Journal of Applied Mathematics

Journal of Applied Mathematics / 2013 / Article

Research Article | Open Access

Volume 2013 |Article ID 801395 | https://doi.org/10.1155/2013/801395

Mingxu Yi, Kangwen Sun, Jun Huang, Lifeng Wang, "Numerical Solutions of Fractional Integrodifferential Equations of Bratu Type by Using CAS Wavelets", Journal of Applied Mathematics, vol. 2013, Article ID 801395, 7 pages, 2013. https://doi.org/10.1155/2013/801395

Numerical Solutions of Fractional Integrodifferential Equations of Bratu Type by Using CAS Wavelets

Academic Editor: Ning Hu
Received28 Sep 2013
Accepted31 Oct 2013
Published02 Dec 2013

Abstract

A numerical method based on the CAS wavelets is presented for the fractional integrodifferential equations of Bratu type. The CAS wavelets operational matrix of fractional order integration is derived. A truncated CAS wavelets series together with this operational matrix is utilized to reduce the fractional integrodifferential equations to a system of algebraic equations. The solution of this system gives the approximation solution for the truncated limited . The convergence and error estimation of CAS wavelets are also given. Two examples are included to demonstrate the validity and applicability of the approach.

1. Introduction

A lot of scientific and engineering problems involving fractional phenomenon are already very large and still growing. One of the main advantages of the fractional phenomenon is that the fractional derivatives and fractional integrals provide an excellent approach to the different kinds of physical fields, such as dispersive transports in amorphous semiconductors, tracer transfer in underground water, and seepage in soil or rocks [14]. In recent years, more and more researchers are finding that a variety of dynamical problems exhibit fractional order behavior. This indicates that variable order calculus is an effective mathematical framework to describe the complex dynamical problems [57]. Many of the numerical methods using various fractional derivative operators and integral operators for solving fractional differential equations have been proposed. Podlubny [8] used the Laplace transform method to solve the fractional partial differential equations with constant coefficients. Odibat and Momani [9] applied generalized differential transform method to solve the numerical solution of linear partial differential equations of fractional order. Zhang [10] discussed a practical implicit method to solve a class of initial boundary value space-time fractional convection-diffusion equations with variable coefficients. Zhuang et al. [11] proposed explicit and implicit Euler method for the variable order fractional advection-diffusion equation.

Bratu’s problem is also discussed in all kinds of applications, such as chemical reaction theory, the fuel ignition model of the thermal combustion theory, and nanotechnology [1215]. Both mathematicians and physicists have devoted a lot of effort to Bratu’s problem. In [16], Syam and Hamdan presented the Laplace Adomian decomposition method for solving Bratu’s problem. Wazwaz [17] proposed the Adomian decomposition method for solving Bratu’s problem. Aksoy and Pakdemirli [18] had solved Bratu-type equation of new perturbation iteration solutions.

In this paper, we consider the following fractional integrodifferential equations of Bratu type by means of CAS wavelets: with initial condition

2. Definitions and Properties of Fractional Operator

Here we just recall the most typical definitions which are easy to use in physics. The Caputo fractional differential operator of order is defined as [8]

The Riemann-Liouville fractional integration of order is defined as where is a positive integer.

It has the following two basic properties for :

3. CAS Wavelets and Some of Their Properties

3.1. CAS Wavelets

The CAS wavelets have four arguments, , where is any nonnegative integer, is any integer, and is the normalized time. The orthonormal CAS wavelets are defined on the interval by [19] where .

3.2. Function Approximation

A function may be expanded as where , in which denotes the inner product. The series (7) is truncated as where and are two vectors given by

3.3. Convergence of the CAS Wavelet Bases

In this section, we indicate that the CAS wavelets expansion of a function , with bounded second derivative, converges uniformly to .

Lemma 1. If the CAS wavelet expansion of a continuous function converges uniformly, then the CAS wavelet expansion converges to the function .

Proof. Let where . Multiplying both sides of (11) by , , and are fixed and then integrating termwise, justified by uniformly convergence, on , we have
Thus for . Consequently have same Fourier expansions with the CAS wavelets basis and therefore .

Theorem 2. A function , with bounded second derivative, say , can be expanded as an infinite sum of the CAS wavelets and the series converges uniformly to ; that is . Furthermore, we have

Proof. From (6), we obtain
Substituting in (13) yields
Thus, we get from orthonormality of CAS wavelets, we know that , since , we have . Hence the series is absolutely convergent. On the other hand, we can obtain
Using Lemma 1, the series converges to .
Moreover, we conclude that
This completes the proof.

3.4. Operational Matrix of the Fractional Integration

In this part, we may simply introduce the operational matrix of fractional integration of CAS wavelets; more detailed introduction can be found in [19].

