Nuovi copoliesteri statistici cicloalifatici contenenti acido canforico per applicazioni nel food packaging

Il presente progetto di Tesi ha come obiettivo il design di nuovi copolimeri statistici bio-based, caratterizzati da idonee proprietà meccaniche e barriera per impieghi come film sottili nell’imballaggio alimentare. I materiali sintetizzati appartengono alla classe dei poliesteri alifatici, caratterizzati dalla facilità di sintesi in assenza di solventi, relativamente economici, caratterizzati da proprietà modulabili in funzione della struttura chimica. Come omopolimero di partenza è stato scelto il poli(butilene trans-1,4-cicloesanoato) (PBCE), un poliestere potenzialmente bio-based con elevata resistenza ad alte temperature, umidità, radiazioni UV e buone proprietà meccaniche e barriera, e, benchè non ancora disponibile in commercio, molto interessante. Esso risulta troppo rigido per la realizzazione di film flessibili. Il PBCE è stato quindi copolimerizzato introducendo l’(1R,3S)-(+)-Acido Canforico, un monomero bio-based ottenibile dalla canfora. L’obiettivo del lavoro è modulare la cristallinità, le proprietà termiche, meccaniche e barriera dell’omopolimero di partenza. Dopo la sintesi, effettuata mediante policondensazione in massa a due stadi, tali copolimeri sono stati sottoposti a caratterizzazioni molecolari, termiche e meccaniche per valutare l’effetto dell’introduzione di comonomero nella catena macromolecolare del PBCE.

Hardware-In-The Loop setup and test of an air spring control system

In this work, a Hardware-in-the-loop test bench is designed. The bench is used to test the behaviour of an electronic control unit used in Maserati to control the dynamics of an air spring system. First the mathematical model of the plant has been defined, then the simulation enviroment and the test environment have been set up. The performed tests succesfully highlighted some bugs in the device under test.

Modelling, control and testing of internal combustion engines to minimize consumption and pollutant emissions

The objective of the PhD thesis was to research technologies and strategies to reduce fuel consumption and pollutants emission produced by internal combustion engines. In order to meet this objective my activity was focused on the research of advanced controls based on cylinder pressure feedback. These types of control strategies were studied because they present promising results in terms of engine efficiency enhancement. In the PhD dissertation two study cases are presented. The first case is relative to a control strategy to be used at the test bench for the optimisation of the spark advance calibration of motorcycle Engine. The second case is relative to a control strategy to be used directly on board of mining engines with the objective or reducing the engine consumption and correct ageing effects. In both cases the strategies proved to be effective but their implementation required the use of specific toolchains for the measure of the cylinder pressure feedback that for a matter of cost makes feasible the strategy use only for applications: • At test bench • In small-markets like large off-road engines The major bottleneck that prevents the implementation of these strategies on mass production is the cost of cylinder pressure sensor. In order to tackle this issue, during the PhD research, the development of a low-cost sensor for the estimation of cylinder pressure was studied. The prototype was a piezo-electric washer designed to replace the standard spark-plug washer or high-pressure fuel injectors gasket. From the data analysis emerged the possibility to use the piezo-electric prototype signal to evaluate with accuracy several combustion metrics compatible for the implementation of advanced control strategies in on-board applications. Overall, the research shows that advanced combustion controls are feasible and beneficial, not only at the test bench or on stationary engines, but also in mass-produced engines.

Identificazione di un nuovo meccanismo microRNA-dipendente di resistenza all'inibizione della via di segnale PI3K/AKT nel carcinoma della prostata

Benché le alterazioni della via PI3K/AKT siano molto sudiate a causa del loro ruolo nella tumorigenesi, e rappresentino pertanto un importante bersaglio terapeutico, i risultati di numerosi studi clinici con inibitori di PI3K o AKT sono finora deludenti, in parte a causa dell’insorgenza di resistenza provocata dall'interruzione dei circuiti di feedback negativo. In questo studio, abbiamo scoperto che l’inattivazione farmacologica di AKT in cellule di carcinoma prostatico PC3 porta alla down-regolazione di un microRNA con funzione di oncosoppressore, il miR-145-5p, e ad un drammatico aumento di espressione di uno dei suoi geni target, cioè N/KRas. E’ interessante sottolineare che questo microRNA è considerato un marker di progressione metastatica nel carcinoma prostatico, il cui livello di espressione aiuta a discriminare tra pazienti con iperplasia prostatica benigna e cancro alla prostata. Inoltre, la bassa espressione di miR-145 aumenta il rischio di progressione della malattia da localizzata a metastatica. La conferma che l’aumento di Ras, osservato sia in termini di mRNA che di proteina, è dipendente dalla caduta del miR-145-5p, è stata poi ottenuta tramite un modello di PC3 ingegnerizzate per ottenere il silenziamento inducibile del miR-145-5p. Tramite un array di fosfoproteine siamo poi stati in grado di verificare che l’aumento di Ras provoca la riattivazione della cascata di PI3K/AKT e di ERK. Dal punto di vista meccanicistico, quindi, lo studio ha portato all’identificazione di un nuovo meccanismo di resistenza adattativa, in cui l’inattivazione di AKT provoca una caduta del miR-145-5p che, a sua volta, aumenta l’espressione di Ras e riattiva il signaling di PI3K, rendendo inefficace il trattamento farmacologico. Questi risultati sono particolarmente rilevanti alla luce di recenti studi (NCT04493853; NCT03072238; NCT02525068) e di trial clinici in corso (NCT04737109; NCT03673787), basati sulla somministrazione combinata di inibitori della sintesi degli androgeni con gli inibitori di AKT capitasertib o ipatasertib.

