In this article, two new modified variational iteration algorithms are investigated for the numerical solution of coupled Burgers' equations. These modifications are made with the help of auxiliary parameters to speed up the convergence rate of the series solutions. Three numerical test problems are given to judge the behavior of the modified algorithms, and error norms are used to evaluate the accuracy of the method. Numerical simulations are carried out for different values of parameters. The results are also compared with the existing methods in the literature. Arora [5] proposed a scheme known as the Lai cubic B-spline collocation scheme for the solution of coupled viscous Burger equations, where the authors used a crank Nicholson scheme and cubic B-spline functions for time integration and space integration, respectively. Lai and Ma [6] proposed a new lattice Boltzmann model for the solution of coupled Burger equations, after selecting the distribution functions, Chapman-Enskog expansion was employed for the solution of coupled Burger equations. The Chebyshev-Legendre pseudospectral method [7] has been utilized by Rashid et al. for coupled viscous Burgers (VB) equations, where the leapfrog scheme and Chebyshev-Legendre Pseudo-Spectral method (CLPS) method were used for the time direction and space direction, respectively. Kumar and Pandit [8] used a composite numerical scheme for the numerical evaluation of coupled Burger equations, where the scheme was developed based on Haar wavelets and finite difference. Mohammadi and Mokhtari [9] used a reproducing Kernal method for an analytical solution in the form series of systems of Burger equations. At last, in 2019, Bak et al.[10] developed a new approach named a semi-Lagrangian approach for the numerical solution of coupled Burger equations. We compare our results with those of [10], and show the applicability of our proposed method to handle such problems as those that arise in applied science and engineering.This paper aims to solve three types of coupled Burgers equations by employing variational iteration algorithm-II and one of the examples to be solved by modified variational iteration algorithm-I. The organization of the rest of the paper is as follows; in Section 2, we elucidate the variational iteration algorithm-II, in the next Section 3, the semi-numerical method is applied to three test problems, and a comparison is made with some other methods; lastly, some conclusions are drawn in the last Section 4.
Modified Variational Iteration Algorithm-IIConsider the nonlinear diffusion equation:where the terms L[w(x, t)] and N[w(x, t)] are linear and nonlinear terms in that order, while c(x, t) is the source term. For a given w 0 (x, t), the approximate solution w n+1 (x, t) of Equation (4) can be obtained as below:w n+1 (x, t) = w n (x, t) + t 0