8 resultados para Illinois Spent Nuclear Fuel and High-Level Waste Inspection and Escort Program.
em AMS Tesi di Dottorato - Alm@DL - Università di Bologna
Resumo:
The present PhD thesis summarizes the three-years study about the neutronic investigation of a new concept nuclear reactor aiming at the optimization and the sustainable management of nuclear fuel in a possible European scenario. A new generation nuclear reactor for the nuclear reinassance is indeed desired by the actual industrialized world, both for the solution of the energetic question arising from the continuously growing energy demand together with the corresponding reduction of oil availability, and the environment question for a sustainable energy source free from Long Lived Radioisotopes and therefore geological repositories. Among the Generation IV candidate typologies, the Lead Fast Reactor concept has been pursued, being the one top rated in sustainability. The European Lead-cooled SYstem (ELSY) has been at first investigated. The neutronic analysis of the ELSY core has been performed via deterministic analysis by means of the ERANOS code, in order to retrieve a stable configuration for the overall design of the reactor. Further analyses have been carried out by means of the Monte Carlo general purpose transport code MCNP, in order to check the former one and to define an exact model of the system. An innovative system of absorbers has been conceptualized and designed for both the reactivity compensation and regulation of the core due to cycle swing, as well as for safety in order to guarantee the cold shutdown of the system in case of accident. Aiming at the sustainability of nuclear energy, the steady-state nuclear equilibrium has been investigated and generalized into the definition of the ``extended'' equilibrium state. According to this, the Adiabatic Reactor Theory has been developed, together with a New Paradigm for Nuclear Power: in order to design a reactor that does not exchange with the environment anything valuable (thus the term ``adiabatic''), in the sense of both Plutonium and Minor Actinides, it is required indeed to revert the logical design scheme of nuclear cores, starting from the definition of the equilibrium composition of the fuel and submitting to the latter the whole core design. The New Paradigm has been applied then to the core design of an Adiabatic Lead Fast Reactor complying with the ELSY overall system layout. A complete core characterization has been done in order to asses criticality and power flattening; a preliminary evaluation of the main safety parameters has been also done to verify the viability of the system. Burn up calculations have been then performed in order to investigate the operating cycle for the Adiabatic Lead Fast Reactor; the fuel performances have been therefore extracted and inserted in a more general analysis for an European scenario. The present nuclear reactors fleet has been modeled and its evolution simulated by means of the COSI code in order to investigate the materials fluxes to be managed in the European region. Different plausible scenarios have been identified to forecast the evolution of the European nuclear energy production, including the one involving the introduction of Adiabatic Lead Fast Reactors, and compared to better analyze the advantages introduced by the adoption of new concept reactors. At last, since both ELSY and the ALFR represent new concept systems based upon innovative solutions, the neutronic design of a demonstrator reactor has been carried out: such a system is intended to prove the viability of technology to be implemented in the First-of-a-Kind industrial power plant, with the aim at attesting the general strategy to use, to the largest extent. It was chosen then to base the DEMO design upon a compromise between demonstration of developed technology and testing of emerging technology in order to significantly subserve the purpose of reducing uncertainties about construction and licensing, both validating ELSY/ALFR main features and performances, and to qualify numerical codes and tools.
Resumo:
Bivalvia represents an ancient taxon including around 25,000 living species that have adapted to a wide range of environmental conditions, and show a great diversity in body size, shell shapes, and anatomic structure. Bivalves are characterized by highly variable genome sizes and extremely high levels of heterozygosity, which obstacle complete and accurate genome assemblies and hinder further genomic studies. Moreover, some bivalve species presented a stable evolutionary exception to the strictly maternal inheritance of mitochondria, namely doubly uniparental inheritance (DUI), making these species a precious model to study mitochondrial biology. During my PhD, I focused on a DUI species, the Manila clam Ruditapes philippinarum, and my work was two-folded. First, taking advantage of a newly assembled draft genome and a large RNA-seq dataset from different tissues of both sexes, I investigated 1) the role of gene expression and alternative splicing in tissue differentiation; 2) the relationship across tissue specificity, regulatory network connectivity, and sequence evolution; 3) sexual contrasting genetic markers potentially associated with sexual differentiation. The detailed information for this part is in Chapter 2. Second, using the same RNA-seq data, I investigated how nuclear oxidative phosphorylation (OXPHOS) genes coordinate with two divergent mitochondrial genomes in DUI species (mito-nuclear coordination and coevolution). To address this question, I compared transcription, polymorphism, and synonymous codon usage in the mitochondrial and nuclear OXPHOS genes of R. philippinarum in Chapter 3. To my knowledge, this thesis represents the first study exploring the role of alternative splicing in tissue differentiation, and the first study analyzing both transcriptional regulation and sequence evolution to investigate the coordination of OXPHOS genes in bivalves.
