Research Article  Open Access
Qi Wei, Rongjun Cheng, "The Improved Moving LeastSquare Ritz Method for the OneDimensional SineGordon Equation", Mathematical Problems in Engineering, vol. 2014, Article ID 383219, 10 pages, 2014. https://doi.org/10.1155/2014/383219
The Improved Moving LeastSquare Ritz Method for the OneDimensional SineGordon Equation
Abstract
Analysis of the onedimensional sineGordon equation is performed using the improved moving leastsquare Ritz method (IMLSRitz method). The improved moving leastsquare approximation is employed to approximate the 1D displacement field. A system of discrete equations is obtained by application of the Ritz minimization procedure. The effectiveness and accuracy of the IMLSRitz method for the sineGordon equation are investigated by numerical examples in this paper.
1. Introduction
It is well known that many physical phenomena in one or higherdimensional space can be described by a soliton model. Many of these models are based on simple integrable models such as Kortewegde Vries equation and the nonlinear Schrdinger equation. Solitons have found to model among others shallowwater waves, optical fibres, Josephsonjunction oscillators, and so forth. Equations which also lead to solitary waves are the sineGordon. The sineGordon equation arises in extended rectangular Josephson junctions, which consist of two layers of super conducting materials separated by an isolating barrier. A typical arrangement is a layer of lead and a layer of niobium separated by a layer of niobium oxide. A quantum particle has a nonzero significant probability of being able to penetrate to the other side of a potential barrier that would be impenetrable to the corresponding classical particle. This phenomenon is usually referred to as quantum tunneling [1–3].
A numerical study for sineGordon equation has been proposed including the finite difference schemes [4–6], the finite element methods [7, 8], the modified Adomian decomposition method [9], the boundary integral equation approach [10], radius basis function (RBF) [11], the meshless local PetrovGalerkin (MLPG) [12], the discrete singular convolution [13], meshless local boundary integral equation method (LBIE) [14], the dual reciprocity boundary element method (DRBEM) [15], and the meshfree kpRitz method [16].
The meshless method is a new and interesting numerical technique. Important meshless methods have been developed and proposed, such as smooth particle hydrodynamics methods (SPH) [17], radial basis function (RBF) [18], element free Galerkin method (EFG) [19], meshless local PetrovGalerkin method (MLPG) [20], reproducing kernel particle method (RKPM) [21–23], the boundary element free method (BEFM) [24–27], the complex variable meshless method [28–36], improved element free Galerkin method (IEFG) [37–41], and the improved meshless local PetrovGalerkin method [42–46].
The moving leastsquare (MLS) technique was originally used for data fitting. Nowadays, the MLS technique has been employed as the shape functions of the meshless method or elementfree Galerkin (EFG) method [47]. Though EFG method is now a very popular numerical computational method, a disadvantage of the method is that the final algebraic equations system is sometimes illconditioned. Sometimes a poor solution will be obtained due to the illconditioned system. The improved moving leastsquare (IMLS) approximation has been proposed [48–52] to overcome this disadvantage. In the IMLS, the orthogonal function system with a weight function is chosen to be the basis functions. The algebraic equations system in the IMLS approximation will be no more illconditioned.
The Ritz [53] approximation technique is a generalization of the Rayleigh [54] method and it has been widely used in computational mechanics. The elementfree kpRitz method is firstly developed and implemented for the free vibration analysis of rotating cylindrical panels by Liew et al. [55]. The kpRitz method was widely applied and used in many kinds of problems, such as free vibration of twoside simplysupported laminated cylindrical panels [56], nonlinear analysis of laminated composite plates [57], SineGordon equation [16], 3D wave equation [58], and biological population problem [59].
A new numerical method which is named the IMLSRitz method for the sineGordon equation is presented in this paper. In this paper, the unknown function is approximated by these IMLS approximations; a system of nonlinear discrete equations is obtained by the Ritz minimization procedure, and the boundary conditions are enforced by the penalty method.
2. IMLSRitz Formulation for the SineGordon Equation
Consider the following onedimensional sineGordon equation: with initial conditions and boundary conditions where denotes the domain of , denotes the boundaries, and and are wave modes or kinks and velocity, respectively. Parameter is the socalled dissipative term, assumed to be a real number with .
The weighted integral form of (1a) is obtained as follows:
The weak form of (2) is
The energy functional can be written as
In the improved moving leastsquare approximation [19], define a local approximation by
This defines the quadratic form
Equation (6) can be rewritten in the vector form
To find the coefficients , we obtain the extremum of by which results in the equation system
If the functions satisfy the conditions then is called a weighted orthogonal function set with a weight function about points . The weighted orthogonal basis function set can be formed with the Schmidt method [39–41], Equation (9) can be rewritten as The coefficients can be directly obtained as follows: that is, where
From (12), the approximation function can be rewritten as where is the shape function and
Taking derivatives of (17), we can obtain the first derivatives of shape function
Imposing boundary conditions by penalty method, the total energy functional for this problem will be obtained:
By (16), we can derive the approximation function Substituting (20) into (19) and applying the Ritz minimization procedure to the energy function , we obtain In the matrix form, the results can be expressed as where
Making time discretization of (22) by the center difference method, we get where
The numerical solution of the onedimensional sineGordon equation will be obtained by solving the above iteration equation.
3. Numerical Examples and Analysis
To verify the efficiency and accuracy of the proposed IMLSRitz method for the sineGordon equation, two examples are studied and the numerical results are presented. The weight function is chosen to be cubic spline and the bases are chosen to be linear in all examples.
Example 1. Consider the sineGordon Equation (1a)–(1d) without nonlinear term over the region with initial conditions
with boundary conditions
The exact solution is
The IMLSRitz method is applied to solve the above equation with penalty factor and time step length , . In Figure 1, the numerical solution and exact solution are plotted at times 0.1, 0.2, 0.3, and 0.4, respectively. In Figures 2, 3, and 4, the graphs of error function are plotted at times 0.1, 0.2, and 0.3, respectively, where is the exact solution and numerical solution is obtained by using the IMLSRitz method. Table 1 shows the comparison of exact solutions and numerical solutions by IMLSRitz method and EFG method. From the results of Table 1, we can draw the conclusion that IMLSRitz method has higher accuracy than the EFG method. The surfaces of the numerical solution with the IMLSRitz method and exact solutions are plotted in Figures 5 and 6.

