Development of advanced tools and methods for the assessment and management of risk due to atypical major accident scenarios

Proper hazard identification has become progressively more difficult to achieve, as witnessed by several major accidents that took place in Europe, such as the Ammonium Nitrate explosion at Toulouse (2001) and the vapour cloud explosion at Buncefield (2005), whose accident scenarios were not considered by their site safety case. Furthermore, the rapid renewal in the industrial technology has brought about the need to upgrade hazard identification methodologies. Accident scenarios of emerging technologies, which are not still properly identified, may remain unidentified until they take place for the first time. The consideration of atypical scenarios deviating from normal expectations of unwanted events or worst case reference scenarios is thus extremely challenging. A specific method named Dynamic Procedure for Atypical Scenarios Identification (DyPASI) was developed as a complementary tool to bow-tie identification techniques. The main aim of the methodology is to provide an easier but comprehensive hazard identification of the industrial process analysed, by systematizing information from early signals of risk related to past events, near misses and inherent studies. DyPASI was validated on the two examples of new and emerging technologies: Liquefied Natural Gas regasification and Carbon Capture and Storage. The study broadened the knowledge on the related emerging risks and, at the same time, demonstrated that DyPASI is a valuable tool to obtain a complete and updated overview of potential hazards. Moreover, in order to tackle underlying accident causes of atypical events, three methods for the development of early warning indicators were assessed: the Resilience-based Early Warning Indicator (REWI) method, the Dual Assurance method and the Emerging Risk Key Performance Indicator method. REWI was found to be the most complementary and effective of the three, demonstrating that its synergy with DyPASI would be an adequate strategy to improve hazard identification methodologies towards the capture of atypical accident scenarios.

Advanced Numerical Simulation of Silicon-Based Solar Cells

Photovoltaic (PV) conversion is the direct production of electrical energy from sun without involving the emission of polluting substances. In order to be competitive with other energy sources, cost of the PV technology must be reduced ensuring adequate conversion efficiencies. These goals have motivated the interest of researchers in investigating advanced designs of crystalline silicon solar (c-Si) cells. Since lowering the cost of PV devices involves the reduction of the volume of semiconductor, an effective light trapping strategy aimed at increasing the photon absorption is required. Modeling of solar cells by electro-optical numerical simulation is helpful to predict the performance of future generations devices exhibiting advanced light-trapping schemes and to provide new and more specific guidelines to industry. The approaches to optical simulation commonly adopted for c-Si solar cells may lead to inaccurate results in case of thin film and nano-stuctured solar cells. On the other hand, rigorous solvers of Maxwell equations are really cpu- and memory-intensive. Recently, in optical simulation of solar cells, the RCWA method has gained relevance, providing a good trade-off between accuracy and computational resources requirement. This thesis is a contribution to the numerical simulation of advanced silicon solar cells by means of a state-of-the-art numerical 2-D/3-D device simulator, that has been successfully applied to the simulation of selective emitter and the rear point contact solar cells, for which the multi-dimensionality of the transport model is required in order to properly account for all physical competing mechanisms. In the second part of the thesis, the optical problems is discussed. Two novel and computationally efficient RCWA implementations for 2-D simulation domains as well as a third RCWA for 3-D structures based on an eigenvalues calculation approach have been presented. The proposed simulators have been validated in terms of accuracy, numerical convergence, computation time and correctness of results.

Design and optimization of components and processes for plasma sources in advanced material treatments

