Flow and Noise Predictions of Coaxial Jets using LES and RANS Methods

Flow and noise solutions of the two Large Eddy Simulation (LES) approaches are evaluated for the jet flow conditions corresponding to a benchmark co-axial jet case from the EU CoJeN (Computation of Coaxial Jet Noise) experiment. The jet is heated and issues for a short-cowl axi-symmetric nozzle with a central body at a transonic speed. The first LES method is based on the Compact Accurately Boundary-Adjusting high-REsolution Technique (CABARET) scheme, for which implementation features include asynchronous time stepping at an optimal Courant–Friedrichs–Lewy (CFL) number, a wall model, and a synthetic turbulence inflow boundary condition. The CABARET LES is implemented on Graphics Processing Units (GPUs). The second LES approach is based on the hybrid Reynolds Averaged Navier-Stokes (RANS)/ Implicit LES method that uses a mixture of high-order Roe and WENO scheme and a wall distance model of the Improved Delayed Detached Eddy Simulation (IDDES) type. The RANS/ILES method is run on an MPI cluster. Two grid generation approaches are considered: the unstructured grid using OpenFOAM utility “snappyHexMesh” (sHM) and the conventional structured multiblock body-fitted curvilinear grid. The LES flow solutions are compared with the experiment and also with solutions obtained from the standard axi-symmetric RANS method using the k- turbulence model. For noise predictions, The LES solutions are coupled with the penetrable surface formation of the Ffowcs Williams –Hawkings method. The results of noise predictions are compared with the experiment and the effect of different LES grids and acoustic integration surfaces is discussed

TRY plant trait database - enhanced coverage and open access

Plant traits-the morphological, anatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

TRY plant trait database - enhanced coverage and open access

Plant traits—the morphological, anatomical, physiological, biochemical and phenological characteristics of plants—determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait‐based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits—almost complete coverage for ‘plant growth form’. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait–environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

A new non-linear two-time-level Central Leapfrog scheme in staggered conservation-flux variables for fluctuating hydrodynamics equations with GPU implementation

The work of AM and SK has been supported by Engineering and Physical Sciences Research Council (EP/J004308/1) and the work of YG and VM has been supported by Russian Foundation for Basic Research (11-07-93938-G8_a) in the framework of the G8 Research Councils Initiative on Multilateral Research Funding. SK is grateful to the Royal Society of London (UF090023) for their continuing support

Tunable hydrodynamic chromatography of microparticles localized in short microchannels.

This paper describes a new way to perform hydrodynamic chromatography (HDC) for the size separation of particles based on a unique recirculating flow pattern. Pressure-driven (PF) and electro-osmotic flows (EOF) are opposed in narrow glass microchannels that expand at both ends. The resulting bidirectional flow turns into recirculating flow because of nonuniform microchannel dimensions. This hydrodynamic effect, combined with the electrokinetic migration of the particles themselves, results in a trapping phenomenon, which we have termed flow-induced electrokinetic trapping (FIET). In this paper, we exploit recirculating flow and FIET to perform a size-based separation of samples of microparticles trapped in a short separation channel using a HDC approach. Because these particles have the same charge (same zeta potential), they exhibit the same electrophoretic mobility, but they can be separated according to size in the recirculating flow. While trapped, particles have a net drift velocity toward the low-pressure end of the channel. When, because of a change in the externally applied PF or electric field, the sign of the net drift velocity reverses, particles can escape the separation channel in the direction of EOF. Larger particles exhibit a larger net drift velocity opposing EOF, so that the smaller particles escape the separation channel first. In the example presented here, a sample plug containing 2.33 and 2.82 microm polymer particles was introduced from the inlet into a 3-mm-long separation channel and trapped. Through tuning of the electric field with respect to the applied PF, the particles could be separated, with the advantage that larger particles remained trapped. The separation of particles with less than 500 nm differences in diameter was performed with an analytical resolution comparable to that of baseline separation in chromatography. When the sample was not trapped in the separation channel but located further downstream, separations could be carried out continuously rather than in batch. Smaller particles could successfully pass through the separation channel, and particles were separated by size. One of the main advantages of exploiting FIET for HDC is that this method can be applied in quite short (a few millimeters) channel geometries. This is in great contrast to examples published to date for the separation of nanoparticles in much longer micro- and nanochannels

Flow injection of polymers into nanopores

We use a mesoscale simulation to measure the strength of the velocity flux needed to push a polymer into a narrow channel. We find excellent agreement with the prediction by T. Sakaue, E. Raphaël, P.G. de Gennes and F. Brochard-Wyart, Europhys. Lett., 2009, 72, 83, based on a de Gennes blob model of the polymer, that the critical velocity flux for translocation depends linearly on the temperature, but is independent of the length of the polymer chain or the width of the channel. © 2009 The Royal Society of Chemistry