Các bài viết có thể truy cập công khai - Trond KvamsdalTìm hiểu thêm
Không có ở bất kỳ nơi nào: 1
Numerical assessment of RANS turbulence models for the development of data driven Reduced Order Models
MS Siddiqui, A Rasheed, T Kvamsdal
Ocean Engineering 196, 106799, 2020
Các cơ quan ủy nhiệm: Research Council of Norway
Có tại một số nơi: 54
Digital twin: Values, challenges and enablers from a modeling perspective
A Rasheed, O San, T Kvamsdal
IEEE access 8, 21980-22012, 2020
Các cơ quan ủy nhiệm: US National Science Foundation, US Department of Energy
Physics guided machine learning using simplified theories
S Pawar, O San, B Aksoylu, A Rasheed, T Kvamsdal
Physics of Fluids 33 (1), 2021
Các cơ quan ủy nhiệm: US Department of Energy
Superconvergent patch recovery and a posteriori error estimation technique in adaptive isogeometric analysis
M Kumar, T Kvamsdal, KA Johannessen
Computer Methods in Applied Mechanics and Engineering 316, 1086-1156, 2017
Các cơ quan ủy nhiệm: Research Council of Norway
On the similarities and differences between Classical Hierarchical, Truncated Hierarchical and LR B-splines
KA Johannessen, F Remonato, T Kvamsdal
Computer Methods in Applied Mechanics and Engineering 291, 64-101, 2015
Các cơ quan ủy nhiệm: Research Council of Norway
Isogeometric divergence-conforming variational multiscale formulation of incompressible turbulent flows
TM van Opstal, J Yan, C Coley, JA Evans, T Kvamsdal, Y Bazilevs
Computer Methods in Applied Mechanics and Engineering 316, 859-879, 2017
Các cơ quan ủy nhiệm: US National Science Foundation, US Department of Defense, Research Council …
Hybrid analysis and modeling, eclecticism, and multifidelity computing toward digital twin revolution
O San, A Rasheed, T Kvamsdal
GAMM‐Mitteilungen 44 (2), e202100007, 2021
Các cơ quan ủy nhiệm: US National Science Foundation, US Department of Energy, Research Council of …
Isogeometric analysis of THM coupled processes in ground freezing
YW Bekele, H Kyokawa, AM Kvarving, T Kvamsdal, S Nordal
Computers and Geotechnics 88, 129-145, 2017
Các cơ quan ủy nhiệm: Research Council of Norway
Divergence-conforming discretization for Stokes problem on locally refined meshes using LR B-splines
KA Johannessen, M Kumar, T Kvamsdal
Computer Methods in Applied Mechanics and Engineering 293, 38-70, 2015
Các cơ quan ủy nhiệm: Research Council of Norway
A simple embedded discrete fracture–matrix model for a coupled flow and transport problem in porous media
LH Odsæter, T Kvamsdal, MG Larson
Computer methods in applied mechanics and engineering 343, 572-601, 2019
Các cơ quan ủy nhiệm: Swedish Research Council
Simulation of airflow past a 2D NACA0015 airfoil using an isogeometric incompressible Navier–Stokes solver with the Spalart–Allmaras turbulence model
K Nordanger, R Holdahl, T Kvamsdal, AM Kvarving, A Rasheed
Computer Methods in Applied Mechanics and Engineering 290, 183-208, 2015
Các cơ quan ủy nhiệm: Research Council of Norway
Simple a posteriori error estimators in adaptive isogeometric analysis
M Kumar, T Kvamsdal, KA Johannessen
Computers & Mathematics with Applications 70 (7), 1555-1582, 2015
Các cơ quan ủy nhiệm: Research Council of Norway
Deep neural network enabled corrective source term approach to hybrid analysis and modeling
SS Blakseth, A Rasheed, T Kvamsdal, O San
Neural Networks 146, 181-199, 2022
Các cơ quan ủy nhiệm: US Department of Energy, Research Council of Norway
Digital twins in wind energy: Emerging technologies and industry-informed future directions
F Stadtmann, A Rasheed, T Kvamsdal, KA Johannessen, O San, K Kölle, ...
IEEE Access 11, 110762-110795, 2023
Các cơ quan ủy nhiệm: Research Council of Norway
Fast divergence-conforming reduced basis methods for steady Navier–Stokes flow
E Fonn, H van Brummelen, T Kvamsdal, A Rasheed
Computer Methods in Applied Mechanics and Engineering 346, 486-512, 2019
Các cơ quan ủy nhiệm: Research Council of Norway
Combining physics-based and data-driven techniques for reliable hybrid analysis and modeling using the corrective source term approach
SS Blakseth, A Rasheed, T Kvamsdal, O San
Applied Soft Computing 128, 109533, 2022
Các cơ quan ủy nhiệm: US Department of Energy, Research Council of Norway
Model fusion with physics-guided machine learning: Projection-based reduced-order modeling
S Pawar, O San, A Nair, A Rasheed, T Kvamsdal
Physics of Fluids 33 (6), 2021
Các cơ quan ủy nhiệm: US Department of Energy
Implementation and comparison of three isogeometric Navier–Stokes solvers applied to simulation of flow past a fixed 2D NACA0012 airfoil at high Reynolds number
K Nordanger, R Holdahl, AM Kvarving, A Rasheed, T Kvamsdal
Computer Methods in Applied Mechanics and Engineering 284, 664-688, 2015
Các cơ quan ủy nhiệm: Research Council of Norway
Multi-fidelity information fusion with concatenated neural networks
S Pawar, O San, P Vedula, A Rasheed, T Kvamsdal
Scientific Reports 12 (1), 5900, 2022
Các cơ quan ủy nhiệm: US Department of Energy
Adaptive isogeometric finite element analysis of steady‐state groundwater flow
YW Bekele, T Kvamsdal, AM Kvarving, S Nordal
International Journal for Numerical and Analytical Methods in Geomechanics …, 2016
Các cơ quan ủy nhiệm: Research Council of Norway
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