Aerodynamic interaction between tandem propellers in eVTOL transition flight configurations

The present study investigates the aerodynamic interactions in a tandem propellers configuration typical of a tilt-wing eVTOL aircraft during the transition manoeuvre. Particular focus is on how the relative position and the propeller's tilting angle influence the aerodynamic performance. A systematic series of wind tunnel tests, including thrust and torque measurements with Particle Image Velocimetry (PIV) surveys, were performed on two co-rotating propellers models with fixed axial distance while the propellers tilting angle and the lateral separation distance were changed. The comprehensive wind tunnel campaign explored all the phases of the transition from take-off to cruise, thus highlighting possible detrimental effects on the multi-rotor system due to aerodynamic interactional mechanisms occurring due to front propeller impingement on rear propeller disks. To achieve detailed insights into the physical comprehension of the complex interactional effects produced on the rear propeller disk, the activity was completed by a numerical investigation performed through the mid-fidelity solver DUST, based on Vortex Particle Method for the wake modelling. From the perspective of a preliminary design phase of eVTOL concepts, this work showed that particular attention must be paid to the transition flight regime since both the tilting angle of attack of propellers and the free-stream velocity heavily affects the propulsive system behaviour. As a general outcome, higher vertical distances between propellers guarantee to reduce the performance losses on the rear propeller despite the presence of mutual interference phenomena

A search for time dependent neutrino emission from microquasars with the ANTARES telescope

Results are presented on a search for neutrino emission from a sample of six microquasars, based on the data collected by the ANTARES neutrino telescope between 2007 and 2010. By means of appropriate time cuts, the neutrino search has been restricted to the periods when the acceleration of relativistic jets was taking place at the microquasars under study. The time cuts have been chosen using the information from the X-ray telescopes RXTE/ASM and Swift/BAT, and, in one case, the gamma-ray telescope Fermi/LAT. No statistically significant excess has been observed, thus upper limits on the neutrino fluences have been derived and compared to the predictions by models. Constraints have been put on the ratio of proton to electron luminosity in the jets

A search for neutrino emission from the Fermi bubbles with the ANTARES telescope

Analysis of the Fermi-LAT data has revealed two extended structures above and below the Galactic Centre emitting gamma rays with a hard spectrum, the so-called Fermi bubbles. Hadronic models attempting to explain the origin of the Fermi bubbles predict the emission of high-energy neutrinos and gamma rays with similar fluxes. The ANTARES detector, a neutrino telescope located in the Mediterranean Sea, has a good visibility to the Fermi bubble regions. Using data collected from 2008 to 2011 no statistically significant excess of events is observed and therefore upper limits on the neutrino flux in TeV range from the Fermi bubbles are derived for various assumed energy cutoffs of the source

Event reconstruction for KM3NeT/ORCA using convolutional neural networks

The KM3NeT research infrastructure is currently under construction at two locations in the Mediterranean Sea. The KM3NeT/ORCA water-Cherenkov neutrino detector off the French coast will instrument several megatons of seawater with photosensors. Its main objective is the determination of the neutrino mass ordering. This work aims at demonstrating the general applicability of deep convolutional neural networks to neutrino telescopes, using simulated datasets for the KM3NeT/ORCA detector as an example. To this end, the networks are employed to achieve reconstruction and classification tasks that constitute an alternative to the analysis pipeline presented for KM3NeT/ORCA in the KM3NeT Letter of Intent. They are used to infer event reconstruction estimates for the energy, the direction, and the interaction point of incident neutrinos. The spatial distribution of Cherenkov light generated by charged particles induced in neutrino interactions is classified as shower- or track-like, and the main background processes associated with the detection of atmospheric neutrinos are recognized. Performance comparisons to machine-learning classification and maximum-likelihood reconstruction algorithms previously developed for KM3NeT/ORCA are provided. It is shown that this application of deep convolutional neural networks to simulated datasets for a large-volume neutrino telescope yields competitive reconstruction results and performance improvements with respect to classical approaches

Event reconstruction for KM3NeT/ORCA using convolutional neural networks

The KM3NeT research infrastructure is currently under construction at two locations in the Mediterranean Sea. The KM3NeT/ORCA water-Cherenkov neutrino de tector off the French coast will instrument several megatons of seawater with photosensors. Its main objective is the determination of the neutrino mass ordering. This work aims at demonstrating the general applicability of deep convolutional neural networks to neutrino telescopes, using simulated datasets for the KM3NeT/ORCA detector as an example. To this end, the networks are employed to achieve reconstruction and classification tasks that constitute an alternative to the analysis pipeline presented for KM3NeT/ORCA in the KM3NeT Letter of Intent. They are used to infer event reconstruction estimates for the energy, the direction, and the interaction point of incident neutrinos. The spatial distribution of Cherenkov light generated by charged particles induced in neutrino interactions is classified as shower-or track-like, and the main background processes associated with the detection of atmospheric neutrinos are recognized. Performance comparisons to machine-learning classification and maximum-likelihood reconstruction algorithms previously developed for KM3NeT/ORCA are provided. It is shown that this application of deep convolutional neural networks to simulated datasets for a large-volume neutrino telescope yields competitive reconstruction results and performance improvements with respect to classical approaches

