Active Control of the Acoustic Field in a Vehicle Cabin

In this thesis, a thorough investigation on acoustic noise control systems for realistic automotive scenarios is presented. The thesis is organized in two parts dealing with the main topics treated: Active Noise Control (ANC) systems and Virtual Microphone Technique (VMT), respectively. The technology of ANC allows to increase the driver's/passenger's comfort and safety exploiting the principle of mitigating the disturbing acoustic noise by the superposition of a secondary sound wave of equal amplitude but opposite phase. Performance analyses of both FeedForwrd (FF) and FeedBack (FB) ANC systems, in experimental scenarios, are presented. Since, environmental vibration noises within a car cabin are time-varying, most of the ANC solutions are adaptive. However, in this work, an effective fixed FB ANC system is proposed. Various ANC schemes are considered and compared with each other. In order to find the best possible ANC configuration which optimizes the performance in terms of disturbing noise attenuation, a thorough research of \gls{KPI}, system parameters and experimental setups design, is carried out. In the second part of this thesis, VMT, based on the estimation of specific acoustic channels, is investigated with the aim of generating a quiet acoustic zone around a confined area, e.g., the driver's ears. Performance analysis and comparison of various estimation approaches is presented. Several measurement campaigns were performed in order to acquire a sufficient duration and number of microphone signals in a significant variety of driving scenarios and employed cars. To do this, different experimental setups were designed and their performance compared. Design guidelines are given to obtain good trade-off between accuracy performance and equipment costs. Finally, a preliminary analysis with an innovative approach based on Neural Networks (NNs) to improve the current state of the art in microphone virtualization is proposed.

Cooperative communication and distributed detection in wireless sensor networks

Recent progress in microelectronic and wireless communications have enabled the development of low cost, low power, multifunctional sensors, which has allowed the birth of new type of networks named wireless sensor networks (WSNs). The main features of such networks are: the nodes can be positioned randomly over a given field with a high density; each node operates both like sensor (for collection of environmental data) as well as transceiver (for transmission of information to the data retrieval); the nodes have limited energy resources. The use of wireless communications and the small size of nodes, make this type of networks suitable for a large number of applications. For example, sensor nodes can be used to monitor a high risk region, as near a volcano; in a hospital they could be used to monitor physical conditions of patients. For each of these possible application scenarios, it is necessary to guarantee a trade-off between energy consumptions and communication reliability. The thesis investigates the use of WSNs in two possible scenarios and for each of them suggests a solution that permits to solve relating problems considering the trade-off introduced. The first scenario considers a network with a high number of nodes deployed in a given geographical area without detailed planning that have to transmit data toward a coordinator node, named sink, that we assume to be located onboard an unmanned aerial vehicle (UAV). This is a practical example of reachback communication, characterized by the high density of nodes that have to transmit data reliably and efficiently towards a far receiver. It is considered that each node transmits a common shared message directly to the receiver onboard the UAV whenever it receives a broadcast message (triggered for example by the vehicle). We assume that the communication channels between the local nodes and the receiver are subject to fading and noise. The receiver onboard the UAV must be able to fuse the weak and noisy signals in a coherent way to receive the data reliably. It is proposed a cooperative diversity concept as an effective solution to the reachback problem. In particular, it is considered a spread spectrum (SS) transmission scheme in conjunction with a fusion center that can exploit cooperative diversity, without requiring stringent synchronization between nodes. The idea consists of simultaneous transmission of the common message among the nodes and a Rake reception at the fusion center. The proposed solution is mainly motivated by two goals: the necessity to have simple nodes (to this aim we move the computational complexity to the receiver onboard the UAV), and the importance to guarantee high levels of energy efficiency of the network, thus increasing the network lifetime. The proposed scheme is analyzed in order to better understand the effectiveness of the approach presented. The performance metrics considered are both the theoretical limit on the maximum amount of data that can be collected by the receiver, as well as the error probability with a given modulation scheme. Since we deal with a WSN, both of these performance are evaluated taking into consideration the energy efficiency of the network. The second scenario considers the use of a chain network for the detection of fires by using nodes that have a double function of sensors and routers. The first one is relative to the monitoring of a temperature parameter that allows to take a local binary decision of target (fire) absent/present. The second one considers that each node receives a decision made by the previous node of the chain, compares this with that deriving by the observation of the phenomenon, and transmits the final result to the next node. The chain ends at the sink node that transmits the received decision to the user. In this network the goals are to limit throughput in each sensor-to-sensor link and minimize probability of error at the last stage of the chain. This is a typical scenario of distributed detection. To obtain good performance it is necessary to define some fusion rules for each node to summarize local observations and decisions of the previous nodes, to get a final decision that it is transmitted to the next node. WSNs have been studied also under a practical point of view, describing both the main characteristics of IEEE802:15:4 standard and two commercial WSN platforms. By using a commercial WSN platform it is realized an agricultural application that has been tested in a six months on-field experimentation.

