Techniques for Lagrangian modelling of dispersion in geophysical flows

Basic concepts and definitions relative to Lagrangian Particle Dispersion Models (LPDMs)for the description of turbulent dispersion are introduced. The study focusses on LPDMs that use as input, for the large scale motion, fields produced by Eulerian models, with the small scale motions described by Lagrangian Stochastic Models (LSMs). The data of two different dynamical model have been used: a Large Eddy Simulation (LES) and a General Circulation Model (GCM). After reviewing the small scale closure adopted by the Eulerian model, the development and implementation of appropriate LSMs is outlined. The basic requirement of every LPDM used in this work is its fullfillment of the Well Mixed Condition (WMC). For the dispersion description in the GCM domain, a stochastic model of Markov order 0, consistent with the eddy-viscosity closure of the dynamical model, is implemented. A LSM of Markov order 1, more suitable for shorter timescales, has been implemented for the description of the unresolved motion of the LES fields. Different assumptions on the small scale correlation time are made. Tests of the LSM on GCM fields suggest that the use of an interpolation algorithm able to maintain an analytical consistency between the diffusion coefficient and its derivative is mandatory if the model has to satisfy the WMC. Also a dynamical time step selection scheme based on the diffusion coefficient shape is introduced, and the criteria for the integration step selection are discussed. Absolute and relative dispersion experiments are made with various unresolved motion settings for the LSM on LES data, and the results are compared with laboratory data. The study shows that the unresolved turbulence parameterization has a negligible influence on the absolute dispersion, while it affects the contribution of the relative dispersion and meandering to absolute dispersion, as well as the Lagrangian correlation.

Studio numerico e sperimentale delle miscele di aggregati per i conglomerati bituminosi

I crescenti volumi di traffico che interessano le pavimentazioni stradali causano sollecitazioni tensionali di notevole entit�� che provocano danni permanenti alla sovrastruttura. Tali danni ne riducono la vita utile e comportano elevati costi di manutenzione. Il conglomerato bituminoso �� un materiale multifase composto da inerti, bitume e vuoti d'aria. Le propriet�� fisiche e le prestazioni della miscela dipendono dalle caratteristiche dell'aggregato, del legante e dalla loro interazione. L���approccio tradizionalmente utilizzato per la modellazione numerica del conglomerato bituminoso si basa su uno studio macroscopico della sua risposta meccanica attraverso modelli costitutivi al continuo che, per loro natura, non considerano la mutua interazione tra le fasi eterogenee che lo compongono ed utilizzano schematizzazioni omogenee equivalenti. Nell���ottica di un���evoluzione di tali metodologie �� necessario superare questa semplificazione, considerando il carattere discreto del sistema ed adottando un approccio di tipo microscopico, che consenta di rappresentare i reali processi fisico-meccanici dai quali dipende la risposta macroscopica d���insieme. Nel presente lavoro, dopo una rassegna generale dei principali metodi numerici tradizionalmente impiegati per lo studio del conglomerato bituminoso, viene approfondita la teoria degli Elementi Discreti Particellari (DEM-P), che schematizza il materiale granulare come un insieme di particelle indipendenti che interagiscono tra loro nei punti di reciproco contatto secondo appropriate leggi costitutive. Viene valutata l���influenza della forma e delle dimensioni dell���aggregato sulle caratteristiche macroscopiche (tensione deviatorica massima) e microscopiche (forze di contatto normali e tangenziali, numero di contatti, indice dei vuoti, porosit��, addensamento, angolo di attrito interno) della miscela. Ci�� �� reso possibile dal confronto tra risultati numerici e sperimentali di test triassiali condotti su provini costituiti da tre diverse miscele formate da sfere ed elementi di forma generica.

