Development of numerical tools for the simulation, design and optimization of a Helicon Plasma Thruster

This work thesis focuses on the Helicon Plasma Thruster (HPT) as a candidate for generating thrust for small satellites and CubeSats. Two main topics are addressed: the development of a Global Model (GM) and a 3D self-consistent numerical tool. The GM is suitable for preliminary analysis of HPTs with noble gases such as argon, neon, krypton, and xenon, and alternative propellants such as air and iodine. A lumping methodology is developed to reduce the computational cost when modelling the excited species in the plasma chemistry. A 3D self-consistent numerical tool is also developed that can treat discharges with a generic 3D geometry and model the actual plasma-antenna coupling. The tool consists of two main modules, an EM module and a FLUID module, which run iteratively until a steady state solution is converged. A third module is available for solving the plume with a simplified semi-analytical approach, a PIC code, or directly by integration of the fluid equations. Results obtained from both the numerical tools are benchmarked against experimental measures of HPTs or Helicon reactors, obtaining very good qualitative agreement with the experimental trend for what concerns the GM, and an excellent agreement of the physical trends predicted against the measured data for the 3D numerical strategy.

Network assimilation methodology and sectorization of water distribution systems by graph mining and optimization algorithm

Water Distribution Networks (WDNs) play a vital importance rule in communities, ensuring well-being band supporting economic growth and productivity. The need for greater investment requires design choices will impact on the efficiency of management in the coming decades. This thesis proposes an algorithmic approach to address two related problems:(i) identify the fundamental asset of large WDNs in terms of main infrastructure;(ii) sectorize large WDNs into isolated sectors in order to respect the minimum service to be guaranteed to users. Two methodologies have been developed to meet these objectives and subsequently they were integrated to guarantee an overall process which allows to optimize the sectorized configuration of WDN taking into account the needs to integrated in a global vision the two problems (i) and (ii). With regards to the problem (i), the methodology developed introduces the concept of primary network to give an answer with a dual approach, of connecting main nodes of WDN in terms of hydraulic infrastructures (reservoirs, tanks, pumps stations) and identifying hypothetical paths with the minimal energy losses. This primary network thus identified can be used as an initial basis to design the sectors. The sectorization problem (ii) has been faced using optimization techniques by the development of a new dedicated Tabu Search algorithm able to deal with real case studies of WDNs. For this reason, three new large WDNs models have been developed in order to test the capabilities of the algorithm on different and complex real cases. The developed methodology also allows to automatically identify the deficient parts of the primary network and dynamically includes new edges in order to support a sectorized configuration of the WDN. The application of the overall algorithm to the new real case studies and to others from literature has given applicable solutions even in specific complex situations.

Sensor networks optimization and software development for Structural Health Monitoring based on ultrasonic guided waves

The Structural Health Monitoring (SHM) research area is increasingly investigated due to its high potential in reducing the maintenance costs and in ensuring the systems safety in several industrial application fields. A growing demand of new SHM systems, permanently embedded into the structures, for savings in weight and cabling, comes from the aeronautical and aerospace application fields. As consequence, the embedded electronic devices are to be wirelessly connected and battery powered. As result, a low power consumption is requested. At the same time, high performance in defects or impacts detection and localization are to be ensured to assess the structural integrity. To achieve these goals, the design paradigms can be changed together with the associate signal processing. The present thesis proposes design strategies and unconventional solutions, suitable both for real-time monitoring and periodic inspections, relying on piezo-transducers and Ultrasonic Guided Waves. In the first context, arrays of closely located sensors were designed, according to appropriate optimality criteria, by exploiting sensors re-shaping and optimal positioning, to achieve improved damages/impacts localisation performance in noisy environments. An additional sensor re-shaping procedure was developed to tackle another well-known issue which arises in realistic scenario, namely the reverberation. A novel sensor, able to filter undesired mechanical boundaries reflections, was validated via simulations based on the Green's functions formalism and FEM. In the active SHM context, a novel design methodology was used to develop a single transducer, called Spectrum-Scanning Acoustic Transducer, to actively inspect a structure. It can estimate the number of defects and their distances with an accuracy of 2[cm]. It can also estimate the damage angular coordinate with an equivalent mainlobe aperture of 8[deg], when a 24[cm] radial gap between two defects is ensured. A suitable signal processing was developed in order to limit the computational cost, allowing its use with embedded electronic devices.

