9,544 research outputs found

    Atypical developmental trajectories of white matter microstructure in prenatal alcohol exposure: Preliminary evidence from neurite orientation dispersion and density imaging

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    IntroductionFetal alcohol spectrum disorder (FASD), a life-long condition resulting from prenatal alcohol exposure (PAE), is associated with structural brain anomalies and neurobehavioral differences. Evidence from longitudinal neuroimaging suggest trajectories of white matter microstructure maturation are atypical in PAE. We aimed to further characterize longitudinal trajectories of developmental white matter microstructure change in children and adolescents with PAE compared to typically-developing Controls using diffusion-weighted Neurite Orientation Dispersion and Density Imaging (NODDI).Materials and methodsParticipants: Youth with PAE (n = 34) and typically-developing Controls (n = 31) ages 8–17 years at enrollment. Participants underwent formal evaluation of growth and facial dysmorphology. Participants also completed two study visits (17 months apart on average), both of which involved cognitive testing and an MRI scan (data collected on a Siemens Prisma 3 T scanner). Age-related changes in the orientation dispersion index (ODI) and the neurite density index (NDI) were examined across five corpus callosum (CC) regions defined by tractography.ResultsWhile linear trajectories suggested similar overall microstructural integrity in PAE and Controls, analyses of symmetrized percent change (SPC) indicated group differences in the timing and magnitude of age-related increases in ODI (indexing the bending and fanning of axons) in the central region of the CC, with PAE participants demonstrating atypically steep increases in dispersion with age compared to Controls. Participants with PAE also demonstrated greater increases in ODI in the mid posterior CC (trend-level group difference). In addition, SPC in ODI and NDI was differentially correlated with executive function performance for PAE participants and Controls, suggesting an atypical relationship between white matter microstructure maturation and cognitive function in PAE.DiscussionPreliminary findings suggest subtle atypicality in the timing and magnitude of age-related white matter microstructure maturation in PAE compared to typically-developing Controls. These findings add to the existing literature on neurodevelopmental trajectories in PAE and suggest that advanced biophysical diffusion modeling (NODDI) may be sensitive to biologically-meaningful microstructural changes in the CC that are disrupted by PAE. Findings of atypical brain maturation-behavior relationships in PAE highlight the need for further study. Further longitudinal research aimed at characterizing white matter neurodevelopmental trajectories in PAE will be important

    Anuário científico da Escola Superior de Tecnologia da Saúde de Lisboa - 2021

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    É com grande prazer que apresentamos a mais recente edição (a 11.ª) do Anuário Científico da Escola Superior de Tecnologia da Saúde de Lisboa. Como instituição de ensino superior, temos o compromisso de promover e incentivar a pesquisa científica em todas as áreas do conhecimento que contemplam a nossa missão. Esta publicação tem como objetivo divulgar toda a produção científica desenvolvida pelos Professores, Investigadores, Estudantes e Pessoal não Docente da ESTeSL durante 2021. Este Anuário é, assim, o reflexo do trabalho árduo e dedicado da nossa comunidade, que se empenhou na produção de conteúdo científico de elevada qualidade e partilhada com a Sociedade na forma de livros, capítulos de livros, artigos publicados em revistas nacionais e internacionais, resumos de comunicações orais e pósteres, bem como resultado dos trabalhos de 1º e 2º ciclo. Com isto, o conteúdo desta publicação abrange uma ampla variedade de tópicos, desde temas mais fundamentais até estudos de aplicação prática em contextos específicos de Saúde, refletindo desta forma a pluralidade e diversidade de áreas que definem, e tornam única, a ESTeSL. Acreditamos que a investigação e pesquisa científica é um eixo fundamental para o desenvolvimento da sociedade e é por isso que incentivamos os nossos estudantes a envolverem-se em atividades de pesquisa e prática baseada na evidência desde o início dos seus estudos na ESTeSL. Esta publicação é um exemplo do sucesso desses esforços, sendo a maior de sempre, o que faz com que estejamos muito orgulhosos em partilhar os resultados e descobertas dos nossos investigadores com a comunidade científica e o público em geral. Esperamos que este Anuário inspire e motive outros estudantes, profissionais de saúde, professores e outros colaboradores a continuarem a explorar novas ideias e contribuir para o avanço da ciência e da tecnologia no corpo de conhecimento próprio das áreas que compõe a ESTeSL. Agradecemos a todos os envolvidos na produção deste anuário e desejamos uma leitura inspiradora e agradável.info:eu-repo/semantics/publishedVersio