Characterization and modeling of low-frequency noise in MOSFETs

For many years, RF and analog integrated circuits have been mainly developed using bipolar and compound semiconductor technologies due to their better performance. In the last years, the advance made in CMOS technology allowed analog and RF circuits to be built with such a technology, but the use of CMOS technology in RF application instead of bipolar technology has brought more issues in terms of noise. The noise cannot be completely eliminated and will therefore ultimately limit the accuracy of measurements and set a lower limit on how small signals can be detected and processed in an electronic circuit. One kind of noise which affects MOS transistors much more than bipolar ones is the low-frequency noise. In MOSFETs, low-frequency noise is mainly of two kinds: flicker or 1/f noise and random telegraph signal noise (RTS). The objective of this thesis is to characterize and to model the low-frequency noise by studying RTS and flicker noise under both constant and switched bias conditions. The effect of different biasing schemes on both RTS and flicker noise in time and frequency domain has been investigated.

Mathematical models of cognitive processes

The research activity carried out during the PhD course was focused on the development of mathematical models of some cognitive processes and their validation by means of data present in literature, with a double aim: i) to achieve a better interpretation and explanation of the great amount of data obtained on these processes from different methodologies (electrophysiological recordings on animals, neuropsychological, psychophysical and neuroimaging studies in humans), ii) to exploit model predictions and results to guide future research and experiments. In particular, the research activity has been focused on two different projects: 1) the first one concerns the development of neural oscillators networks, in order to investigate the mechanisms of synchronization of the neural oscillatory activity during cognitive processes, such as object recognition, memory, language, attention; 2) the second one concerns the mathematical modelling of multisensory integration processes (e.g. visual-acoustic), which occur in several cortical and subcortical regions (in particular in a subcortical structure named Superior Colliculus (SC)), and which are fundamental for orienting motor and attentive responses to external world stimuli. This activity has been realized in collaboration with the Center for Studies and Researches in Cognitive Neuroscience of the University of Bologna (in Cesena) and the Department of Neurobiology and Anatomy of the Wake Forest University School of Medicine (NC, USA). PART 1. Objects representation in a number of cognitive functions, like perception and recognition, foresees distribute processes in different cortical areas. One of the main neurophysiological question concerns how the correlation between these disparate areas is realized, in order to succeed in grouping together the characteristics of the same object (binding problem) and in maintaining segregated the properties belonging to different objects simultaneously present (segmentation problem). Different theories have been proposed to address these questions (Barlow, 1972). One of the most influential theory is the so called “assembly coding”, postulated by Singer (2003), according to which 1) an object is well described by a few fundamental properties, processing in different and distributed cortical areas; 2) the recognition of the object would be realized by means of the simultaneously activation of the cortical areas representing its different features; 3) groups of properties belonging to different objects would be kept separated in the time domain. In Chapter 1.1 and in Chapter 1.2 we present two neural network models for object recognition, based on the “assembly coding” hypothesis. These models are networks of Wilson-Cowan oscillators which exploit: i) two high-level “Gestalt Rules” (the similarity and previous knowledge rules), to realize the functional link between elements of different cortical areas representing properties of the same object (binding problem); 2) the synchronization of the neural oscillatory activity in the γ-band (30-100Hz), to segregate in time the representations of different objects simultaneously present (segmentation problem). These models are able to recognize and reconstruct multiple simultaneous external objects, even in difficult case (some wrong or lacking features, shared features, superimposed noise). In Chapter 1.3 the previous models are extended to realize a semantic memory, in which sensory-motor representations of objects are linked with words. To this aim, the network, previously developed, devoted to the representation of objects