Structural partitioning of systems of ordinary differential equations is made on base of right-hand side dependencies on the unknown variables. It is used to construct fully explicit Runge–Kutta methods with several computational schemes applied to different parts of the system. The constructed structural methods require fewer right-hand side evaluations (stages) per step for some parts of the system than classic explicit Runge–Kutta methods of the same order. The full structural form of the system is presented, which after permutation of variables can be applied to any system of ordinary differential equation. For such structure a multischeme method is formulated and conditions of the sixth order are written down. We present simplifying conditions and reduce the system to a solvable smaller system. A particular computational scheme, that requires seven stages for a group without special structure and only six stages for other equations, is presented. Its sixth order is confirmed by a numerical convergence test.

Original languageEnglish
Title of host publicationComputational Science and Its Applications – ICCSA 2019
Subtitle of host publication19th International Conference, Saint Petersburg, Russia, July 1–4, 2019, Proceedings, Part I
EditorsSanjay Misra, et al.
PublisherSpringer Nature
Pages89-102
ISBN (Electronic)978-3-030-24289-3
ISBN (Print)9783030242886
DOIs
StatePublished - 1 Jul 2019
Event19th International Conference on Computational Science and Its Applications, ICCSA 2019 - Saint Petersburg, Russian Federation
Duration: 1 Jul 20194 Jul 2019
Conference number: 19

Publication series

NameLecture Notes in Computer Science
Volume11619
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference19th International Conference on Computational Science and Its Applications, ICCSA 2019
Abbreviated titleICCSA 2019
Country/TerritoryRussian Federation
CitySaint Petersburg
Period1/07/194/07/19

    Research areas

  • explicit Runge–Kutta, Multischeme methods, Order conditions, Partitioned methods, Structural partitioning

    Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

ID: 45105825