Atle Jensen

• Mossige, Endre Joachim; Edvardsen, Bente; Jensen, Atle & Mielnik, Michal Marek (2019). A tunable, microfluidic filter for clog‑free concentration and separation of complex algal cells. Microfluidics and Nanofluidics.  ISSN 1613-4982.  23(56) . doi: 10.1007/s10404-019-2209-y
• Rabault, Jean; Kuchta, Miroslav; Jensen, Atle; Reglade, Ulysse & Cerardi, Nicolas (2019). Artificial neural networks trained through deep reinforcement learning discover control strategies for active flow control. Journal of Fluid Mechanics.  ISSN 0022-1120.  865, s 281- 302 . doi: 10.1017/jfm.2019.62 Full text in Research Archive.
• Rabault, Jean; Sutherland, Graig; Jensen, Atle; Christensen, Kai Håkon & Marchenko, Aleksey (2019). Experiments on wave propagation in grease ice: combined wave gauges and particle image velocimetry measurements. Journal of Fluid Mechanics.  ISSN 0022-1120.  864, s 876- 898 . doi: 10.1017/jfm.2019.16 Full text in Research Archive.
• Sutherland, Graig; Rabault, Jean; Christensen, Kai Håkon & Jensen, Atle (2019). A two layer model for wave dissipation in sea ice. Applied Ocean Research.  ISSN 0141-1187.  88, s 111- 118 . doi: 10.1016/j.apor.2019.03.023
• Vollestad, Petter; Ayati, Anis Awal; Angheluta, Luiza; Lacasce, Joseph Henry & Jensen, Atle (2019). Experimental investigation of airflow above waves in a horizontal pipe. International Journal of Multiphase Flow.  ISSN 0301-9322.  110, s 37- 49 . doi: 10.1016/j.ijmultiphaseflow.2018.08.008
• Vollestad, Petter; Ayati, Anis Awal & Jensen, Atle (2019). Microscale wave breaking in stratified air-water pipe flow. Physics of fluids.  ISSN 1070-6631.  31(3), s 1- 19 . doi: 10.1063/1.5082607
• Ayati, Anis Awal; Vollestad, Petter & Jensen, Atle (2018). Detailed measurements of interfacial dynamics in air-water pipe flow. Procedia IUTAM.  ISSN 2210-9838.  26, s 59- 69 . doi: 10.1016/j.piutam.2018.03.006 Full text in Research Archive.
• Dong, Tao; Shi, Zhongyuan & Jensen, Atle (2018). Bi-objective optimization of axial profile of pin fin with uniform base heat flux. Applied Thermal Engineering.  ISSN 1359-4311.  128, s 830- 836 . doi: 10.1016/j.applthermaleng.2017.09.037 Show summary

  Cone shaped pin fin with curved profile and uniform base heat flux was investigated. The result from simultaneous optimization in regard of fin efficiency and total volume is presented. The profile is represented by the Non-Uniform Rational B-Spline (NURBS) for an additional degree of freedom to morph during the optimization process. An overall dominance was obtained from the present work, as compared to the classic concave parabolic profile, the practical constraint in fabrication taken into consideration. The profiles corresponding to the acquired Pareto solution sets tend to comply with the constructal law of design, in which freestream of heat flow is expected.

• Jensen, Atle (2018). Solitary wave impact on a vertical wall. European journal of mechanics. B, Fluids.  ISSN 0997-7546.  73, s 69- 74 . doi: 10.1016/j.euromechflu.2018.05.004
• Kolaas, Jostein; Riise, Bjørn; Sveen, Kristian & Jensen, Atle (2018). Bichromatic synthetic schlieren applied to surface wave measurements. Experiments in Fluids.  ISSN 0723-4864.  59(8) . doi: 10.1007/s00348-018-2580-6 Full text in Research Archive.
• Mossige, Endre Joachim; Jensen, Atle & Mielnik, Michal Marek (2018). Separation and Concentration without Clogging Using a High-Throughput Tunable Filter. Physical Review Applied.  ISSN 2331-7019.  9(5) . doi: 10.1103/PhysRevApplied.9.054007 Full text in Research Archive. Show summary

  We present a detailed experimental study of a hydrodynamic filtration microchip and show how chip performance can be tuned and clogging avoided by adjusting the flow rates. We demonstrate concentration and separation of microspheres at throughputs as high as 29  ml/min and with 96% pureness. Results of streakline visualizations show that the thickness of a tunable filtration layer dictates the cutoff size and that two different concentration mechanisms exist. Particles larger than pores are concentrated by low-velocity rolling over the filtration pillars, while particles smaller than pores are concentrated by lateral drift across the filtration layer. Results of microscopic particle image velocimetry and particle-tracking velocimetry show that the degree of lateral migration can be quantified by the slip velocity between the particle and the surrounding fluid. Finally, by utilizing differences in inertia and separation mode, we demonstrate size-based separation of particles in a mixture

• Rabault, Jean; Kuchta, Miroslav; Jensen, Atle; Reglade, Ulysse & Cerardi, Nicolas (2018). Artificial Neural Networks trained through Deep Reinforcement Learning discover control strategies for active flow control. arXiv.org.  ISSN 2331-8422.
• Rabault, Jean; Kuchta, Miroslav; Jensen, Atle; Reglade, Ulysse & Nicolas, Cerardi (2018). Deep Reinforcement Learning achieves flow control of the 2D Karman Vortex Street. arXiv.org.  ISSN 2331-8422.

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• Breivik, Øyvind; Rabault, Jean; Hole, Lars R; Christensen, Kai Håkon; Müller, Malte; Jensen, Atle & Mauritzen, Cecilie (2019). Bølger i isen påvirker Arktis. Å forstå isdønningene kan forbedre værvarsler og klimamodeller.. Forskning.no.  ISSN 1891-635X.
• Løken, Trygve Kvåle; Rabault, Jean; Jensen, Atle; Christensen, Kai Håkon & Müller, Malte (2019). Wave statistics from ship mounted sensors in the marginal ice zone.
• Rabault, Jean; Jensen, Atle & Kuchta, Miroslav (2019). Deep Reinforcement Learning reduces cylinder drag in a 2D flow simulation: a first step towards novel Active Flow Control methodology?.
• Rabault, Jean; Sutherland, Graig; Marchenko, Aleksey & Jensen, Atle (2019). Diving into the Physics of Wave-Ice interaction: recent evidences of complex viscous dynamics.
• Rabault, Jean; Jensen, Atle; Sutherland, Graig & Christensen, Kai Håkon (2018). An investigation into the interaction between waves and ice. Full text in Research Archive.
• Rabault, Jean; Kolaas, Jostein & Jensen, Atle (2018). Using modern Artificial Neural Networks for performing end-to-end Particle Image Velocimetry.
• Rabault, Jean; Nicolas, Cerardi; Reglade, Ulysse; Kuchta, Miroslav & Jensen, Atle (2018). An Artificial Neural Network trained through Deep Reinforcement Learning achieves Active Flow Control of the 2D Karman Vortex Street behind a Cylinder at moderate Reynolds number.

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