1,012 research outputs found

    Influence of sediments burying the discharge area of a karst aquifer on the groundwater flow field—Numerical testing of conceptual models

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    Karst springs are a natural result of karst water discharging to the surface through unimpeded pathways where the water table meets the surface. This study investigates the impact of alluvial deposits of varying thicknesses and permeabilities burying the main outlet (karst spring) of a well-developed conduit network on karst drainage, including the development of hydraulic heads, drainage patterns and conduit-matrix interactions in response to a positive base-level shift. Numerical testing using FEFLOW on a simplified conceptual model of a hypothetical karst aquifer with six different model configurations was used to examine various drainage structures (with and without flow through a conduit), spring conditions (free vs. partially/fully clogged), sediment cover thickness (20 and 50 m), and hydraulic conductivity of the sediments (low and high). The numerical testing model incorporated one-dimensional discrete feature elements to simulate conduit flow and coupled conduit-matrix interactions. Results indicate that even with a fully plugged outlet, the conduit network remains a significant contributor to the drainage system, collecting water from the matrix in the recharge zone. As the outlet becomes buried, the hydraulic head increases along the conduit, forcing water back up into the matrix. The elevated hydraulic head in the karst system will cause new conduits to form at the contact between limestone and sediments, creating new potential spring sites (or reactivating existing paleo-phreatic levels). Artesian conditions will occur below the low permeability sediments. These findings provide valuable insights into the responses of natural karst systems

    Dynamic analysis and energy management strategies of micro gas turbine systems integrated with mechanical, electrochemical and thermal energy storage devices

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    The growing concern related to the rise of greenhouse gases in the atmosphere has led to an increase of share of renewable energy sources. Due to their unpredictability and intermittency, new flexible and efficient power systems need to be developed to compensate for this fluctuating power production. In this context, micro gas turbines have high potential for small-scale combined heat and power (CHP) applications considering their fuel flexibility, quick load changes, low maintenance, low vibrations, and high overall efficiency. Furthermore, the combination of micro gas turbines with energy storage systems can further increase the overall system flexibility and the response to rapid load changes. This thesis aims to analyse the integration of micro gas turbines with the following energy storage systems: compressed air energy storage (CAES), chemical energy storage (using hydrogen and ammonia), battery storage, and thermal energy storage. In particular, micro gas turbines integrated with CAES systems and alternative fuels operate in different working conditions compared to their standard conditions. Applications requiring increased mass flow rate at the expander, such as CAES and the use of fuels with low LHV, such as ammonia, can potentially reduce the compressor surge margin. Conversely, sudden composition changes of high LHV fuels, such as hydrogen, can cause temperature peaks, detrimental for the turbine and recuperator life. A validated model of a T100 micro gas turbine is used to analyse transitions between different conditions, identify operational limits and test the control system. Starting from the dynamic constraints defined in the related chapters, in the final part, an optimisation tool for energy management is developed to couple the micro gas turbine with energy storage systems, maximizing the plant profitability and satisfying the local electrical and thermal demands. For the modelling of the CAES system and alternative fuels, the operating constraints obtained from the initial analyses are implemented in the optimisation tool. In addition, a battery and thermal energy storage system are also considered. In the first part, a comprehensive analysis of the T100 combined with a second-generation CAES system showed enhanced efficiency, reduced fuel consumption, reduced thermal power output and increased maximum electrical power output due to the reduction of the rotational speed. The study identified optimal air injection constraints, demonstrating a +3.23% efficiency increase at 80 kW net power with a maximum mass flow rate of 50 g/s. The dynamic analysis exposed potential instabilities issues during air step injections, mitigated by using ramps at a rate of +0.5 (g/s)/s for safe and rapid dynamic mode operation. The second part explored the effects of varying H2-NG and NH3-NG blends on the T100 mGT. Steady-state results showed increased power output with hydrogen or ammonia, notably +6.1 kW for 100% H2 and up to +11.3 kW for 100% NH3. Transient power steps simulations showed surge margin reductions, especially at lower power levels with high concentrations of ammonia, highlighting the need for controlled transitions. Controlled ramps were effective in preventing extreme temperature peaks during fuel composition changes. The final chapter focused on developing an energy scheduler for different plant setups, evaluating four configurations. For a typical day of the month of April of the Savona Campus, the integration of the CAES lead to relative savings of +8.1% and power-to-H2 of +5.3% when surplus electricity was not sold to the grid. Conversely, with the ability to sell excess electricity, CAES and battery energy storage (BES) systems exhibit modest savings of +1.2% and +2.4%, respectively, while the power-to-H2 system failed to provide economic advantages