The research activities described in the present thesis have been oriented to the design and development of components and technological processes aimed at optimizing the performance of plasma sources in advanced in material treatments. Consumables components for high definition plasma arc cutting (PAC) torches were studied and developed. Experimental activities have in particular focussed on the modifications of the emissive insert with respect to the standard electrode configuration, which comprises a press fit hafnium insert in a copper body holder, to improve its durability. Based on a deep analysis of both the scientific and patent literature, different solutions were proposed and tested. First, the behaviour of Hf cathodes when operating at high current levels (250A) in oxidizing atmosphere has been experimentally investigated optimizing, with respect to expected service life, the initial shape of the electrode emissive surface. Moreover, the microstructural modifications of the Hf insert in PAC electrodes were experimentally investigated during first cycles, in order to understand those phenomena occurring on and under the Hf emissive surface and involved in the electrode erosion process. Thereafter, the research activity focussed on producing, characterizing and testing prototypes of composite inserts, combining powders of a high thermal conductibility (Cu, Ag) and high thermionic emissivity (Hf, Zr) materials The complexity of the thermal plasma torch environment required and integrated approach also involving physical modelling. Accordingly, a detailed line-by-line method was developed to compute the net emission coefficient of Ar plasmas at temperatures ranging from 3000 K to 25000 K and pressure ranging from 50 kPa to 200 kPa, for optically thin and partially autoabsorbed plasmas. Finally, prototypal electrodes were studied and realized for a newly developed plasma source, based on the plasma needle concept and devoted to the generation of atmospheric pressure non-thermal plasmas for biomedical applications.

Advanced CMOS Interfaces for Bio-Nanosensors

The improvement of devices provided by Nanotechnology has put forward new classes of sensors, called bio-nanosensors, which are very promising for the detection of biochemical molecules in a large variety of applications. Their use in lab-on-a-chip could gives rise to new opportunities in many fields, from health-care and bio-warfare to environmental and high-throughput screening for pharmaceutical industry. Bio-nanosensors have great advantages in terms of cost, performance, and parallelization. Indeed, they require very low quantities of reagents and improve the overall signal-to-noise-ratio due to increase of binding signal variations vs. area and reduction of stray capacitances. Additionally, they give rise to new challenges, such as the need to design high-performance low-noise integrated electronic interfaces. This thesis is related to the design of high-performance advanced CMOS interfaces for electrochemical bio-nanosensors. The main focus of the thesis is: 1) critical analysis of noise in sensing interfaces, 2) devising new techniques for noise reduction in discrete-time approaches, 3) developing new architectures for low-noise, low-power sensing interfaces. The manuscript reports a multi-project activity focusing on low-noise design and presents two developed integrated circuits (ICs) as examples of advanced CMOS interfaces for bio-nanosensors. The first project concerns low-noise current-sensing interface for DC and transient measurements of electrophysiological signals. The focus of this research activity is on the noise optimization of the electronic interface. A new noise reduction technique has been developed so as to realize an integrated CMOS interfaces with performance comparable with state-of-the-art instrumentations. The second project intends to realize a stand-alone, high-accuracy electrochemical impedance spectroscopy interface. The system is tailored for conductivity-temperature-depth sensors in environmental applications, as well as for bio-nanosensors. It is based on a band-pass delta-sigma technique and combines low-noise performance with low-power requirements.

Advanced Waste-To-Energy Cycles

The increase in environmental and healthy concerns, combined with the possibility to exploit waste as a valuable energy resource, has led to explore alternative methods for waste final disposal. In this context, the energy conversion of Municipal Solid Waste (MSW) in Waste-To-Energy (WTE) power plant is increasing throughout Europe, both in terms of plants number and capacity, furthered by legislative directives. Due to the heterogeneous nature of waste, some differences with respect to a conventional fossil fuel power plant have to be considered in the energy conversion process. In fact, as a consequence of the well-known corrosion problems, the thermodynamic efficiency of WTE power plants typically ranging in the interval 25% ÷ 30%. The new Waste Framework Directive 2008/98/EC promotes production of energy from waste introducing an energy efficiency criteria (the so-called “R1 formula”) to evaluate plant recovery status. The aim of the Directive is to drive WTE facilities to maximize energy recovery and utilization of waste heat, in order to substitute energy produced with conventional fossil fuels fired power plants. This calls for novel approaches and possibilities to maximize the conversion of MSW into energy. In particular, the idea of an integrated configuration made up of a WTE and a Gas Turbine (GT) originates, driven by the desire to eliminate or, at least, mitigate limitations affecting the WTE conversion process bounding the thermodynamic efficiency of the cycle. The aim of this Ph.D thesis is to investigate, from a thermodynamic point of view, the integrated WTE-GT system sharing the steam cycle, sharing the flue gas paths or combining both ways. The carried out analysis investigates and defines the logic governing plants match in terms of steam production and steam turbine power output as function of the thermal powers introduced.