    Unmanned Aerial Vehicles (UAVs) to compare foraging sea turtle density and distribution of sea turtles in two contrasting habitats in the Chagos Archipelago

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    Unmanned Aerial Vehicles (UAVs) facilitate observation of elusive species or remote locations, and are increasingly used to survey marine habitats. Marine Protected Areas (MPAs) are a conservation tool used to protect marine species, and regular population assessments can establish if MPAs are effectively facilitating the recovery of endangered species. Sea turtles in the Western Indian Ocean have been historically exploited through trade and by-catch causing a reduction in numbers. Here, UAVs were utilised to assess the population density and distribution of green (Chelonia mydas) and hawksbill (Eretmochelys imbricata) turtles between ocean and lagoon environments in the Chagos Archipelago. Analysis protocols were developed to process UAV imagery, including carapace-measurement techniques, and certainty-classing turtle observations (Definite, Probable or Possible). Along 20 km of coastline, 5.13 km2 was surveyed across 11 days between July 2019 – February 2021 resulting in a high-certainty estimate of 381 turtles and a low-certainty estimate of 660. Species and life-stage identification implicate Chagos as developmental habitat for immature hawksbill turtles: 78.47% (n = 299/381) of identified definite turtles were immature, of which 66.55% (n = 199/299) were hawksbill. Diego Garcia Ocean Site 1, West sites and Turtle Cove were significant turtle hotspots (high-certainty results: 257.19 individuals/km2, 146.15 individuals/km2, and 135.08 individuals/km2, respectively), while Marina sites were least-dense (0 - 4.87 individuals/km2). Results for low-certainty data were comparable: 325.27 individuals/km2 in Diego Garcia Site 1, followed by 309.27 and 292.67 individuals/km2 in Turtle Cove. Population density decreased significantly with increasing distance from the shore, and decreased with increasing distance from Turtle Cove. Green turtles were smaller (50.33 ± 17.65 cm straight-carapace length, SCL) than hawksbill turtles (53.16 ± 11.17 cm SCL). This study highlights the Chagos Archipelago as developmental habitat for immature turtles, and demonstrates the applicability of UAVs for in-situ population monitoring to infer conservation status of marine megafauna

