Refined Estimation of Earthquake Source Parameters: Methods, Applications and Scaling Relationships

The objective of this work of thesis is the refined estimations of source parameters. To such a purpose we used two different approaches, one in the frequency domain and the other in the time domain. In frequency domain, we analyzed the P- and S-wave displacement spectra to estimate spectral parameters, that is corner frequencies and low frequency spectral amplitudes. We used a parametric modeling approach which is combined with a multi-step, non-linear inversion strategy and includes the correction for attenuation and site effects. The iterative multi-step procedure was applied to about 700 microearthquakes in the moment range 1011-1014 N•m and recorded at the dense, wide-dynamic range, seismic networks operating in Southern Apennines (Italy). The analysis of the source parameters is often complicated when we are not able to model the propagation accurately. In this case the empirical Green function approach is a very useful tool to study the seismic source properties. In fact the Empirical Green Functions (EGFs) consent to represent the contribution of propagation and site effects to signal without using approximate velocity models. An EGF is a recorded three-component set of time-histories of a small earthquake whose source mechanism and propagation path are similar to those of the master event. Thus, in time domain, the deconvolution method of Vallée (2004) was applied to calculate the source time functions (RSTFs) and to accurately estimate source size and rupture velocity. This technique was applied to 1) large event, that is Mw=6.3 2009 L’Aquila mainshock (Central Italy), 2) moderate events, that is cluster of earthquakes of 2009 L’Aquila sequence with moment magnitude ranging between 3 and 5.6, 3) small event, i.e. Mw=2.9 Laviano mainshock (Southern Italy).

Statistical Physics and Modeling of Human Mobility

In this thesis, we extend some ideas of statistical physics to describe the properties of human mobility. By using a database containing GPS measures of individual paths (position, velocity and covered space at a spatial scale of 2 Km or a time scale of 30 sec), which includes the 2% of the private vehicles in Italy, we succeed in determining some statistical empirical laws pointing out "universal" characteristics of human mobility. Developing simple stochastic models suggesting possible explanations of the empirical observations, we are able to indicate what are the key quantities and cognitive features that are ruling individuals' mobility. To understand the features of individual dynamics, we have studied different aspects of urban mobility from a physical point of view. We discuss the implications of the Benford's law emerging from the distribution of times elapsed between successive trips. We observe how the daily travel-time budget is related with many aspects of the urban environment, and describe how the daily mobility budget is then spent. We link the scaling properties of individual mobility networks to the inhomogeneous average durations of the activities that are performed, and those of the networks describing people's common use of space with the fractional dimension of the urban territory. We study entropy measures of individual mobility patterns, showing that they carry almost the same information of the related mobility networks, but are also influenced by a hierarchy among the activities performed. We discover that Wardrop's principles are violated as drivers have only incomplete information on traffic state and therefore rely on knowledge on the average travel-times. We propose an assimilation model to solve the intrinsic scattering of GPS data on the street network, permitting the real-time reconstruction of traffic state at a urban scale.

An architecture for scaling ontology networks

Constructing ontology networks typically occurs at design time at the hands of knowledge engineers who assemble their components statically. There are, however, use cases where ontology networks need to be assembled upon request and processed at runtime, without altering the stored ontologies and without tampering with one another. These are what we call "virtual [ontology] networks", and keeping track of how an ontology changes in each virtual network is called "multiplexing". Issues may arise from the connectivity of ontology networks. In many cases, simple flat import schemes will not work, because many ontology managers can cause property assertions to be erroneously interpreted as annotations and ignored by reasoners. Also, multiple virtual networks should optimize their cumulative memory footprint, and where they cannot, this should occur for very limited periods of time. We claim that these problems should be handled by the software that serves these ontology networks, rather than by ontology engineering methodologies. We propose a method that spreads multiple virtual networks across a 3-tier structure, and can reduce the amount of erroneously interpreted axioms, under certain raw statement distributions across the ontologies. We assumed OWL as the core language handled by semantic applications in the framework at hand, due to the greater availability of reasoners and rule engines. We also verified that, in common OWL ontology management software, OWL axiom interpretation occurs in the worst case scenario of pre-order visit. To measure the effectiveness and space-efficiency of our solution, a Java and RESTful implementation was produced within an Apache project. We verified that a 3-tier structure can accommodate reasonably complex ontology networks better, in terms of the expressivity OWL axiom interpretation, than flat-tree import schemes can. We measured both the memory overhead of the additional components we put on top of traditional ontology networks, and the framework's caching capabilities.

