Geological and hydrogeological features affecting migration, multi-phase partitioning and degradation of chlorinated hydrocarbons through unconsolidated porous media.

Chlorinated solvents are the most ubiquitous organic contaminants found in groundwater since the last five decades. They generally reach groundwater as Dense Non-Aqueous Phase Liquid (DNAPL). This phase can migrate through aquifers, and also through aquitards, in ways that aqueous contaminants cannot. The complex phase partitioning to which chlorinated solvent DNAPLs can undergo (i.e. to the dissolved, vapor or sorbed phase), as well as their transformations (e.g. degradation), depend on the physico-chemical properties of the contaminants themselves and on features of the hydrogeological system. The main goal of the thesis is to provide new knowledge for the future investigations of sites contaminated by DNAPLs in alluvial settings, proposing innovative investigative approaches and emphasizing some of the key issues and main criticalities of this kind of contaminants in such a setting. To achieve this goal, the hydrogeologic setting below the city of Ferrara (Po plain, northern Italy), which is affected by scattered contamination by chlorinated solvents, has been investigated at different scales (regional and site specific), both from an intrinsic (i.e. groundwater flow systems) and specific (i.e. chlorinated solvent DNAPL behavior) point of view. Detailed investigations were carried out in particular in one selected test-site, known as “Caretti site”, where high-resolution vertical profiling of different kind of data were collected by means of multilevel monitoring systems and other innovative sampling and analytical techniques. This allowed to achieve a deep geological and hydrogeological knowledge of the system and to reconstruct in detail the architecture of contaminants in relationship to the features of the hosting porous medium. The results achieved in this thesis are useful not only at local scale, e.g. employable to interpret the origin of contamination in other sites of the Ferrara area, but also at global scale, in order to address future remediation and protection actions of similar hydrogeologic settings.

Power flow forecasting and smart charging for electric vehicle charging systems with photovoltaic integration

An essential role in the global energy transition is attributed to Electric Vehicles (EVs) the energy for EV traction can be generated by renewable energy sources (RES), also at a local level through distributed power plants, such as photovoltaic (PV) systems. However, EV integration with electrical systems might not be straightforward. The intermittent RES, combined with the high and uncontrolled aggregate EV charging, require an evolution toward new planning and paradigms of energy systems. In this context, this work aims to provide a practical solution for EV charging integration in electrical systems with RES. A method for predicting the power required by an EV fleet at the charging hub (CH) is developed in this thesis. The proposed forecasting method considers the main parameters on which charging demand depends. The results of the EV charging forecasting method are deeply analyzed under different scenarios. To reduce the EV load intermittency, methods for managing the charging power of EVs are proposed. The main target was to provide Charging Management Systems (CMS) that modulate EV charging to optimize specific performance indicators such as system self-consumption, peak load reduction, and PV exploitation. Controlling the EV charging power to achieve specific optimization goals is also known as Smart Charging (SC). The proposed techniques are applied to real-world scenarios demonstrating performance improvements in using SC strategies. A viable alternative to maximize integration with intermittent RES generation is the integration of energy storage. Battery Energy Storage Systems (BESS) may be a buffer between peak load and RES production. A sizing algorithm for PV+BESS integration in EV charging hubs is provided. The sizing optimization aims to optimize the system's energy and economic performance. The results provide an overview of the optimal size that the PV+BESS plant should have to improve whole system performance in different scenarios.