Scene Reconstruction And Understanding By RGB-D Sensors

This thesis investigates interactive scene reconstruction and understanding using RGB-D data only. Indeed, we believe that depth cameras will still be in the near future a cheap and low-power 3D sensing alternative suitable for mobile devices too. Therefore, our contributions build on top of state-of-the-art approaches to achieve advances in three main challenging scenarios, namely mobile mapping, large scale surface reconstruction and semantic modeling. First, we will describe an effective approach dealing with Simultaneous Localization And Mapping (SLAM) on platforms with limited resources, such as a tablet device. Unlike previous methods, dense reconstruction is achieved by reprojection of RGB-D frames, while local consistency is maintained by deploying relative bundle adjustment principles. We will show quantitative results comparing our technique to the state-of-the-art as well as detailed reconstruction of various environments ranging from rooms to small apartments. Then, we will address large scale surface modeling from depth maps exploiting parallel GPU computing. We will develop a real-time camera tracking method based on the popular KinectFusion system and an online surface alignment technique capable of counteracting drift errors and closing small loops. We will show very high quality meshes outperforming existing methods on publicly available datasets as well as on data recorded with our RGB-D camera even in complete darkness. Finally, we will move to our Semantic Bundle Adjustment framework to effectively combine object detection and SLAM in a uni���ed system. Though the mathematical framework we will describe does not restrict to a particular sensing technology, in the experimental section we will refer, again, only to RGB-D sensing. We will discuss successful implementations of our algorithm showing the bene���t of a joint object detection, camera tracking and environment mapping.

Diffusive models and chaos indicators for non-linear betatron motion in circular hadron accelerators

Understanding the complex dynamics of beam-halo formation and evolution in circular particle accelerators is crucial for the design of current and future rings, particularly those utilizing superconducting magnets such as the CERN Large Hadron Collider (LHC), its luminosity upgrade HL-LHC, and the proposed Future Circular Hadron Collider (FCC-hh). A recent diffusive framework, which describes the evolution of the beam distribution by means of a Fokker-Planck equation, with diffusion coefficient derived from the Nekhoroshev theorem, has been proposed to describe the long-term behaviour of beam dynamics and particle losses. In this thesis, we discuss the theoretical foundations of this framework, and propose the implementation of an original measurement protocol based on collimator scans in view of measuring the Nekhoroshev-like diffusive coefficient by means of beam loss data. The available LHC collimator scan data, unfortunately collected without the proposed measurement protocol, have been successfully analysed using the proposed framework. This approach is also applied to datasets from detailed measurements of the impact on the beam losses of so-called long-range beam-beam compensators also at the LHC. Furthermore, dynamic indicators have been studied as a tool for exploring the phase-space properties of realistic accelerator lattices in single-particle tracking simulations. By first examining the classification performance of known and new indicators in detecting the chaotic character of initial conditions for a modulated H��non map and then applying this knowledge to study the properties of realistic accelerator lattices, we tried to identify a connection between the presence of chaotic regions in the phase space and Nekhoroshev-like diffusive behaviour, providing new tools to the accelerator physics community.

Fast and accurate numerical solutions in some problems of particle and radiation transport: synthetic acceleration for the method of short characteristics, Doppler-broadened scattering kernel, remote sensing of the cryosphere

The aim of this work is to present various aspects of numerical simulation of particle and radiation transport for industrial and environmental protection applications, to enable the analysis of complex physical processes in a fast, reliable, and efficient way. In the first part we deal with speed-up of numerical simulation of neutron transport for nuclear reactor core analysis. The convergence properties of the source iteration scheme of the Method of Characteristics applied to be heterogeneous structured geometries has been enhanced by means of Boundary Projection Acceleration, enabling the study of 2D and 3D geometries with transport theory without spatial homogenization. The computational performances have been verified with the C5G7 2D and 3D benchmarks, showing a sensible reduction of iterations and CPU time. The second part is devoted to the study of temperature-dependent elastic scattering of neutrons for heavy isotopes near to the thermal zone. A numerical computation of the Doppler convolution of the elastic scattering kernel based on the gas model is presented, for a general energy dependent cross section and scattering law in the center of mass system. The range of integration has been optimized employing a numerical cutoff, allowing a faster numerical evaluation of the convolution integral. Legendre moments of the transfer kernel are subsequently obtained by direct quadrature and a numerical analysis of the convergence is presented. In the third part we focus our attention to remote sensing applications of radiative transfer employed to investigate the Earth's cryosphere. The photon transport equation is applied to simulate reflectivity of glaciers varying the age of the layer of snow or ice, its thickness, the presence or not other underlying layers, the degree of dust included in the snow, creating a framework able to decipher spectral signals collected by orbiting detectors.