    Short‐term biogeomorphology of a gravel‐bed river: Integrating remote sensing with hydraulic modelling and field analysis

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    In recent decades, fluvial geomorphology and ecohydraulic research have extensively used field observations, remote sensing or hydrodynamic modelling to understand river systems. This study presents an innovative approach that combines field surveys, Light Detection and Ranging (LiDAR)-based topographical and biomass analyses and model-derived hydro-morphodynamic geostatistics to examine short-term bio-geomorphological changes in the wandering gravel-bed Orco River in Italy. Our primary hypothesis is that hydro-morphological variables can be robust descriptors for riparian vegetation distribution. From a geomorphological perspective, our study con-firms the prevalent wandering behaviour of the Orco River. Moreover, we identified a widening trend in braiding and anabranching sections, particularly downstream.This is evident because of hotspots of flood-induced morphological reactivation and the redistribution of sediments from the riverbed to lateral bars, resulting in a multi-thread pattern. Our analysis reveals a net increase in biomass during the observation period despite frequent flood disturbances. We attributed it to two opposing bio-geomorphological dynamics: the reduced flow disturbance in some regions due to flood-induced geomorphological changes and the self-healing of lateral connectivity through river wandering. Such a net increase indicates that transitional rivers store carbon in the form of vegetation biomass due to their short-term morphological instability and the different timescales between vegetation and morphological adjustments. Finally, we supported our initial hypothesis with three key findings: (i) a signature of vegetation not just on topography but also on hydro-morphological conditions, summarised by inundation probability; (ii) the lower variance in vertical topographical changes in vegetated areas compared with bare ones; and (iii) the introduction of a new parameter, named inundation viscosity, derived from the product of mean bed shear stress and average inundation duration, as a discriminating factor for colonisation conditions. These results underscore the value of our comprehensive approach

    Evacuação de Edifícios – Caso de estudo de um edifício escolar

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    O objetivo deste trabalho é o levantamento dos aspetos que influenciam o tempo de evacuação num edifício escolar, desde o comportamento humano às caraterísticas físicas do edifício e às metodologias possíveis de adotar para a gestão da emergência, com vista a calcular o tempo necessário e disponível para a evacuação do referido edifício. A evacuação de edifícios em situação de incêndio tem como propósito a proteção da vida humana que é inseparável das condições de emergência as quais são afetadas por fatores de difícil determinação e que necessitam de ser definidos para estimar o tempo e as condições de evacuação.info:eu-repo/semantics/publishedVersio

    Digital agriculture: research, development and innovation in production chains.

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    Digital transformation in the field towards sustainable and smart agriculture. Digital agriculture: definitions and technologies. Agroenvironmental modeling and the digital transformation of agriculture. Geotechnologies in digital agriculture. Scientific computing in agriculture. Computer vision applied to agriculture. Technologies developed in precision agriculture. Information engineering: contributions to digital agriculture. DIPN: a dictionary of the internal proteins nanoenvironments and their potential for transformation into agricultural assets. Applications of bioinformatics in agriculture. Genomics applied to climate change: biotechnology for digital agriculture. Innovation ecosystem in agriculture: Embrapa?s evolution and contributions. The law related to the digitization of agriculture. Innovating communication in the age of digital agriculture. Driving forces for Brazilian agriculture in the next decade: implications for digital agriculture. Challenges, trends and opportunities in digital agriculture in Brazil

