars, Paris, 1969.

[LX09] Xianjuan Li and Chuanju Xu. A space-time spectral method for the time fractional diffusion equation.SIAM J. Numer. Anal., 47(3):2108–2131, 2009.

[NS76] J. A. Nohel and D. F. Shea. Frequency domain methods for Volterra equations.Ad- vances in Math., 22(3):278–304, 1976.

[Pod99] Igor Podlubny.Fractional differential equations, volume 198 ofMathematics in Science and Engineering. Academic Press, Inc., San Diego, CA, 1999.

[Tem88] Roger Temam.Infinite-dimensional dynamical systems in mechanics and physics, vol- ume 68 ofApplied Mathematical Sciences. Springer-Verlag, New York, 1988.

[TM15] Qing Tang and Qingxia Ma. Variational formulation and optimal control of fractional diffusion equations with Caputo derivatives.Adv. Difference Equ., pages 2015:283, 14, 2015.

[ZPAA17] Yong Zhou, Li Peng, Bashir Ahmad, and Ahmed Alsaedi. Energy methods for fractional Navier–Stokes equations.Chaos Solitons Fractals, 102:78–85, 2017.

Laid Djilali

Département de mathématiques, Université Abdelhamid Ibn Badis Mostaganem. Al- gérie

E-mail address: laid.djilali@univ-mosta.dz

Arnaud Rougirel

Laboratoire de Mathématiques, Université de Poitiers & CNRS. Téléport 2, BP 179, 86960 Chassneuil du Poitou Cedex, France

E-mail address: rougirel@math.univ-poitiers.fr