Deep space orbit determination and guidance of the LICIACube microsatellite mission

Recently, the JPL's MarCO mission demonstrated that these probes are also mature enough to be employed in the deep space, even though with the limitations related to the employed commercial components. Currently, other deep space CubeSats are planned either as stand-alone missions or as companions of a traditional large probe. Therefore, developing a dedicated navigation suite is crucial to reaching the mission's goals, considering the limitations of the onboard components compared to typical deep space missions. In this framework, the LICIACube mission represents an ideal candidate test-bench, as it performs a flyby of the Didymos asteroid system subject to a strong position, epochs, and pointing requirements. This mission will also allow us to infer the capabilities of such microsatellites and highlight their limitations compared with the benefits of a lighter design and tailoring efforts. In this work, the OD and guidance methods and tools adopted for classical deep space missions have been tailored for the CubeSat applications and validated through extensive analyses. In addition, navigation procedures and interfaces have been designed in view of the operations foreseen in late 2022. The pre-launch covariance analysis has been performed to assess the mission's feasibility for the nominal trajectory and its associated uncertainties, based on conservative assumptions on the main parameters. Extensive sensitivity analyses have been carried out to understand the main mission parameters affecting the performance and to demonstrate the robustness of the designed trajectory and operation schedule in fulfilling the mission requirements. The developed system was also stressed by tuning the models to access different reconstruction methods for the maneuvers. The analysis demonstrated the feasibility of the LICIACube mission navigation in compliance with the mission requirements, compatible with the limited resources available, both in space and on the ground.

Design and testing of innovative, artificial intelligence-based techniques to model and control the combustion process and to reduce the Co2 emissions in modern, high-performance, gasoline direct injection engines

This work deals with the development of calibration procedures and control systems to improve the performance and efficiency of modern spark ignition turbocharged engines. The algorithms developed are used to optimize and manage the spark advance and the air-to-fuel ratio to control the knock and the exhaust gas temperature at the turbine inlet. The described work falls within the activity that the research group started in the previous years with the industrial partner Ferrari S.p.a. . The first chapter deals with the development of a control-oriented engine simulator based on a neural network approach, with which the main combustion indexes can be simulated. The second chapter deals with the development of a procedure to calibrate offline the spark advance and the air-to-fuel ratio to run the engine under knock-limited conditions and with the maximum admissible exhaust gas temperature at the turbine inlet. This procedure is then converted into a model-based control system and validated with a Software in the Loop approach using the engine simulator developed in the first chapter. Finally, it is implemented in a rapid control prototyping hardware to manage the combustion in steady-state and transient operating conditions at the test bench. The third chapter deals with the study of an innovative and cheap sensor for the in-cylinder pressure measurement, which is a piezoelectric washer that can be installed between the spark plug and the engine head. The signal generated by this kind of sensor is studied, developing a specific algorithm to adjust the value of the knock index in real-time. Finally, with the engine simulator developed in the first chapter, it is demonstrated that the innovative sensor can be coupled with the control system described in the second chapter and that the performance obtained could be the same reachable with the standard in-cylinder pressure sensors.

Excitonic properties of transition metal oxide perovskites and workflow automatization of GW schemes