    Sistemi basati su ossidi metallici per l'efficiente conversione di luce visibile

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    Oggigiorno la ricerca nel campo delle fonti di energia rinnovabile è fondamentale per arginare la crisi climatica e superare la riduzione della disponibilità di combustibili fossili. Grazie all'elevata intensità dell'energia solare, molte ricerche si concentrano su metodi efficienti per convertirla in altre forme di energia (ad esempio, elettrica o chimica). Uno dei metodi più promettenti per convertire l'energia solare in energia chimica è la fotocatalisi a luce visibile. L'obiettivo principale di questa tesi è lo studio di sistemi su scala nanometrica che siano candidati promettenti per la fotocatalisi di luce visibile, ed in particolare di film sottili di ossido di rame e di ossido di cerio combinati con nanoparticelle (NPs) plasmoniche. Nel secondo caso, l'ossido di cerio è stato accoppiato con le NPs dal momento che l’energia di gap dell'ossido nudo è troppo ampia per l’assorbimento della radiazione visibile; mentre lavori precedenti hanno dimostrato che la formazione di un’eterogiunzione, ottenuta accoppiando nanostrutture plasmoniche con semiconduttori, può aumentare notevolmente l'attività di fotocatalizzatori mediante trasferimento di energia plasmonica dalla nanostruttura metallica al semiconduttore. La prima parte della tesi descriverà la crescita e la caratterizzazione di questi sistemi, volti ad estrarre informazioni sulle loro proprietà ottiche, con un focus specifico sulla dinamica ultraveloce e sull'evoluzione temporale degli stati eccitati. A tale scopo, sono stati studiati sistemi composti da Ag, Au e Cu NPs circondati da CeO2 mediante analisi di assorbanza ed emissione statiche e risolte nel tempo. In primo luogo, sono stati studiati sistemi composti da Ag NP con CeO2 con spettroscopia di fotoemissione risolta in tempo e spettroscopia di assorbimento a raggi X risolta in tempo con laser a elettroni liberi. In secondo luogo, la dinamica ultraveloce degli stati eccitati indotti dall'eccitazione della luce ultravioletta e visibile è stata esplorata in sistemi composti da Au NPs combinate con ossido di cerio, volti a comprendere i meccanismi di eccitazione, utilizzando la spettroscopia di assorbimento transitorio ultraveloce. Infine, l'ultima parte della tesi è focalizzata sulle Cu NPs, anch'esse incorporate in film di CeO2, o circondate da ossidi, in particolare Cu2O, che, grazie al suo band gap nella regione del visibile, è un candidato promettente per la catalisi della luce solare. Le Cu NPs sono state studiate in termini di morfologia, proprietà ottiche e stabilità in condizioni atmosferiche ed è stata sviluppata e studiata una procedura per la crescita di NPs con core metallico e shell di Cu2O. Infine, cristalli e film di Cu2O di diverso spessore sono stati cresciuti e analizzati mediante diffrazione elettronica a bassa energia, microscopia a effetto tunnel e spettroscopia di fotoluminescenza in un ampio intervallo di temperature per ottenere informazioni sul comportamento degli eccitoni.Nowadays, the research in the field of renewable energy sources is fundamental, to stem the climate crisis and to overcome the reducing availability of fossil fuels. Thanks to the high magnitude of solar energy a lot of research is focused on efficient methods to convert it into other energy forms (e.g. electric or chemical). One of the most promising methods to convert solar into chemical energy is visible light photocatalysis. The main aim of this thesis is the investigations of systems at the nanoscale that are promising candidates for visible light photocatalysis, and in particular of thin films of cuprous oxide and of cerium oxide combined with plasmonic nanoparticles (NPs). In the latter, cerium oxide has been coupled with NPs because the band gap of the bare oxide is too wide for the absorption of visible radiation, but previous works demonstrated that the formation of heterojunctions by coupling plasmonic nanostructures with semiconductors can greatly enhance the activity of photocatalysts by plasmonic energy transfer from the metal nanostructure to the semiconductor. The first part of the thesis will describe the growth and characterization of these systems, aimed to extract information on their optical properties, with a specific focus on the ultrafast dynamics and temporal evolution of excited states. For this purpose, systems composed by Ag, Au and Cu NPs surrounded by CeO2 have been investigated by means of time-resolved and static absorbance and emission analysis. First, systems composed by Ag NPs with CeO2 have been studied with time-resolved photoemission spectroscopy and free electron laser time-resolved X-ray absorption spectroscopy. Secondly, the ultrafast dynamics of excited states induced by ultra-violet and visible light excitation has been explored in Au NPs combined with cerium oxide, aimed at understanding the excitation pathways, using femtosecond transient absorption spectroscopy. Finally, the last part of the thesis is focused on Cu NPs, also embedded in CeO2 films, or surrounded by oxides, in particular on Cu2O, that, thanks to its band gap in the visible region, is a promising candidate for solar light catalysis. Cu NPs have been investigated in terms of their morphology, optical properties, and stability in air conditions, and a procedure for growing metallic core-Cu2O shell has been developed and investigated. Finally, Cu2O crystals and films of different thickness have been grown and analyzed by means of low energy electron diffraction, scanning tunneling microscopy and photoluminescence spectroscopy in a wide temperature range to obtain information on the behavior of excitons

