Shear behaviour of reinforced cconcrete slab under concentrated load: an investigation through non-linear and sequentially linear analysis

English: The assessment of safety in existing bridges and viaducts led the Ministry of Public Works of the Netherlands to finance a specific campaing aimed at the study of the response of the elements of these infrastructures. Therefore, this activity is focused on the investigation of the behaviour of reinforced concrete slabs under concentrated loads, adopting finite element modeling and comparison with experimental results. These elements are characterized by shear behaviour and crisi, whose modeling is, from a computational point of view, a hard challeng, due to the brittle behavior combined with three-dimensional effects. The numerical modeling of the failure is studied through Sequentially Linear Analysis (SLA), an alternative Finite Element method, with respect to traditional incremental and iterative approaches. The comparison between the two different numerical techniques represents one of the first works and comparisons in a three-dimensional environment. It's carried out adopting one of the experimental test executed on reinforced concrete slabs as well. The advantage of the SLA is to avoid the well known problems of convergence of typical non-linear analysis, by directly specifying a damage increment, in terms of reduction of stiffness and resistance in particular finite element, instead of load or displacement increasing on the whole structure . For the first time, particular attention has been paid to specific aspects of the slabs, like an accurate constraints modeling and sensitivity of the solution with respect to the mesh density. This detailed analysis with respect to the main parameters proofed a strong influence of the tensile fracture energy, mesh density and chosen model on the solution in terms of force-displacement diagram, distribution of the crack patterns and shear failure mode. The SLA showed a great potential, but it requires a further developments for what regards two aspects of modeling: load conditions (constant and proportional loads) and softening behaviour of brittle materials (like concrete) in the three-dimensional field, in order to widen its horizons in these new contexts of study.

Creating a terminology resource for local food from Modena and localizing a traditional restaurant's website.

This thesis describes a project of terminology and localization focused on local and traditional cuisine from the province of Modena: the final products of this project are a specialized termbase and the localized version of the website of Trattoria Ermes, a small Modenese restaurant offering traditional dishes. It is a known fact the Internet has drastically altered the way companies and businesses communicate with their audience. Considering that food tourism is an invaluable sector of Italy’s economy and a great aid to safeguarding its culinary traditions, business owners can benefit from localizing their websites, allowing them to reach wider international audiences. The project is divided into two main sections: the first focuses on the terminological systematization of specialized terminology collected from Sandro Bellei’s cooking book and two web-derived monolingual corpora, while the second section offers insight into the analysis of the localization and optimization process of Trattoria Ermes website. In particular, the thesis approaches localization from the point of view of web marketing, with a theoretical and practical section dedicated to the Search Engine Optimization (SEO) processes employed by web marketing teams to ensure the visibility and popularity of the website

Neural Network based Non Orthogonal Random Access for 6G NTN-IoT

Pervasive and distributed Internet of Things (IoT) devices demand ubiquitous coverage beyond No-man’s land. To satisfy plethora of IoT devices with resilient connectivity, Non-Terrestrial Networks (NTN) will be pivotal to assist and complement terrestrial systems. In a massiveMTC scenario over NTN, characterized by sporadic uplink data reports, all the terminals within a satellite beam shall be served during the short visibility window of the flying platform, thus generating congestion due to simultaneous access attempts of IoT devices on the same radio resource. The more terminals collide, the more average-time it takes to complete an access which is due to the decreased number of successful attempts caused by Back-off commands of legacy methods. A possible countermeasure is represented by Non-Orthogonal Multiple Access scheme, which requires the knowledge of the number of superimposed NPRACH preambles. This work addresses this problem by proposing a Neural Network (NN) algorithm to cope with the uncoordinated random access performed by a prodigious number of Narrowband-IoT devices. Our proposed method classifies the number of colliding users, and for each estimates the Time of Arrival (ToA). The performance assessment, under Line of Sight (LoS) and Non-LoS conditions in sub-urban environments with two different satellite configurations, shows significant benefits of the proposed NN algorithm with respect to traditional methods for the ToA estimation.