4H silicon carbide particle detectors: study of the defects induced by high energy neutron irradiation

During the last decade advances in the field of sensor design and improved base materials have pushed the radiation hardness of the current silicon detector technology to impressive performance. It should allow operation of the tracking systems of the Large Hadron Collider (LHC) experiments at nominal luminosity (1034 cm-2s-1) for about 10 years. The current silicon detectors are unable to cope with such an environment. Silicon carbide (SiC), which has recently been recognized as potentially radiation hard, is now studied. In this work it was analyzed the effect of high energy neutron irradiation on 4H-SiC particle detectors. Schottky and junction particle detectors were irradiated with 1 MeV neutrons up to fluence of 1016 cm-2. It is well known that the degradation of the detectors with irradiation, independently of the structure used for their realization, is caused by lattice defects, like creation of point-like defect, dopant deactivation and dead layer formation and that a crucial aspect for the understanding of the defect kinetics at a microscopic level is the correct identification of the crystal defects in terms of their electrical activity. In order to clarify the defect kinetic it were carried out a thermal transient spectroscopy (DLTS and PICTS) analysis of different samples irradiated at increasing fluences. The defect evolution was correlated with the transport properties of the irradiated detector, always comparing with the un-irradiated one. The charge collection efficiency degradation of Schottky detectors induced by neutron irradiation was related to the increasing concentration of defects as function of the neutron fluence.

Study of the inter-annual variability of particle vertical fluxes in two moorings in the Ross Sea (Antarctica)

The most ocean - atmosphere exchanges take place in polar environments due to the low temperatures which favor the absorption processes of atmospheric gases, in particular CO2. For this reason, the alterations of biogeochemical cycles in these areas can have a strong impact on the global climate. With the aim of contributing to the definition of the mechanisms regulating the biogeochemical fluxes we have analyzed the particles collected in the Ross Sea in different years (ROSSMIZE, BIOSESO 1 and 2, ROAVERRS and ABIOCLEAR projects) in two sites (mooring A and B). So it has been developed a more efficient method to prepare sediment trap samples for the analyses. We have also processed satellite data of sea ice, chlorophyll a and diatoms concentration. At both sites, in each year considered, there was a high seasonal and inter-annual variability of biogeochemical fluxes closely correlated with sea ice cover and primary productivity. The comparison between the samples collected at mooring A and B in 2008 highlighted the main differences between these two sites. Particle fluxes at Mooring A, located in a polynia area, are higher than mooring B ones and they happen about a month before. In the mooring B area it has been possible to correlate the particles fluxes to the ice concentration anomalies and with the atmospheric changes in response to El Ni��o Southern Oscillations. In 1996 and 1999, years subjected to La Ni��a, the concentrations of sea ice in this area have been less than in 1998, year subjected to El Ni��o. Inverse correlation was found for 2005 and 2008. In the mooring A area significant differences in mass and biogenic fluxes during 2005 and 2008 has been recorded. This allowed to underline the high variability of lateral advection processes and to connect them to the physical forcing.

Development Of New Toolkits For Orbit Determination Codes For Precise Radio Tracking Experiments

This thesis describes the developments of new models and toolkits for the orbit determination codes to support and improve the precise radio tracking experiments of the Cassini-Huygens mission, an interplanetary mission to study the Saturn system. The core of the orbit determination process is the comparison between observed observables and computed observables. Disturbances in either the observed or computed observables degrades the orbit determination process. Chapter 2 describes a detailed study of the numerical errors in the Doppler observables computed by NASA's ODP and MONTE, and ESA's AMFIN. A mathematical model of the numerical noise was developed and successfully validated analyzing against the Doppler observables computed by the ODP and MONTE, with typical relative errors smaller than 10%. The numerical noise proved to be, in general, an important source of noise in the orbit determination process and, in some conditions, it may becomes the dominant noise source. Three different approaches to reduce the numerical noise were proposed. Chapter 3 describes the development of the multiarc library, which allows to perform a multi-arc orbit determination with MONTE. The library was developed during the analysis of the Cassini radio science gravity experiments of the Saturn's satellite Rhea. Chapter 4 presents the estimation of the Rhea's gravity field obtained from a joint multi-arc analysis of Cassini R1 and R4 fly-bys, describing in details the spacecraft dynamical model used, the data selection and calibration procedure, and the analysis method followed. In particular, the approach of estimating the full unconstrained quadrupole gravity field was followed, obtaining a solution statistically not compatible with the condition of hydrostatic equilibrium. The solution proved to be stable and reliable. The normalized moment of inertia is in the range 0.37-0.4 indicating that Rhea's may be almost homogeneous, or at least characterized by a small degree of differentiation.

