A novel two-parameter class of optimized hybrid block methods for integrating differential systems numerically

IF 0.9 Q3 MATHEMATICS, APPLIED Computational and Mathematical Methods Pub Date : 2021-11-29 DOI:10.1002/cmm4.1214
Gurjinder Singh, Arvind Garg, Rajat Singla, Vinay Kanwar
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引用次数: 5

Abstract

In this article, a two-parameter class of hybrid block methods for integrating first-order initial value ordinary differential systems is proposed. The methods exhibit hybrid nature which helps in bypassing the first Dahlquist barrier existing for linear multistep methods. The approach used in the development of a class of methods is purely interpolation and collocation technique. The class of methods is based on four intra-step points from which two intra-step points have been optimized by using an optimization strategy. In this optimization strategy, the values of two intra-step points are obtained by minimizing the local truncation errors of the formulas at the points x n + 1 / 2 and x n + 1 .The order of accuracy of the proposed methods is six. A method as a special case of this class of methods is considered and developed into a block form which produces approximate numerical solutions at several points simultaneously. Further, the method is formulated into an adaptive step-size algorithm using an embedded type procedure. This method which is a special case of this class of methods has been tested on six well-known first-order differential systems.

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一种新的双参数优化混合块法用于微分系统的数值积分
本文提出了一阶初值常微分系统积分的一类双参数混合块法。该方法表现出混合性质,有助于绕过线性多步骤方法存在的第一Dahlquist势垒。在一类方法的开发中使用的方法是纯粹的插值和搭配技术。该类方法基于四个步内点,其中两个步内点通过使用优化策略进行优化。在此优化策略中,通过最小化公式在x n + 1 / 2和x处的局部截断误差,得到两个步内点的值所提方法的精度阶数为6。作为这类方法的一个特例,我们考虑了一种方法,并将其发展成一种块形式,它可以同时在几个点上产生近似的数值解。此外,该方法采用嵌入型程序形成自适应步长算法。这个方法是这类方法的一个特例,已经在六个著名的一阶微分系统上进行了检验。
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