Performance analysis of wind fence models when used for truck protection under crosswind through numerical modeling

This paper is focused on truck aerodynamic analysis under crosswind conditions by means of numerical modeling. The truck was located on the crest of an embankment during the study. In order to analyze the performance of three wind fence models, the truck's aerodynamic coefficients were obtained and compared in two different situations either with or without the wind fences installed. In addition, the effect of both height and porosity of wind fence models on the aerodynamic coefficients acting on truck with respect to separation distance between the truck and the wind fence, was analyzed. A finite volume (or computational fluid dynamic) code was used to carry out the numerical modeling. The Reynolds-averaged Navier?Stokes (RANS) equations along with the k?? SST turbulence model were used to predict the behavior of turbulent flow. With respect to the results, the influence of the distance on the rollover coefficient is soft for all height values studied except for the lowest value (1 m of fence height), where the maximum value of rollover coefficient was obtained for the truck position closer to the fence. Regarding fence porosity, its effect on rollover coefficient is stronger for truck positions on road closer to the wind fence model.This work was supported by the OASIS Research Project that was co-financed by CDTI (Spanish Science and Innovation Ministry) and developed with the Spanish companies: Iridium, OHL Concesiones, Abertis, Sice, Indra, Dragados, OHL, Geocisa, GMV, Asfaltos Augusta, Hidrofersa, Eipsa, PyG, CPS, AEC and Torre de Comares Arquitectos S.L. and 16 research centres. The authors would also like to thank the GICONSIME research group of the University of Oviedo (Spain) for their collaboration in this research

Dark Matter Sees The Light

We construct a Dark Matter (DM) annihilation module that can encompass the predictions from a wide array of models built to explain the recently reported PAMELA and ATIC/PPB-BETS excesses. We present a detailed analysis of the injection spectrums for DM annihilation and quantitatively demonstrate effects that have previously not been included from the particle physics perspective. With this module we demonstrate the parameter space that can account for the aforementioned excesses and be compatible with existing high energy gamma ray and neutrino experiments. However, we find that it is relatively generic to have some tension between the results of the HESS experiment and the ATIC/PPB-BETS experiments within the context of annihilating DM. We discuss ways to alleviate this tension and how upcoming experiments will be able to differentiate amongst the various possible explanations of the purported excesses.Comment: 47 pages, 17 figure

Graph Neural Networks for low-energy event classification & reconstruction in IceCube

IceCube, a cubic-kilometer array of optical sensors built to detect atmospheric and astrophysical neutrinos between 1 GeV and 1 PeV, is deployed 1.45 km to 2.45 km below the surface of the ice sheet at the South Pole. The classification and reconstruction of events from the in-ice detectors play a central role in the analysis of data from IceCube. Reconstructing and classifying events is a challenge due to the irregular detector geometry, inhomogeneous scattering and absorption of light in the ice and, below 100 GeV, the relatively low number of signal photons produced per event. To address this challenge, it is possible to represent IceCube events as point cloud graphs and use a Graph Neural Network (GNN) as the classification and reconstruction method. The GNN is capable of distinguishing neutrino events from cosmic-ray backgrounds, classifying different neutrino event types, and reconstructing the deposited energy, direction and interaction vertex. Based on simulation, we provide a comparison in the 1 GeV–100 GeV energy range to the current state-of-the-art maximum likelihood techniques used in current IceCube analyses, including the effects of known systematic uncertainties. For neutrino event classification, the GNN increases the signal efficiency by 18% at a fixed background rate, compared to current IceCube methods. Alternatively, the GNN offers a reduction of the background (i.e. false positive) rate by over a factor 8 (to below half a percent) at a fixed signal efficiency. For the reconstruction of energy, direction, and interaction vertex, the resolution improves by an average of 13%–20% compared to current maximum likelihood techniques in the energy range of 1 GeV–30 GeV. The GNN, when run on a GPU, is capable of processing IceCube events at a rate nearly double of the median IceCube trigger rate of 2.7 kHz, which opens the possibility of using low energy neutrinos in online searches for transient events.Peer Reviewe

A muon-track reconstruction exploiting stochastic losses for large-scale Cherenkov detectors

IceCube is a cubic-kilometer Cherenkov telescope operating at the South Pole. The main goal of IceCube is the detection of astrophysical neutrinos and the identification of their sources. High-energy muon neutrinos are observed via the secondary muons produced in charge current interactions with nuclei in the ice. Currently, the best performing muon track directional reconstruction is based on a maximum likelihood method using the arrival time distribution of Cherenkov photons registered by the experiment\u27s photomultipliers. A known systematic shortcoming of the prevailing method is to assume a continuous energy loss along the muon track. However at energies >1 TeV the light yield from muons is dominated by stochastic showers. This paper discusses a generalized ansatz where the expected arrival time distribution is parametrized by a stochastic muon energy loss pattern. This more realistic parametrization of the loss profile leads to an improvement of the muon angular resolution of up to 20% for through-going tracks and up to a factor 2 for starting tracks over existing algorithms. Additionally, the procedure to estimate the directional reconstruction uncertainty has been improved to be more robust against numerical errors

Multimessenger observations of a flaring blazar coincident with high-energy neutrino IceCube-170922A

Previous detections of individual astrophysical sources of neutrinos are limited to the Sun and the supernova 1987A, whereas the origins of the diffuse flux of high-energy cosmic neutrinos remain unidentified. On 22 September 2017, we detected a high-energy neutrino, IceCube-170922A, with an energy of e290 tera-electron volts. Its arrival direction was consistent with the location of a known g-ray blazar, TXS 0506+056, observed to be in a flaring state. An extensive multiwavelength campaign followed, ranging from radio frequencies to g-rays. These observations characterize the variability and energetics of the blazar and include the detection of TXS 0506+056 in very-high-energy g-rays. This observation of a neutrino in spatial coincidence with a g-ray-emitting blazar during an active phase suggests that blazars may be a source of high-energy neutrinos

Direct luminous efficacy and atmospheric turbidity—Improving model performance

Of all the atmospheric constituents, aerosol content is shown to be responsible for the greatest variations in direct luminous efficacy. Some clarity is brought to the comparison between Linke's and Ångström's turbidity coefficients, respectively TL and β. Grenier's recent formulation of the optical thickness of a water and aerosol free atmosphere is presented here in a simplified expression. Based on these results and Dogniaux's illuminance turbidity factor, Til, two direct luminous efficacy models are derived, one of which is tuned to our experimental data. The input parameters are optical air mass, β, and water vapour content in the tuned version. These models perform significantly better than any of twelve other models found in the literature when compared to 1 yr's measurements from each of two sites in the U.S. and Switzerland. In both sites, β was derived from horizontal visibility estimated in a nearby airport

Metal-oxynitride core-shell nanowire array on film structure for efficient solar water splitting

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Optical and electrical properties of ZnO nanoparticles fabricated by advanced physical methods for down-shifting applications

International audienc