Example 2. Consider the case in (1a)–(1d) over the rectangular region and initial condition which derives the analytic solution and the boundary conditions can be obtained from (30).
The IMLSRitz method is applied to solve the above equation with penalty factor and time step length , . Figure 7 depicts the numerical and exact solution when 1, 5, 10, 20, and 30, respectively. In Figures 8, 9, and 10, the graphs of error function are plotted at times 1, 5, and 10, respectively, where is the exact solution and numerical solution is obtained by using the IMLSRitz method. Table 2 shows the comparison of exact solutions and numerical solutions by IMLSRitz method and EFG method. From the results of Table 2, it is shown that IMLSRitz method has higher accuracy than the EFG method. The surfaces of the numerical solution with the IMLSRitz method and exact solution are plotted in Figures 11 and 12.

Example 3. Consider the case in (1a)–(1d) over the rectangular region and initial condition and the boundary conditions can be derived from the following exact solitary wave solution: where and is the velocity of solitary wave.
The IMLSRitz method is applied to solve the above equation with penalty factor and time step length , , . Table 3 shows the comparison of exact solutions and numerical solutions by IMLSRitz method and EFG method. From the results of Table 3, it is shown that IMLSRitz method has higher accuracy than the EFG method. The surfaces of the numerical solution with the IMLSRitz method and exact solution are plotted in Figures 13 and 14. In Figure 15, the graph of error function is plotted at time , where is the exact solution and the numerical solution is obtained by using the IMLSRitz method.

From these figures, it is shown that numerical results obtained by the IMLSRitz method are in good agreement with the exact solutions.
4. Conclusion
This paper presents a numerical method, named the IMLSRitz method, for the onedimensional sineGordon equation. The IMLS approximation is employed to approximate the 1D displacement field. A system of discrete equations is obtained through application of the Ritz minimization. In the IMLS approximation, the basis function is chosen as the orthogonal function system with a weight function. The IMLS approximation has greater computational efficiency and precision than the MLS approximation, and it does not lead to an illconditioned system of equations. The numerical results show that the technique is accurate and efficient.
Conflict of Interests
The authors declare that there is no conflict of interests regarding the publication of this paper.
Acknowledgments
This work was supported by the National Natural Science Foundation of Ningbo City (Grant nos. 2013A610067, 2102A610023, and 2013A610103), the Natural Science Foundation of Zhejiang Province of China (Grant no. Y6110007), and the National Natural Science of China (Grant no. 41305016).
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Copyright © 2014 Qi Wei and Rongjun Cheng. 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.