6 resultados para Crack-bridging

em AMS Tesi di Dottorato - Alm@DL - Università di Bologna


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The main scope of this Ph.D. thesis has concerned the possible transformations of bridging ligands in diiron complexes, in order to explore unconventional routes to the synthesis of new functionalized multisite bound organic frames. The results achieved during the Ph.D. can be summarized in the following points: 1) We have extended the assembling between small unsaturated molecules and bridging carbyne ligands in diiron complexes to other species. In particular, we have investigated the coupling between olefins and thiocarbyne, leading to the synthesis of thioallylidene bridging diiron complexes. Then, we have extended the study to the coupling between olefins and aminocarbyne. This result shows that the coupling between activated olefins and heteroatom substituted bridging carbynes has a general character. 2) As we have shown, the coupling of bridging alkylidyne ligands with alkynes and alkenes provides excellent routes to the synthesis of bridging C3 hydrocarbyl ligands. As a possible extension of these results we have examined the synthesis of C4 bridging frames through the combination of bridging alkylidynes with allenes. Also in this case the reaction has a general character. 3) Diiron complexes bearing bridging functionalized C3 organic frames display the presence of donor atoms, such as N and S, potentially able to coordinate unsaturated metal fragments. Thus, we have studied the possibility for these systems to act as ‘organometallic ligands’, in particular towards Pd and Rh. 4) The possibility of releasing the organic frame from the bridging coordination appears particularly appealing in the direction of a metal-assisted organic synthesis. Within this field, we have investigated the possibility of involving the C3 bridging ligand in cycloaddition reactions with alkynes, with the aim of generating variously functionalized five-membered cycles. The [3+2] cyclization does not lead to the complete release of the organic fragment but rather it produces its transformation into a cyclopentadienyl ring, which remains coordinated to one Fe atom. This result introduces a new approach to the formation of polyfunctionalised ferrocenes. 5) Furthermore, I have spent a research period of about six months at the Department of Inorganic Chemistry of the Barcelona University, under the supervision of Prof. Concepción López, with the aim of studying the chemistry of polydentate ferrocenyl ligands and their use in organometallic synthesis.

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In the frame of EU rural policy, always more oriented towards environmental concerns and green livelihoods, Romania stands out for the predominance of rural areas and high nature value farming. The country has to face the challenge of joining the modernization process of rural farming systems with the valorization of local assets. Tourism has emerged as one of the main drivers of change and contributors for a sustainable exploitation of local resources. Rural tourism (RT) can foster the enhancement of the territorial capital (TC), the preservation of public goods (PGs) and the promotion of a more environmental oriented livelihood. The research focuses on a case study area, two valleys from Maramureş, where environmental approaches as diversification strategies are partially explored. The work investigates the role of tourism initiatives for the promotion of green oriented practices. The first part of the work is based on a literature review and interdisciplinary analysis of secondary data to identify the key issues: from rural development policy, to the concept of TC, of PGs and RT. The Romanian development programmes and related strategies are investigated; afterwards the characteristics of the County and the role of RT as diversification and valorisation policies is considered. The second part is based on the collection of primary data through interviews to different local stakeholders (farmers owners of rural guesthouses, local administrators, networks and artisans). The main frequencies are analyzed, a cluster analysis is computed to evaluate the similarities within the most representative groups and a comparative analysis is carried out between the two Valleys. The frame of the analysis is based on a set of indicators following the dimensions of the TC, to assess the characteristics of the local stakeholders and to outline the perception about the local PGs and on the adopted strategies to manage the territory. Final considerations are elaborated and few scenarios are outlined, giving relevance to the importance of improving awareness and creating embeddedness among public-private local stakeholders and resources as a tool for a socio-economic and environmental development of the area.

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On the basis of well-known literature, an analytical tool named LEAF (Linear Elastic Analysis of Fracture) was developed to predict the Damage Tolerance (DT) proprieties of aeronautical stiffened panels. The tool is based on the linear elastic fracture mechanics and the displacement compatibility method. By means of LEAF, an extensive parametric analysis of stiffened panels, representative of typical aeronautical constructions, was performed to provide meaningful design guidelines. The effects of riveted, integral and adhesively bonded stringers on the fatigue crack propagation performances of stiffened panels were investigated, as well as the crack retarder contribution using metallic straps (named doublers) bonded in the middle of the stringers bays. The effect of both perfectly bonded and partially debonded doublers was investigated as well. Adhesively bonded stiffeners showed the best DT properties in comparison with riveted and integral ones. A great reduction of the skin crack growth propagation rate can be achieved with the adoption of additional doublers bonded between the stringers.