Progress in x-ray spectroscopies for the study of advanced materials

This thesis work is focused on the use of selected core-level x-ray spectroscopies to study semiconductor materials of great technological interest and on the development of a new implementation of appearance potential spectroscopy. Core-level spectroscopies can be exploited to study these materials with a local approach since they are sensitive to the electronic structure localized on a chemical species present in the sample examined. This approach, in fact, provides important micro-structural information that is difficult to obtain with techniques sensitive to the average properties of materials. In this thesis work we present a novel approach to the study of semiconductors with core-level spectroscopies based on an original analysis procedure that leads to an insightful understanding of the correlation between the local micro-structure and the spectral features observed. In particular, we studied the micro-structure of Hydrogen induced defects in nitride semiconductors, since the analysed materials show substantial variations of optical and electronic properties as a consequence of H incorporation. Finally, we present a novel implementation of soft x-ray appearance potential spectroscopy, a core-level spectroscopy that uses electrons as a source of excitation and has the great advantage of being an in-house technique. The original set-up illustrated was designed to reach a high signal-to-noise ratio for the acquisition of good quality spectra that can then be analyzed in the framework of the real space full multiple scattering theory. This technique has never been coupled with this analysis approach and therefore our work unite a novel implementation with an original data analysis method, enlarging the field of application of this technique.

Advanced spectroscopic techniques and chemometric analysis for atmospheric organic aerosol characterization and source apportionment

Atmospheric aerosol particles directly impact air quality and participate in controlling the climate system. Organic Aerosol (OA) in general accounts for a large fraction (10–90%) of the global submicron (PM1) particulate mass. Chemometric methods for source identification are used in many disciplines, but methods relying on the analysis of NMR datasets are rarely used in atmospheric sciences. This thesis provides an original application of NMR-based chemometric methods to atmospheric OA source apportionment. The method was tested on chemical composition databases obtained from samples collected at different environments in Europe, hence exploring the impact of a great diversity of natural and anthropogenic sources. We focused on sources of water-soluble OA (WSOA), for which NMR analysis provides substantial advantages compared to alternative methods. Different factor analysis techniques are applied independently to NMR datasets from nine field campaigns of the project EUCAARI and allowed the identification of recurrent source contributions to WSOA in European background troposphere: 1) Marine SOA; 2) Aliphatic amines from ground sources (agricultural activities, etc.); 3) Biomass burning POA; 4) Biogenic SOA from terpene oxidation; 5) “Aged” SOAs, including humic-like substances (HULIS); 6) Other factors possibly including contributions from Primary Biological Aerosol Particles, and products of cooking activities. Biomass burning POA accounted for more than 50% of WSOC in winter months. Aged SOA associated with HULIS was predominant (> 75%) during the spring-summer, suggesting that secondary sources and transboundary transport become more important in spring and summer. Complex aerosol measurements carried out, involving several foreign research groups, provided the opportunity to compare source apportionment results obtained by NMR analysis with those provided by more widespread Aerodyne aerosol mass spectrometers (AMS) techniques that now provided categorization schemes of OA which are becoming a standard for atmospheric chemists. Results emerging from this thesis partly confirm AMS classification and partly challenge it.