Target Tracking in UWB Multistatic Radars

Detection, localization and tracking of non-collaborative objects moving inside an area is of great interest to many surveillance applications. An ultra- wideband (UWB) multistatic radar is considered as a good infrastructure for such anti-intruder systems, due to the high range resolution provided by the UWB impulse-radio and the spatial diversity achieved with a multistatic configuration. Detection of targets, which are typically human beings, is a challenging task due to reflections from unwanted objects in the area, shadowing, antenna cross-talks, low transmit power, and the blind zones arised from intrinsic peculiarities of UWB multistatic radars. Hence, we propose more effective detection, localization, as well as clutter removal techniques for these systems. However, the majority of the thesis effort is devoted to the tracking phase, which is an essential part for improving the localization accuracy, predicting the target position and filling out the missed detections. Since UWB radars are not linear Gaussian systems, the widely used tracking filters, such as the Kalman filter, are not expected to provide a satisfactory performance. Thus, we propose the Bayesian filter as an appropriate candidate for UWB radars. In particular, we develop tracking algorithms based on particle filtering, which is the most common approximation of Bayesian filtering, for both single and multiple target scenarios. Also, we propose some effective detection and tracking algorithms based on image processing tools. We evaluate the performance of our proposed approaches by numerical simulations. Moreover, we provide experimental results by channel measurements for tracking a person walking in an indoor area, with the presence of a significant clutter. We discuss the existing practical issues and address them by proposing more robust algorithms.

Smart tracking of composite parts: feasibility study and effect on mechanical behaviour

This research proposes a solution for integrating RFID - Radio Frequency Identification technology within a structure based on CFRPs - Carbon Fiber Reinforced Polymers. Therefore, the main objective is to use technology to monitor and track composite components during manufacturing and service life. The study can be divided into two macro-areas. The first portion of the research evaluates the impact of the composite materials used on transmitting the electromagnetic signal to and from the tag. RFID technology communicates through radio frequencies to to track and trace items associated with the tags. In the first instance, a feasibility study was carried out to assess using commercially available tags. Then, after evaluating different solutions, it was decided to incorporate the tags into coupons during production. The second portion of the research is focused on evaluating the impact on the composite material's resistance to tag embedding. It starts with designing tensile test specimens through the FEM model with different housing configurations. Subsequently, the best configuration was tested in the facilities of the In the Faculty of Aerospace Engineering at TU Delft, particularly in the Structure & Materials Laboratory, two tests were conducted: the first one based on ASTM D3039/D3039 - 14 - Standard Test Method for Tensile Properties of Polymer Matrix Composite Materials, the second one dividing the path to failure into failure intervals in a load-unload-reload. Both tests were accompanied by instruments such as DIC, AE, C-Scan and Optical Microscopes. The expected result of the inclusion of RFID tags in composite components is that it brings added value to the parts with which it is associated without affecting too much its mechanical properties. This comes first from the automatic identification of RFID during the production cycle and its useful life. As a result, improvements were made in the design of production facilities.

Study of the tracking performance of a liquid Argon detector based on a novel optical imaging concept

The Deep Underground Neutrino Experiment (DUNE) is a long-baseline accelerator experiment designed to make a significant contribution to the study of neutrino oscillations with unprecedented sensitivity. The main goal of DUNE is the determination of the neutrino mass ordering and the leptonic CP violation phase, key parameters of the three-neutrino flavor mixing that have yet to be determined. An important component of the DUNE Near Detector complex is the System for on-Axis Neutrino Detection (SAND) apparatus, which will include GRAIN (GRanular Argon for Interactions of Neutrinos), a novel liquid Argon detector aimed at imaging neutrino interactions using only scintillation light. For this purpose, an innovative optical readout system based on Coded Aperture Masks is investigated. This dissertation aims to demonstrate the feasibility of reconstructing particle tracks and the topology of CCQE (Charged Current Quasi Elastic) neutrino events in GRAIN with such a technique. To this end, the development and implementation of a reconstruction algorithm based on Maximum Likelihood Expectation Maximization was carried out to directly obtain a three-dimensional distribution proportional to the energy deposited by charged particles crossing the LAr volume. This study includes the evaluation of the design of several camera configurations and the simulation of a multi-camera optical system in GRAIN.