Zobrazeno 1 - 2
of 2
pro vyhledávání: '"Mücke, N. T."'
This study investigates the integration of machine learning (ML) and data assimilation (DA) techniques, focusing on implementing surrogate models for Geological Carbon Storage (GCS) projects while maintaining high fidelity physical results in posteri
Externí odkaz:
http://arxiv.org/abs/2402.06110
Publikováno v:
Technical University of Denmark Orbit
Eroglu, F G, Mücke, N T, Visbech, J & Engsig-Karup, A P 2022, ' Reduced Order Modelling for Wave-Structure Modelling ', 22 nd IACM Computational Fluids Conference, Cannes, France, 25/04/2023-28/04/2023 .
Eroglu, F G, Mücke, N T, Visbech, J & Engsig-Karup, A P 2022, ' Reduced Order Modelling for Wave-Structure Modelling ', 22 nd IACM Computational Fluids Conference, Cannes, France, 25/04/2023-28/04/2023 .
In offshore engineering, the simulation of ocean waves and their interaction with structures has become more prominent. High-fidelity simulations of these problems are costly and burden the computational resources. To address this issue, we investiga
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::a9f68b102899169567cb7550c97bbdea
https://orbit.dtu.dk/en/publications/9af2a8d2-0e92-4c17-bec2-c6a55a73f7aa
https://orbit.dtu.dk/en/publications/9af2a8d2-0e92-4c17-bec2-c6a55a73f7aa