Resumo:
Nowadays, the spreading of the air pollution crisis enhanced by greenhouse gases emission is leading to the worsening of global warming. Recently, several metropolitan cities introduced Zero-Emissions Zones where the use of the Internal Combustion Engine is forbidden to reduce localized pollutants emissions. This is particularly problematic for Plug-in Hybrid Electric Vehicles, which usually work in depleting mode. In order to address these issues, the present thesis presents a viable solution by exploiting vehicular connectivity to retrieve navigation data of the urban event along a selected route. The battery energy needed, in the form of a minimum State of Charge (SoC), is calculated by a Speed Profile Prediction algorithm and a Backward Vehicle Model. That value is then fed to both a Rule-Based Strategy, developed specifically for this application, and an Adaptive Equivalent Consumption Minimization Strategy (A-ECMS). The effectiveness of this approach has been tested with a Connected Hardware-in-the-Loop (C-HiL) on a driving cycle measured on-road, stimulating the predictions with multiple re-routings. However, even if hybrid electric vehicles have been recognized as a valid solution in response to increasingly tight regulations, the reduced engine load and the repeated engine starts and stops may reduce substantially the temperature of the exhaust after-treatment system (EATS), leading to relevant issues related to pollutant emission control. In this context, electrically heated catalysts (EHCs) represent a promising solution to ensure high pollutant conversion efficiency without affecting engine efficiency and performance. This work aims at studying the advantages provided by the introduction of a predictive EHC control function for a light-duty Diesel plug-in hybrid electric vehicle (PHEV) equipped with a Euro 7-oriented EATS. Based on the knowledge of future driving scenarios provided by vehicular connectivity, engine first start can be predicted and therefore an EATS pre-heating phase can be planned.
Resumo:
The abundance of visual data and the push for robust AI are driving the need for automated visual sensemaking. Computer Vision (CV) faces growing demand for models that can discern not only what images "represent," but also what they "evoke." This is a demand for tools mimicking human perception at a high semantic level, categorizing images based on concepts like freedom, danger, or safety. However, automating this process is challenging due to entropy, scarcity, subjectivity, and ethical considerations. These challenges not only impact performance but also underscore the critical need for interoperability. This dissertation focuses on abstract concept-based (AC) image classification, guided by three technical principles: situated grounding, performance enhancement, and interpretability. We introduce ART-stract, a novel dataset of cultural images annotated with ACs, serving as the foundation for a series of experiments across four key domains: assessing the effectiveness of the end-to-end DL paradigm, exploring cognitive-inspired semantic intermediaries, incorporating cultural and commonsense aspects, and neuro-symbolic integration of sensory-perceptual data with cognitive-based knowledge. Our results demonstrate that integrating CV approaches with semantic technologies yields methods that surpass the current state of the art in AC image classification, outperforming the end-to-end deep vision paradigm. The results emphasize the role semantic technologies can play in developing both effective and interpretable systems, through the capturing, situating, and reasoning over knowledge related to visual data. Furthermore, this dissertation explores the complex interplay between technical and socio-technical factors. By merging technical expertise with an understanding of human and societal aspects, we advocate for responsible labeling and training practices in visual media. These insights and techniques not only advance efforts in CV and explainable artificial intelligence but also propel us toward an era of AI development that harmonizes technical prowess with deep awareness of its human and societal implications.
