Astrophysical sources for the observed electron and positron axcess at high energy with AMS-02 experiment.

Cosmic ray electrons and positrons represent only _ 1% of the total particles which reach the Earth. The standard scenario predicts that the main component of the electron spectrum is the one produced by supernova remnants, while positrons are supposed to be mainly originated from the decay of muons produced by cosmic ray interactions with the interstellar medium. In the last years, space born experiments, like AMS-02, have detected an anomalous electron and positron abundance with respect to the theoretical model predictions, for energy above _ 10 GeV, where the solar modulation e_ects are negligible. This di_erence, between data and model prediction, shows an extra contribution suggesting an equal amount for both electrons and positrons. These kinds of particles, with an initial energy of 100 GeV, can travel at most for _ 2 kpc; thus, a source of electron-positron pairs is expected inside this region. We studied the contribution from Vela-X Pulsar Wind Nebula starting from its photon spectrum; a di_usion model is applied from the source up to the Solar System and the propagated spectra are compared with the AMS-02 data. Above 100 GeV, Vela-X is the main candidate to contribute to the observed excess and it could give an anisotropic signal in the arrival cosmic ray directions

Weighted reduced order methods for parametrized partial differential equations with random inputs

In this manuscript we discuss weighted reduced order methods for stochastic partial differential equations. Random inputs (such as forcing terms, equation coefficients, boundary conditions) are considered as parameters of the equations. We take advantage of the resulting parametrized formulation to propose an efficient reduced order model; we also profit by the underlying stochastic assumption in the definition of suitable weights to drive to reduction process. Two viable strategies are discussed, namely the weighted reduced basis method and the weighted proper orthogonal decomposition method. A numerical example on a parametrized elasticity problem is shown

An optimisation-based domain-decomposition reduced order model for parameter-dependent non-stationary fluid dynamics problems

In this work, we address parametric non-stationary fluid dynamics problems within a model order reduction setting based on domain decomposition. Starting from the optimisation-based domain decomposition approach, we derive an optimal control problem, for which we present a convergence analysis in the case of non-stationary incompressible Navier-Stokes equations. We discretize the problem with the finite element method and we compare different model order reduction techniques: POD-Galerkin and a non-intrusive neural network procedure. We show that the classical POD-Galerkin is more robust and accurate also in transient areas, while the neural network can obtain simulations very quickly though being less precise in the presence of discontinuities in time or parameter domain. We test the proposed methodologies on two fluid dynamics benchmarks with physical parameters and time dependency: the non-stationary backward-facing step and lid-driven cavity flow.Comment: arXiv admin note: substantial text overlap with arXiv:2211.1452

Displacement Damage dose and DLTS Analyses on Triple and Single Junction solar cells irradiated with electrons and protons

Space solar cells radiation hardness is of fundamental importance in view of the future missions towards harsh radiation environment (like e.g. missions to Jupiter) and for the new spacecraft using electrical propulsion. In this paper we report the radiation data for triple junction (TJ) solar cells and related component cells. Triple junction solar cells, InGaP top cells and GaAs middle cells degrade after electron radiation as expected. With proton irradiation, a high spread in the remaining factors was observed, especially for the TJ and bottom cells. Very surprising was the germanium bottom junction that showed very high degradation after protons whereas it is quite stable against electrons. Radiation results have been analyzed by means of the Displacement Damage Dose method and DLTS spectroscopy.Comment: Abstract accepted for poster session at 2017 IEEE Nuclear and Space Radiation Effects Conference, July 17-21, New Orlean

Efficient reduction in shape parameter space dimension for ship propeller blade design

In this work, we present the results of a ship propeller design optimization campaign carried out in the framework of the research project PRELICA, funded by the Friuli Venezia Giulia regional government. The main idea of this work is to operate on a multidisciplinary level to identify propeller shapes that lead to reduced tip vortex-induced pressure and increased efficiency without altering the thrust. First, a specific tool for the bottom-up construction of parameterized propeller blade geometries has been developed. The algorithm proposed operates with a user defined number of arbitrary shaped or NACA airfoil sections, and employs arbitrary degree NURBS to represent the chord, pitch, skew and rake distribution as a function of the blade radial coordinate. The control points of such curves have been modified to generate, in a fully automated way, a family of blade geometries depending on as many as 20 shape parameters. Such geometries have then been used to carry out potential flow simulations with the Boundary Element Method based software PROCAL. Given the high number of parameters considered, such a preliminary stage allowed for a fast evaluation of the performance of several hundreds of shapes. In addition, the data obtained from the potential flow simulation allowed for the application of a parameter space reduction methodology based on active subspaces (AS) property, which suggested that the main propeller performance indices are, at a first but rather accurate approximation, only depending on a single parameter which is a linear combination of all the original geometric ones. AS analysis has also been used to carry out a constrained optimization exploiting response surface method in the reduced parameter space, and a sensitivity analysis based on such surrogate model. The few selected shapes were finally used to set up high fidelity RANS simulations and select an optimal shape