Optimizing fused deposition modelling: the impact of geometrical slicing parameters on mechanical properties

This comprehensive study explores the intricate world of 3D printing, with a focus on Fused Deposition Modelling (FDM). It sheds light on the critical factors that influence the quality and mechanical properties of 3D printed objects. Using an optical microscope with 40X magnification, the shapes of the printed beads is correlated to specific slicing parameters, resulting in a 2D parametric model. This mathematical model, derived from real samples, serves as a tool to predict general mechanical behaviour, bridging the gap between theory and practice in FDM printing. The study begins by emphasising the importance of geometric parameters such as layer height, line width and filament tolerance on the final printed bead geometry and the resulting theoretical effect on mechanical properties. The introduction of VPratio parameter (ratio between the area of the voids and the area occupied by printed material) allows the quantification of the variation of geometric slicing parameters on the improvement or reduction of mechanical properties. The study also addresses the effect of overhang and the role of filament diameter tolerances. The research continues with the introduction of 3D FEM (Finite Element Analysis) models based on the RVE (Representative Volume Element) to verify the results obtained from the 2D model and to analyse other aspects that affect mechanical properties and not directly observable with the 2D model. The study also proposes a model for the examination of 3D printed infill structures, introducing also an innovative methodology called “double RVE” which speeds up the calculation of mechanical properties and is also more computationally efficient. Finally, the limitations of the RVE model are shown and a so-called Hybrid RVE-based model is created to overcome the limitations and inaccuracy of the conventional RVE model and homogenization procedure on some printed geometries.

Urban air mobility: modelling the future transport system

The advances in the aviation field, particularly the development of electric flying vehicles, as UAV and eVTOL, paved the way for setting Urban Air Mobility (UAM) services. UAM would provide services for passengers, goods and emergencies and could offer faster trips than ground ones. It is expected that early UAM operations will be performed at Very Low-Level airspace as 0-500 m Above Ground Level. The purpose of this research is to both explore the main features of UAM and test an aerial network model, which could be integrated in a multimodal transport system where ground and aerial mobility services are provided. Analyses on UAM transport system involved two sub-systems: the transport demand sub-system, i.e., the mobility requirements, and the transport supply sub-system, i.e., the service and facilities enabling mobility. At first, the UAM demand levels and features for an Airport Shuttle service have been explored through a suitable survey, by combining Revealed and Stated Preference methodologies, and by calibrating some discrete mode choice models. Then, the focus has been on the transport supply model for UAM services, by focusing on both the ground access points (vertiports) and the aerial network model. A suitable three-dimensional urban aerial network (3D-UAN) model that could support fast aerial connections between O/D pairs has been proposed. Some tests have been implemented to verify the feasibility of the proposed model. Some flying vehicles supporting an Airport Shuttle service have been simulated on the aerial network, which has been specified in terms of both topological features and link transport costs. The preliminary results have showed that the proposed 3D-UAN model could be suitable for supporting UAM services. As for transport engineering, the UAM system framework proposed in this thesis paves the way for further research on air-ground multimodality in urban areas.

Modelling the infrastructure of the “Śivadharma Database”

A Digital Scholarly Edition is a conceptually and structurally sophisticated entity. Throughout the centuries, diverse methodologies have been employed to reconstruct a text transmitted through one or multiple sources, resulting in various edition types. With the advent of digital technology in philology, these practices have undergone a significant transformation, compelling scholars to reconsider their approach in light of the web. In the digital age, philologists are expected to possess (too) advanced technical skills to prepare interactive and enriched editions, even though, in most cases, only mechanical or documentary editions are published online. The Śivadharma Database is a web Content Management System (CMS) designed to facilitate the preparation, publication, and updating of Digital Scholarly Editions. By providing scholars with a user-friendly CRUD web application to reconstruct and annotate a text, they can prepare their textus with additional components such as apparatus, notes, translations, citations, and parallels. It is possible by leveraging an annotation system based on HTML and graph data structure. This choice is made because the text entity is multidimensional and multifaceted, even if its sequential presentation constrains it. In particular, editions of South Asian texts of the Śivadharma corpus, the case study of this research, contain a series of phenomena that are difficult to manage formally, such as overlapping hierarchies. Hence, it becomes necessary to establish the data structure best suited to represent this complexity. In Śivadharma Database, the textus is an HTML file readily displayable. Textual fragments, annotated via an interface without requiring philologists to write code and saved in the backend, form the atomic unit of multiple relationships organised in a graph database. This approach enables the formal representation of complex and overlapping textual phenomena, allowing for good annotation expressiveness with minimal effort to learn the relevant technologies during the editing workflow.

