Navigation design and flight dynamics operations of the ArgoMoon cis-lunar CubeSat.

On November 16, 2022, the NASA’s Space Launch System (SLS) has been launched for the first time in the context of Artemis-1 mission where, together with the Orion Multi-Purpose Crew Vehicle, a set of 10 CubeSats have been delivered into a translunar trajectory. Among the small satellites deployed during Artemis-1 there is ArgoMoon, a 6U CubeSat built by the Italian company Argotec and coordinated by Italian Space Agency (ASI). The primary goal of ArgoMoon is to capture images of the Interim Cryogenic Propulsion Stage. The ArgoMoon trajectory has been designed as a highly elliptical geocentric orbit, with several encounters with the Moon. In order to successfully fly ArgoMoon along the designed cis-lunar trajectory, a ground-based navigation system has been developed exploiting the guidance techniques also used for regular deep space missions. The navigation process is subdivided into Orbit Determi- nation (OD) and a Flight Path Control (FPC), and it is designed to follow the reference trajectory, prevent impacts with the Earth and the Moon, intensively test the navigation techniques, and guarantee the spacecraft disposal at the end of the mission. The work done in this thesis has accomplished the navigation of ArgoMoon, covering all aspects of the project life, from pre-launch design and analysis to actual operations. Firstly, the designed navigation process and the pre-mission assessment of its performance will be presented. Then, the results of the ArgoMoon navigation operations performed after the launch in November 2022 will be described in detail by discussing the main encountered challenges and the adopted solutions. The results of the operations confirmed the robustness of the designed navigation which allowed to accurately estimate the trajectory of ArgoMoon despite a series of complex events.

Advanced statistical models for the segregation, identification and measurement of coexisting sound sources

Long-term monitoring of acoustical environments is gaining popularity thanks to the relevant amount of scientific and engineering insights that it provides. The increasing interest is due to the constant growth of storage capacity and computational power to process large amounts of data. In this perspective, machine learning (ML) provides a broad family of data-driven statistical techniques to deal with large databases. Nowadays, the conventional praxis of sound level meter measurements limits the global description of a sound scene to an energetic point of view. The equivalent continuous level Leq represents the main metric to define an acoustic environment, indeed. Finer analyses involve the use of statistical levels. However, acoustic percentiles are based on temporal assumptions, which are not always reliable. A statistical approach, based on the study of the occurrences of sound pressure levels, would bring a different perspective to the analysis of long-term monitoring. Depicting a sound scene through the most probable sound pressure level, rather than portions of energy, brought more specific information about the activity carried out during the measurements. The statistical mode of the occurrences can capture typical behaviors of specific kinds of sound sources. The present work aims to propose an ML-based method to identify, separate and measure coexisting sound sources in real-world scenarios. It is based on long-term monitoring and is addressed to acousticians focused on the analysis of environmental noise in manifold contexts. The presented method is based on clustering analysis. Two algorithms, Gaussian Mixture Model and K-means clustering, represent the main core of a process to investigate different active spaces monitored through sound level meters. The procedure has been applied in two different contexts: university lecture halls and offices. The proposed method shows robust and reliable results in describing the acoustic scenario and it could represent an important analytical tool for acousticians.

Developing a methodology for co-creation using extended reality technologies.

Amid the remarkable growth of innovative technologies, particularly immersive technologies like Extended Reality (XR) (comprising of Virtual Reality (VR), Augmented Reality (AR) & Mixed Reality (MR)), a transformation is unfolding in the way we collaborate and interact. The current research takes the initiative to explore XR’s potential for co-creation activities and proposes XR as a future co-creation platform. It strives to develop a XR-based co-creation system, actively engage stakeholders in the co-creation process, with the goal of enhancing their creative businesses. The research leverages XR tools to investigate how they can enhance digital co-creation methods and determine if the system facilitates efficient and effective value creation during XR-based co-creation sessions. In specific terms, the research probes into whether the XR-based co-creation method and environment enhances the quality and novelty of ideas, reduce communication challenges by providing better understanding of the product, problem or process and optimize the process in terms of reduction in time and costs. The research introduces a multi-user, multi-sensory collaborative and interactive XR platform that adapts to various use-case scenarios. This thesis also presents the user testing performed to collect both qualitative and quantitative data, which serves to substantiate the hypothesis. What sets this XR system apart is its incorporation of fully functional prototypes into a mixed reality environment, providing users with a unique dimension within an immersive digital landscape. The outcomes derived from the experimental studies demonstrate that XR-based co-creation surpasses conventional desktop co-creation methods and remarkably, the results are even comparable to a full mock-up test. In conclusion, the research underscores that the utilization of XR as a tool for co-creation generates substantial value. It serves as a method that enhances the process, an environment that fosters interaction and collaboration, and a platform that equips stakeholders with the means to engage effectively.