Take the points , , then we define

If is fractional integration operator of CAS wavelets, we can get where is called operational matrix of fractional integration of CAS wavelets.

Apart from the CAS wavelets, we consider another basis set of block pulse functions. The set of these functions, over the interval , is defined as with a positive integer value for , we suppose in this paper.

Let , then the block pulse functions operational matrix of fractional integration is given by [20] where

There is a relation between the block pulse functions and CAS wavelets:

Therefore we can derive easily by using (19), (21), and (23):

4. Numerical Solution of (1)-(2)

Consider the nonlinear fractional integrodifferential equations of Bratu type

where is arbitrary parameter, , and is a known function.

Let , , , and , then where coefficient is known and can be obtained by using the initial conditions.

Substituting (23) into (26), we obtain

Define , then .

Applying the properties of BPFs, we have

By substituting the above expanded forms into (1), we get where is the product operational matrix of .

Putting the collocation points into (29), (29) will be

Solving the nonlinear algebraic equations (30) by using Newton iteration method, we obtain the vector , and then we get the approximate solution .

5. Existence of Uniqueness

Theorem 3 (uniqueness theorem). Equation (1) has a unique solution whenever , where

Proof. Suppose , then is bounded. Therefore the nonlinear term in (1) is Lipschitz continuous with ,??.
Let and be two different solutions of (1), then we can get
Using Riemann-Liouville fractional integration, we have
Because , so (33) can transform as
Then we have
Therefore .
This implies that , where .
As , ; implying , we can prove (1) has the uniqueness solution.

6. Numerical Examples

To show the efficiency and the accuracy of the proposed method, we consider the following two examples.

Example 1. Consider the following equation: with this condition and . The exact solution of this problem is . Table 1 shows the absolute errors of the approximate solutions and the exact solution. The comparison between the numerical solutions and the exact solution for different is shown in Figures 1, 2, and 3.


, , ,

00.053450586986370.025904328611200.00591634971861
1/60.065274076773390.038502762484400.00861046012104
2/60.051428707904910.012739409641040.00925569874104
3/60.023765703580660.007824177050080.00174295063041
4/60.037868551458190.008110012550980.00314673017636
5/60.087258881053600.044406450993740.03718748499037

Taking a closer look at Table 1 and Figures 13, with increasing, we find that the approximate solutions converge to the exact solution.

Example 2. Consider this equation such that the initial conditions , . The exact solution of the problem for is given by . The comparison of numerical results for , , and and the exact solution for are shown in Figure 4. From Figure 4, we can see clearly that the numerical solutions are in very good agreement with the exact solution when .

It is evident from Figure 4 that, as close to 1, the numerical solution of the CAS wavelets converges to the exact solution; that is, the solution of fractional integrodifferential equation approaches to the solution of integer order integrodifferential equation.

7. Conclusion

In this paper, a numerical method is presented by numerical solutions of fractional integrodifferential equations of Bratu type. Taking full advantage of the definition of Caputo type fractional derivative and the properties of CAS wavelet, we transform the initial problem into a nonlinear algebraic system equation. By solving the nonlinear system, numerical solutions are obtained. The convergence analysis of CAS wavelets and the uniqueness theorem of this equation are proposed. The numerical results show that the approximation is in very good coincidence with the exact solution.

Acknowledgment

This paper was supported by the International Science & Technology Cooperation Program of China (no. 2012DFG61930).