as a collection of sensory-motor features, is reciprocally linked with a second network devoted to the representation of words (lexical network) Synapses linking the two networks are trained via a time-dependent Hebbian rule, during a training period in which individual objects are presented together with the corresponding words. Simulation results demonstrate that, during the retrieval phase, the network can deal with the simultaneous presence of objects (from sensory-motor inputs) and words (from linguistic inputs), can correctly associate objects with words and segment objects even in the presence of incomplete information. Moreover, the network can realize some semantic links among words representing objects with some shared features. These results support the idea that semantic memory can be described as an integrated process, whose content is retrieved by the co-activation of different multimodal regions. In perspective, extended versions of this model may be used to test conceptual theories, and to provide a quantitative assessment of existing data (for instance concerning patients with neural deficits). PART 2. The ability of the brain to integrate information from different sensory channels is fundamental to perception of the external world (Stein et al, 1993). It is well documented that a number of extraprimary areas have neurons capable of such a task; one of the best known of these is the superior colliculus (SC). This midbrain structure receives auditory, visual and somatosensory inputs from different subcortical and cortical areas, and is involved in the control of orientation to external events (Wallace et al, 1993). SC neurons respond to each of these sensory inputs separately, but is also capable of integrating them (Stein et al, 1993) so that the response to the combined multisensory stimuli is greater than that to the individual component stimuli (enhancement). This enhancement is proportionately greater if the modality-specific paired stimuli are weaker (the principle of inverse effectiveness). Several studies have shown that the capability of SC neurons to engage in multisensory integration requires inputs from cortex; primarily the anterior ectosylvian sulcus (AES), but also the rostral lateral suprasylvian sulcus (rLS). If these cortical inputs are deactivated the response of SC neurons to cross-modal stimulation is no different from that evoked by the most effective of its individual component stimuli (Jiang et al 2001). This phenomenon can be better understood through mathematical models. The use of mathematical models and neural networks can place the mass of data that has been accumulated about this phenomenon and its underlying circuitry into a coherent theoretical structure. In Chapter 2.1 a simple neural network model of this structure is presented; this model is able to reproduce a large number of SC behaviours like multisensory enhancement, multisensory and unisensory depression, inverse effectiveness. In Chapter 2.2 this model was improved by incorporating more neurophysiological knowledge about the neural circuitry underlying SC multisensory integration, in order to suggest possible physiological mechanisms through which it is effected. This endeavour was realized in collaboration with Professor B.E. Stein and Doctor B. Rowland during the 6 months-period spent at the Department of Neurobiology and Anatomy of the Wake Forest University School of Medicine (NC, USA), within the Marco Polo Project. The model includes four distinct unisensory areas that are devoted to a topological representation of external stimuli. Two of them represent subregions of the AES (i.e., FAES, an auditory area, and AEV, a visual area) and send descending inputs to the ipsilateral SC; the other two represent subcortical areas (one auditory and one visual) projecting ascending inputs to the same SC. Different competitive mechanisms, realized by means of population of interneurons, are used in the model to reproduce the different behaviour of SC neurons in conditions of cortical activation and deactivation. The model, with a single set of parameters, is able to mimic the behaviour of SC multisensory neurons in response to very different stimulus conditions (multisensory enhancement, inverse effectiveness, within- and cross-modal suppression of spatially disparate stimuli), with cortex functional and cortex deactivated, and with a particular type of membrane receptors (NMDA receptors) active or inhibited. All these results agree with the data reported in Jiang et al. (2001) and in Binns and Salt (1996). The model suggests that non-linearities in neural responses and synaptic (excitatory and inhibitory) connections can explain the fundamental aspects of multisensory integration, and provides a biologically plausible hypothesis about the underlying circuitry.

