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Sibirskii Zhurnal Vychislitel'noi Matematiki, 2025, Volume 28, Number 2, Pages 185–205
DOI: https://doi.org/10.15372/SJNM20250205
(Mi sjvm903)
 

Algorithm for approximate solution of ODE ensembles using clustering and sensitivity matrices

A. V. Penenkoa, G. I. Kazakovb, K. O. Ivanovb

a Institute of Computational Mathematics and Mathematical Geophysics of Siberian Branch of Russian Academy of Sciences, Novosibirsk
b Novosibirsk State University
References:
Abstract: Algorithms for solving ensembles of ODEs with sets of different input data arising from modeling chemical kinetics are considered with an operator splitting scheme for multiphysical calculations. The efficiency of an algorithm combining clustering of an input data ensemble and estimating of the solution within the cluster is evaluated by using a sensitivity matrix obtained by solving adjoint equations. The algorithm is implemented on the basis of numerical schemes consistent in the sense of a discrete Lagrange identity for solving ODE systems of the production-destruction type. The contribution of the clustering and the sensitivity matrix to the performance of the algorithm is evaluated. The results of testing the algorithm with atmospheric chemistry scenarios show that the algorithm allows one to reduce the calculation time with an acceptable decrease in accuracy.
Key words: chemical kinetics, ODE ensembles, sensitivity matrix, clusterization.
Received: 28.06.2024
Revised: 03.10.2024
Accepted: 15.01.2025
Bibliographic databases:
Document Type: Article
UDC: 519.62
Language: Russian
Citation: A. V. Penenko, G. I. Kazakov, K. O. Ivanov, “Algorithm for approximate solution of ODE ensembles using clustering and sensitivity matrices”, Sib. Zh. Vychisl. Mat., 28:2 (2025), 185–205
Citation in format AMSBIB
\Bibitem{PenKazIva25}
\by A.~V.~Penenko, G.~I.~Kazakov, K.~O.~Ivanov
\paper Algorithm for approximate solution of ODE ensembles using clustering and sensitivity matrices
\jour Sib. Zh. Vychisl. Mat.
\yr 2025
\vol 28
\issue 2
\pages 185--205
\mathnet{http://mi.mathnet.ru/sjvm903}
\crossref{https://doi.org/10.15372/SJNM20250205}
\edn{https://elibrary.ru/KMTJUC}
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