Letter of intent for KM3NeT 2.0

The main objectives of the KM3NeT Collaboration are ( i ) the discovery and subsequent observation of high-energy neutrino sources in the Universe and ( ii ) the determination of the mass hierarchy of neutrinos. These objectives are strongly motivated by two recent important discoveries, namely: ( 1 ) the high- energy astrophysical neutrino signal reported by IceCube and ( 2 ) the sizable contribution of electron neutrinos to the third neutrino mass eigenstate as reported by Daya Bay, Reno and others. To meet these objectives, the KM3NeT Collaboration plans to build a new Research Infrastructure con- sisting of a network of deep-sea neutrino telescopes in the Mediterranean Sea. A phased and distributed implementation is pursued which maximises the access to regional funds, the availability of human resources and the syner- gistic opportunities for the Earth and sea sciences community. Three suitable deep-sea sites are selected, namely off-shore Toulon ( France ) , Capo Passero ( Sicily, Italy ) and Pylos ( Peloponnese, Greece ) . The infrastructure will consist of three so-called building blocks. A building block comprises 115 strings, each string comprises 18 optical modules and each optical module comprises 31 photo-multiplier tubes. Each building block thus constitutes a three- dimensional array of photo sensors that can be used to detect the Cherenkov light produced by relativistic particles emerging from neutrino interactions. Two building blocks will be sparsely con fi gured to fully explore the IceCube signal with similar instrumented volume, different methodology, improved resolution and complementary fi eld of view, including the galactic plane. One building block will be densely con fi gured to precisely measure atmospheric neutrino oscillations. Original content from this work may be used under the ter

Hilos

Guanyadora de l’accèssit de la modalitat de sèrie fotogràfica del Premi Sant Jordi de la UPF 2010Personal d'Administració i Serveis de la UP

Analysis of morphological and haemodynamical indexes in abdominal aortic aneurysms as preliminary indicators of intraluminal thrombus deposition

In this paper we study the correlation between the Wall Shear Stress (WSS), a haemodynamical index derived from numerical simulations, and an new index MFA-ILT for the characterisation of intraluminal thrombus (ILT) in presence of abdominal aortic aneurysms. Based on the processing of medical images, we define our index MFA-ILT by projecting onto lumen surface a measure of the ILT thickness. From the physical point of view, haemodynamical indexes describe the mechanical stimuli at which the luminal surface of the vessel wall is subject to, due to blood flow. Specifically, we consider the time-averaged wall shear stress and the oscillatory shear index. The first index provides a measurement of the averaged magnitude of the shear stress; the second index measures the rate of change of shear stress. To reconstruct the haemodynamical indexes, we build \emph{in silico} three-dimensional models. We use the same physical parameters and boundary conditions for all the aneurysms in the sample. The computer simulations do not require any additional invasive patient examination. We consider eleven cases of abdominal aortic aneurysms spanning a wide range of different morphological features. All the cases are characterized by a thin intraluminal thrombus. We can, therefore, assume that the lumen we currently observe does not significantly differ from the one before the thrombus deposition. Our results suggest that the value of wall shear stresses and intraluminal thrombus deposition are correlated. Moreover, we conclude that in six cases time-averaged wall shear stress provides a preliminary indication of the area at risk of thrombus deposition

Portable Nanocomposite System for Wound Healing in Space

It is well known that skin wound healing could be severely impaired in space. In particular, the skin is the tissue at risk of injury, especially during human-crewed space missions. Here, we propose a hybrid system based on the biocompatible poly 2-hydroxyethyl methacrylate (pHEMA) to actively support a nanocontainer filled with the drug. Specifically, during the cryo-polymerization of HEMA, halloysite nanotubes (HNTs) embedded with thymol (Thy) were added as a component. Thy is a natural pharmaceutical ingredient used to confer wound healing properties to the material, whereas HNTs were used to entrap the Thy into the lumen to ensure a sustained release of the drug. The as-obtained material was characterized by chemical–physical methods, and tests were performed to assess its ability for a prolonged drug release. The results showed that the adopted synthetic procedure allows the formation of a super absorbent system with good swelling ability that can contain up to 5.5 mg of Thy in about 90 mg of dried sponge. Releasing tests demonstrated the excellent material’s ability to perform a slow controlled delivery of 62% of charged Thy within a week. As humans venture deeper into space, with more extended missions, limited medical capabilities, and a higher risk of skin wounds, the proposed device would be a versatile miniaturized device for skin repair in space