Partial discharge in power distribution electrical systems: pulse propagation models and detection optimization

Investigation on impulsive signals, originated from Partial Discharge (PD) phenomena, represents an effective tool for preventing electric failures in High Voltage (HV) and Medium Voltage (MV) systems. The determination of both sensors and instruments bandwidths is the key to achieve meaningful measurements, that is to say, obtaining the maximum Signal-To-Noise Ratio (SNR). The optimum bandwidth depends on the characteristics of the system under test, which can be often represented as a transmission line characterized by signal attenuation and dispersion phenomena. It is therefore necessary to develop both models and techniques which can characterize accurately the PD propagation mechanisms in each system and work out the frequency characteristics of the PD pulses at detection point, in order to design proper sensors able to carry out PD measurement on-line with maximum SNR. Analytical models will be devised in order to predict PD propagation in MV apparatuses. Furthermore, simulation tools will be used where complex geometries make analytical models to be unfeasible. In particular, PD propagation in MV cables, transformers and switchgears will be investigated, taking into account both irradiated and conducted signals associated to PD events, in order to design proper sensors.

Modulation Techniques for Multi-Phase Converters and Control Strategies for Multi-Phase Electric Drives

The ever-increasing spread of automation in industry puts the electrical engineer in a central role as a promoter of technological development in a sector such as the use of electricity, which is the basis of all the machinery and productive processes. Moreover the spread of drives for motor control and static converters with structures ever more complex, places the electrical engineer to face new challenges whose solution has as critical elements in the implementation of digital control techniques with the requirements of inexpensiveness and efficiency of the final product. The successfully application of solutions using non-conventional static converters awake an increasing interest in science and industry due to the promising opportunities. However, in the same time, new problems emerge whose solution is still under study and debate in the scientific community During the Ph.D. course several themes have been developed that, while obtaining the recent and growing interest of scientific community, have much space for the development of research activity and for industrial applications. The first area of research is related to the control of three phase induction motors with high dynamic performance and the sensorless control in the high speed range. The management of the operation of induction machine without position or speed sensors awakes interest in the industrial world due to the increased reliability and robustness of this solution combined with a lower cost of production and purchase of this technology compared to the others available in the market. During this dissertation control techniques will be proposed which are able to exploit the total dc link voltage and at the same time capable to exploit the maximum torque capability in whole speed range with good dynamic performance. The proposed solution preserves the simplicity of tuning of the regulators. Furthermore, in order to validate the effectiveness of presented solution, it is assessed in terms of performance and complexity and compared to two other algorithm presented in literature. The feasibility of the proposed algorithm is also tested on induction motor drive fed by a matrix converter. Another important research area is connected to the development of technology for vehicular applications. In this field the dynamic performances and the low power consumption is one of most important goals for an effective algorithm. Towards this direction, a control scheme for induction motor that integrates within a coherent solution some of the features that are commonly required to an electric vehicle drive is presented. The main features of the proposed control scheme are the capability to exploit the maximum torque in the whole speed range, a weak dependence on the motor parameters, a good robustness against the variations of the dc-link voltage and, whenever possible, the maximum efficiency. The second part of this dissertation is dedicated to the multi-phase systems. This technology, in fact, is characterized by a number of issues worthy of investigation that make it competitive with other technologies already on the market. Multiphase systems, allow to redistribute power at a higher number of phases, thus making possible the construction of electronic converters which otherwise would be very difficult to achieve due to the limits of present power electronics. Multiphase drives have an intrinsic reliability given by the possibility that a fault of a phase, caused by the possible failure of a component of the converter, can be solved without inefficiency of the machine or application of a pulsating torque. The control of the magnetic field spatial harmonics in the air-gap with order higher than one allows to reduce torque noise and to obtain high torque density motor and multi-motor applications. In one of the next chapters a control scheme able to increase the motor torque by adding a third harmonic component to the air-gap magnetic field will be presented. Above the base speed the control system reduces the motor flux in such a way to ensure the maximum torque capability. The presented analysis considers the drive constrains and shows how these limits modify the motor performance. The multi-motor applications are described by a well-defined number of multiphase machines, having series connected stator windings, with an opportune permutation of the phases these machines can be independently controlled with a single multi-phase inverter. In this dissertation this solution will be presented and an electric drive consisting of two five-phase PM tubular actuators fed by a single five-phase inverter will be presented. Finally the modulation strategies for a multi-phase inverter will be illustrated. The problem of the space vector modulation of multiphase inverters with an odd number of phases is solved in different way. An algorithmic approach and a look-up table solution will be proposed. The inverter output voltage capability will be investigated, showing that the proposed modulation strategy is able to fully exploit the dc input voltage either in sinusoidal or non-sinusoidal operating conditions. All this aspects are considered in the next chapters. In particular, Chapter 1 summarizes the mathematical model of induction motor. The Chapter 2 is a brief state of art on three-phase inverter. Chapter 3 proposes a stator flux vector control for a three- phase induction machine and compares this solution with two other algorithms presented in literature. Furthermore, in the same chapter, a complete electric drive based on matrix converter is presented. In Chapter 4 a control strategy suitable for electric vehicles is illustrated. Chapter 5 describes the mathematical model of multi-phase induction machines whereas chapter 6 analyzes the multi-phase inverter and its modulation strategies. Chapter 7 discusses the minimization of the power losses in IGBT multi-phase inverters with carrier-based pulse width modulation. In Chapter 8 an extended stator flux vector control for a seven-phase induction motor is presented. Chapter 9 concerns the high torque density applications and in Chapter 10 different fault tolerant control strategies are analyzed. Finally, the last chapter presents a positioning multi-motor drive consisting of two PM tubular five-phase actuators fed by a single five-phase inverter.