    Agroenvironmental modeling and the digital transformation of agriculture.

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    Introduction. The evolution of agroenvironmental modelling. Agroenvironmental modeling products to support decision-making. Databases for agricultural and environmental research: Agritempo, Conprees. Risk assessments and climate resilience evaluation: Agricultural Climate Risk Zoning (ZARC), Plantio Certo (Sure Sowing). Support for agricultural planning and monitoring: Invernada, WebAgritec. Climate change impact assessments and agricultural adaptation based on agroenvironmental models. Climatic projections. Agricultural impacts. Simulation of future agricultural scenarios. Territorial planning and land use: Agroideal, DINACER. Applications of agroenvironmental models for the conservation of ecosystem services: WebAmbiente, Hydric resources, Integration of socio-economic analysis in agro-environmental modeling, Applications for quantification and mitigation strategies for GHG emissions. Final considerations

    The Flow Matrix Offers a Straightforward Alternative to the Problematic Markov Matrix

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    The Flow matrix is a novel method to describe and extrapolate transitions among categories. The Flow matrix extrapolates a constant transition size per unit of time on a time continuum with a maximum of one incident per observation during the extrapolation. The Flow matrix extrapolates linearly until the persistence of a category shrinks to zero. The Flow matrix has concepts and mathematics that are more straightforward than the Markov matrix. However, many scientists apply the Markov matrix by default because popular software packages offer no alternative to the Markov matrix, despite the conceptual and mathematical challenges that the Markov matrix poses. The Markov matrix extrapolates a constant transition proportion per time interval during whole-number multiples of the duration of the calibration time interval. The Markov extrapolation allows at most one incident per observation during each time interval but allows repeated incidents per observation through sequential time intervals. Many Markov extrapolations approach a steady state asymptotically through time as each category size approaches a constant. We use case studies concerning land change to illustrate the characteristics of the Flow and Markov matrices. The Flow and Markov extrapolations both deviate from the reference data during a validation time interval, implying there is no reason to prefer one matrix to the other in terms of correspondence with the processes that we analyzed. The two matrices differ substantially in terms of their underlying concepts and mathematical behaviors. Scientists should consider the ease of use and interpretation for each matrix when extrapolating transitions among categories. © 2023 by the authors

    Machine Learning Algorithm for the Scansion of Old Saxon Poetry

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    Several scholars designed tools to perform the automatic scansion of poetry in many languages, but none of these tools deal with Old Saxon or Old English. This project aims to be a first attempt to create a tool for these languages. We implemented a Bidirectional Long Short-Term Memory (BiLSTM) model to perform the automatic scansion of Old Saxon and Old English poems. Since this model uses supervised learning, we manually annotated the Heliand manuscript, and we used the resulting corpus as labeled dataset to train the model. The evaluation of the performance of the algorithm reached a 97% for the accuracy and a 99% of weighted average for precision, recall and F1 Score. In addition, we tested the model with some verses from the Old Saxon Genesis and some from The Battle of Brunanburh, and we observed that the model predicted almost all Old Saxon metrical patterns correctly misclassified the majority of the Old English input verses
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