Studio di fenomeni d'instabilità gravitativa sui fondali marini, con particolare riferimento all'isola di Stromboli

In the last decade the interest for submarine instability grew up, driven by the increasing exploitation of natural resources (primary hydrocarbons), the emplacement of bottom-lying structures (cables and pipelines) and by the development of coastal areas, whose infrastructures increasingly protrude to the sea. The great interest for this topic promoted a number of international projects such as: STEAM (Sediment Transport on European Atlantic Margins, 93-96), ENAM II (European North Atlantic Margin, 96-99), GITEC (Genesis and Impact of Tsunamis on the European Coast 92-95), STRATAFORM (STRATA FORmation on Margins, 95-01), Seabed Slope Process in Deep Water Continental Margin (Northwest Gulf of Mexico, 96-04), COSTA (Continental slope Stability, 00-05), EUROMARGINS (Slope Stability on Europe’s Passive Continental Margin), SPACOMA (04-07), EUROSTRATAFORM (European Margin Strata Formation), NGI's internal project SIP-8 (Offshore Geohazards), IGCP-511: Submarine Mass Movements and Their Consequences (05-09) and projects indirectly related to instability processes, such as TRANSFER (Tsunami Risk ANd Strategies For the European region, 06-09) or NEAREST (integrated observations from NEAR shore sourcES of Tsunamis: towards an early warning system, 06-09). In Italy, apart from a national project realized within the activities of the National Group of Volcanology during the framework 2000-2003 “Conoscenza delle parti sommerse dei vulcani italiani e valutazione del potenziale rischio vulcanico”, the study of submarine mass-movement has been underestimated until the occurrence of the landslide-tsunami events that affected Stromboli on December 30, 2002. This event made the Italian Institutions and the scientific community more aware of the hazard related to submarine landslides, mainly in light of the growing anthropization of coastal sectors, that increases the vulnerability of these areas to the consequences of such processes. In this regard, two important national projects have been recently funded in order to study coastal instabilities (PRIN 24, 06-08) and to map the main submarine hazard features on continental shelves and upper slopes around the most part of Italian coast (MaGIC Project). The study realized in this Thesis is addressed to the understanding of these processes, with particular reference to Stromboli submerged flanks. These latter represent a natural laboratory in this regard, as several kind of instability phenomena are present on the submerged flanks, affecting about 90% of the entire submerged areal and often (strongly) influencing the morphological evolution of subaerial slopes, as witnessed by the event occurred on 30 December 2002. Furthermore, each phenomenon is characterized by different pre-failure, failure and post-failure mechanisms, ranging from rock-falls, to turbidity currents up to catastrophic sector collapses. The Thesis is divided into three introductive chapters, regarding a brief review of submarine instability phenomena and related hazard (cap. 1), a “bird’s-eye” view on methodologies and available dataset (cap. 2) and a short introduction on the evolution and the morpho-structural setting of the Stromboli edifice (cap. 3). This latter seems to play a major role in the development of largescale sector collapses at Stromboli, as they occurred perpendicular to the orientation of the main volcanic rift axis (oriented in NE-SW direction). The characterization of these events and their relationships with successive erosive-depositional processes represents the main focus of cap.4 (Offshore evidence of large-scale lateral collapses on the eastern flank of Stromboli, Italy, due to structurally-controlled, bilateral flank instability) and cap. 5 (Lateral collapses and active sedimentary processes on the North-western flank of Stromboli Volcano), represented by articles accepted for publication on international papers (Marine Geology). Moreover, these studies highlight the hazard related to these catastrophic events; several calamities (with more than 40000 casualties only in the last two century) have been, in fact, the direct or indirect result of landslides affecting volcanic flanks, as observed at Oshima-Oshima (1741) and Unzen Volcano (1792) in Japan (Satake&Kato, 2001; Brantley&Scott, 1993), Krakatau (1883) in Indonesia (Self&Rampino, 1981), Ritter Island (1888), Sissano in Papua New Guinea (Ward& Day, 2003; Johnson, 1987; Tappin et al., 2001) and Mt St. Augustine (1883) in Alaska (Beget& Kienle, 1992). Flank landslide are also recognized as the most important and efficient mass-wasting process on volcanoes, contributing to the development of the edifices by widening their base and to the growth of a volcaniclastic apron at the foot of a volcano; a number of small and medium-scale erosive processes are also responsible for the carving of Stromboli submarine flanks and the transport of debris towards the deeper areas. The characterization of features associated to these processes is the main focus of cap. 6; it is also important to highlight that some small-scale events are able to create damage to coastal areas, as also witnessed by recent events of Gioia Tauro 1978, Nizza, 1979 and Stromboli 2002. The hazard potential related to these phenomena is, in fact, very high, as they commonly occur at higher frequency with respect to large-scale collapses, therefore being more significant in terms of human timescales. In the last chapter (cap. 7), a brief review and discussion of instability processes identified on Stromboli submerged flanks is presented; they are also compared with respect to analogous processes recognized in other submerged areas in order to shed lights on the main factors involved in their development. Finally, some applications of multibeam data to assess the hazard related to these phenomena are also discussed.