Structure of the Southern Tyrrhenian subduction system: insights from seismological analysis of anisotropy and attenuation

The Southern Tyrrhenian subduction system shows a complex interaction among asthenospheric flow, subducting slab and overriding plate. To shed light on the deformations and mechanical properties of the slab and surrounding mantle, I investigated seismic anisotropy and attenuation properties through the subduction region. I used both teleseisms and slab earthquakes, analyzing shear-wave splitting on SKS and S phases, respectively. The fast polarization directions φ, and the delay time, δt, were retrieved using the method of Silver and Chan [1991. SKS and S φ reveal a complex anisotropy pattern across the subduction zone. SKS-rays sample primarily the sub-slab region showing rotation of fast directions following the curved shape of the slab and very strong anisotropy. S-rays sample mainly the slab, showing variable φ and a smaller δt. SKS and S splitting reveals a well developed toroidal flow at SW edge of the slab, while at its NE edge the pattern is not very clear. This suggests that the anisotropy is controlled by the slab rollback, responsible for about 100 km slab parallel φ in the sub-slab mantle. The slab is weakly anisotropic, suggesting the asthenosphere as main source of anisotropy. To investigate the physical properties of the slab and surrounding regions, I analyzed the seismic P and S wave attenuation. By inverting high-quality S-waves t* from slab earthquakes, 3D attenuation models down to 300 km were obtained. Attenuation results image the slab as low-attenuation body, but with heterogeneous QS and QP structure showing spot of high attenuation , between 100-200 km depth, which could be due dehydration associated to the slab metamorphism. A low QS anomaly is present in the mantle wedge beneath the Aeolian volcanic arc and could indicate mantle melting and slab dehydration.