    Gasificação direta de biomassa para produção de gás combustível

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    The excessive consumption of fossil fuels to satisfy the world necessities of energy and commodities led to the emission of large amounts of greenhouse gases in the last decades, contributing significantly to the greatest environmental threat of the 21st century: Climate Change. The answer to this man-made disaster is not simple and can only be made if distinct stakeholders and governments are brought to cooperate and work together. This is mandatory if we want to change our economy to one more sustainable and based in renewable materials, and whose energy is provided by the eternal nature energies (e.g., wind, solar). In this regard, biomass can have a main role as an adjustable and renewable feedstock that allows the replacement of fossil fuels in various applications, and the conversion by gasification allows the necessary flexibility for that purpose. In fact, fossil fuels are just biomass that underwent extreme pressures and heat for millions of years. Furthermore, biomass is a resource that, if not used or managed, increases wildfire risks. Consequently, we also have the obligation of valorizing and using this resource. In this work, it was obtained new scientific knowledge to support the development of direct (air) gasification of biomass in bubbling fluidized bed reactors to obtain a fuel gas with suitable properties to replace natural gas in industrial gas burners. This is the first step for the integration and development of gasification-based biorefineries, which will produce a diverse number of value-added products from biomass and compete with current petrochemical refineries in the future. In this regard, solutions for the improvement of the raw producer gas quality and process efficiency parameters were defined and analyzed. First, addition of superheated steam as primary measure allowed the increase of H2 concentration and H2/CO molar ratio in the producer gas without compromising the stability of the process. However, the measure mainly showed potential for the direct (air) gasification of high-density biomass (e.g., pellets), due to the necessity of having char accumulation in the reactor bottom bed for char-steam reforming reactions. Secondly, addition of refused derived fuel to the biomass feedstock led to enhanced gasification products, revealing itself as a highly promising strategy in terms of economic viability and environmental benefits of future gasification-based biorefineries, due to the high availability and low costs of wastes. Nevertheless, integrated techno economic and life cycle analyses must be performed to fully characterize the process. Thirdly, application of low-cost catalyst as primary measure revealed potential by allowing the improvement of the producer gas quality (e.g., H2 and CO concentration, lower heating value) and process efficiency parameters with distinct solid materials; particularly, the application of concrete, synthetic fayalite and wood pellets chars, showed promising results. Finally, the economic viability of the integration of direct (air) biomass gasification processes in the pulp and paper industry was also shown, despite still lacking interest to potential investors. In this context, the role of government policies and appropriate economic instruments are of major relevance to increase the implementation of these projects.O consumo excessivo de combustíveis fósseis para garantir as necessidades e interesses da sociedade conduziu à emissão de elevadas quantidades de gases com efeito de estufa nas últimas décadas, contribuindo significativamente para a maior ameaça ambiental do século XXI: Alterações Climáticas. A solução para este desastre de origem humana é de caráter complexo e só pode ser atingida através da cooperação de todos os governos e partes interessadas. Para isto, é obrigatória a criação de uma bioeconomia como base de um futuro mais sustentável, cujas necessidades energéticas e materiais sejam garantidas pelas eternas energias da natureza (e.g., vento, sol). Neste sentido, a biomassa pode ter um papel principal como uma matéria prima ajustável e renovável que permite a substituição de combustíveis fósseis num variado número de aplicações, e a sua conversão através da gasificação pode ser a chave para este propósito. Afinal, na prática, os combustíveis fósseis são apenas biomassa sujeita a elevada temperatura e pressão durante milhões de anos. Além do mais, a gestão eficaz da biomassa é fundamental para a redução dos riscos de incêndio florestal e, como tal, temos o dever de utilizar e valorizar este recurso. Neste trabalho, foi obtido novo conhecimento científico para suporte do desenvolvimento das tecnologias de gasificação direta (ar) de biomassa em leitos fluidizados borbulhantes para produção de gás combustível, com o objetivo da substituição de gás natural em queimadores industriais. Este é o primeiro passo para o desenvolvimento de biorrefinarias de gasificação, uma potencial futura indústria que irá providenciar um variado número de produtos de valor acrescentado através da biomassa e competir com a atual indústria petroquímica. Neste sentido, foram analisadas várias medidas para a melhoria da qualidade do gás produto bruto e dos parâmetros de eficiência do processo. Em primeiro, a adição de vapor sobreaquecido como medida primária permitiu o aumento da concentração de H2 e da razão molar H2/CO no gás produto sem comprometer a estabilidade do processo. No entanto, esta medida somente revelou potencial para a gasificação direta (ar) de biomassa de alta densidade (e.g., pellets) devido à necessidade da acumulação de carbonizados no leito do reator para a ocorrência de reações de reforma com vapor. Em segundo, a mistura de combustíveis derivados de resíduos e biomassa residual florestal permitiu a melhoria dos produtos de gasificação, constituindo desta forma uma estratégia bastante promissora a nível económico e ambiental, devido à elevada abundância e baixo custo dos resíduos urbanos. Contudo, devem ser efetuadas análises técnico-económicas e de ciclo de vida para a completa caraterização do processo. Em terceiro, a aplicação de catalisadores de baixo custo como medida primária demonstrou elevado potencial para a melhoria do gás produto (e.g., concentração de H2 e CO, poder calorífico inferior) e para o incremento dos parâmetros de eficiência do processo; em particular, a aplicação de betão, faialite sintética e carbonizados de pellets de madeira, demonstrou resultados promissores. Finalmente, foi demonstrada a viabilidade económica da integração do processo de gasificação direta (ar) de biomassa na indústria da pasta e papel, apesar dos parâmetros determinados não serem atrativos para potenciais investidores. Neste contexto, a intervenção dos governos e o desenvolvimento de instrumentos de apoio económico é de grande relevância para a implementação destes projetos.Este trabalho foi financiado pela The Navigator Company e por Fundos Nacionais através da Fundação para a Ciência e a Tecnologia (FCT).Programa Doutoral em Engenharia da Refinação, Petroquímica e Químic

    Predictive Maintenance of Critical Equipment for Floating Liquefied Natural Gas Liquefaction Process