Architectures and design patterns for functional design of logic control and diagnostics in industrial automation

Recently in most of the industrial automation process an ever increasing degree of automation has been observed. This increasing is motivated by the higher requirement of systems with great performance in terms of quality of products/services generated, productivity, efficiency and low costs in the design, realization and maintenance. This trend in the growth of complex automation systems is rapidly spreading over automated manufacturing systems (AMS), where the integration of the mechanical and electronic technology, typical of the Mechatronics, is merging with other technologies such as Informatics and the communication networks. An AMS is a very complex system that can be thought constituted by a set of flexible working stations, one or more transportation systems. To understand how this machine are important in our society let considerate that every day most of us use bottles of water or soda, buy product in box like food or cigarets and so on. Another important consideration from its complexity derive from the fact that the the consortium of machine producers has estimated around 350 types of manufacturing machine. A large number of manufacturing machine industry are presented in Italy and notably packaging machine industry,in particular a great concentration of this kind of industry is located in Bologna area; for this reason the Bologna area is called “packaging valley”. Usually, the various parts of the AMS interact among them in a concurrent and asynchronous way, and coordinate the parts of the machine to obtain a desiderated overall behaviour is an hard task. Often, this is the case in large scale systems, organized in a modular and distributed manner. Even if the success of a modern AMS from a functional and behavioural point of view is still to attribute to the design choices operated in the definition of the mechanical structure and electrical electronic architecture, the system that governs the control of the plant is becoming crucial, because of the large number of duties associated to it. Apart from the activity inherent to the automation of themachine cycles, the supervisory system is called to perform other main functions such as: emulating the behaviour of traditional mechanical members thus allowing a drastic constructive simplification of the machine and a crucial functional flexibility; dynamically adapting the control strategies according to the different productive needs and to the different operational scenarios; obtaining a high quality of the final product through the verification of the correctness of the processing; addressing the operator devoted to themachine to promptly and carefully take the actions devoted to establish or restore the optimal operating conditions; managing in real time information on diagnostics, as a support of the maintenance operations of the machine. The kind of facilities that designers can directly find on themarket, in terms of software component libraries provides in fact an adequate support as regard the implementation of either top-level or bottom-level functionalities, typically pertaining to the domains of user-friendly HMIs, closed-loop regulation and motion control, fieldbus-based interconnection of remote smart devices. What is still lacking is a reference framework comprising a comprehensive set of highly reusable logic control components that, focussing on the cross-cutting functionalities characterizing the automation domain, may help the designers in the process of modelling and structuring their applications according to the specific needs. Historically, the design and verification process for complex automated industrial systems is performed in empirical way, without a clear distinction between functional and technological-implementation concepts and without a systematic method to organically deal with the complete system. Traditionally, in the field of analog and digital control design and verification through formal and simulation tools have been adopted since a long time ago, at least for multivariable and/or nonlinear controllers for complex time-driven dynamics as in the fields of vehicles, aircrafts, robots, electric drives and complex power electronics equipments. Moving to the field of logic control, typical for industrial manufacturing automation, the design and verification process is approached in a completely different way, usually very “unstructured”. No clear distinction between functions and implementations, between functional architectures and technological architectures and platforms is considered. Probably this difference is due to the different “dynamical framework”of logic control with respect to analog/digital control. As a matter of facts, in logic control discrete-events dynamics replace time-driven dynamics; hence most of the formal and mathematical tools of analog/digital control cannot be directly migrated to logic control to enlighten the distinction between functions and implementations. In addition, in the common view of application technicians, logic control design is strictly connected to the adopted implementation technology (relays in the past, software nowadays), leading again to a deep confusion among functional view and technological view. In Industrial automation software engineering, concepts as modularity, encapsulation, composability and reusability are strongly emphasized and profitably realized in the so-calledobject-oriented methodologies. Industrial