Imaging of crustal scatterers using multiple seismic arrays

Array seismology is an useful tool to perform a detailed investigation of the Earth’s interior. Seismic arrays by using the coherence properties of the wavefield are able to extract directivity information and to increase the ratio of the coherent signal amplitude relative to the amplitude of incoherent noise. The Double Beam Method (DBM), developed by Krüger et al. (1993, 1996), is one of the possible applications to perform a refined seismic investigation of the crust and mantle by using seismic arrays. The DBM is based on a combination of source and receiver arrays leading to a further improvement of the signal-to-noise ratio by reducing the error in the location of coherent phases. Previous DBM works have been performed for mantle and core/mantle resolution (Krüger et al., 1993; Scherbaum et al., 1997; Krüger et al., 2001). An implementation of the DBM has been presented at 2D large-scale (Italian data-set for Mw=9.3, Sumatra earthquake) and at 3D crustal-scale as proposed by Rietbrock & Scherbaum (1999), by applying the revised version of Source Scanning Algorithm (SSA; Kao & Shan, 2004). In the 2D application, the rupture front propagation in time has been computed. In 3D application, the study area (20x20x33 km3), the data-set and the source-receiver configurations are related to the KTB-1994 seismic experiment (Jost et al., 1998). We used 60 short-period seismic stations (200-Hz sampling rate, 1-Hz sensors) arranged in 9 small arrays deployed in 2 concentric rings about 1 km (A-arrays) and 5 km (B-array) radius. The coherence values of the scattering points have been computed in the crustal volume, for a finite time-window along all array stations given the hypothesized origin time and source location. The resulting images can be seen as a (relative) joint log-likelihood of any point in the subsurface that have contributed to the full set of observed seismograms.

Attenuation of Eph Receptor Kinase Activation in Cancer Cells by Coexpressed Ephrin Ligands

The Eph receptor tyrosine kinases mediate juxtacrine signals by interacting “in trans” with ligands anchored to the surface of neighboring cells via a GPI-anchor (ephrin-As) or a transmembrane segment (ephrin-Bs), which leads to receptor clustering and increased kinase activity. Additionally, soluble forms of the ephrin-A ligands released from the cell surface by matrix metalloproteases can also activate EphA receptor signaling. Besides these trans interactions, recent studies have revealed that Eph receptors and ephrins coexpressed in neurons can also engage in lateral “cis” associations that attenuate receptor activation by ephrins in trans with critical functional consequences. Despite the importance of the Eph/ephrin system in tumorigenesis, Eph receptor-ephrin cis interactions have not been previously investigated in cancer cells. Here we show that in cancer cells, coexpressed ephrin-A3 can inhibit the ability of EphA2 and EphA3 to bind ephrins in trans and become activated, while ephrin-B2 can inhibit not only EphB4 but also EphA3. The cis-inhibition of EphA3 by ephrin-B2 implies that in some cases ephrins that cannot activate a particular Eph receptor in trans can nevertheless inhibit its signaling ability through cis association. We also found that an EphA3 mutation identified in lung cancer enhances cis interaction with ephrin-A3. These results suggest a novel mechanism that may contribute to cancer pathogenesis by attenuating the tumor suppressing effects of Eph receptor signaling pathways activated by ephrins in trans (Falivelli et al. 2013).

An Integrated Transmission-Media Noise Calibration Software For Deep-Space Radio Science Experiments