Interconnection systems for highly integrated computation devices

The sustained demand for faster,more powerful chips has beenmet by the availability of chip manufacturing processes allowing for the integration of increasing numbers of computation units onto a single die. The resulting outcome, especially in the embedded domain, has often been called SYSTEM-ON-CHIP (SOC) or MULTI-PROCESSOR SYSTEM-ON-CHIP (MPSOC). MPSoC design brings to the foreground a large number of challenges, one of the most prominent of which is the design of the chip interconnection. With a number of on-chip blocks presently ranging in the tens, and quickly approaching the hundreds, the novel issue of how to best provide on-chip communication resources is clearly felt. NETWORKS-ON-CHIPS (NOCS) are the most comprehensive and scalable answer to this design concern. By bringing large-scale networking concepts to the on-chip domain, they guarantee a structured answer to present and future communication requirements. The point-to-point connection and packet switching paradigms they involve are also of great help in minimizing wiring overhead and physical routing issues. However, as with any technology of recent inception, NoC design is still an evolving discipline. Several main areas of interest require deep investigation for NoCs to become viable solutions: • The design of the NoC architecture needs to strike the best tradeoff among performance, features and the tight area and power constraints of the on-chip domain. • Simulation and verification infrastructure must be put in place to explore, validate and optimize the NoC performance. • NoCs offer a huge design space, thanks to their extreme customizability in terms of topology and architectural parameters. Design tools are needed to prune this space and pick the best solutions. • Even more so given their global, distributed nature, it is essential to evaluate the physical implementation of NoCs to evaluate their suitability for next-generation designs and their area and power costs. This dissertation focuses on all of the above points, by describing a NoC architectural implementation called ×pipes; a NoC simulation environment within a cycle-accurate MPSoC emulator called MPARM; a NoC design flow consisting of a front-end tool for optimal NoC instantiation, called SunFloor, and a set of back-end facilities for the study of NoC physical implementations. This dissertation proves the viability of NoCs for current and upcoming designs, by outlining their advantages (alongwith a fewtradeoffs) and by providing a full NoC implementation framework. It also presents some examples of additional extensions of NoCs, allowing e.g. for increased fault tolerance, and outlines where NoCsmay find further application scenarios, such as in stacked chips.

Development of Clinical Decision Support Systems based on Mathematical Models of Physiological Systems

In the last years of research, I focused my studies on different physiological problems. Together with my supervisors, I developed/improved different mathematical models in order to create valid tools useful for a better understanding of important clinical issues. The aim of all this work is to develop tools for learning and understanding cardiac and cerebrovascular physiology as well as pathology, generating research questions and developing clinical decision support systems useful for intensive care unit patients. I. ICP-model Designed for Medical Education We developed a comprehensive cerebral blood flow and intracranial pressure model to simulate and study the complex interactions in cerebrovascular dynamics caused by multiple simultaneous alterations, including normal and abnormal functional states of auto-regulation of the brain. Individual published equations (derived from prior animal and human studies) were implemented into a comprehensive simulation program. Included in the normal physiological modelling was: intracranial pressure, cerebral blood flow, blood pressure, and carbon dioxide (CO2) partial pressure. We also added external and pathological perturbations, such as head up position and intracranial haemorrhage. The model performed clinically realistically given inputs of published traumatized patients, and cases encountered by clinicians. The pulsatile nature of the output graphics was easy for clinicians to interpret. The manoeuvres simulated include changes of basic physiological inputs (e.g. blood pressure, central venous pressure, CO2 tension, head up position, and respiratory effects on vascular pressures) as well as pathological inputs (e.g. acute intracranial bleeding, and obstruction of cerebrospinal outflow). Based on the results, we believe the model would be useful to teach complex relationships of brain haemodynamics and study clinical research questions such as the optimal head-up position, the effects of intracranial haemorrhage on cerebral haemodynamics, as well as the best CO2 concentration to reach the optimal compromise between intracranial pressure and perfusion. We believe this model would be useful for both beginners and advanced learners. It could be used by practicing clinicians to model individual patients (entering the effects of needed clinical manipulations, and then running the model to test for optimal combinations of therapeutic manoeuvres). II. A Heterogeneous Cerebrovascular Mathematical Model Cerebrovascular pathologies are extremely complex, due to the multitude of factors acting simultaneously on cerebral haemodynamics. In this work, the mathematical model of cerebral haemodynamics and intracranial pressure dynamics, described in the point I, is extended to account for heterogeneity in cerebral blood flow. The model includes the Circle of Willis, six regional districts independently regulated by autoregulation and CO2 reactivity, distal cortical anastomoses, venous circulation, the cerebrospinal fluid circulation, and the intracranial pressure-volume relationship. Results agree with data in the literature and highlight the existence of a monotonic relationship between transient hyperemic response and the autoregulation gain. During unilateral internal carotid artery stenosis, local blood flow regulation is progressively lost in the ipsilateral territory with the presence of a steal phenomenon, while the anterior communicating artery plays the major role to redistribute the available blood flow. Conversely, distal collateral circulation plays a major role during unilateral occlusion of the middle cerebral artery. In conclusion, the model is able to reproduce several different pathological conditions characterized by heterogeneity in cerebrovascular haemodynamics and can not only explain generalized results in terms of physiological mechanisms involved, but also, by individualizing parameters, may represent a valuable tool to help with difficult clinical decisions. III. Effect of Cushing Response on Systemic Arterial Pressure. During cerebral hypoxic conditions, the sympathetic system causes an increase in arterial pressure (Cushing response), creating a link between the cerebral and the systemic circulation. This work investigates the complex relationships among cerebrovascular dynamics, intracranial pressure, Cushing response, and short-term systemic regulation, during plateau waves, by means of an original mathematical model. The model incorporates the pulsating heart, the pulmonary circulation and the systemic circulation, with an accurate description of the cerebral circulation and the intracranial pressure dynamics (same model as in the first paragraph). Various regulatory mechanisms are included: cerebral autoregulation, local blood flow control by oxygen (O2) and/or CO2 changes, sympathetic and vagal regulation of cardiovascular parameters by several reflex mechanisms (chemoreceptors, lung-stretch receptors, baroreceptors). The Cushing response has been described assuming a dramatic increase in sympathetic activity to vessels during a fall in brain O2 delivery. With this assumption, the model is able to simulate the cardiovascular effects experimentally observed when intracranial pressure is artificially elevated and maintained at constant level (arterial pressure increase and bradicardia). According to the model, these effects arise from the interaction between the Cushing response and the baroreflex response (secondary to arterial pressure increase). Then, patients with severe head injury have been simulated by reducing intracranial compliance and cerebrospinal fluid reabsorption. With these changes, oscillations with plateau waves developed. In these conditions, model results indicate that the Cushing response may have both positive effects, reducing the duration of the plateau phase via an increase in cerebral perfusion pressure, and negative effects, increasing the intracranial pressure plateau level, with a risk of greater compression of the cerebral vessels. This model may be of value to assist clinicians in finding the balance between clinical benefits of the Cushing response and its shortcomings. IV. Comprehensive Cardiopulmonary Simulation Model for the Analysis of Hypercapnic Respiratory Failure We developed a new comprehensive cardiopulmonary model that takes into account the mutual interactions between the cardiovascular and the respiratory systems along with their short-term regulatory mechanisms. The model includes the heart, systemic and pulmonary circulations, lung mechanics, gas exchange and transport equations, and cardio-ventilatory control. Results show good agreement with published patient data in case of normoxic and hyperoxic hypercapnia simulations. In particular, simulations predict a moderate increase in mean systemic arterial pressure and heart rate, with almost no change in cardiac output, paralleled by a relevant increase in minute ventilation, tidal volume and respiratory rate. The model can represent a valid tool for clinical practice and medical research, providing an alternative way to experience-based clinical decisions. In conclusion, models are not only capable of summarizing current knowledge, but also identifying missing knowledge. In the former case they can serve as training aids for teaching the operation of complex systems, especially if the model can be used to demonstrate the outcome of experiments. In the latter case they generate experiments to be performed to gather the missing data.