Advanced Beamforming for Distributed and Multi-Beam Networks

Beamforming entails joint processing of multiple signals received or transmitted by an array of antennas. This thesis addresses the implementation of beamforming in two distinct systems, namely a distributed network of independent sensors, and a broad-band multi-beam satellite network. With the rising popularity of wireless sensors, scientists are taking advantage of the flexibility of these devices, which come with very low implementation costs. Simplicity, however, is intertwined with scarce power resources, which must be carefully rationed to ensure successful measurement campaigns throughout the whole duration of the application. In this scenario, distributed beamforming is a cooperative communication technique, which allows nodes in the network to emulate a virtual antenna array seeking power gains in the order of the size of the network itself, when required to deliver a common message signal to the receiver. To achieve a desired beamforming configuration, however, all nodes in the network must agree upon the same phase reference, which is challenging in a distributed set-up where all devices are independent. The first part of this thesis presents new algorithms for phase alignment, which prove to be more energy efficient than existing solutions. With the ever-growing demand for broad-band connectivity, satellite systems have the great potential to guarantee service where terrestrial systems can not penetrate. In order to satisfy the constantly increasing demand for throughput, satellites are equipped with multi-fed reflector antennas to resolve spatially separated signals. However, incrementing the number of feeds on the payload corresponds to burdening the link between the satellite and the gateway with an extensive amount of signaling, and to possibly calling for much more expensive multiple-gateway infrastructures. This thesis focuses on an on-board non-adaptive signal processing scheme denoted as Coarse Beamforming, whose objective is to reduce the communication load on the link between the ground station and space segment.

Modelling and Design of Advanced Reliable Circuits and Devices for Energy Efficiency

Reliable electronic systems, namely a set of reliable electronic devices connected to each other and working correctly together for the same functionality, represent an essential ingredient for the large-scale commercial implementation of any technological advancement. Microelectronics technologies and new powerful integrated circuits provide noticeable improvements in performance and cost-effectiveness, and allow introducing electronic systems in increasingly diversified contexts. On the other hand, opening of new fields of application leads to new, unexplored reliability issues. The development of semiconductor device and electrical models (such as the well known SPICE models) able to describe the electrical behavior of devices and circuits, is a useful means to simulate and analyze the functionality of new electronic architectures and new technologies. Moreover, it represents an effective way to point out the reliability issues due to the employment of advanced electronic systems in new application contexts. In this thesis modeling and design of both advanced reliable circuits for general-purpose applications and devices for energy efficiency are considered. More in details, the following activities have been carried out: first, reliability issues in terms of security of standard communication protocols in wireless sensor networks are discussed. A new communication protocol is introduced, allows increasing the network security. Second, a novel scheme for the on-die measurement of either clock jitter or process parameter variations is proposed. The developed scheme can be used for an evaluation of both jitter and process parameter variations at low costs. Then, reliability issues in the field of “energy scavenging systems” have been analyzed. An accurate analysis and modeling of the effects of faults affecting circuit for energy harvesting from mechanical vibrations is performed. Finally, the problem of modeling the electrical and thermal behavior of photovoltaic (PV) cells under hot-spot condition is addressed with the development of an electrical and thermal model.

Generalized Differential Quadrature Finite Element Method applied to Advanced Structural Mechanics

Over the years the Differential Quadrature (DQ) method has distinguished because of its high accuracy, straightforward implementation and general ap- plication to a variety of problems. There has been an increase in this topic by several researchers who experienced significant development in the last years. DQ is essentially a generalization of the popular Gaussian Quadrature (GQ) used for numerical integration functions. GQ approximates a finite in- tegral as a weighted sum of integrand values at selected points in a problem domain whereas DQ approximate the derivatives of a smooth function at a point as a weighted sum of function values at selected nodes. A direct appli- cation of this elegant methodology is to solve ordinary and partial differential equations. Furthermore in recent years the DQ formulation has been gener- alized in the weighting coefficients computations to let the approach to be more flexible and accurate. As a result it has been indicated as Generalized Differential Quadrature (GDQ) method. However the applicability of GDQ in its original form is still limited. It has been proven to fail for problems with strong material discontinuities as well as problems involving singularities and irregularities. On the other hand the very well-known Finite Element (FE) method could overcome these issues because it subdivides the computational domain into a certain number of elements in which the solution is calculated. Recently, some researchers have been studying a numerical technique which could use the advantages of the GDQ method and the advantages of FE method. This methodology has got different names among each research group, it will be indicated here as Generalized Differential Quadrature Finite Element Method (GDQFEM).

Influence of advanced load simulation models on fatigue design of jackets for offshore wind turbines.

