scholarly journals Lobatto-Runge-Kutta Collocation and Adomian Decomposition Methods on Stiff Differential Equations

2017 ◽  
Vol 6 (2) ◽  
pp. 53-59
Author(s):  
E. U. Agom ◽  
F. O. Ogunfiditimi ◽  
Edet Valentine Bassey
2019 ◽  
Vol 2019 ◽  
pp. 1-8
Author(s):  
M. Y. Liu ◽  
L. Zhang ◽  
C. F. Zhang

The implicit Runge–Kutta method with A-stability is suitable for solving stiff differential equations. However, the fully implicit Runge–Kutta method is very expensive in solving large system problems. Although some implicit Runge–Kutta methods can reduce the cost of computation, their accuracy and stability are also adversely affected. Therefore, an effective banded implicit Runge–Kutta method with high accuracy and high stability is proposed, which reduces the computation cost by changing the Jacobian matrix from a full coefficient matrix to a banded matrix. Numerical solutions and results of stiff equations obtained by the methods involved are compared, and the results show that the banded implicit Runge–Kutta method is advantageous to solve large stiff problems and conducive to the development of simulation.


1970 ◽  
Vol 30 ◽  
pp. 122-132
Author(s):  
Sharaban Thohura ◽  
Azad Rahman

Special classes of Initial value problem of differential equations termed as stiff differential equations occur naturally in a wide variety of applications including the studies of spring and damping systems, chemical kinetics, electrical circuits, and so on. Most realistic stiff systems do not have analytical solutions so that a numerical procedure must be used. In this paper we have discussed the phenomenon of stiffness and the general purpose procedures for the solution of stiff differential equation. Because of their applications in many branches of engineering and science, many algorithms have been proposed to solve such problems. In this study we have focused on some conventional methods namely Runge-Kutta method, Adaptive Stepsize Control for Runge-Kutta and an ODE Solver package, EPISODE. We describe the characteristics shared by these methods. We compare the performance and the computational effort of such methods. In order to achieve higher accuracy in the solution, the traditional numerical methods such as Euler, explicit Runge-Kutta and Adams –Moulton methods step size need to be very small. This however introduces enough round-off errors to cause instability of the solution. To overcome this problem we have used two other algorithms namely Adaptive Stepsize Control for Runge-Kutta and EPISODE. The results are compared with exact one to determine the efficiency of the above mentioned method. GANIT J. Bangladesh Math. Soc. (ISSN 1606-3694) 30 (2010) 121-132  DOI: http://dx.doi.org/10.3329/ganit.v30i0.8509


2014 ◽  
Vol 2014 ◽  
pp. 1-7 ◽  
Author(s):  
Sheng-Ping Yan ◽  
Hossein Jafari ◽  
Hassan Kamil Jassim

We perform a comparison between the local fractional Adomian decomposition and local fractional function decomposition methods applied to the Laplace equation. The operators are taken in the local sense. The results illustrate the significant features of the two methods which are both very effective and straightforward for solving the differential equations with local fractional derivative.


2016 ◽  
Vol 12 (8) ◽  
pp. 6530-6544
Author(s):  
Mohamed S M. Bahgat

Aim of the paper is to investigate applications of Laplace Adomian Decomposition Method (LADM) on nonlinear physical problems. Some coupled system of non-linear partial differential equations (NLPDEs) are considered and solved numerically using LADM. The results obtained by LADM are compared with those obtained by standard and modified Adomian Decomposition Methods. The behavior of the numerical solution is shown through graphs. It is observed that LADM is an effective method with high accuracy with less number of components.


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