Conference Papers in Mathematics

Volume 2013 (2013), Article ID 454329, 8 pages

http://dx.doi.org/10.1155/2013/454329

## Stability and Error Analysis of the Semidiscretized Fractional Nonlocal Thermistor Problem

^{1}Department of Mathematics, AMNEA Group, Faculty of Sciences and Techniques, Moulay Ismail University, B.P. 509, Errachidia, Morocco^{2}Department of Mathematics, Faculty of Sciences, University Mohammed V, B.P. 1014, Rabat, Morocco

Received 9 June 2013; Accepted 20 July 2013

Academic Editors: G. S. F. Frederico, N. Martins, D. F. M. Torres, and A. J. Zaslavski

Copyright © 2013 M. R. Sidi Ammi and A. El Hachimi. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

#### Abstract

A finite difference scheme is proposed for temporal discretization of the nonlocal time-fractional thermistor problem. Stability and error analysis of the proposed scheme are provided.

#### 1. Introduction

Let be a bounded domain in with a sufficiently smooth boundary and let . In this work, we propose a finite difference scheme for the following nonlocal time-fractional thermistor problem: where denotes the Caputo fractional derivative of order , is the Laplacian with respect to the spacial variables, is supposed to be a smooth function prescribed next, and is a fixed positive real. Here denotes the outward unit normal and is the normal derivative on . Such problems arise in many applications, for instance, in studying the heat transfer in a resistor device whose electrical conductivity is strongly dependent on the temperature . When , (1) describes the diffusion of the temperature with the presence of a nonlocal term. Constant is a dimensionless parameter, which can be identified with the square of the applied potential difference at the ends of the conductor. Function is the positive thermal transfer coefficient. The given value is the temperature outside . For the sake of simplicity, boundary conditions are chosen of homogeneous Neumann type. Mixed or more general boundary conditions which model the coupling of the thermistor to its surroundings appear naturally. is the temperature inside the conductor, and is the temperature dependent electrical conductivity. Recall that (1) is obtained from the so-called nonlocal thermistor problem by replacing the first-order time derivative with a fractional derivative of order . For more description about the history of thermistors and more detailed accounts of their advantages and applications in industry, refer to [1–4].

In recent years, it has been turned out that fractional differential equations can be used successfully to model many phenomena in various fields as fluids mechanics, viscoelasticity, chemistry, and engineering [5–8]. In [4], existence and uniqueness of a positive solution to a generalized nonlocal thermistor problem with fractional-order derivatives were proved. In this work, a finite difference method is proposed for solving the time-fractional nonlocal thermistor system. Stability and error analysis for this scheme are presented showing that the temporal accuracy is of order.

#### 2. Formulation and Statement of the Problem

We consider the time-fractional thermistor problem (1), which is obtained from by replacing the first-order time derivative with a fractional derivative on Caputo sense as defined in [9] and given by subject to the initial and homogenous boundary conditions and where is the order of the time-fractional derivative. (1) covers (2) and extends it to general cases. The classical nonlocal thermistor problem (2) with the time derivative of integer order can be obtained by taking the limit in (1). While the case corresponds to the steady state thermistor problem, in the case , the Caputo fractional derivative depends on and uses the information of the solutions at all previous time levels (non-Markovian process). In this case, the physical interpretation of fractional derivative is that it represents a degree of memory in the diffusing material [10].

In the analysis of the numerical method, we will assume that problem (1) has a unique and sufficiently smooth solution which can be established by assuming more hypotheses and regularity on the data (see [11]). In the sequel, we will assume the following assumptions: (H1) is a positive Lipshitzian continuous function;(H2) there exist positive constants and such that for all we have (H3).It can be shown (e.g., see [12, 13]) that the quantity where is given next, defines a norm on which is equivalent to the norm.