Packaging and food waste preventing strategies for sustainable food supply chain networks

The central aim of this dissertation is to introduce innovative methods, models, and tools to enhance the overall performance of supply chains responsible for handling perishable products. This concept of improved performance encompasses several critical dimensions, including enhanced efficiency in supply chain operations, product quality, safety, sustainability, waste generation minimization, and compliance with norms and regulations. The research is structured around three specific research questions that provide a solid foundation for delving into and narrowing down the array of potential solutions. These questions primarily concern enhancing the overall performance of distribution networks for perishable products and optimizing the package hierarchy, extending to unconventional packaging solutions. To address these research questions effectively, a well-defined research framework guides the approach. However, the dissertation adheres to an overarching methodological approach that comprises three fundamental aspects. The first aspect centers on the necessity of systematic data sampling and categorization, including identifying critical points within food supply chains. The data collected in this context must then be organized within a customized data structure designed to feed both cyber-physical and digital twins to quantify and analyze supply chain failures with a preventive perspective.

Contributions to the performance analysis of continuum parallel robots

Continuum parallel robots (CPRs) are manipulators employing multiple flexible beams arranged in parallel and connected to a rigid end-effector. CPRs promise higher payload and accuracy than serial CRs while keeping great flexibility. As the risk of injury during accidental contacts between a human and a CPR should be reduced, CPRs may be used in large-scale collaborative tasks or assisted robotic surgery. There exist various CPR designs, but the prototype conception is rarely based on performance considerations, and the CPRs realization in mainly based on intuitions or rigid-link parallel manipulators architectures. This thesis focuses on the performance analysis of CPRs, and the tools needed for such evaluation, such as workspace computation algorithms. In particular, workspace computation strategies for CPRs are essential for the performance assessment, since the CPRs workspace may be used as a performance index or it can serve for optimal-design tools. Two new workspace computation algorithms are proposed in this manuscript, the former focusing on the workspace volume computation and the certification of its numerical results, while the latter aims at computing the workspace boundary only. Due to the elastic nature of CPRs, a key performance indicator for these robots is the stability of their equilibrium configurations. This thesis proposes the experimental validation of the equilibrium stability assessment on a real prototype, demonstrating limitations of some commonly used assumptions. Additionally, a performance index measuring the distance to instability is originally proposed in this manuscript. Differently from the majority of the existing approaches, the clear advantage of the proposed index is a sound physical meaning; accordingly, the index can be used for a more straightforward performance quantification, and to derive robot specifications.

Development of gripping devices based on electroadhesive forces

In a context of technological innovation, the aim of this thesis is to develop a technology that has gained interest in both scientific and industrial realms. This technology serves as a viable alternative to outdated and energy-consuming industrial systems. Electro-adhesive devices (EADs) leverage electrostatic forces for grasping objects or adhering to surfaces. The advantage of employing electrostatics lies in its adaptability to various materials without compromising the structure or chemistry of the object or surface. These benefits have led the industry to explore this technology as a replacement for costly vacuum systems and suction cups currently used for handling most products. Furthermore, the broad applicability of this technology extends to extreme environments, such as space with ultra-high vacuum conditions. Unfortunately, research in this area has yet to yield practical results for industrially effective gripper prototyping. This is primarily due to the inherent complexity of electro-adhesive technology, which operates on basic capacitive principles that does not find satisfying physical descriptions. This thesis aims to address these challenges through a series of studies, starting with the manufacturing process and testing of an EAD that has become the standard in our laboratory. It then delves into material and electrode geometry studies to enhance system performance, ultimately presenting potential industrial applications of the technology. All the presented results are encouraging, as they have yielded shear force values three times higher than those previously reported in the literature. The various applications have demonstrated the significant effectiveness of EADs as brakes or, more broadly, in exerting shear forces. This opens up the possibility of utilizing cutting-edge technologies to push the boundaries of technology to the fullest.