Constant developments in the field of offshore wind energy have increased the range of water depths at which wind farms are planned to be installed. Therefore, in addition to monopile support structures suitable in shallow waters (up to 30 m), different types of support structures, able to withstand severe sea conditions at the greater water depths, have been developed. For water depths above 30 m, the jacket is one of the preferred support types. Jacket represents a lightweight support structure, which, in combination with complex nature of environmental loads, is prone to highly dynamic behavior. As a consequence, high stresses with great variability in time can be observed in all structural members. The highest concentration of stresses occurs in joints due to their nature (structural discontinuities) and due to the existence of notches along the welds present in the joints. This makes them the weakest elements of the jacket in terms of fatigue. In the numerical modeling of jackets for offshore wind turbines, a reduction of local stresses at the chord-brace joints, and consequently an optimization of the model, can be achieved by implementing joint flexibility in the chord-brace joints. Therefore, in this work, the influence of joint flexibility on the fatigue damage in chord-brace joints of a numerical jacket model, subjected to advanced load simulations, is studied.

Advanced schemes for surface plasmon resonance and plasmon-enhanced fluorescence biosensors

Advanced optical biosensor platforms exploiting long range surface plasmons (LRSPs) and responsive N-isopropylacrylamide (NIPAAm) hydrogel binding matrix for the detection of protein and bacterial pathogen analytes were carried out. LRSPs are optical waves that originate from coupling of surface plasmons on the opposite sites of a thin metallic film embedded between two dielectrics with similar refractive indices. LRSPs exhibit orders of magnitude lower damping and more extended profile of field compared to regular surface plasmons (SPs). Their excitation is accompanied with narrow resonance and provides stronger enhancement of electromagnetic field intensity that can advance the sensitivity of surface plasmon resonance (SPR) and surface plasmon-enhanced fluorescence spectroscopy (SPFS) biosensors. Firstly, we investigated thin gold layers deposited on fluoropolymer surface for the excitation of LRSPs. The study indicates that the morphological, optical and electrical properties of gold film can be changed by the surface energy of fluoropolymer and affect the performance of a SPFS biosensor. A photo-crosslinkable NIPAAm hydrogel was grafted to the sensor surface in order to serve as a binding matrix. It was modified with bio-recognition elements (BREs) via amine coupling chemistry and offered the advantage of large binding capacity, stimuli responsive properties and good biocompatibility. Through experimental observations supported by numerical simulations describing diffusion mass transfer and affinity binding of target molecules in the hydrogel, the hydrogel binding matrix thickness, concentration of BREs and the profile of the probing evanescent field was optimized. Hydrogel with a up to micrometer thickness was shown to support additional hydrogel optical waveguide (HOW) mode which was employed for probing affinity binding events in the gel by means of refractometric and fluorescence measurements. These schemes allow to reach limits of detection (LODs) at picomolar and femtomolar levels, respectively. Besides hydrogel based experiments for detection of molecular analytes, long range surface plasmon-enhanced fluorescence spectroscopy (LRSP-FS) was employed for detection of bacterial pathogens. The influence of capture efficiency of bacteria on surfaces and the profile of the probing field on sensor response were investigated. The potential of LRSP-FS with extended evanescent field is demonstrated for detection of pathogenic E. coli O157:H7 on sandwich immunoassays . LOD as low as 6 cfu mL-1 with a detection time of 40 minutes was achieved.rn

Diagnosis and Fault detection in Electrical Machines and Drives based on Advanced Signal Processing Techniques

