31,397 research outputs found

    A computational study of high-speed microdroplet impact onto a smooth solid surface

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    Numerical solutions of high-speed microdroplet impact onto a smooth solid surface are computed, using the interFoam VoF solver of the OpenFOAM CFD package. Toward the solid surface, the liquid microdroplet is moving with an impinging gas flow, simulating the situation of ink droplets being deposited onto substrate with a collimated mist jet in the Optomec Aerosol Jet printing process. The computed values of maximum spread factor, for the range of parameters of practical interest to Aerosol Jet printing, were found in very good agreement with some of the correlation formulas proposed by previous authors in the literature. Combining formulas selected from different authors with appropriate modifications yields a maximum spread factor formula that can be used for first-order evaluations of deposited in droplet size during the Aerosol Jet technology development. The computational results also illustrate droplet impact dynamics with lamella shape evolution throughout the spreading, receding-relaxation, and wetting equilibrium phases, consistent with that observed and described by many previous authors. This suggests a scale-invariant nature of the basic droplet impact behavior such that experiments with larger droplets at the same nondimensional parameter values may be considered for studying microdroplet impact dynamics. Significant free surface oscillations can be observed when the droplet viscosity is relatively low. The border line between periodic free surface oscillations and aperiodic creeping to capillary equilibrium free surface shape appears at the value of Ohnesorge number around 0.25. Droplet bouncing after receding is prompted with large contact angles at solid surface (as consistent with findings reported in the literature), but can be suppressed by increasing the droplet viscosity

    A citizen-science approach to muon events in imaging atmospheric Cherenkov telescope data: the Muon Hunter

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    Event classification is a common task in gamma-ray astrophysics. It can be treated with rapidly-advancing machine learning algorithms, which have the potential to outperform traditional analysis methods. However, a major challenge for machine learning models is extracting reliably labelled training examples from real data. Citizen science offers a promising approach to tackle this challenge. We present "Muon Hunter", a citizen science project hosted on the Zooniverse platform, where VERITAS data are classified multiple times by individual users in order to select and parameterize muon events, a product from cosmic ray induced showers. We use this dataset to train and validate a convolutional neural-network model to identify muon events for use in monitoring and calibration. The results of this work and our experience of using the Zooniverse are presented.Comment: 8 pages, 3 figures, in Proceedings of the 35th International Cosmic Ray Conference (ICRC 2017), Busan, South Kore

    Gluon saturation and pseudo-rapidity distributions of charged hadrons at RHIC energy regions

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    We modified the gluon saturation model by rescaling the momentum fraction according to saturation momentum and introduced the Cooper-Frye hydrodynamic evolution to systematically study the pseudo-rapidity distributions of final charged hadrons at different energies and different centralities for Au-Au collisions in relativistic heavy-ion collisions at BNL Relativistic Heavy Ion Collider (RHIC). The features of both gluon saturation and hydrodynamic evolution at different energies and different centralities for Au-Au collisions are investigated in this paper.Comment: 14 pages, 4 figure

    Enhancing coverage and reducing power consumption in peer-to-peer networks through airborne relaying

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    Deficient Reasoning for Dark Matter in Galaxies

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    Astronomers have been using the measured luminosity to estimate the {\em luminous mass} of stars, based on empirically established mass-to-light ratio which seems to be only applicable to a special class of stars---the main-sequence stars---with still considerable uncertainties. Another basic tool to determine the mass of a system of stars or galaxies comes from the study of their motion, as Newton demonstrated with his law of gravitation, which yields the {\em gravitational mass}. Because the luminous mass can at best only represent a portion of the gravitational mass, finding the luminous mass to be different or less than the gravitational mass should not be surprising. Using such an apparent discrepancy as a compelling evidence for the so-called dark matter, which has been believed to possess mysterious nonbaryonic properties and present a dominant amount in galaxies and the universe, seems to be too far a stretch when seriously examining the facts and uncertainties in the measurement techniques. In our opinion, a galaxy with star type distribution varying from its center to edge may have a mass-to-light ratio varying accordingly. With the thin-disk model computations based on measured rotation curves, we found that most galaxies have a typical mass density profile that peaks at the galactic center and decreases rapidly within 5\sim 5% of the cut-off radius, and then declines nearly exponentially toward the edge. The predicted mass density in the Galactic disk is reasonably within the reported range of that observed in interstellar medium. This leads us to believe that ordinary baryonic matter can be sufficient for supporting the observed galactic rotation curves; speculation of large amount of non-baryonic matter may be based on an ill-conceived discrepancy between gravitational mass and luminous mass which appears to be unjustified
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