Integrating the age factor in designing industrial environments and workstations in the workforce ageing era

As people spend a third of their lives at work and, in most cases, indoors, the work environment assumes crucial importance. The continuous and dynamic interaction between people and the working environment surrounding them produces physiological and psychological effects on operators. Recognizing the substantial impact of comfort and well-being on employee satisfaction and job performance, the literature underscores the need for industries to implement indoor environment control strategies to ensure long-term success and profitability. However, managing physical risks (i.e., ergonomic and microclimate) in industrial environments is often constrained by production and energy requirements. In the food processing industry, for example, the safety of perishable products dictates storage temperatures that do not allow for operator comfort. Conversely, warehouses dedicated to non-perishable products often lack cooling systems to limit energy expenditure, reaching high temperatures in the summer period. Moreover, exceptional events, like the COVID-19 pandemic, introduce new constraints, with recommendations impacting thermal stress and respiratory health. Furthermore, the thesis highlights how workers' variables, particularly the aging process, reduce tolerance to environmental stresses. Consequently, prolonged exposure to environmental stress conditions at work results in cardiovascular disease and musculoskeletal disorders. In response to the global trend of an aging workforce, the thesis bridges a literature gap by proposing methods and models that integrate the age factor into comfort assessment. It aims to present technical and technological solutions to mitigate microclimate risks in industrial environments, ultimately seeking innovative ways to enhance the aging workforce's comfort, performance, experience, and skills. The research outlines a logical-conceptual scheme with three main areas of focus: analyzing factors influencing the work environment, recognizing constraints to worker comfort, and designing solutions. The results significantly contribute to science by laying the foundation for new research in worker health and safety in an ageing working population's extremely current industrial context.

Impatto dell'uso dell'Edmonton Symptom Assessment System all'interno di un ambulatorio integrato di radioterapia e cure palliative sull'ottimizzazione della qualita di cura

I pazienti affetti da patologie oncologiche avanzate hanno un'esperienza di sintomi multipli spesso concomitanti tra loro. Lo scopo di questo progetto è quello di valutare come, nel contesto di un’ambulatorio integrato di Radioterapia e Cure Palliative (rep), sia possibile descrivere e quantificare i sintomi riportati dal paziente attraverso uno strumento di analisi convalidato, nello specifico l’Edmonton Symptom Assessment System (ESAS) al fine di costruire una proposta terapeutica ottimizzata per il singolo paziente. Da aprile 2016 ad aprile 2020, sono stati analizzati gli accessi al rep per un totale di 519 accessi, quindi abbiamo selezionato solo le visite dei pazienti che avevano completato totalmente lo strumento ESAS per la valutazione dei sintomi. La popolazione in studio era quindi composta da 212 pazienti, di questi 120 erano uomini, 92 erano donne, l'età media era di 72 anni, del totale il 36% era stato sottoposto a radioterapia. I principali risultati ottenuti dall'analisi dei dati relativi alla popolazione in studio sono stati i seguenti: 1) il 25% dei pazienti muore entro 2,2 mesi, il 60% entro 6 mesi; 2) la popolazione maschile ha un rischio di morte più elevato rispetto alla popolazione femminile; 3) Esiste una chiara differenza negli indici di correlazione tra la popolazione femminile e quella maschile 4) I principali sintomi correlati sono: dolore, mancanza di appetito, ansia, sonnolenza; 5) Il sintomo del dolore non è associato ad un aumento del rischio di morte, mentre la mancanza di appetito e sonnolenza sono associati ad un aumento del rischio di morte. In conclusione, i dati a nostra disposizione hanno dimostrato che un'analisi approfondita dei sintomi attraverso lo strumento ESAS è fattibile e necessaria portando informazioni fondamentali per una gestione ottimale del paziente, dandoci la possibilità di muoverci verso l'opportunità di trattamenti sempre più personalizzati e individualizzati in base alle caratteristiche dei singoli pazienti.

Numerical simulation of the flow and performance evaluation of an aerospike engine

The main focus of this work is to define a numerical methodology to simulate an aerospike engine and then to analyse the performance of DemoP1, which is a small aerospike demonstrator built by Pangea Aerospace. The aerospike is a promising solution to build more efficient engine than the actual one. Its main advantage is the expansion adaptation that allows to reach the optimal expansion in a wide range of ambient pressures delivering more thrust than an equivalent bell-shaped nozzle. The main drawbacks are the cooling system design and the spike manufacturing but nowadays, these issues seem to be overcome with the use of the additive manufacturing method. The simulations are performed with dbnsTurbFoam which is a solver of OpenFOAM. It has been designed to simulate a supersonic compressible turbulent flow. This work is divided in four chapters. The first one is a short introduction. The second one shows a brief summary of the theoretical performance of the aerospike. The third one introduces the numerical methodology to simulate a compressible supersonic flow. In the fourth chapter, the solver has been verified with an experiment found in literature. And in the fifth chapter, the simulations on DemoP1 engine are illustrated.