Applying Cubic B-Spline Quasi-Interpolation to Solve 1D Wave Equations in Polar Coordinates

We provide numerical solution to the one-dimensional wave equations in polar coordinates, based on the cubic B-spline quasi-interpolation. The numerical scheme is obtained by using the derivative of the quasi-interpolation to approximate the spatial derivative of the dependent variable and a forward difference to approximate the time derivative of the dependent variable. The accuracy of the proposed method is demonstrated by three test problems. The results of numerical experiments are compared with analytical solutions by calculating errors -norm and -norm. The numerical results are found to be in good agreement with the exact solutions. The advantage of the resulting scheme is that the algorithm is very simple so it is very easy to implement. 1. Introduction The term “spline” in the spline function arises from the prefabricated wood or plastic curve board, which is called spline, and is used by the draftsman to plot smooth curves through connecting the known point. The use of spline function and its approximation play an important role in the formation of stable numerical methods. As the piecewise polynomial, spline, especially B-spline, have become a fundamental tool for numerical methods to get the solution of the differential equations. In the past, several numerical schemes for the solution of boundary value problems and partial differential equations based on the spline function have been developed by many researchers. As early in 1968 Bickley [1] has discussed the second-order accurate spline method for the solution of linear two-point boundary value problems. Raggett and Wilson [2] have used a cubic spline technique of lower order accuracy to solve the wave equation. Chawla et al. [3] solved the one-dimensional transient nonlinear heat conduction problems using the cubic spline collocation method in 1975. Rubin and Khosla [4] first proposed the spline alternating direction implicit method to solve the partial differential equation using the cubic spline and enhanced accuracy of the approximate solution of the second derivative to the same as that of the first derivative. Jain and Aziz [5] have derived fourth-order cubic spline method for solving the nonlinear two-point boundary value problems with significant first derivative terms. In recent years, El-Hawary and Mahmoud [6], Mohanty [7], Mohebbi and Dehghan [8], Zhu and Wang [9], Ma et al. [10], Dosti and Nazemi [11], Wang et al. [12], and other researchers [13–16] have derived various numerical methods for solution of partial differential equations based on the spline function. The hyperbolic