Separation and Concentration without Clogging Using a High-Throughput Tunable Filter

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 mixtureacceptedVersio

A two layer model for wave dissipation in sea ice

Sea ice is highly complex due to the inhomogeneity of the physical properties (e.g. temperature and salinity) as well as the permeability and mixture of water and a matrix of sea ice and/or sea ice crystals. Such complexity has proven itself to be difficult to parameterize in operational wave models. Instead, we assume that there exists a self-similarity scaling law which captures the first order properties. Using dimensional analysis, an equation for the kinematic viscosity is derived which is proportional to the wave frequency and the ice thickness squared. In addition, the model allows for a two-layer structure where the oscillating pressure gradient due to wave propagation only exists in a fraction of the total ice thickness. These two assumptions lead to a spatial dissipation rate that is a function of ice thickness and wavenumber. The derived dissipation rate compares favourably with available field and laboratory observations.Comment: Accepted to special issue on wave-ice interaction in Applied Ocean Research. 15 pages, 7 figure

Artificial Neural Networks trained through Deep Reinforcement Learning discover control strategies for active flow control

We present the first application of an Artificial Neural Network trained through a Deep Reinforcement Learning agent to perform active flow control. It is shown that, in a 2D simulation of the Karman vortex street at moderate Reynolds number (Re = 100), our Artificial Neural Network is able to learn an active control strategy from experimenting with the mass flow rates of two jets on the sides of a cylinder. By interacting with the unsteady wake, the Artificial Neural Network successfully stabilizes the vortex alley and reduces drag by about 8%. This is performed while using small mass flow rates for the actuation, on the order of 0.5% of the mass flow rate intersecting the cylinder cross section once a new pseudo-periodic shedding regime is found. This opens the way to a new class of methods for performing active flow control

Beyond ‘periphery’: a detailed and nuanced taxonomy of the Norwegian regions

Increasing attention is being paid towards the influence of regional contexts on innovation activities within regional development studies. Some of the literature in economic geography tends to consider the various peripheral areas as being homogenous and partly characterized by their remote location, weak innovation inputs and lack of knowledge exchange. This paper questions this approach by examining the role of innovation activities in peripheral regions. We offer a detailed and multifaceted taxonomy of the Norwegian economic regions. From an empirical viewpoint, the adoption of cluster analysis and a broad set of innovation, economic and territorial indicators allowed us to provide a nuanced picture of the current fabric of Norwegian innovation and economic-production. With the benefit of insights from relevant strands of literature (e.g. regional development, innovation systems and multi-scalar innovation networks), the case of Norway presented in our paper contributes to the scholarly debate on the role of structural preconditions for the innovation of firms in diverse peripheral areas.publishedVersio

Turbulent kinetic energy dissipation from colliding ice floes

Increased knowledge about wave attenuation processes in sea ice, and hence atmosphere-wave-ice-ocean energy transfer, is necessary to improve sea ice dynamics models used for climate modeling and offshore applications. The aim of this study is to generate such much needed data by investigating colliding ice floes dynamics in a large-scale experiment and directly measuring and quantifying the turbulent kinetic energy (TKE). The field work was carried out at Van Mijen Fjord on Svalbard, where a 3x4 m ice floe was sawed out in the fast ice. Wave motion was simulated by pulling the ice floe back and forth in an oscillatory manner in a 4x6 m pool, using two electrical winches. Ice floe motion was measured with a range meter and accelerometers, and the water turbulence was measured acoustically with an acoustic Doppler current profiler and optically with a remotely operated vehicle and bubbles as tracers. TKE frequency spectra were found to contain an inertial subrange where energy was cascading at a rate proportional to the -5/3 power law. The TKE dissipation rate was found to decrease exponentially with depth. The total TKE dissipation rate was estimated by assuming that turbulence was induced over an area corresponding to the surface of the floe. The results suggest that approximately 37% and 8% of the input power from the winches was dissipated in turbulence and absorbed in the collisions, respectively, which experimentally confirms that energy dissipation by induced turbulent water motion is an important mechanism for colliding ice floe fields

Elastic modulus measurements of cooked Lutefisk

Lutefisk is a traditional Norwegian Christmas dish, made of dry cod soaked in a lye solution before re-hydrated. We report measurements of the tissue softness of cooked Lutefisk. Surprisingly, we find that the elastic modulus does not seem to depend heavily on cooking time, cooking temperature and the amount of salt, but depends instead mainly on the size of the fish fillets and the period of fishing. Although the salting and cooking of the Lutefisk affects strongly the visual aspect of the fish fillets, these changes are not measurable with a rheometer.Comment: 14 pages, 6 figure