Modelling the Halo mass number counts in modified gravity cosmological scenarios

In this Thesis work we investigate some of different cosmological background scenarios using one of the main probes used in cosmology: the halo mass function. The observed abundance of galaxy clusters (or similarly DM haloes) can indeed be compared to its theoretical predictions to derive fundamental constrains on the cosmological scenario assumed. Given the importance of exploring and constraining models degenerate with the ΛCDM one, we test the applicability of some notable halo mass function models to these scenarios. To this purpose, we made use of the DUSTGRAIN-pathfinder N-body simulations, which assume cosmological scenarios that include modified gravity in the form of f(R) models and massive neutrinos. We carried on the analysis of 3 simulation snapshots at different redshifts, z = 0, 0.5, 1, building multiple samples of dark matter haloes by applying different overdensity thresholds during the procedure of halo identification. We started our analysis by considering the halo mass function model introduced by Despali et al. (2016), who proposed a parametrization that encapsulates the effect of the different halo mass definitions and the relative evolution with the redshift. We calibrated the main parameters of this relation by using the ΛCDM halo catalogues extracted from the DUSTGRAIN-pathfinder simulations, fitting the measured halo abundances at all redshifts and density thresholds. Afterwards we tested the same model parametrization with halo catalogues extracted from the simulations implementing both modified gravity and massive neutrinos. We repeated therefore the calibration procedure on these data to search for discrepancies with respect to the ΛCDM model. Finally we focused the analysis on the cosmological models implementing modified gravity only. We took our ΛCDM calibrated halo mass function and we modified it with the additional f (R) gravity form proposed by Gupta et al. (2022).

Mobile Robot navigation modelling, control and applications

This work presents and discusses the main topics involved on the design of a mobile robot system and focus on the control and navigation systems for autonomous mobile robots. Introduces the main aspects of the Robot design, which is a holistic vision about all the steps of the development process of an autonomous mobile robot; discusses the problems addressed to the conceptualization of the mobile robot physical structure and its relation to the world. Presents the dynamic and control analysis for navigation robots with kinematic and dynamic model and, for final, presents applications for a robotic platform of Automation, Simulation, Control and Supervision of Mobile Robots Navigation, with studies of dynamic and kinematic modelling, control algorithms, mechanisms for mapping and localization, trajectory planning and the platform simulator. © 2012 Praise Worthy Prize S.r.l. - All rights reserved.

Cheaper Faster Drug Development Validated By The Repositioning Of Drugs Against Neglected Tropical Diseases.

There is an urgent need to make drug discovery cheaper and faster. This will enable the development of treatments for diseases currently neglected for economic reasons, such as tropical and orphan diseases, and generally increase the supply of new drugs. Here, we report the Robot Scientist 'Eve' designed to make drug discovery more economical. A Robot Scientist is a laboratory automation system that uses artificial intelligence (AI) techniques to discover scientific knowledge through cycles of experimentation. Eve integrates and automates library-screening, hit-confirmation, and lead generation through cycles of quantitative structure activity relationship learning and testing. Using econometric modelling we demonstrate that the use of AI to select compounds economically outperforms standard drug screening. For further efficiency Eve uses a standardized form of assay to compute Boolean functions of compound properties. These assays can be quickly and cheaply engineered using synthetic biology, enabling more targets to be assayed for a given budget. Eve has repositioned several drugs against specific targets in parasites that cause tropical diseases. One validated discovery is that the anti-cancer compound TNP-470 is a potent inhibitor of dihydrofolate reductase from the malaria-causing parasite Plasmodium vivax.

Robust Mixture Modelling Using the t Distribution

Normal mixture models are being increasingly used to model the distributions of a wide variety of random phenomena and to cluster sets of continuous multivariate data. However, for a set of data containing a group or groups of observations with longer than normal tails or atypical observations, the use of normal components may unduly affect the fit of the mixture model. In this paper, we consider a more robust approach by modelling the data by a mixture of t distributions. The use of the ECM algorithm to fit this t mixture model is described and examples of its use are given in the context of clustering multivariate data in the presence of atypical observations in the form of background noise.