Analysis of charge-transport properties in GST materials for next generation phase-change memory devices

The quest for universal memory is driving the rapid development of memories with superior all-round capabilities in non-volatility, high speed, high endurance and low power. The memory subsystem accounts for a significant cost and power budget of a computer system. Current DRAM-based main memory systems are starting to hit the power and cost limit. To resolve this issue the industry is improving existing technologies such as Flash and exploring new ones. Among those new technologies is the Phase Change Memory (PCM), which overcomes some of the shortcomings of the Flash such as durability and scalability. This alternative non-volatile memory technology, which uses resistance contrast in phase-change materials, offers more density relative to DRAM, and can help to increase main memory capacity of future systems while remaining within the cost and power constraints. Chalcogenide materials can suitably be exploited for manufacturing phase-change memory devices. Charge transport in amorphous chalcogenide-GST used for memory devices is modeled using two contributions: hopping of trapped electrons and motion of band electrons in extended states. Crystalline GST exhibits an almost Ohmic I(V) curve. In contrast amorphous GST shows a high resistance at low biases while, above a threshold voltage, a transition takes place from a highly resistive to a conductive state, characterized by a negative differential-resistance behavior. A clear and complete understanding of the threshold behavior of the amorphous phase is fundamental for exploiting such materials in the fabrication of innovative nonvolatile memories. The type of feedback that produces the snapback phenomenon is described as a filamentation in energy that is controlled by electron–electron interactions between trapped electrons and band electrons. The model thus derived is implemented within a state-of-the-art simulator. An analytical version of the model is also derived and is useful for discussing the snapback behavior and the scaling properties of the device.

A universal delta model

This thesis presents a universal model of documents and deltas. This model formalize what it means to find differences between documents and to shows a single shared formalization that can be used by any algorithm to describe the differences found between any kind of comparable documents. The main scientific contribution of this thesis is a universal delta model that can be used to represent the changes found by an algorithm. The main part of this model are the formal definition of changes (the pieces of information that records that something has changed), operations (the definitions of the kind of change that happened) and deltas (coherent summaries of what has changed between two documents). The fundamental mechanism tha makes the universal delta model a very expressive tool is the use of encapsulation relations between changes. In the universal delta model, changes are not always simple records of what has changed, they can also be combined into more complex changes that reflects the detection of more meaningful modifications. In addition to the main entities (i.e., changes, operations and deltas), the model describes and defines also documents and the concept of equivalence between documents. As a corollary to the model, there is also an extensible catalog of possible operations that algorithms can detect, used to create a common library of operations, and an UML serialization of the model, useful as a reference when implementing APIs that deal with deltas. The universal delta model presented in this thesis acts as the formal groundwork upon which algorithm can be based and libraries can be implemented. It removes the need to recreate a new delta model and terminology whenever a new algorithm is devised. It also alleviates the problems that toolmakers have when adapting their software to new diff algorithms.

The Dynamics of Passive Torsional Fatigue Test Rigs: Innovative Applications of Universal Joints

The dynamics of a passive back-to-back test rig have been characterised, leading to a multi-coordinate approach for the analysis of arbitrary test configurations. Universal joints have been introduced into a typical pre-loaded back-to-back system in order to produce an oscillating torsional moment in a test specimen. Two different arrangements have been investigated using a frequency-based sub-structuring approach: the receptance method. A numerical model has been developed in accordance with this theory, allowing interconnection of systems with two-coordinates and closed multi-loop schemes. The model calculates the receptance functions and modal and deflected shapes of a general system. Closed form expressions of the following individual elements have been developed: a servomotor, damped continuous shaft and a universal joint. Numerical results for specific cases have been compared with published data in literature and experimental measurements undertaken in the present work. Due to the complexity of the universal joint and its oscillating dynamic effects, a more detailed analysis of this component has been developed. Two models have been presented. The first represents the joint as two inertias connected by a massless cross-piece. The second, derived by the dynamic analysis of a spherical four-link mechanism, considers the contribution of the floating element and its gyroscopic effects. An investigation into non-linear behaviour has led to a time domain model that utilises the Runge-Kutta fourth order method for resolution of the dynamic equations. It has been demonstrated that the torsional receptances of a universal joint, derived using the simple model, result in representation of the joint as an equivalent variable inertia. In order to verify the model, a test rig has been built and experimental validation undertaken. The variable inertia of a universal joint has lead to a novel application of the component as a passive device for the balancing of inertia variations in slider-crank mechanisms.