Modeling, design and experimental characterization of Micro-Electro-Mechanical-Systems for gas chromatographic applications

Design parameters, process flows, electro-thermal-fluidic simulations and experimental characterizations of Micro-Electro-Mechanical-Systems (MEMS) suited for gas-chromatographic (GC) applications are presented and thoroughly described in this thesis, whose topic belongs to the research activities the Institute for Microelectronics and Microsystems (IMM)-Bologna is involved since several years, i.e. the development of micro-systems for chemical analysis, based on silicon micro-machining techniques and able to perform analysis of complex gaseous mixtures, especially in the field of environmental monitoring. In this regard, attention has been focused on the development of micro-fabricated devices to be employed in a portable mini-GC system for the analysis of aromatic Volatile Organic Compounds (VOC) like Benzene, Toluene, Ethyl-benzene and Xylene (BTEX), i.e. chemical compounds which can significantly affect environment and human health because of their demonstrated carcinogenicity (benzene) or toxicity (toluene, xylene) even at parts per billion (ppb) concentrations. The most significant results achieved through the laboratory functional characterization of the mini-GC system have been reported, together with in-field analysis results carried out in a station of the Bologna air monitoring network and compared with those provided by a commercial GC system. The development of more advanced prototypes of micro-fabricated devices specifically suited for FAST-GC have been also presented (silicon capillary columns, Ultra-Low-Power (ULP) Metal OXide (MOX) sensor, Thermal Conductivity Detector (TCD)), together with the technological processes for their fabrication. The experimentally demonstrated very high sensitivity of ULP-MOX sensors to VOCs, coupled with the extremely low power consumption, makes the developed ULP-MOX sensor the most performing metal oxide sensor reported up to now in literature, while preliminary test results proved that the developed silicon capillary columns are capable of performances comparable to those of the best fused silica capillary columns. Finally, the development and the validation of a coupled electro-thermal Finite Element Model suited for both steady-state and transient analysis of the micro-devices has been described, and subsequently implemented with a fluidic part to investigate devices behaviour in presence of a gas flowing with certain volumetric flow rates.

