Ekspertise
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Publikasjoner
- Enhancing elasticity models with deep learning: A novel corrective source term approach for accurate predictions Les publikasjonen
- Digital Twin for Wind Energy: Latest Updates From the NorthWind Project
- Physics-guided federated learning as an enabler for digital twins
- An efficient and easy-to-implement recovery-based a posteriori error estimator for isogeometric analysis of the Stokes equation
- PoroTwin: A Digital Twin for a FluidFlower Rig Les publikasjonen
- Digital Twins in Wind Energy: Emerging Technologies and Industry-Informed Future Directions
- Nested computational fluid dynamic modeling of mean turbulent quantities estimation in complex topography using AROME-SIMRA
- Hybrid deep-learning POD-based parametric reduced order model for flow around wind-turbine blade Les publikasjonen
- Isogeometric analysis of acoustic scattering with perfectly matched layers (IGAPML)
- Combining physics-based and data-driven techniques for reliable hybrid analysis and modeling using the corrective source term approach Les publikasjonen
Annen formidling
- Reduced Order Modelling (ROM) and Hybrid Analysis and Modelling (HAM) as Enablers for Predictive Digital Twins (DT)
- PoroTwin: A Digital Twin for a Meter-Scale Porous Medium
- PoroTwin: A Digital Twin for a Meter-Scale Porous Media
- CONWIND – research on smart operation control technologies for offshore wind farms
- Adaptive Isogeometric Analysis of Thin Shell Problems with Kirchhoff–Love Elements
- Deep Neural Network Enabled Corrective Source Term Approach for Predictive Digital Twins
- Høringssvar om havvind fra SINTEF og NTNU Kunnskapsbasert utvikling, kvalitative konkurranser og raskt tempo
- Adaptive Isogeometric Methods for Thin Plates
- On Adaptive Isogeometric Analysis of Thin Plate Problems
- Near wake region of an industrial scale wind turbine: comparing LES-ALM with LES-SMI simulations using data mining