Resumo:
Visual search and oculomotor behaviour are believed to be very relevant for athlete performance, especially for sports requiring refined visuo-motor coordination skills. Modern coaches believe that a correct visuo-motor strategy may be part of advanced training programs. In this thesis two experiments are reported in which gaze behaviour of expert and novice athletes were investigated while they were doing a real sport specific task. The experiments concern two different sports: judo and soccer. In each experiment, number of fixations, fixation locations and mean fixation duration (ms) were considered. An observational analysis was done at the end of the paper to see perceptual differences between near and far space. Purpose: The aim of the judo study was to delineate differences in gaze behaviour characteristics between a population of athletes and one of non athletes. Aspects specifically investigated were: search rate, search order and viewing time across different conditions in a real-world task. The second study was aimed at identifying gaze behaviour in varsity soccer goalkeepers while facing a penalty kick executed with instep and inside foot. Then an attempt has been done to compare the gaze strategies of expert judoka and soccer goalkeepers in order to delineate possible differences related to the different conditions of reacting to events occurring in near (peripersonal) or far (extrapersonal) space. Judo Methods: A sample of 9 judoka (black belt) and 11 near judoka (white belt) were studied. Eye movements were recorded at 500Hz using a video based eye tracker (EyeLink II). Each subject participated in 40 sessions for about 40 minutes. Gaze behaviour was considered as average number of locations fixated per trial, the average number of fixations per trial, and mean fixation duration. Soccer Methods: Seven (n = 7) intermediate level male volunteered for the experiment. The kickers and goalkeepers, had at least varsity level soccer experience. The vision-in-action (VIA) system (Vickers 1996; Vickers 2007) was used to collect the coupled gaze and motor behaviours of the goalkeepers. This system integrated input from a mobile eye tracking system (Applied Sciences Laboratories) with an external video of the goalkeeper’s saving actions. The goalkeepers took 30 penalty kicks on a synthetic pitch in accordance with FIFA (2008) laws. Judo Results: Results indicate that experts group differed significantly from near expert for fixations duration, and number of fixations per trial. The expert judokas used a less exhaustive search strategy involving fewer fixations of longer duration than their novice counterparts and focused on central regions of the body. The results showed that in defence and attack situation expert group did a greater number of transitions with respect to their novice counterpart. Soccer Results: We found significant main effect for the number of locations fixated across outcome (goal/save) but not for foot contact (instep/inside). Participants spent more time fixating the areas in instep than inside kick and in goal than in save situation. Mean and standard error in search strategy as a result of foot contact and outcome indicate that the most gaze behaviour start and finish on ball interest areas. Conclusions: Expert goalkeepers tend to spend more time in inside-save than instep-save penalty, differences that was opposite in scored penalty kick. Judo results show that differences in visual behaviour related to the level of expertise appear mainly when the test presentation is continuous, last for a relatively long period of time and present a high level of uncertainty with regard to the chronology and the nature of events. Expert judoist performers “anchor” the fovea on central regions of the scene (lapel and face) while using peripheral vision to monitor opponents’ limb movements. The differences between judo and soccer gaze strategies are discussed on the light of physiological and neuropsychological differences between near and far space perception.
Resumo:
In the last decades the automotive sector has seen a technological revolution, due mainly to the more restrictive regulation, the newly introduced technologies and, as last, to the poor resources of fossil fuels remaining on Earth. Promising solution in vehicles’ propulsion are represented by alternative architectures and energy sources, for example fuel-cells and pure electric vehicles. The automotive transition to new and green vehicles is passing through the development of hybrid vehicles, that usually combine positive aspects of each technology. To fully exploit the powerful of hybrid vehicles, however, it is important to manage the powertrain’s degrees of freedom in the smartest way possible, otherwise hybridization would be worthless. To this aim, this dissertation is focused on the development of energy management strategies and predictive control functions. Such algorithms have the goal of increasing the powertrain overall efficiency and contextually increasing the driver safety. Such control algorithms have been applied to an axle-split Plug-in Hybrid Electric Vehicle with a complex architecture that allows more than one driving modes, including the pure electric one. The different energy management strategies investigated are mainly three: the vehicle baseline heuristic controller, in the following mentioned as rule-based controller, a sub-optimal controller that can include also predictive functionalities, referred to as Equivalent Consumption Minimization Strategy, and a vehicle global optimum control technique, called Dynamic Programming, also including the high-voltage battery thermal management. During this project, different modelling approaches have been applied to the powertrain, including Hardware-in-the-loop, and diverse powertrain high-level controllers have been developed and implemented, increasing at each step their complexity. It has been proven the potential of using sophisticated powertrain control techniques, and that the gainable benefits in terms of fuel economy are largely influenced by the chose energy management strategy, even considering the powerful vehicle investigated.
Resumo:
In the framework of a global transition to a low-carbon energy mix, the interest in advanced nuclear Small Modular Reactors (SMRs) has been growing at the international level. Due to the high level of maturity reached by Severe Accident Codes for currently operating rectors, their applicability to advanced SMRs is starting to be studied. Within the present work of thesis and in the framework of a collaboration between ENEA, UNIBO and IRSN, an ASTEC code model of a generic IRIS reactor has been developed. The simulation of a DBA sequence involving the operation of all the passive safety systems of the generic IRIS has been carried out to investigate the code model capability in the prediction of the thermal-hydraulics characterizing an integral SMR adopting a passive mitigation strategy. The following simulation of 4 BDBAs sequences explores the applicability of Severe Accident Codes to advance SMRs in beyond-design and core-degradation conditions. The uncertainty affecting a code simulation can be estimated by using the method of Input Uncertainty Propagation, whose application has been realized through the RAVEN-ASTEC coupling and implementation on an HPC platform. This probabilistic methodology has been employed in a study of the uncertainty affecting the passive safety system operation in the DBA simulation of ASTEC, providing a further characterization of the thermal-hydraulics of this sequence. The application of the Uncertainty Quantification method to early core-melt phenomena has been investigated in the framework of a BEPU analysis of the ASTEC simulation of the QUENCH test-6 experiment. A possible solution to the encountered challenges has been proposed through the application of a Limit Surface search algorithm.
Resumo:
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.