Comparative Analysis of Alternative Hybrid Systems for Automotive Applications

The main objective of this work was to investigate the impact of different hybridization concepts and levels of hybridization on fuel economy of a standard road vehicle where both conventional and non-conventional hybrid architectures are treated exactly in the same way from the point of view of overall energy flow optimization. Hybrid component models were developed and presented in detail as well as the simulations results mainly for NEDC cycle. The analysis was performed on four different parallel hybrid powertrain concepts: Hybrid Electric Vehicle (HEV), High Speed Flywheel Hybrid Vehicle (HSF-HV), Hydraulic Hybrid Vehicle (HHV) and Pneumatic Hybrid Vehicle (PHV). In order to perform equitable analysis of different hybrid systems, comparison was performed also on the basis of the same usable system energy storage capacity (i.e. 625kJ for HEV, HSF and the HHV) but in the case of pneumatic hybrid systems maximal storage capacity was limited by the size of the systems in order to comply with the packaging requirements of the vehicle. The simulations were performed within the IAV Gmbh - VeLoDyn software simulator based on Matlab / Simulink software package. Advanced cycle independent control strategy (ECMS) was implemented into the hybrid supervisory control unit in order to solve power management problem for all hybrid powertrain solutions. In order to maintain State of Charge within desired boundaries during different cycles and to facilitate easy implementation and recalibration of the control strategy for very different hybrid systems, Charge Sustaining Algorithm was added into the ECMS framework. Also, a Variable Shift Pattern VSP-ECMS algorithm was proposed as an extension of ECMS capabilities so as to include gear selection into the determination of minimal (energy) cost function of the hybrid system. Further, cycle-based energetic analysis was performed in all the simulated cases, and the results have been reported in the corresponding chapters.

On the renormalization flow representation of field theory and some applications

In this thesis we discuss a representation of quantum mechanics and quantum and statistical field theory based on a functional renormalization flow equation for the one-particle-irreducible average effective action, and we employ it to get information on some specific systems.

Photophysical investigation of light-harvesting systems for solar-to-fuel conversion

In recent years, an increasing attention has been given to the optimization of the performances of new supramolecular systems, as antennas for light collection. In such background, the aim of this thesis was the study of multichromophoric architectures capable of performing such basic action. A synthetic antenna should consist of a structure with large UV-Vis absorption cross-section, panchromatic absorption, fixed orientation of the components and suitable energy gradients between them, in order to funnel absorbed energy towards a specific site, through fast energy-transfer processes. Among the systems investigated in this thesis, three suitable classes of compounds can be identified: 1) transition metal-based multichromophoric arrays, as models for antenna construction, 2) free-base trans-A2B-phenylcorroles, as self-assembling systems to make effective mimics of the photosynthetic system, and 3) a natural harvester, the Photosystem I, immobilized on the photoanode of a solar-to-fuel conversion device. The discussion starts with the description of the photophysical properties of dinuclear quinonoid organometallic systems, able to fulfil some of the above mentioned absorption requirements, displaying in some cases panchromatic absorption. The investigation is extended to the efficient energy transfer processes occurring in supramolecular architectures, suitably organized around rigid organic scaffolds, such as spiro-bifluorene and triptycene. Furthermore, the photophysical characterization of three trans-A2B-phenylcorroles with different substituents on the meso-phenyl ring is introduced, revealing the tendency of such macrocycles to self-organize into dimers, by mimicking natural self-aggregates antenna systems. In the end, the photophysical analysis moved towards the natural super-complex PSI-LHCI, immobilized on the hematite surface of the photoanode of a bio-hybrid dye-sensitized solar cell. The importance of the entire work is related to the need for a deep understanding of the energy transfer mechanisms occurring in supramolecules, to gain insights and improve the strategies for governing the directionality of the energy flow in the construction of well-performing antenna systems.

