dc.contributor.advisor | Celledoni, Elena | |
dc.contributor.advisor | Arnold, Martin | |
dc.contributor.advisor | Moe, Per Thomas | |
dc.contributor.author | Leone, Andrea | |
dc.date.accessioned | 2024-05-30T10:57:38Z | |
dc.date.available | 2024-05-30T10:57:38Z | |
dc.date.issued | 2024 | |
dc.identifier.isbn | 978-82-326-8071-9 | |
dc.identifier.issn | 2703-8084 | |
dc.identifier.uri | https://hdl.handle.net/11250/3131987 | |
dc.language.iso | eng | en_US |
dc.publisher | NTNU | en_US |
dc.relation.ispartofseries | Doctoral theses at NTNU;2024:240 | |
dc.relation.haspart | Paper 1: Celledoni, Elena; Çokaj, Ergys; Leone, Andrea; Murari, Davide; Owren, Brynjulf. Lie Group integrators for mechanical systems. International Journal of Computer Mathematics 2021 s. 58-88. Published by Taylor & Francis. This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives License CC BY-NC-ND. Available at: http://dx.doi.org/10.1080/00207160.2021.1966772 | en_US |
dc.relation.haspart | Paper 2: Celledoni, Elena; Cokaj, Ergys; Leone, Andrea; Murari, Davide; Owren, Brynjulf Rustad. Dynamics of the N-fold Pendulum in the Framework of Lie Group Integrators. Mathematics in Industry 2022 ;Volum 39. s. 297-304. Copyrught © TheAuthor(s), under exclusive license to Springer Nature Switzerland AG 2022. Available at: http://dx.doi.org/10.1007/978-3-031-11818-0_39 | en_US |
dc.relation.haspart | Paper 3: Celledoni, Elena; Leone, Andrea; Murari, Davide; Owren, Brynjulf. Learning Hamiltonians of constrained mechanical systems. Journal of Computational and Applied Mathematics 2022 ;Volum 417. s. - Published by Elsevier B.V. This is an open access article under the CC BY license. Available at: http://dx.doi.org/10.1016/j.cam.2022.114608 | en_US |
dc.relation.haspart | Paper 4: Celledoni, Elena; Cokaj, Ergys; Cokaj, Ergys; Leyendecker, Sigrid; Murari, Davide; Owren, Brynjulf, de Almagro, de Almagro; Stavole, Martina. Neural networks for the approximation of Euler's elastica. This paper is submitted for publication. Preprint available at arXiv https://doi.org/10.48550/arXiv.2312.00644 | en_US |
dc.relation.haspart | Paper 5: Çokaj, Ergys; Gustad, Halvor Snersrud; Leone, Andrea; Moe, Per Thomas; Moldestad, Lasse. Supervised time series classification for anomaly detection in subsea engineering. Journal of Computational Dynamics 2024 ;Volum 11.(3) s. 376-408. This is the authors' accepted manuscript to an article published by AIMS. The definitive publisher-authenticated version is available online at: http://dx.doi.org/10.3934/jcd.2024019 | en_US |
dc.title | Data-driven and geometric numerical methods for mechanical systems | en_US |
dc.type | Doctoral thesis | en_US |
dc.subject.nsi | VDP::Matematikk og Naturvitenskap: 400::Matematikk: 410 | en_US |