References

  1. V. V. Anh, J. M. Angulo, and M. D. Ruiz-Medina, “Diffusion on multifractals,” Nonlinear Analysis, Theory, Methods and Applications, vol. 63, no. 5–7, pp. e2043–e2056, 2005. View at: Publisher Site | Google Scholar
  2. W. Chen, “A speculative study of 2/3-order fractional Laplacian modeling of turbulence: some thoughts and conjectures,” Chaos, vol. 16, no. 2, Article ID 023126, 2006. View at: Publisher Site | Google Scholar
  3. M. M. Meerschaert and C. Tadjeran, “Finite difference approximations for fractional advection-dispersion flow equations,” Journal of Computational and Applied Mathematics, vol. 172, no. 1, pp. 65–77, 2004. View at: Publisher Site | Google Scholar | Zentralblatt MATH | MathSciNet
  4. H. Sun, W. Chen, H. Sheng, and Y. Chen, “On mean square displacement behaviors of anomalous diffusions with variable and random orders,” Physics Letters A, vol. 374, no. 7, pp. 906–910, 2010. View at: Publisher Site | Google Scholar
  5. V. V. Anh and N. N. Leonenko, “Spectral analysis of fractional kinetic equations with random data,” Journal of Statistical Physics, vol. 104, no. 5-6, pp. 1349–1387, 2001. View at: Publisher Site | Google Scholar | Zentralblatt MATH | MathSciNet
  6. T. Blaszczyk, M. Ciesielski, M. Klimek, and J. Leszczynski, “Numerical solution of fractional oscillator equation,” Applied Mathematics and Computation, vol. 218, no. 6, pp. 2480–2488, 2011. View at: Publisher Site | Google Scholar | Zentralblatt MATH | MathSciNet
  7. C.-M. Chen, F. Liu, V. Anh, and I. Turner, “Numerical schemes with high spatial accuracy for a variable-order anomalous subdiffusion equation,” SIAM Journal on Scientific Computing, vol. 32, no. 4, pp. 1740–1760, 2010. View at: Publisher Site | Google Scholar | Zentralblatt MATH | MathSciNet
  8. I. Podlubny, Fractional Differential Equations, Mathematics in Science and Engineering, Academic Press, San Diego, Calif, USA, 1999. View at: MathSciNet
  9. Z. Odibat and S. Momani, “A generalized differential transform method for linear partial differential equations of fractional order,” Applied Mathematics Letters, vol. 21, no. 2, pp. 194–199, 2008. View at: Publisher Site | Google Scholar | Zentralblatt MATH | MathSciNet
  10. Y. Zhang, “A finite difference method for fractional partial differential equation,” Applied Mathematics and Computation, vol. 215, no. 2, pp. 524–529, 2009. View at: Publisher Site | Google Scholar | Zentralblatt MATH | MathSciNet
  11. P. Zhuang, F. Liu, V. Anh, and I. Turner, “Numerical methods for the variable-order fractional advection-diffusion equation with a nonlinear source term,” SIAM Journal on Numerical Analysis, vol. 47, no. 3, pp. 1760–1781, 2009. View at: Publisher Site | Google Scholar | Zentralblatt MATH | MathSciNet
  12. C. K. Chui, Wavelets: A Mathematical Tool for Signal Processing, SIAM Monographs on Mathematical Modeling and Computation, SIAM, Philadelphia, Pa, USA, 1997. View at: MathSciNet
  13. H. T. Davis, Introduction to Nonlinear Differential and Integral Equations, Dover, New York, NY, USA, 1962. View at: MathSciNet
  14. D. A. Frank-Kamenetski, Diffusion and Heat Exchange in Chemical Kinetics, Princeton University Press, Princeton, NJ, USA, 1955.
  15. I. H. A. H. Hassan and V. S. Ertürk, “Applying differential transformation method to the one-dimensional planar Bratu problem,” International Journal of Contemporary Mathematical Sciences, vol. 2, no. 29–32, pp. 1493–1504, 2007. View at: Google Scholar | Zentralblatt MATH | MathSciNet
  16. M. I. Syam and A. Hamdan, “An efficient method for solving Bratu equations,” Applied Mathematics and Computation, vol. 176, no. 2, pp. 704–713, 2006. View at: Publisher Site | Google Scholar | Zentralblatt MATH | MathSciNet
  17. A.-M. Wazwaz, “Adomian decomposition method for a reliable treatment of the Bratu-type equations,” Applied Mathematics and Computation, vol. 166, no. 3, pp. 652–663, 2005. View at: Publisher Site | Google Scholar | Zentralblatt MATH | MathSciNet
  18. Y. Aksoy and M. Pakdemirli, “New perturbation-iteration solutions for Bratu-type equations,” Computers & Mathematics with Applications, vol. 59, no. 8, pp. 2802–2808, 2010. View at: Publisher Site | Google Scholar | Zentralblatt MATH | MathSciNet
  19. H. Saeedi and M. M. Moghadam, “Numerical solution of nonlinear Volterra integro-differential equations of arbitrary order by CAS wavelets,” Communications in Nonlinear Science and Numerical Simulation, vol. 16, no. 3, pp. 1216–1226, 2011. View at: Publisher Site | Google Scholar | Zentralblatt MATH | MathSciNet
  20. Y. Li and N. Sun, “Numerical solution of fractional differential equations using the generalized block pulse operational matrix,” Computers & Mathematics with Applications, vol. 62, no. 3, pp. 1046–1054, 2011. View at: Publisher Site | Google Scholar | Zentralblatt MATH | MathSciNet

Copyright © 2013 Mingxu Yi et al. 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.


More related articles

792 Views | 669 Downloads | 2 Citations
 PDF Download Citation Citation
 Download other formatsMore
 Order printed copiesOrder

Related articles

We are committed to sharing findings related to COVID-19 as quickly as possible. We will be providing unlimited waivers of publication charges for accepted research articles as well as case reports and case series related to COVID-19. Review articles are excluded from this waiver policy. Sign up here as a reviewer to help fast-track new submissions.