automation is receiving lately this approach, as testified by some IEC standards IEC 611313, IEC 61499 which have been considered in commercial products only recently. On the other hand, in the scientific and technical literature many contributions have been already proposed to establish a suitable modelling framework for industrial automation. During last years it was possible to note a considerable growth in the exploitation of innovative concepts and technologies from ICT world in industrial automation systems. For what concerns the logic control design, Model Based Design (MBD) is being imported in industrial automation from software engineering field. Another key-point in industrial automated systems is the growth of requirements in terms of availability, reliability and safety for technological systems. In other words, the control system should not only deal with the nominal behaviour, but should also deal with other important duties, such as diagnosis and faults isolations, recovery and safety management. Indeed, together with high performance, in complex systems fault occurrences increase. This is a consequence of the fact that, as it typically occurs in reliable mechatronic systems, in complex systems such as AMS, together with reliable mechanical elements, an increasing number of electronic devices are also present, that are more vulnerable by their own nature. The diagnosis problem and the faults isolation in a generic dynamical system consists in the design of an elaboration unit that, appropriately processing the inputs and outputs of the dynamical system, is also capable of detecting incipient faults on the plant devices, reconfiguring the control system so as to guarantee satisfactory performance. The designer should be able to formally verify the product, certifying that, in its final implementation, it will perform itsrequired function guarantying the desired level of reliability and safety; the next step is that of preventing faults and eventually reconfiguring the control system so that faults are tolerated. On this topic an important improvement to formal verification of logic control, fault diagnosis and fault tolerant control results derive from Discrete Event Systems theory. The aimof this work is to define a design pattern and a control architecture to help the designer of control logic in industrial automated systems. The work starts with a brief discussion on main characteristics and description of industrial automated systems on Chapter 1. In Chapter 2 a survey on the state of the software engineering paradigm applied to industrial automation is discussed. Chapter 3 presentes a architecture for industrial automated systems based on the new concept of Generalized Actuator showing its benefits, while in Chapter 4 this architecture is refined using a novel entity, the Generalized Device in order to have a better reusability and modularity of the control logic. In Chapter 5 a new approach will be present based on Discrete Event Systems for the problemof software formal verification and an active fault tolerant control architecture using online diagnostic. Finally conclusive remarks and some ideas on new directions to explore are given. In Appendix A are briefly reported some concepts and results about Discrete Event Systems which should help the reader in understanding some crucial points in chapter 5; while in Appendix B an overview on the experimental testbed of the Laboratory of Automation of University of Bologna, is reported to validated the approach presented in chapter 3, chapter 4 and chapter 5. In Appendix C some components model used in chapter 5 for formal verification are reported.

Monitoring Complex Processes to Verify System Conformance: A Declarative Rule-Based Framework

Over the last 60 years, computers and software have favoured incredible advancements in every field. Nowadays, however, these systems are so complicated that it is difficult – if not challenging – to understand whether they meet some requirement or are able to show some desired behaviour or property. This dissertation introduces a Just-In-Time (JIT) a posteriori approach to perform the conformance check to identify any deviation from the desired behaviour as soon as possible, and possibly apply some corrections. The declarative framework that implements our approach – entirely developed on the promising open source forward-chaining Production Rule System (PRS) named Drools – consists of three components: 1. a monitoring module based on a novel, efficient implementation of Event Calculus (EC), 2. a general purpose hybrid reasoning module (the first of its genre) merging temporal, semantic, fuzzy and rule-based reasoning, 3. a logic formalism based on the concept of expectations introducing Event-Condition-Expectation rules (ECE-rules) to assess the global conformance of a system. The framework is also accompanied by an optional module that provides Probabilistic Inductive Logic Programming (PILP). By shifting the conformance check from after execution to just in time, this approach combines the advantages of many a posteriori and a priori methods proposed in literature. Quite remarkably, if the corrective actions are explicitly given, the reactive nature of this methodology allows to reconcile any deviations from the desired behaviour as soon as it is detected. In conclusion, the proposed methodology brings some advancements to solve the problem of the conformance checking, helping to fill the gap between humans and the increasingly complex technology.

