Fluid dynamic analysis and modelling of industrial chemical equipment

The research is aimed at contributing to the identification of reliable fully predictive Computational Fluid Dynamics (CFD) methods for the numerical simulation of equipment typically adopted in the chemical and process industries. The apparatuses selected for the investigation, specifically membrane modules, stirred vessels and fluidized beds, were characterized by a different and often complex fluid dynamic behaviour and in some cases the momentum transfer phenomena were coupled with mass transfer or multiphase interactions. Firs of all, a novel modelling approach based on CFD for the prediction of the gas separation process in membrane modules for hydrogen purification is developed. The reliability of the gas velocity field calculated numerically is assessed by comparison of the predictions with experimental velocity data collected by Particle Image Velocimetry, while the applicability of the model to properly predict the separation process under a wide range of operating conditions is assessed through a strict comparison with permeation experimental data. Then, the effect of numerical issues on the RANS-based predictions of single phase stirred tanks is analysed. The homogenisation process of a scalar tracer is also investigated and simulation results are compared to original passive tracer homogenisation curves determined with Planar Laser Induced Fluorescence. The capability of a CFD approach based on the solution of RANS equations is also investigated for describing the fluid dynamic characteristics of the dispersion of organics in water. Finally, an Eulerian-Eulerian fluid-dynamic model is used to simulate mono-disperse suspensions of Geldart A Group particles fluidized by a Newtonian incompressible fluid as well as binary segregating fluidized beds of particles differing in size and density. The results obtained under a number of different operating conditions are compared with literature experimental data and the effect of numerical uncertainties on axial segregation is also discussed.

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.

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.