Analysis of the error of difference solutions as a basis for improving accuracy : научное издание

Описание

Тип публикации: статья из журнала

Год издания: 2025

Идентификатор DOI: 10.1515/rnam-2025-0016

Аннотация: <jats:title>Abstract</jats:title> <jats:p>First, we give a short history of four algorithmic approaches in computational mathematics based on the analysis and use of the asymptotic behavior of the error of an approximate solution where the mesh size of a difference grid tends to zero. These approaches are Richardson’s ‘extrapolatioПоказать полностьюn to the limit’, Runge’s accuracy rule, Romberg’s rule for calculating integrals, and improving the grid solutions by high-order differences. The first two approaches were initially developed based on the intuitive conclusion about the asymptotic behavior of the error back in the early 20th century. The last two algorithms, at the time of their appearance in the second half of the 20th century, already used theoretical results on the special asymptotic behavior of the error of quadrature rules or difference solutions.</jats:p> <jats:p>The latter approach, despite its good computational efficiency for ordinary differential equations, has not yet been properly developed for solving multidimensional difference problems. Therefore, as an introductory illustration, we present a method for increasing the order of convergence in time for the solution of an initial boundary value problem for a parabolic equation by correcting the right-hand side with differences of a higher order. The increase in accuracy order is justified theoretically and demonstrated by a numerical example.</jats:p>

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Издание

Журнал: Russian Journal of Numerical Analysis and Mathematical Modelling

Выпуск журнала: Т. 40, 3

Номера страниц: 199-207

ISSN журнала: 09276467

Место издания: Москва

Издатель: Walter de Gruyter GmbH &amp; Co. KG

Персоны

  • Shaydurov Vladimir V. (Institute of Computational Modeling, Siberian Branch of Russian Academy of Sciences, Krasnoyarsk, Russia)
  • Gileva Lidiya V. (Institute of Computational Modeling, Siberian Branch of Russian Academy of Sciences, Krasnoyarsk, Russia)
  • Golubev Roman A. (Institute of Computational Modeling, Siberian Branch of Russian Academy of Sciences, Krasnoyarsk, Russia)

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