نتایج جستجو برای Runge-Kutta Method

تعداد نتایج: 1068838  
Journal: :J. Comput. Physics 2006
Zheming Zheng, Linda R. Petzold,

In this paper a fully explicit, stabilized projection method called the Runge-Kutta-Chebyshev (RKC) Projection method is presented for the solution of incompressible Navier-Stokes systems. This method preserves the extended stability property of the RKC method for solving ODEs, and it requires only one projection per step. An additional projection on the time derivative of the velocity is perfo...

When one solves differential equations, modeling physical phenomena, it is of great importance to take physical constraints into account. More precisely, numerical schemes have to be designed such that discrete solutions satisfy the same constraints as exact solutions. Based on general theory for positivity, with an explicit third-order Runge-Kutta method (we will refer to it as RK3 method) pos...

2006
Zheming Zheng, Linda Petzold,

In this paper a fully explicit, stabilized projection method called the Runge–Kutta–Chebyshev (RKC) projection method is presented for the solution of incompressible Navier–Stokes systems. This method preserves the extended stability property of the RKC method for solving ODEs, and it requires only one projection per step. An additional projection on the time derivative of the velocity is perfo...

Journal: :Math. Comput. 1999
Ibrahim Coulibaly, Christian Lécot,

We analyze a quasi-Monte Carlo method to solve the initial-value problem for a system of differential equations y′(t) = f(t, y(t)). The function f is smooth in y and we suppose that f and D1 yf are of bounded variation in t and that D2 yf is bounded in a neighborhood of the graph of the solution. The method is akin to the second order Heun method of the Runge-Kutta family. It uses a quasi-Monte...

2014
Peter Alfeld,

Literature For a great deal of information on Runge-Kutta methods consult J.C. Butcher, Numerical Methods for Ordinary Differential Equations, second edition, Wiley and Sons, 2008, ISBN 9780470723357. That book also has a good introduction to linear multistep methods. In these notes we refer to this books simply as Butcher. The notes were written independently of the book which accounts for som...

2008
Firdaus E. Udwadia, Artin Farahani, Leonid Berezansky,

Standard Runge-Kutta methods are explicit, one-step, and generally constant step-size numerical integrators for the solution of initial value problems. Such integration schemes of orders 3, 4, and 5 require 3, 4, and 6 function evaluations per time step of integration, respectively. In this paper, we propose a set of simple, explicit, and constant step-size Accerelated-Runge-Kutta methods that ...

2010
R. L. JOHNSTON, Mervin E. Muller, Mervin E. Müller, R. L. Johnston,

The optimum Runge-Kutta method of a particular order is the one whose truncation error is a minimum. Various measures of the size of the truncation error are considered. The optimum method is practically independent of the measure being used. Moreover, among methods of the same order which one might consider using the difference in size of the estimated error is not more than a factor of 2 or 3...

1997
Desmond J. Higham,

Time-stepping methods that guarantee to avoid spurious fixed points are said to be regular. For fixed stepsize Runge-Kutta formulas, this concept has been well studied. Here, the theory of regularity is extended to the case of embedded Runge-Kutta pairs used in variable stepsize mode with local error control. First, the limiting case of a zero error tolerance is considered. A recursive regulari...

2000
S Blanes, P C Moan,

We present new symmetric fourth and sixth-order symplectic Partitioned Runge{ Kutta and Runge{Kutta{Nystrr om methods. We studied compositions using several extra stages, optimising the eeciency. An eeective error, E f , is deened and an extensive search is carried out using the extra parameters. The new methods have smaller values of E f than other methods found in the literature. When applied...

Journal: :علوم 0

in this paper, the numerical algorithms for solving ‘fuzzy ordinary differential equations’ are considered. a scheme based on the 4th order runge-kutta method is discussed in detail and it is followed by a complete error analysis. the algorithm is illustrated by solving some linear and nonlinear fuzzy cauchy problems.

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