Search
Now showing items 1-9 of 9
(Journal article / Tidsskriftartikkel / PublishedVersion; Peer reviewed, 2021)
Machine learning has recently become a promising technique in fluid mechanics, especially for active flow control (AFC) applications. A recent work [Rabault et al., J. Fluid Mech. 865, 281–302 (2019)] has demonstrated the ...
(Journal article / Tidsskriftartikkel / PublishedVersion; Peer reviewed, 2021)
Abstract. Observations of wave dissipation and dispersion in sea ice are a necessity for the development and validation of wave–ice interaction models. As the composition of the ice layer can be extremely complex, most ...
(Journal article / Tidsskriftartikkel / PublishedVersion; Peer reviewed, 2021)
This study presents wave measurements in the Marginal Ice Zone (MIZ) obtained from ship mounted sensors. The system combines altimeter readings from the ship bow with ship motion correction data to provide estimated single ...
(Journal article / Tidsskriftartikkel / PublishedVersion; Peer reviewed, 2021)
(Journal article / Tidsskriftartikkel / PublishedVersion; Peer reviewed, 2021)
(Journal article / Tidsskriftartikkel / AcceptedVersion; Peer reviewed, 2021)
Detailed water kinematics are important for understanding atmosphere–ice–ocean energy transfer processes in the Arctic. There are few in situ observations of 2D velocity fields in the marginal ice zone. Particle tracking ...
(Journal article / Tidsskriftartikkel / PublishedVersion; Peer reviewed, 2021)
An experimental investigation of flexural-gravity waves was performed in the Hamburg Ship Model Basin HSVA ice tank. Physical characteristics of the water-ice system were measured in several locations of the tank with a ...
(Journal article / Tidsskriftartikkel / AcceptedVersion; Peer reviewed, 2021)
Deep Reinforcement Learning (DRL) has recently spread into a range of domains within physics and engineering, with multiple remarkable achievements. Still, much remains to be explored before the capabilities of these methods ...
(Journal article / Tidsskriftartikkel / AcceptedVersion; Peer reviewed, 2021)
Deep reinforcement learning (DRL) has recently been adopted in a wide range of physics and engineering domains for its ability to solve decision-making problems that were previously out of reach due to a combination of ...