The thesis describes the implementation of a calibration, format-translation and data conditioning software for radiometric tracking data of deep-space spacecraft. All of the available propagation-media noise rejection techniques available as features in the code are covered in their mathematical formulations, performance and software implementations. Some techniques are retrieved from literature and current state of the art, while other algorithms have been conceived ex novo. All of the three typical deep-space refractive environments (solar plasma, ionosphere, troposphere) are dealt with by employing specific subroutines. Specific attention has been reserved to the GNSS-based tropospheric path delay calibration subroutine, since it is the most bulky module of the software suite, in terms of both the sheer number of lines of code, and development time. The software is currently in its final stage of development and once completed will serve as a pre-processing stage for orbit determination codes. Calibration of transmission-media noise sources in radiometric observables proved to be an essential operation to be performed of radiometric data in order to meet the more and more demanding error budget requirements of modern deep-space missions. A completely autonomous and all-around propagation-media calibration software is a novelty in orbit determination, although standalone codes are currently employed by ESA and NASA. The described S/W is planned to be compatible with the current standards for tropospheric noise calibration used by both these agencies like the AMC, TSAC and ESA IFMS weather data, and it natively works with the Tracking Data Message file format (TDM) adopted by CCSDS as standard aimed to promote and simplify inter-agency collaboration.

Context-sensitive design in transportation infrastructure: relating tire/pavement noise with wearing course characteristics

A design can be defined as context-sensitive when it achieves effective technical and functional transportation solutions, while preserving and enhancing natural environments and minimizing impacts on local communities. Traffic noise is one of the most critical environmental impacts of transportation infrastructure and it affects both humans and ecosystems. Tire/pavement noise is caused by a set of interactions at the contact patch and it is the predominant source of road noise at the regular traffic speeds. Wearing course characteristics affect tire/pavement noise through various mechanisms. Furthermore, acoustic performance of road pavements varies over time and it is influenced by both aging and temperature. Three experimentations have been carried out to evaluate wearing course characteristics effects on tire/pavement noise. The first study involves the evaluation of skid resistance, surface texture and tire/pavement noise of an innovative application of multipurpose cold-laid microsurfacing. The second one involves the evaluation of the surface and acoustic characteristics of the different pavement sections of the test track of the Centre for Pavement and Transportation Technology (CPATT) at the University of Waterloo. In the third study, a set of highway sections have been selected in Southern Ontario with various types of pavements. Noise measurements were carried out by means of the Statistical Pass-by (SPB) method in the first case study, whereas in the second and in the third one, Close-proximity (CPX) and the On-Board Sound Intensity (OBSI) methods have been performed in parallel. Test results have contributed to understand the effects of pavement materials, temperature and aging on tire/pavement noise. Negligible correlation was found between surface texture and roughness with noise. As a general trend, aged and stiffer materials have shown to provide higher noise levels than newer and less stiff ones. Noise levels were also observed to be higher with temperature increase.

Towards the 3D attenuation imaging of active volcanoes: methods and tests on real and simulated data

The purpose of my PhD thesis has been to face the issue of retrieving a three dimensional attenuation model in volcanic areas. To this purpose, I first elaborated a robust strategy for the analysis of seismic data. This was done by performing several synthetic tests to assess the applicability of spectral ratio method to our purposes. The results of the tests allowed us to conclude that: 1) spectral ratio method gives reliable differential attenuation (dt*) measurements in smooth velocity models; 2) short signal time window has to be chosen to perform spectral analysis; 3) the frequency range over which to compute spectral ratios greatly affects dt* measurements. Furthermore, a refined approach for the application of spectral ratio method has been developed and tested. Through this procedure, the effects caused by heterogeneities of propagation medium on the seismic signals may be removed. The tested data analysis technique was applied to the real active seismic SERAPIS database. It provided a dataset of dt* measurements which was used to obtain a three dimensional attenuation model of the shallowest part of Campi Flegrei caldera. Then, a linearized, iterative, damped attenuation tomography technique has been tested and applied to the selected dataset. The tomography, with a resolution of 0.5 km in the horizontal directions and 0.25 km in the vertical direction, allowed to image important features in the off-shore part of Campi Flegrei caldera. High QP bodies are immersed in a high attenuation body (Qp=30). The latter is well correlated with low Vp and high Vp/Vs values and it is interpreted as a saturated marine and volcanic sediments layer. High Qp anomalies, instead, are interpreted as the effects either of cooled lava bodies or of a CO2 reservoir. A pseudo-circular high Qp anomaly was detected and interpreted as the buried rim of NYT caldera.