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Laser Shock Peening (LSP) is a surface enhancement treatment which induces a significant layer of beneficial compressive residual stresses up to several mm underneath the surface of metal components in order to improve the detrimental effects of crack growth behavior rate in it. The aim of this thesis is to predict the crack growth behavior of thin Aluminum specimens with one or more LSP stripes defining a compressive residual stress area. The LSP treatment has been applied as crack retardation stripes perpendicular to the crack growing direction, with the objective of slowing down the crack when approaching the LSP patterns. Different finite element approaches have been implemented to predict the residual stress field left by the laser treatment, mostly by means of the commercial software Abaqus/Explicit. The Afgrow software has been used to predict the crack growth behavior of the component following the laser peening treatment and to detect the improvement in fatigue life comparing to the specimen baseline. Furthermore, an analytical model has been implemented on the Matlab software to make more accurate predictions on fatigue life of the treated components. An educational internship at the Research and Technologies Germany- Hamburg department of Airbus helped to achieve knowledge and experience to write this thesis. The main tasks of the thesis are the following: -To up to date Literature Survey related to laser shock peening in metallic structures -To validate the FE models developed against experimental measurements at coupon level -To develop design of crack growth slow down in centered and edge cracked tension specimens based on residual stress engineering approach using laser peened patterns transversal to the crack path -To predict crack growth behavior of thin aluminum panels -To validate numerical and analytical results by means of experimental tests.

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This exploratory research project developed a cognitive situated approach to studying aspects of simultaneous interpreting with quantitative, confirmatory methods. To do so, it explored how to determine the potential benefits of using a computer-assisted interpreting tool, InterpretBank, among 22 Chinese interpreting trainees with Chinese L1 and English L2. The informants were mostly 2nd-year female students with an average age of 24.7 enrolled in Chinese MA interpreting programs. The study adopted a pretest and posttest design with three cycles. The independent variable was using Excel or InterpretBank. After Cycle I (pre-test), the sample split into control (Excel) and experimental (InterpretBank) groups. Tool choice was compulsory in Cycle II but not Cycle III. The source materials for each cycle were pairs of matching transcripts from popular science podcasts. Informants compiled glossaries out of one transcript, while the other one was edited for simultaneous interpreting, with 39 terms as potential problem triggers. Quantitative profiling results showed that InterpretBank informants spent less time on glossary compilation, generated more terms faster than Excel informants, but their glossaries were less diverse (personal) and longer. The booth tasks yielded no significant differences in fluency indicators except for more bumps (200-600ms silent time gaps) for InterpretBank in Cycle II. InterpretBank informants had more correct renditions in Cycles II and III but there was no statistically significant difference among accuracy indicators per cycle. Holistic quality assessments by PhD raters showed InterpretBank consistently outperforming Excel, suggesting a positive InterpretBank impact on SI quality. However, some InterpretBank implementations raised cognitive ergonomic concerns for Chinese, potentially undermining its utility. Overall, results were mixed regarding InterpretBank benefits for Chinese trainees, but the project was successful in developing cognitive situated interpreting study methods, constructs and indicators.

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Riding the wave of recent groundbreaking achievements, artificial intelligence (AI) is currently the buzzword on everybody’s lips and, allowing algorithms to learn from historical data, Machine Learning (ML) emerged as its pinnacle. The multitude of algorithms, each with unique strengths and weaknesses, highlights the absence of a universal solution and poses a challenging optimization problem. In response, automated machine learning (AutoML) navigates vast search spaces within minimal time constraints. By lowering entry barriers, AutoML emerged as promising the democratization of AI, yet facing some challenges. In data-centric AI, the discipline of systematically engineering data used to build an AI system, the challenge of configuring data pipelines is rather simple. We devise a methodology for building effective data pre-processing pipelines in supervised learning as well as a data-centric AutoML solution for unsupervised learning. In human-centric AI, many current AutoML tools were not built around the user but rather around algorithmic ideas, raising ethical and social bias concerns. We contribute by deploying AutoML tools aiming at complementing, instead of replacing, human intelligence. In particular, we provide solutions for single-objective and multi-objective optimization and showcase the challenges and potential of novel interfaces featuring large language models. Finally, there are application areas that rely on numerical simulators, often related to earth observations, they tend to be particularly high-impact and address important challenges such as climate change and crop life cycles. We commit to coupling these physical simulators with (Auto)ML solutions towards a physics-aware AI. Specifically, in precision farming, we design a smart irrigation platform that: allows real-time monitoring of soil moisture, predicts future moisture values, and estimates water demand to schedule the irrigation.