The Many-Body-Perturbation Theory approach is among the most successful theoretical frameworks for the study of excited state properties. It allows to describe the excitonic interactions, which play a fundamental role in the optical response of insulators and semiconductors. The first part of the thesis focuses on the study of the quasiparticle, optical and excitonic properties of \textit{bulk} Transition Metal Oxide (TMO) perovskites using a G$_0$W$_0$+Bethe Salpeter Equation (BSE) approach. A representative set of 14 compounds has been selected, including 3d, 4d and 5d perovskites. An approximation of the BSE scheme, based on an analytic diagonal expression for the inverse dielectric function, is used to compute the exciton binding energies and is carefully bench-marked against the standard BSE results. In 2019 an important breakthrough has been achieved with the synthesis of ultrathin SrTiO3 films down to the monolayer limit. This allows us to explore how the quasiparticle and optical properties of SrTiO3 evolve from the bulk to the two-dimensional limit. The electronic structure is computed with G0W0 approach: we prove that the inclusion of the off-diagonal self-energy terms is required to avoid non-physical band dispersions. The excitonic properties are investigated beyond the optical limit at finite momenta. Lastly a study of the under pressure optical response of the topological nodal line semimetal ZrSiS is presented, in conjunction with the experimental results from the group of Prof. Dr. Kuntscher of the Augsburg University. The second part of the thesis discusses the implementation of a workflow to automate G$_0$W$_0$ and BSE calculations with the VASP software. The workflow adopts a convergence scheme based on an explicit basis-extrapolation approach [J. Klimeš \textit{et al.}, Phys. Rev.B 90, 075125 (2014)] which allows to reduce the number of intermediate calculations required to reach convergence and to explicit estimate the error associated to the basis-set truncation.

Application of the Extended Kalman filter for speed sensorless control of PM synchronous machines

The increasing interest in the decarbonization process led to a rapidly growing trend of electrification strategies in the automotive industry. In particular, OEMs are pushing towards the development and production of efficient electric vehicles. Moreover, research on electric motors and their control are exploding in popularity. The increase of computational power in embedded control hardware is allowing the development of new control algorithm, such as sensorless control strategy. Such control strategy allows the reduction of the number of sensors, which implies reduced costs and increased system reliability. The thesis objective is to realize a sensorless control for high-performance automotive motors. Several algorithms for rotor angle observers are implemented in the MATLAB and Simulink environment, with emphasis on the Kalman observer. One of the Kalman algorithms already available in the literature has been selected, implemented and benchmarked, with emphasis on its comparison with the Sliding Mode observer. Different models characterized by increasing levels of complexity are simulated. A simplified synchronous motor with ”constant parameters”, controlled by an ideal inverter is first analyzed; followed by a complete model defined by real motor maps, and controlled by a switching inverter. Finally, it was possible to test the developed algorithm on a real electric motor mounted on a test bench. A wide range of different electric motors have been simulated, which led to an exhaustive review of the sensorless control algorithm. The final results underline the capability of the Kalman observer to effectively control the motor on a real test bench.

Experimental analysis of the aerodynamic and mixing performance of a ventilation device

Numerous types of acute respiratory failure are routinely treated using non-invasive ventilatory support (NIV). Its efficacy is well documented: NIV lowers intubation and death rates in various respiratory disorders. It can be delivered by means of face masks or head helmets. Currently the scientific community’s interest about NIV helmets is mostly focused on optimising the mixing between CO2 and clean air and on improving patient comfort. To this end, fluid dynamic analysis plays a particularly important role and a two- pronged approach is frequently employed. While on one hand numerical simulations provide information about the entire flow field and different geometries, they exhibit require huge temporal and computational resources. Experiments on the other hand help to validate simulations and provide results with a much smaller time investment and thus remain at the core of research in fluid dynamics. The aim of this thesis work was to develop a flow bench and to utilise it for the analysis of NIV helmets. A flow test bench and an instrumented mannequin were successfully designed, produced and put into use. Experiments were performed to characterise the helmet interface in terms of pressure drop and flow rate drop over different inlet flow rates and outlet pressure set points. Velocity measurements by means of Particle Image Velocimetry were performed. Pressure drop and flow rate characteristics from experiments were contrasted with CFD data and sufficient agreement was observed between both numerical and experimental results. PIV studies permitted qualitative and quantitative comparisons with numerical simulation data and offered a clear picture of the internal flow behaviour, aiding the identification of coherent flow features.

Design and implementation of a synchronous interleaved boost converter for fuel cell-powered catamaran

The present work describes the different stages of design, implementation, and validation procedures for an interleaved DC-DC boost converter intended for the 2022 Futura, a fuel cell-powered racing catamaran developed by the UniBoAT team. The main goal of the entire design has been the significant reduction of the weight of the converter by removing heat sinks and reducing component size while increasing its efficiency by adopting high-end power switches and the interleaved architecture operated with a synchronous control strategy. The obtained converter has been integrated into the structure containing the fuel cell stack obtaining a fully integrated system. The realized device has been based on an interleaved architecture with six phases controlled digitally through the average current mode control. The design has been validated through simulations carried out using the software LT-Spice, whereas experimental validations have been performed by means of laboratory bench tests and on-field tests. Detailed thermal and efficiency analyses are provided with the bench tests under the two synchronous and non-synchronous operating modes and with the adoption of the phase shedding technique. The prototype implementation and its performance in real operating conditions are also discussed. Eventually, it is underlined as the designed converter can be used in other applications requiring a voltage-controlled boost converter.