Modelling of the kinetics of municipal solid waste composting in full-scale mechanical-biological treatment plants

A thesis submitted in fulfilment of the requirements for the Degree of Doctor of Philosophy in Sanitary Engineering in the Faculty of Sciences and Technology of the New University of Lisbon

Stochastic modelling of the reservoir lithological and petrophysical attributes. A case study of the Middle East carbonate reservoir

Dissertação para obtenção do Grau de Mestre em Engenharia Geológica (Georrecursos)

Study on the development of an autonomous mobile robot

Dissertação para obtenção do Grau de Mestre em Engenharia Eletrotécnica e de Computadores

The regional employment impacts of renewable energy expenditures: The case for modelling

One aspect of the case for policy support for renewable energy developments is the wider economic benefits that are expected to be generated. Within Scotland, as with other regions of the UK, there is a focus on encouraging domestically‐based renewable technologies. In this paper, we use a regional computable general equilibrium framework to model the impact on the Scottish economy of expenditures relating to marine energy installations. The results illustrate the potential for (considerable) ‘legacy’ effects after expenditures cease. In identifying the specific sectoral expenditures with the largest impact on (lifetime) regional employment, this approach offers important policy guidance.

The regional employment impacts of renewable energy expenditures: The case for modelling

One aspect of the case for policy support for renewable energy developments is the wider economic benefits that are expected to be generated. Within Scotland, as with other regions of the UK, there is a focus on encouraging domestically‐based renewable technologies. In this paper, we use a regional computable general equilibrium framework to model the impact on the Scottish economy of expenditures relating to marine energy installations. The results illustrate the potential for (considerable) ‘legacy’ effects after expenditures cease. In identifying the specific sectoral expenditures with the largest impact on (lifetime) regional employment, this approach offers important policy guidance.

The regional economic impacts of biofuels: A review of multisectoral modelling techniques and evaluation of applications

The regional economic impact of biofuel production depends upon a number of interrelated factors: the specific biofuels feedstock and production technology employed; the sector’s embeddedness to the rest of the economy, through its demand for local resources; the extent to which new activity is created. These issues can be analysed using multisectoral economic models. Some studies have used (fixed price) Input-Output (IO) and Social Accounting Matrix (SAM) modelling frameworks, whilst a nascent Computable General Equilibrium (CGE) literature has also begun to examine the regional (and national) impact of biofuel development. This paper reviews, compares and evaluates these approaches for modelling the regional economic impacts of biofuels.

The regional economic impacts of biofuels: A review of multisectoral modelling techniques and evaluation of applications

The regional economic impact of biofuel production depends upon a number of interrelated factors: the specific biofuels feedstock and production technology employed; the sector’s embeddedness to the rest of the economy, through its demand for local resources; the extent to which new activity is created. These issues can be analysed using multisectoral economic models. Some studies have used (fixed price) Input-Output (IO) and Social Accounting Matrix (SAM) modelling frameworks, whilst a nascent Computable General Equilibrium (CGE) literature has also begun to examine the regional (and national) impact of biofuel development. This paper reviews, compares and evaluates these approaches for modelling the regional economic impacts of biofuels.

The carbohydrate-binding specificity and molecular modelling of Canavalia maritima and Dioclea grandiflora lectins

The carbohydrate-binding specificity of lectins from the seeds of Canavalia maritima and Dioclea grandiflora was studied by hapten-inhibition of haemagglutination using various sugars and sugar derivatives as inhibitors, including N-acetylneuraminic acid and N-acetylmuramic acid. Despite some discrepancies, both lectins exhibited a very similar carbohydrate-binding specificity as previously reported for other lectins from Diocleinae (tribe Phaseoleae, sub-tribe Diocleinae). Accordingly, both lectins exhibited almost identical hydropathic profiles and their three-dimensional models built up from the atomic coordinates of ConA looked very similar. However, docking experiments of glucose and mannose in their monosaccharide-binding sites, by comparison with the ConA-mannose complex used as a model, revealed conformational changes in side chains of the amino acid residues involved in the binding of monosaccharides. These results fully agree with crystallographic data showing that binding of specific ligands to ConA requires conformational chances of its monosaccharide-binding site.