In the present thesis, a new methodology of diagnosis based on advanced use of time-frequency technique analysis is presented. More precisely, a new fault index that allows tracking individual fault components in a single frequency band is defined. More in detail, a frequency sliding is applied to the signals being analyzed (currents, voltages, vibration signals), so that each single fault frequency component is shifted into a prefixed single frequency band. Then, the discrete Wavelet Transform is applied to the resulting signal to extract the fault signature in the frequency band that has been chosen. Once the state of the machine has been qualitatively diagnosed, a quantitative evaluation of the fault degree is necessary. For this purpose, a fault index based on the energy calculation of approximation and/or detail signals resulting from wavelet decomposition has been introduced to quantify the fault extend. The main advantages of the developed new method over existing Diagnosis techniques are the following: - Capability of monitoring the fault evolution continuously over time under any transient operating condition; - Speed/slip measurement or estimation is not required; - Higher accuracy in filtering frequency components around the fundamental in case of rotor faults; - Reduction in the likelihood of false indications by avoiding confusion with other fault harmonics (the contribution of the most relevant fault frequency components under speed-varying conditions are clamped in a single frequency band); - Low memory requirement due to low sampling frequency; - Reduction in the latency of time processing (no requirement of repeated sampling operation).

Advanced lithium battery chemistries for sustainable transportation

The specific energy of lithium-ion batteries (LIBs) is today 200 Wh/kg, a value not sufficient to power fully electric vehicles with a driving range of 400 km which requires a battery pack of 90 kWh. To deliver such energy the battery weight should be higher than 400 kg and the corresponding increase of vehicle mass would narrow the driving range to 280 km. Two main strategies are pursued to improve the energy of the rechargeable lithium batteries up to the transportation targets. The first is the increase of LIBs working voltage by using high-voltage cathode materials. The second is the increase of battery capacity by the development of a cell chemistry where oxygen redox reaction (ORR) occurs at the cathode and metal lithium is the anode (Li/O2 battery). This PhD work is focused on the development of high-voltage safe cathodes for LIBs, and on the investigation of the feasibility of Li/O2 battery operating with ionic liquid(IL)-based electrolytes. The use of LiMn1-xFexPO4 as high-voltage cathode material is discussed. Synthesis and electrochemical tests of three different phosphates, more safe cathode materials than transition metal oxides, are reported. The feasibility of Li/O2 battery operating in IL-based electrolytes is also discussed. Three aspects have been investigated: basic aspects of ORR, synthesis and characterization of porous carbons as positive electrode materials and study of limiting factors to the electrode capacity and cycle-life. Regarding LIBs, the findings on LiMnPO4 prepared by soluble precursors demonstrate that a good performing Mn-based olivine is viable without the coexistence of iron. Regarding Li/O2 battery, the oxygen diffusion coefficient and concentration values in different ILs were obtained. This work highlighted that the O2 mass transport limits the Li/O2 capacity at high currents; it gave indications on how to increase battery capacity by using a flow-cell and a porous carbon as cathode.

Advanced modelling of time domain electromagnetic data with updated hydrogeological interpretations

Several countries have acquired, over the past decades, large amounts of area covering Airborne Electromagnetic data. Contribution of airborne geophysics has dramatically increased for both groundwater resource mapping and management proving how those systems are appropriate for large-scale and efficient groundwater surveying. We start with processing and inversion of two AEM dataset from two different systems collected over the Spiritwood Valley Aquifer area, Manitoba, Canada respectively, the AeroTEM III (commissioned by the Geological Survey of Canada in 2010) and the “Full waveform VTEM” dataset, collected and tested over the same survey area, during the fall 2011. We demonstrate that in the presence of multiple datasets, either AEM and ground data, due processing, inversion, post-processing, data integration and data calibration is the proper approach capable of providing reliable and consistent resistivity models. Our approach can be of interest to many end users, ranging from Geological Surveys, Universities to Private Companies, which are often proprietary of large geophysical databases to be interpreted for geological and\or hydrogeological purposes. In this study we deeply investigate the role of integration of several complimentary types of geophysical data collected over the same survey area. We show that data integration can improve inversions, reduce ambiguity and deliver high resolution results. We further attempt to use the final, most reliable output resistivity models as a solid basis for building a knowledge-driven 3D geological voxel-based model. A voxel approach allows a quantitative understanding of the hydrogeological setting of the area, and it can be further used to estimate the aquifers volumes (i.e. potential amount of groundwater resources) as well as hydrogeological flow model prediction. In addition, we investigated the impact of an AEM dataset towards hydrogeological mapping and 3D hydrogeological modeling, comparing it to having only a ground based TEM dataset and\or to having only boreholes data.