#### 3. Time Discretization: A Finite Difference Scheme

We introduce a finite difference approximation to discretize the time-fractional derivative. Let be the length of each time step, for some large . . We use the following formulation: for all , where is the truncation error. It can be seen from [14] that the truncation error verifies where is a constant depending only on . On the other hand, by change of variables, we have

Let us denote , and define the discrete fractional differential operator by Then (6) becomes Using this approximation, it yields the following finite difference scheme to (1): for , where are approximations to . Scheme (11) can be reformulated in the form To complete the semidiscrete problem, we consider the boundary conditions and the initial condition , noting that If we set then (12) can be rewritten into for all . When , scheme (12) reads When , scheme (12) becomes We define the error term by Then we get from (7) that

##### 3.1. Existence of the Semidiscrete Scheme

*Definition 1. *We say that is a weak solution of (11) if
where .

At each time step, we solve a discretized fractional thermistor problem.

Theorem 2. *Let hypotheses (H1)–(H3) be satisfied; then there exists at least a weak solution of (12), such that
*

Existence and uniqueness results follow from general results of elliptic problems [3, 4, 13]. From now on, we denote by a generic constant which may not be the same at different occurrences.

##### 3.2. A Priori Estimates

We search a priori estimates for solutions.

Lemma 3. *There exists a positive constant independent of , such that
*

*Proof. *We prove this result by recurrence. First, when , we have, for ,
Notice that . Taking , we have
or
Then
Hence, since the standard -norm and the norm defined by (5) are equivalent, we have
Suppose now that we have
and prove that . Multiplying (16) by and using the fact that , we obtain
Following the same as for the case with respect to the nonlocal term , we then have
Hence,

#### 4. Stability and Error Analysis

##### 4.1. Stability Result

The weak formulation of (16) is for all and :We have the following unconditional stability result.

Theorem 4. *The semidiscretized problem is stable in the sense that for all it holds
*

*Proof. *We prove this result by recurrence. First, when , we have, for ,
On other terms
Taking in (36), we have
In a similar way, we have
We also have
We then obtain by (5) and (36) that
Dividing both sides of the previous inequality (40) by , we get
Suppose now that we have
and prove that . Choosing in (33), we obtain
Then using the recurrence hypothesis (42), we obtain
since . Similarly to the case , we have
Then
We have the following error analysis for the solution of the semidiscretized problem.

Theorem 5. *Let be the exact solution of (1) and let be the time-discrete solution with the initial condition . Then one has the following error estimates: ** **(a)**where and ; is a constant depending on .** **(b)* when ,

*Proof. *Let the difference between the exact solution of (1) and the solution of the time-discrete problem. Obviously .

(a) We will prove the result by induction. We begin with the first case when . For , by gathering equations corresponding to exact and discrete solutions, the error equation reads
Choosing in the previous equation, it yields that
To continue the proof, we will need the following lemma which is used in the sequel.

Lemma 6. * Let , be two weak solutions of (1). Assume that (H1)–(H3) hold. Then one has
**
where and , and are positive constants.*

*Proof. *We have
If we multiply by and integrate over , we get
The proof of Lemma 6 is now completed.

Now, we continue the proof of Theorem 5. Using (50), it follows that
Then, by (5), we have
It follows that
For a good choice of and using (20) and , we obtain
Then point (a) is verified for . Suppose now that we have proven (a) for all , and prove it also for . We have
Taking in (58) and using Lemma 6, we then have
Using the induction assumption and the fact that for a positive integer , we have
We then have
since . Then
By using Young’s inequality, we get
Hence,
For a suitable choice of and dividing both sides by , we get
One can show easily that
Hence, we have, for all , such that ,
(b) We are now interested in the case . We will derive again the following estimation by induction:
The previous inequality is obvious for . Suppose now that (68) holds for all , and we need to prove that it holds also for . Similarly to the previous case, by combining the corresponding equations of the exact and discrete solutions and taking as a test function, it yields that
Notice that
Then, similar to the earlier development, we have
It follows, for an well chosen such that , that
Then the estimate (b) is proved. This completes the proof of the theorem.

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