7 Publikationen
2025 | Artikel | FH-PUB-ID: 6445 | 
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.
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2025 | Preprint | FH-PUB-ID: 6448 |
F. Brandt, A. Heuermann, P. Hannebohm, and B. Bachmann, “Residual-Informed Learning of Solutions to Algebraic Loops,” arXiv:2510.09317. 2025.
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2025 | Konferenzbeitrag | FH-PUB-ID: 6449 |
F. Casella, B. Bachmann, K. Abdelhak, P. Hannebohm, and T. Van der Stelt, “Diagnosing Newton’s Solver Convergence Failures in the Initialization of Modelica Models,” in Proceedings of the 16th International Modelica&FMI Conference, September 8 – 10, 2025, Lucerne University of Applied Sciences and Arts (HSLU), 2025, vol. 218.
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2025 | Konferenzbeitrag | FH-PUB-ID: 6359 |
L. Langenkamp, P. Hannebohm, and B. Bachmann, “Efficient Training of Physics-enhanced Neural ODEs via Direct Collocation and Nonlinear Programming,” in Proceedings of the 16th International Modelica&FMI Conference, Luzern, 2025, vol. 218, pp. 445–457.
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2025 | Kurzbeitrag Konferenz | FH-PUB-ID: 6357 |
P. Hannebohm and B. Bachmann, “Selective Evaluation of RHS during Multi-Rate Simulation,” in Proceedings of the 16th International Modelica&FMI Conference, Lucerne, 2025, vol. 218, pp. 943–947.
HSBI-PUB
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2023 | Kurzbeitrag Konferenz | FH-PUB-ID: 4620 |
A. Heuermann, P. Hannebohm, M. Schäfer, and B. Bachmann, “Fehlerkontrollierte ML-Surrogate zur beschleunigten Simulation nichtlinearer Gleichungssysteme in Modelica,” presented at the KI@HSBI 2023 Kongress, Bielefeld, 2023.
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2023 | Konferenzbeitrag | FH-PUB-ID: 4618
A. Heuermann, P. Hannebohm, M. Schäfer, and B. Bachmann, “Accelerating the simulation of equation-based models by replacing non-linear algebraic loops with error-controlled machine learning surrogates,” in Proceedings of the 15th International Modelica Conference 2023, Aachen, October 9-11, Aachen, 2023, vol. 204, pp. 275–284.
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7 Publikationen
2025 | Artikel | FH-PUB-ID: 6445 |
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.
HSBI-PUB
| DOI
| Download (ext.)
2025 | Preprint | FH-PUB-ID: 6448 |
F. Brandt, A. Heuermann, P. Hannebohm, and B. Bachmann, “Residual-Informed Learning of Solutions to Algebraic Loops,” arXiv:2510.09317. 2025.
HSBI-PUB
| Download (ext.)
2025 | Konferenzbeitrag | FH-PUB-ID: 6449 |
F. Casella, B. Bachmann, K. Abdelhak, P. Hannebohm, and T. Van der Stelt, “Diagnosing Newton’s Solver Convergence Failures in the Initialization of Modelica Models,” in Proceedings of the 16th International Modelica&FMI Conference, September 8 – 10, 2025, Lucerne University of Applied Sciences and Arts (HSLU), 2025, vol. 218.
HSBI-PUB
| DOI
| Download (ext.)
2025 | Konferenzbeitrag | FH-PUB-ID: 6359 |
L. Langenkamp, P. Hannebohm, and B. Bachmann, “Efficient Training of Physics-enhanced Neural ODEs via Direct Collocation and Nonlinear Programming,” in Proceedings of the 16th International Modelica&FMI Conference, Luzern, 2025, vol. 218, pp. 445–457.
HSBI-PUB
| Dateien verfügbar
| DOI
| Download (ext.)
2025 | Kurzbeitrag Konferenz | FH-PUB-ID: 6357 |
P. Hannebohm and B. Bachmann, “Selective Evaluation of RHS during Multi-Rate Simulation,” in Proceedings of the 16th International Modelica&FMI Conference, Lucerne, 2025, vol. 218, pp. 943–947.
HSBI-PUB
| Dateien verfügbar
| DOI
2023 | Kurzbeitrag Konferenz | FH-PUB-ID: 4620 |
A. Heuermann, P. Hannebohm, M. Schäfer, and B. Bachmann, “Fehlerkontrollierte ML-Surrogate zur beschleunigten Simulation nichtlinearer Gleichungssysteme in Modelica,” presented at the KI@HSBI 2023 Kongress, Bielefeld, 2023.
HSBI-PUB
| Dateien verfügbar
| DOI
2023 | Konferenzbeitrag | FH-PUB-ID: 4618
A. Heuermann, P. Hannebohm, M. Schäfer, and B. Bachmann, “Accelerating the simulation of equation-based models by replacing non-linear algebraic loops with error-controlled machine learning surrogates,” in Proceedings of the 15th International Modelica Conference 2023, Aachen, October 9-11, Aachen, 2023, vol. 204, pp. 275–284.
HSBI-PUB
| DOI