Discrete Event Systems based Design Patterns for Diagnosability Analysis of Automated Manufacturing Systems

The main goal of this thesis is to facilitate the process of industrial automated systems development applying formal methods to ensure the reliability of systems. A new formulation of distributed diagnosability problem in terms of Discrete Event Systems theory and automata framework is presented, which is then used to enforce the desired property of the system, rather then just verifying it. This approach tackles the state explosion problem with modeling patterns and new algorithms, aimed for verification of diagnosability property in the context of the distributed diagnosability problem. The concepts are validated with a newly developed software tool.

Cascading events triggering industrial accidents: quantitative assessment of NaTech and domino scenarios

The so called cascading events, which lead to high-impact low-frequency scenarios are rising concern worldwide. A chain of events result in a major industrial accident with dreadful (and often unpredicted) consequences. Cascading events can be the result of the realization of an external threat, like a terrorist attack a natural disaster or of “domino effect”. During domino events the escalation of a primary accident is driven by the propagation of the primary event to nearby units, causing an overall increment of the accident severity and an increment of the risk associated to an industrial installation. Also natural disasters, like intense flooding, hurricanes, earthquake and lightning are found capable to enhance the risk of an industrial area, triggering loss of containment of hazardous materials and in major accidents. The scientific community usually refers to those accidents as “NaTechs”: natural events triggering industrial accidents. In this document, a state of the art of available approaches to the modelling, assessment, prevention and management of domino and NaTech events is described. On the other hand, the relevant work carried out during past studies still needs to be consolidated and completed, in order to be applicable in a real industrial framework. New methodologies, developed during my research activity, aimed at the quantitative assessment of domino and NaTech accidents are presented. The tools and methods provided within this very study had the aim to assist the progress toward a consolidated and universal methodology for the assessment and prevention of cascading events, contributing to enhance safety and sustainability of the chemical and process industry.

Dynamics of coastal aquifers: data-driven forecasting and risk analysis

This work is focused on the study of saltwater intrusion in coastal aquifers, and in particular on the realization of conceptual schemes to evaluate the risk associated with it. Saltwater intrusion depends on different natural and anthropic factors, both presenting a strong aleatory behaviour, that should be considered for an optimal management of the territory and water resources. Given the uncertainty of problem parameters, the risk associated with salinization needs to be cast in a probabilistic framework. On the basis of a widely adopted sharp interface formulation, key hydrogeological problem parameters are modeled as random variables, and global sensitivity analysis is used to determine their influence on the position of saltwater interface. The analyses presented in this work rely on an efficient model reduction technique, based on Polynomial Chaos Expansion, able to combine the best description of the model without great computational burden. When the assumptions of classical analytical models are not respected, and this occurs several times in the applications to real cases of study, as in the area analyzed in the present work, one can adopt data-driven techniques, based on the analysis of the data characterizing the system under study. It follows that a model can be defined on the basis of connections between the system state variables, with only a limited number of assumptions about the "physical" behaviour of the system.