Novel catalytic systems and methidologies for organocatalysis and photocatalysis

The thesis is divided into two main parts. In the first one organocatalysis is briefly introduced. Then, new enantiopure trityl pyrrolidines modified with an ionic tag are described. All the catalysts are tested in the benchmark Michael addition reaction to prove their activity and stereoselectivity. In the second part, photocatalysis is first introduced. Then, four different research projects are described. At first, the construction of a hybrid metal-organo-photoredox catalyst is described. The hybrid photocatalysts obtained were employed in the benchmark photoredox alkylation of aldehydes. Then, the use of visible light and a photocatalytic system for the cyclization of iodoaryl vinyl derivatives to tetrahydroquinoline structures is described. In addition, the reaction can also be performed using flow-chemistry. Finally, a mechanistic proposal based on some mechanistic studies is described. Third, a new photoredox catalyzed transformation for the synthesis of 2,3-dihydrofurans is reported. Depending on the involved starting materials, different pathways have arisen. A mechanistic proposal based on reported literatures and experimental data is described. At last, a new photoredox catalyzed transformation for the synthesis of 2-aminofurans is described. Electrophilic radical addition on allenamides and subsequential intramolecular cyclization are exploited. The reaction proceeds under very mild conditions and in 2-aminofurans are obtained in good to high yield. It represents one of the few applications of allenamides in photoredox catalysis. A mechanistic proposal is described. Finally, preliminary investigations on the applicability of the developed transformation under flow chemistry conditions.

Addressing challenges in heterogeneous embedded systems programming: security and performance

Embedded systems are increasingly integral to daily life, improving and facilitating the efficiency of modern Cyber-Physical Systems which provide access to sensor data, and actuators. As modern architectures become increasingly complex and heterogeneous, their optimization becomes a challenging task. Additionally, ensuring platform security is important to avoid harm to individuals and assets. This study primarily addresses challenges in contemporary Embedded Systems, focusing on platform optimization and security enforcement. The initial section of this study delves into the application of machine learning methods to efficiently determine the optimal number of cores for a parallel RISC-V cluster to minimize energy consumption using static source code analysis. Results demonstrate that automated platform configuration is not only viable but also that there is a moderate performance trade-off when relying solely on static features. The second part focuses on addressing the problem of heterogeneous device mapping, which involves assigning tasks to the most suitable computational device in a heterogeneous platform for optimal runtime. The contribution of this section lies in the introduction of novel pre-processing techniques, along with a training framework called Siamese Networks, that enhances the classification performance of DeepLLVM, an advanced approach for task mapping. Importantly, these proposed approaches are independent from the specific deep-learning model used. Finally, this research work focuses on addressing issues concerning the binary exploitation of software running in modern Embedded Systems. It proposes an architecture to implement Control-Flow Integrity in embedded platforms with a Root-of-Trust, aiming to enhance security guarantees with limited hardware modifications. The approach involves enhancing the architecture of a modern RISC-V platform for autonomous vehicles by implementing a side-channel communication mechanism that relays control-flow changes executed by the process running on the host core to the Root-of-Trust. This approach has limited impact on performance and it is effective in enhancing the security of embedded platforms.

Decoding complex flow phenomena via Dynamic Mode Decomposition

In this thesis, the viability of the Dynamic Mode Decomposition (DMD) as a technique to analyze and model complex dynamic real-world systems is presented. This method derives, directly from data, computationally efficient reduced-order models (ROMs) which can replace too onerous or unavailable high-fidelity physics-based models. Optimizations and extensions to the standard implementation of the methodology are proposed, investigating diverse case studies related to the decoding of complex flow phenomena. The flexibility of this data-driven technique allows its application to high-fidelity fluid dynamics simulations, as well as time series of real systems observations. The resulting ROMs are tested against two tasks: (i) reduction of the storage requirements of high-fidelity simulations or observations; (ii) interpolation and extrapolation of missing data. The capabilities of DMD can also be exploited to alleviate the cost of onerous studies that require many simulations, such as uncertainty quantification analysis, especially when dealing with complex high-dimensional systems. In this context, a novel approach to address parameter variability issues when modeling systems with space and time-variant response is proposed. Specifically, DMD is merged with another model-reduction technique, namely the Polynomial Chaos Expansion, for uncertainty quantification purposes. Useful guidelines for DMD deployment result from the study, together with the demonstration of its potential to ease diagnosis and scenario analysis when complex flow processes are involved.