Fourth-Order Ordinary Differential Equations

Author(s):  
Saad A. Ragab ◽  
Hassan E. Fayed
Author(s):  
V. F. Edneral ◽  
O. D. Timofeevskaya

Introduction:The method of resonant normal form is based on reducing a system of nonlinear ordinary differential equations to a simpler form, easier to explore. Moreover, for a number of autonomous nonlinear problems, it is possible to obtain explicit formulas which approximate numerical calculations of families of their periodic solutions. Replacing numerical calculations with their precalculated formulas leads to significant savings in computational time. Similar calculations were made earlier, but their accuracy was insufficient, and their complexity was very high.Purpose:Application of the resonant normal form method and a software package developed for these purposes to fourth-order systems in order to increase the calculation speed.Results:It has been shown that with the help of a single algorithm it is possible to study equations of high orders (4th and higher). Comparing the tabulation of the obtained formulas with the numerical solutions of the corresponding equations shows good quantitative agreement. Moreover, the speed of calculation by prepared approximating formulas is orders of magnitude greater than the numerical calculation speed. The obtained approximations can also be successfully applied to unstable solutions. For example, in the Henon — Heyles system, periodic solutions are surrounded by chaotic solutions and, when numerically integrated, the algorithms are often unstable on them.Practical relevance:The developed approach can be used in the simulation of physical and biological systems.


1985 ◽  
Vol 26 (7) ◽  
pp. 1547-1552 ◽  
Author(s):  
J. S. Dehesa ◽  
E. Buendia ◽  
M. A. Sanchez‐Buendia

2018 ◽  
Vol 387 ◽  
pp. 260-272
Author(s):  
Christian John Etwire ◽  
Ibrahim Yakubu Seini ◽  
Rabiu Musah ◽  
Oluwole Daniel Makinde

The effect of variable heat source on viscoelastic fluid of CuO-oil based nanofluid over a porous nonlinear stretching surface is analyzed. The problem was modelled in the form of partial differential equations and transformed into a coupled fourth order ordinary differential equations by similarity techniques. It was further reduced to a system of first order ordinary differential equations and solved numerically using the fourth order Runge-Kutta algorithm with a shooting method. The results for various controlling parameters have been tabulated and the flow profiles graphically illustrated. The study revealed that the viscoelastic parameter has a decreasing effect on the magnitude of both the skin friction coefficient and the rate of heat transfer from the surface. It enhanced the momentum boundary layer thickness whilst adversely affecting the thermal boundary layer thickness.


2019 ◽  
Vol 25 (1) ◽  
pp. 1 ◽  
Author(s):  
Carlos Campos ◽  
Cristiana J. Silva ◽  
Delfim F. M. Torres

We provide easy and readable GNU Octave/MATLAB code for the simulation of mathematical models described by ordinary differential equations and for the solution of optimal control problems through Pontryagin’s maximum principle. For that, we consider a normalized HIV/AIDS transmission dynamics model based on the one proposed in our recent contribution (Silva, C.J.; Torres, D.F.M. A SICA compartmental model in epidemiology with application to HIV/AIDS in Cape Verde. Ecol. Complex. 2017, 30, 70–75), given by a system of four ordinary differential equations. An HIV initial value problem is solved numerically using the ode45 GNU Octave function and three standard methods implemented by us in Octave/MATLAB: Euler method and second-order and fourth-order Runge–Kutta methods. Afterwards, a control function is introduced into the normalized HIV model and an optimal control problem is formulated, where the goal is to find the optimal HIV prevention strategy that maximizes the fraction of uninfected HIV individuals with the least HIV new infections and cost associated with the control measures. The optimal control problem is characterized analytically using the Pontryagin Maximum Principle, and the extremals are computed numerically by implementing a forward-backward fourth-order Runge–Kutta method. Complete algorithms, for both uncontrolled initial value and optimal control problems, developed under the free GNU Octave software and compatible with MATLAB are provided along the article.


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