Abstract: In this paper, we introduce a generalized Chebyshev
collocation method (GCCM) based on the generalized Chebyshev
polynomials for solving stiff systems. For employing a technique
of the embedded Runge-Kutta method used in explicit schemes, the
property of the generalized Chebyshev polynomials is used, in which
the nodes for the higher degree polynomial are overlapped with those
for the lower degree polynomial. The constructed algorithm controls
both the error and the time step size simultaneously and further
the errors at each integration step are embedded in the algorithm
itself, which provides the efficiency of the computational cost. For
the assessment of the effectiveness, numerical results obtained by the
proposed method and the Radau IIA are presented and compared.
Abstract: In this paper, a backward semi-Lagrangian scheme
combined with the second-order backward difference formula
is designed to calculate the numerical solutions of nonlinear
advection-diffusion equations. The primary aims of this paper are
to remove any iteration process and to get an efficient algorithm
with the convergence order of accuracy 2 in time. In order to achieve
these objects, we use the second-order central finite difference and the
B-spline approximations of degree 2 and 3 in order to approximate
the diffusion term and the spatial discretization, respectively. For the
temporal discretization, the second order backward difference formula
is applied. To calculate the numerical solution of the starting point
of the characteristic curves, we use the error correction methodology
developed by the authors recently. The proposed algorithm turns out
to be completely iteration free, which resolves the main weakness
of the conventional backward semi-Lagrangian method. Also, the
adaptability of the proposed method is indicated by numerical
simulations for Burgers’ equations. Throughout these numerical
simulations, it is shown that the numerical results is in good
agreement with the analytic solution and the present scheme offer
better accuracy in comparison with other existing numerical schemes.
Abstract: In this paper, we introduce a method for improving
the embedded Runge-Kutta-Fehlberg4(5) method. At each integration
step, the proposed method is comprised of two equations for the
solution and the error, respectively. These solution and error are
obtained by solving an initial value problem whose solution has the
information of the error at each integration step. The constructed algorithm
controls both the error and the time step size simultaneously and
possesses a good performance in the computational cost compared to
the original method. For the assessment of the effectiveness, EULR
problem is numerically solved.