Statistical Analysis and Modelling Aspects of Thermally Driven Turbulence

The present work aims to provide a deeper understanding of thermally driven turbulence and to address some modelling aspects related to the physics of the flow. For this purpose, two idealized systems are investigated by Direct Numerical Simulation: the rotating and non-rotating Rayleigh-Bénard convection. The preliminary study of the flow topologies shows how the coherent structures organise into different patterns depending on the rotation rate. From a statistical perspective, the analysis of the turbulent kinetic energy and temperature variance budgets allows to identify the flow regions where the production, the transport, and the dissipation of turbulent fluctuations occur. To provide a multi-scale description of the flows, a theoretical framework based on the Kolmogorov and Yaglom equations is applied for the first time to the Rayleigh-Bénard convection. The analysis shows how the spatial inhomogeneity modulates the dynamics at different scales and wall-distances. Inside the core of the flow, the space of scales can be divided into an inhomogeneity-dominated range at large scales, an inertial-like range at intermediate scales and a dissipative range at small scales. This classic scenario breaks close to the walls, where the inhomogeneous mechanisms and the viscous/diffusive processes are important at every scale and entail more complex dynamics. The same theoretical framework is extended to the filtered velocity and temperature fields of non-rotating Rayleigh-Bénard convection. The analysis of the filtered Kolmogorov and Yaglom equations reveals the influence of the residual scales on the filtered dynamics both in physical and scale space, highlighting the effect of the relative position between the filter length and the crossover that separates the inhomogeneity-dominated range from the quasi-homogeneous range. The assessment of the filtered and residual physics results to be instrumental for the correct use of the existing Large-Eddy Simulation models and for the development of new ones.

Assessment of sea-level variability for the Emilia-Romagna coastal area in the framework of the Mediterranean Sea

Sea–level change is one of the ocean characteristics closely connected to climate change. Understanding its variation is essential since a large portion of the world’s population is located in low–lying locations. Two main techniques are employed to measure sea level: satellite altimetry and tide gauges. Satellite altimetry monitors sea–level relative to a geocentric reference, is unaffected by crustal processes and covers nearly the entire surface of the oceans since 1993. Conversely, tide gauges measure sea level at specific coastal locations and relative to a local ground benchmark, therefore are impacted by vertical land movements. In this study, the linear and non–linear geocentric and relative sea–level trends along the Emilia–Romagna coast (Northern Italy) have been analyzed over different periods. In order to assess the local sea–level variability, data from satellite altimetry and tide gauges have been compared over a common time interval (1993–2019), hence disentangling the contribute of vertical land movements. Non–linearity has been also evaluated at the broader scale of the Mediterranean Sea, in order to depict the main variability in geocentric sea–level trends from regional to sub–basin scale. Furthermore, the anthropogenic and natural influence at the river basin scale has been addressed, in order to shed light on the factors inducing the drastic reduction of riverine sediment supply to the Emilia–Romagna coast over the period 1920–2020. The findings of this analysis indicate that the sediment delivery reduction to the coast by rivers has been driven by several anthropogenic processes, acting on various spatiotemporal scales. Moreover, the local absolute sea–level trend is far from linear and appear "contaminated" by the presence of natural oscillations that act at the multi–decadal, quasi–decadal and inter–annual scale, mainly driven by both large–scale climatic modes and variations in local oceanography.

Data driven regularization models of non-linear ill-posed inverse problems in imaging

Imaging technologies are widely used in application fields such as natural sciences, engineering, medicine, and life sciences. A broad class of imaging problems reduces to solve ill-posed inverse problems (IPs). Traditional strategies to solve these ill-posed IPs rely on variational regularization methods, which are based on minimization of suitable energies, and make use of knowledge about the image formation model (forward operator) and prior knowledge on the solution, but lack in incorporating knowledge directly from data. On the other hand, the more recent learned approaches can easily learn the intricate statistics of images depending on a large set of data, but do not have a systematic method for incorporating prior knowledge about the image formation model. The main purpose of this thesis is to discuss data-driven image reconstruction methods which combine the benefits of these two different reconstruction strategies for the solution of highly nonlinear ill-posed inverse problems. Mathematical formulation and numerical approaches for image IPs, including linear as well as strongly nonlinear problems are described. More specifically we address the Electrical impedance Tomography (EIT) reconstruction problem by unrolling the regularized Gauss-Newton method and integrating the regularization learned by a data-adaptive neural network. Furthermore we investigate the solution of non-linear ill-posed IPs introducing a deep-PnP framework that integrates the graph convolutional denoiser into the proximal Gauss-Newton method with a practical application to the EIT, a recently introduced promising imaging technique. Efficient algorithms are then applied to the solution of the limited electrods problem in EIT, combining compressive sensing techniques and deep learning strategies. Finally, a transformer-based neural network architecture is adapted to restore the noisy solution of the Computed Tomography problem recovered using the filtered back-projection method.