Application of Bernoulli matrix method for solving two-dimensional hyperbolic telegraph equations with Dirichlet boundary conditions. (1st April 2018)

• Record Type: Journal Article
• Authors: Singh, Somveer; Patel, Vijay Kumar; Singh, Vineet Kumar; Tohidi, Emran
• Is Part Of: Computers & mathematics with applications. Volume 75:issue 7(2018)
• Page Start: 2280
• Page End: 2294
• Publication Date: 2018-04-01
• Subjects: Two-dimensional telegraph equations -- Bernoulli polynomials -- Operational matrices -- Bernoulli matrix method -- Accuracy of the method -- Error estimation; Electronic data processing -- Periodicals; Mathematics -- Data processing -- Periodicals; 510.28541
• DOI: 10.1016/j.camwa.2017.12.003
• Languages: English
• ISSNs: 0898-1221

Abstract

Abstract: The present article is devoted to develop a new approach and methodology to find the approximate solution of second order two-dimensional telegraph equations with the Dirichlet boundary conditions. We first transform the telegraph equations into equivalent partial integro-differential equations (PIDEs) which contain both initial and boundary conditions and therefore can be solved numerically in a more appropriate manner. Operational matrices of integration and differentiation of Bernoulli polynomials together with the completeness of these polynomials are used to reduce the PIDEs into the associated algebraic generalized Sylvester equations which can be solved by an efficient Krylov subspace iterative (i.e., BICGSTAB) method. The efficiency of the proposed method has been confirmed with several test examples and it is clear that the results are acceptable and found to be in good agreement with exact solutions. We have compared the numerical results of the proposed method with radial basis function method and differential quadrature method. Also, the method is simple, efficient and produces very accurate numerical results in considerably small number of basis functions and hence reduces computational effort. Moreover, the technique is easy to apply for multidimensional problems.