Integrated analysis and design of optimization and up-scaling of inductively coupled plasma synthesis of nanoparticles

This study is focused on radio-frequency inductively coupled thermal plasma (ICP) synthesis of nanoparticles, combining experimental and modelling approaches towards process optimization and industrial scale-up, in the framework of the FP7-NMP SIMBA European project (Scaling-up of ICP technology for continuous production of Metallic nanopowders for Battery Applications). First the state of the art of nanoparticle production through conventional and plasma routes is summarized, then results for the characterization of the plasma source and on the investigation of the nanoparticle synthesis phenomenon, aiming at highlighting fundamental process parameters while adopting a design oriented modelling approach, are presented. In particular, an energy balance of the torch and of the reaction chamber, employing a calorimetric method, is presented, while results for three- and two-dimensional modelling of an ICP system are compared with calorimetric and enthalpy probe measurements to validate the temperature field predicted by the model and used to characterize the ICP system under powder-free conditions. Moreover, results from the modeling of critical phases of ICP synthesis process, such as precursor evaporation, vapour conversion in nanoparticles and nanoparticle growth, are presented, with the aim of providing useful insights both for the design and optimization of the process and on the underlying physical phenomena. Indeed, precursor evaporation, one of the phases holding the highest impact on industrial feasibility of the process, is discussed; by employing models to describe particle trajectories and thermal histories, adapted from the ones originally developed for other plasma technologies or applications, such as DC non-transferred arc torches and powder spherodization, the evaporation of micro-sized Si solid precursor in a laboratory scale ICP system is investigated. Finally, a discussion on the role of thermo-fluid dynamic fields on nano-particle formation is presented, as well as a study on the effect of the reaction chamber geometry on produced nanoparticle characteristics and process yield.

Scaled down physical properties of semiconductor nanowires for nanoelectronics scaling up

Semiconductor nanowires (NWs) are one- or quasi one-dimensional systems whose physical properties are unique as compared to bulk materials because of their nanoscaled sizes. They bring together quantum world and semiconductor devices. NWs-based technologies may achieve an impact comparable to that of current microelectronic devices if new challenges will be faced. This thesis primarily focuses on two different, cutting-edge aspects of research over semiconductor NW arrays as pivotal components of NW-based devices. The first part deals with the characterization of electrically active defects in NWs. It has been elaborated the set-up of a general procedure which enables to employ Deep Level Transient Spectroscopy (DLTS) to probe NW arrays’ defects. This procedure has been applied to perform the characterization of a specific system, i.e. Reactive Ion Etched (RIE) silicon NW arrays-based Schottky barrier diodes. This study has allowed to shed light over how and if growth conditions introduce defects in RIE processed silicon NWs. The second part of this thesis concerns the bowing induced by electron beam and the subsequent clustering of gallium arsenide NWs. After a justified rejection of the mechanisms previously reported in literature, an original interpretation of the electron beam induced bending has been illustrated. Moreover, this thesis has successfully interpreted the formation of NW clusters in the framework of the lateral collapse of fibrillar structures. These latter are both idealized models and actual artificial structures used to study and to mimic the adhesion properties of natural surfaces in lizards and insects (Gecko effect). Our conclusion are that mechanical and surface properties of the NWs, together with the geometry of the NW arrays, play a key role in their post-growth alignment. The same parameters open, then, to the benign possibility of locally engineering NW arrays in micro- and macro-templates.

Oblique ionograms automatic scaling and eikonal based ray tracing

A method for automatic scaling of oblique ionograms has been introduced. This method also provides a rejection procedure for ionograms that are considered to lack sufficient information, depicting a very good success rate. Observing the Kp index of each autoscaled ionogram, can be noticed that the behavior of the autoscaling program does not depend on geomagnetic conditions. The comparison between the values of the MUF provided by the presented software and those obtained by an experienced operator indicate that the procedure developed for detecting the nose of oblique ionogram traces is sufficiently efficient and becomes much more efficient as the quality of the ionograms improves. These results demonstrate the program allows the real-time evaluation of MUF values associated with a particular radio link through an oblique radio sounding. The automatic recognition of a part of the trace allows determine for certain frequencies, the time taken by the radio wave to travel the path between the transmitter and receiver. The reconstruction of the ionogram traces, suggests the possibility of estimating the electron density between the transmitter and the receiver, from an oblique ionogram. The showed results have been obtained with a ray-tracing procedure based on the integration of the eikonal equation and using an analytical ionospheric model with free parameters. This indicates the possibility of applying an adaptive model and a ray-tracing algorithm to estimate the electron density in the ionosphere between the transmitter and the receiver An additional study has been conducted on a high quality ionospheric soundings data set and another algorithm has been designed for the conversion of an oblique ionogram into a vertical one, using Martyn's theorem. This allows a further analysis of oblique soundings, throw the use of the INGV Autoscala program for the automatic scaling of vertical ionograms.