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Please note that the content of this book primarily consists of articles available from Wikipedia or other free sources online. In numerical analysis, the Runge Kutta methods are an important family of implicit and explicit iterative methods for the approximation of solutions of ordinary differential equations. These techniques were developed around 1900 by the German mathematicians C. Runge and M.W. Kutta. See the article on numerical ordinary differential equations for more background and other methods. See also List of Runge Kutta methods. One member of the family of Runge Kutta methods is so commonly used that it is often referred to as "RK4", "classical Runge-Kutta method" or simply as "the Runge Kutta method".

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The main contribution of this work is illustrated as follows: 1- The derivation for embedded singly diagonally implicit Runge-Kutta (SDIRK) method of fourth-order six stages in fifth-order seven stages is introduced to solve ordinary and delay differential equations. The stability region is presented and the numerical results are compared with the other existing methods. 2- Singly diagonally implicit Runge-Kutta Nystróm (SDIRKN) of third-order three stages embedded in fourth-order four stages is constructed. The stability region of the new method is presented and numerical results are compared with the same method of lower order. 3- A new singly diagonally implicit Runge-Kutta-Nystróm general (SDIRKNG) method of third-order embedded in fourth-order is derived to solve second order ordinary differential equations. Analysis the stability region of the new method is discussed and numerical results are presented.

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Please note that the content of this book primarily consists of articles available from Wikipedia or other free sources online. In mathematics, the Runge Kutta Fehlberg method (or Fehlberg method) is an algorithm of numerical analysis for the numerical solution of ordinary differential equations. It was developed by the German mathematician Erwin Fehlberg and is based on the class of Runge Kutta methods. The Runge Kutta Fehlberg method uses an O(h4) method together with an O(h5) method that uses all of the points of the O(h4) method, and hence is often referred to as an RKF45 method. Similar schemes with different orders have since been developed. By performing one extra calculation that would be required for an RK5 method, the error in the solution can be estimated and controlled and an appropriate step size can be determined automatically, making this method efficient for ordinary problems of automated numerical integration of ordinary differential equations.

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Two implicit Hybrid block methods at step length k=2 and 3 were derived through collocation procedures. The two derived block methods also reconstructed to equivalent S stage Runge-Kutta type methods for the solution of y^'=f(x,y). Both methods were tested on the same numerical experiments. Runge-Kutta Type Methods (RKTM) gives better result over the equivalent linear multi-step methods of the same value of step length k.

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From the first time the author encountered General Linear Methods in general and Almost-Runge-Kutta methods in particular, and realized the enormous potentials and possibilities they provide, there has been a deep desire in the author, to draw the attention of researchers and mathematicians to these methods. As such, in this book the author has engaged in a detailed and comprehensive analysis of Almost Runge-Kutta (ARK) methods, derived new and effective methods especially for non-stiff differential equations. The book provides a comprehensive introduction to numerical methods for solving Ordinary Differential equations, it includes a detailed coverage of Runge-Kutta, linear multistep, and general linear methods,and thoroughly breaks down the derivation process of ARK methods. Extensive numerical experiments are carried out to see how the new ARK methods compare with some selected traditional methods and the results confirms the effectiveness and viability of ARK methods as a means by which Scientists, Mathematicians and Engineers can obtain accurate and reliable results for non-stiff differential equations.

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