Self-Adjusting Multi-Rate Runge-Kutta Methods: Analysis and Efficient Implementation in An Open Source Framework
B. Bachmann, L. Bonaventura, F. Casella, S. Fernández-García, M. Gómez-Mármol, P. Hannebohm, Journal of Scientific Computing 105 (2025).
Artikel
| Veröffentlicht
| Englisch
Autor*in
Bachmann, Bernhard
;
Bonaventura, Luca;
Casella, Francesco;
Fernández-García, Soledad;
Gómez-Mármol, Macarena;
Hannebohm, Philip

Abstract
We present an approach for the efficient implementation of self-adjusting multi-rate Runge-Kutta methods and we introduce a novel stability analysis, that covers the multi-rate extensions of all standard Runge-Kutta methods and allows to assess the impact of different interpolation methods for the latent variables and of the use of an arbitrary number of sub-steps for the active variables. The stability analysis applies successfully to the model problem typically used in the literature for multi-rate methods. Furthermore, we also propose a physically motivated model problem that can be used to assess stability to problems with purely imaginary eigenvalues and in situations closer to those arising in applications. Finally, we present an efficient implementation of multi-rate Runge-Kutta methods in the framework of the OpenModelia open-source modelling and simulation software. Results of several numerical experiments, performed with this implementation of the proposed methods, demonstrate the efficiency gains deriving from the use of the proposed multi-rate approach for physical modelling problems with multiple time scales.
Erscheinungsjahr
Zeitschriftentitel
Journal of Scientific Computing
Band
105
Zeitschriftennummer
1
Artikelnummer
30
ISSN
eISSN
FH-PUB-ID
Zitieren
Bachmann, Bernhard ; Bonaventura, Luca ; Casella, Francesco ; Fernández-García, Soledad ; Gómez-Mármol, Macarena ; Hannebohm, Philip: Self-Adjusting Multi-Rate Runge-Kutta Methods: Analysis and Efficient Implementation in An Open Source Framework. In: Journal of Scientific Computing Bd. 105, Springer Science and Business Media LLC (2025), Nr. 1
Bachmann B, Bonaventura L, Casella F, Fernández-García S, Gómez-Mármol M, Hannebohm P. Self-Adjusting Multi-Rate Runge-Kutta Methods: Analysis and Efficient Implementation in An Open Source Framework. Journal of Scientific Computing. 2025;105(1). doi:10.1007/s10915-025-03049-y
Bachmann, B., Bonaventura, L., Casella, F., Fernández-García, S., Gómez-Mármol, M., & Hannebohm, P. (2025). Self-Adjusting Multi-Rate Runge-Kutta Methods: Analysis and Efficient Implementation in An Open Source Framework. Journal of Scientific Computing, 105(1). https://doi.org/10.1007/s10915-025-03049-y
@article{Bachmann_Bonaventura_Casella_Fernández-García_Gómez-Mármol_Hannebohm_2025, title={Self-Adjusting Multi-Rate Runge-Kutta Methods: Analysis and Efficient Implementation in An Open Source Framework}, volume={105}, DOI={10.1007/s10915-025-03049-y}, number={130}, journal={Journal of Scientific Computing}, publisher={Springer Science and Business Media LLC}, author={Bachmann, Bernhard and Bonaventura, Luca and Casella, Francesco and Fernández-García, Soledad and Gómez-Mármol, Macarena and Hannebohm, Philip}, year={2025} }
Bachmann, Bernhard, Luca Bonaventura, Francesco Casella, Soledad Fernández-García, Macarena Gómez-Mármol, and Philip Hannebohm. “Self-Adjusting Multi-Rate Runge-Kutta Methods: Analysis and Efficient Implementation in An Open Source Framework.” Journal of Scientific Computing 105, no. 1 (2025). https://doi.org/10.1007/s10915-025-03049-y.
B. Bachmann, L. Bonaventura, F. Casella, S. Fernández-García, M. Gómez-Mármol, and P. Hannebohm, “Self-Adjusting Multi-Rate Runge-Kutta Methods: Analysis and Efficient Implementation in An Open Source Framework,” Journal of Scientific Computing, vol. 105, no. 1, 2025.
Bachmann, Bernhard, et al. “Self-Adjusting Multi-Rate Runge-Kutta Methods: Analysis and Efficient Implementation in An Open Source Framework.” Journal of Scientific Computing, vol. 105, no. 1, 30, Springer Science and Business Media LLC, 2025, doi:10.1007/s10915-025-03049-y.
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