Supporting requirement elicitation and ontology testing in knowledge graph engineering

Knowledge graphs and ontologies are closely related concepts in the field of knowledge representation. In recent years, knowledge graphs have gained increasing popularity and are serving as essential components in many knowledge engineering projects that view them as crucial to their success. The conceptual foundation of the knowledge graph is provided by ontologies. Ontology modeling is an iterative engineering process that consists of steps such as the elicitation and formalization of requirements, the development, testing, refactoring, and release of the ontology. The testing of the ontology is a crucial and occasionally overlooked step of the process due to the lack of integrated tools to support it. As a result of this gap in the state-of-the-art, the testing of the ontology is completed manually, which requires a considerable amount of time and effort from the ontology engineers. The lack of tool support is noticed in the requirement elicitation process as well. In this aspect, the rise in the adoption and accessibility of knowledge graphs allows for the development and use of automated tools to assist with the elicitation of requirements from such a complementary source of data. Therefore, this doctoral research is focused on developing methods and tools that support the requirement elicitation and testing steps of an ontology engineering process. To support the testing of the ontology, we have developed XDTesting, a web application that is integrated with the GitHub platform that serves as an ontology testing manager. Concurrently, to support the elicitation and documentation of competency questions, we have defined and implemented RevOnt, a method to extract competency questions from knowledge graphs. Both methods are evaluated through their implementation and the results are promising.

Development of multicomponent models for the prediction of lubricant oil-fuel dilution in internal combustion engines

The current environmental crisis is forcing the automotive industry to face tough challenges for the Internal Combustion Engines development in order to reduce the emissions of pollutants and Greenhouse gases. In this context, in the last decades, the main technological solutions adopted by the manufacturers have been the direct injection and the engine downsizing, which led to the rising of new concerns related to the fuel-cylinder walls physical interaction. The fuel spray possibly impacts the cylinder liner wall, which is wetted by the lubricant oil thus causing the derating of the lubricant properties, increasing the oil consumption, and contaminating the lubricant oil in the crankcase. Also, concerning hydrogen fuelled internal combustion engines, it is likely that the high near-wall temperature, which is typical of the hydrogen flame, results in the evaporation of a portion of the lubricant oil, increasing its consumption. With regards on the innovative combustion systems and their control strategies, optical accessible engines are fundamental tools for experimental investigations on such combustion systems. Though, due to the optical measurement line, optical engines suffer from a high level of blow-by, which must be accounted for. In light of the above, this thesis work aims to develop numerical methodologies with the aim to build useful tools for supporting the design of modern engines. In particular, a one-dimensional modelling of the lubricant oil-fuel dilution and oil evaporation has been performed and coupled with an optimization algorithm to achieve a lubricant oil surrogate. Then, a quasi-dimensional blow-by model has been developed and validated against experimental data. Such model, has been coupled with CFD 3D simulations and directly implemented in CFD 3D. Finally, CFD 3D simulations coupled with the VOF method have been performed in order to validate a methodology for studying the impact of a liquid droplet on a solid surface.

Development of processes for the valorization of lignocellulosic biomass based on renewable energies

The world grapples with climate change from fossil fuel reliance, prompting Europe to pivot to renewable energy. Among renewables, biomass is a bioenergy and bio-carbon source, used to create high-value biomolecules, replacing fossil-based products. Alkyl levulinates, derived from biomass, hold promise as bio-additives and biofuels, especially via acid solvolysis of hexose sugars, necessitating further exploration. Alkyl levulinate's potential extends to converting into γ-valerolactone (GVL), a bio-solvent produced via hydrogenation with molecular-hydrogen. Hydrogen, a key reagent and energy carrier, aids renewable energy integration. This thesis delves into a biorefinery system study, aligning with sustainability goals, integrating biomass valorization, energy production, and hydrogen generation. It investigates optimizing technologies for butyl levulinate production and subsequent GVL hydrogenation. Sustainability remains pivotal, reflecting the global shift towards renewable and carbon bio-resources. The research initially focuses on experimenting with the optimal technology for producing butyl levulinate from biomass-derived hexose fructose. It examines the solvolysis process, investigating optimal conditions, kinetic modeling, and the impact of solvents on fructose conversion. The subsequent part concentrates on the technological aspect of hydrogenating butyl levulinate into GVL. It includes conceptual design, simulation, and optimization of the fructose-to-GVL process scheme based on process intensification. In the final part, the study applies the process to a real case study in Normandy, France, adapting it to local biomass availability and wind energy. It defines a methodology for designing and integrating the energy-supply system, evaluating different scenarios. Sustainability assessment using economic, environmental, and social indicators culminates in an overall sustainability index, indicating scenarios integrating the GVL biorefinery system with wind power and hydrogen energy storage as promising due to high profitability and reduced environmental impact. Sensitivity analyses validate the methodology's reliability, potentially extending to other technological systems.