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    Predictive Maintenance of Critical Equipment for Liquefied Natural Gas Liquefaction Process Meeting global energy demand is a massive challenge, especially with the quest of more affinity towards sustainable and cleaner energy. Natural gas is viewed as a bridge fuel to a renewable energy. LNG as a processed form of natural gas is the fastest growing and cleanest form of fossil fuel. Recently, the unprecedented increased in LNG demand, pushes its exploration and processing into offshore as Floating LNG (FLNG). The offshore topsides gas processes and liquefaction has been identified as one of the great challenges of FLNG. Maintaining topside liquefaction process asset such as gas turbine is critical to profitability and reliability, availability of the process facilities. With the setbacks of widely used reactive and preventive time-based maintenances approaches, to meet the optimal reliability and availability requirements of oil and gas operators, this thesis presents a framework driven by AI-based learning approaches for predictive maintenance. The framework is aimed at leveraging the value of condition-based maintenance to minimises the failures and downtimes of critical FLNG equipment (Aeroderivative gas turbine). In this study, gas turbine thermodynamics were introduced, as well as some factors affecting gas turbine modelling. Some important considerations whilst modelling gas turbine system such as modelling objectives, modelling methods, as well as approaches in modelling gas turbines were investigated. These give basis and mathematical background to develop a gas turbine simulated model. The behaviour of simple cycle HDGT was simulated using thermodynamic laws and operational data based on Rowen model. Simulink model is created using experimental data based on Rowen’s model, which is aimed at exploring transient behaviour of an industrial gas turbine. The results show the capability of Simulink model in capture nonlinear dynamics of the gas turbine system, although constraint to be applied for further condition monitoring studies, due to lack of some suitable relevant correlated features required by the model. AI-based models were found to perform well in predicting gas turbines failures. These capabilities were investigated by this thesis and validated using an experimental data obtained from gas turbine engine facility. The dynamic behaviours gas turbines changes when exposed to different varieties of fuel. A diagnostics-based AI models were developed to diagnose different gas turbine engine’s failures associated with exposure to various types of fuels. The capabilities of Principal Component Analysis (PCA) technique have been harnessed to reduce the dimensionality of the dataset and extract good features for the diagnostics model development. Signal processing-based (time-domain, frequency domain, time-frequency domain) techniques have also been used as feature extraction tools, and significantly added more correlations to the dataset and influences the prediction results obtained. Signal processing played a vital role in extracting good features for the diagnostic models when compared PCA. The overall results obtained from both PCA, and signal processing-based models demonstrated the capabilities of neural network-based models in predicting gas turbine’s failures. Further, deep learning-based LSTM model have been developed, which extract features from the time series dataset directly, and hence does not require any feature extraction tool. The LSTM model achieved the highest performance and prediction accuracy, compared to both PCA-based and signal processing-based the models. In summary, it is concluded from this thesis that despite some challenges related to gas turbines Simulink Model for not being integrated fully for gas turbine condition monitoring studies, yet data-driven models have proven strong potentials and excellent performances on gas turbine’s CBM diagnostics. The models developed in this thesis can be used for design and manufacturing purposes on gas turbines applied to FLNG, especially on condition monitoring and fault detection of gas turbines. The result obtained would provide valuable understanding and helpful guidance for researchers and practitioners to implement robust predictive maintenance models that will enhance the reliability and availability of FLNG critical equipment.Petroleum Technology Development Funds (PTDF) Nigeri

    Annals [...].

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    Pedometrics: innovation in tropics; Legacy data: how turn it useful?; Advances in soil sensing; Pedometric guidelines to systematic soil surveys.Evento online. Coordenado por: Waldir de Carvalho Junior, Helena Saraiva Koenow Pinheiro, Ricardo Simão Diniz Dalmolin

    Physical phenomena controlling quiescent flame spread in porous wildland fuel beds

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    Despite well-developed solid surface flame spread theories, we still lack a coherent theory to describe flame spread through porous wildland fuel beds. This porosity results in additional complexity, reducing the thermal conductivity of the fuel bed, but allowing in-bed radiative and convective heat transfer to occur. While previous studies have explored the effect of fuel bed structure on the overall fire behaviour, there remains a need for further investigation of the effect of fuel structure on the underlying physical phenomena controlling flame spread. Through an extensive series of laboratory-based experiments, this thesis provides detailed, physics-based insights for quiescent flame spread through natural porous beds, across a range of structural conditions. Measurements are presented for fuel beds representative of natural field conditions within an area of the fire-prone New Jersey Pinelands National Reserve, which compliment a related series of field experiments conducted as part of a wider research project. Additional systematic investigation across a wider range of fuel conditions identified independent effects of fuel loading and bulk density on the spread rate, flame height and heat release rate. However, neither fuel loading nor bulk density alone provided adequate prediction of the resulting fire behaviour. Drawing on existing structural descriptors (for both natural and engineered fuel beds) an alternative parameter ασδ was proposed. This parameter (incorporating the fuel bed porosity (α), fuel element surface-to-volume ratio (σ), and the fuel bed height (δ)) was strongly correlated with the spread rate. One effect of the fuel bed structure is to influence the heat transfer mechanisms both above and within the porous fuel bed. Existing descriptions of radiation transport through porous fuel beds are often predicated on the assumption of an isotropic fuel bed. However, given their preferential angle of inclination, the pine needle beds in this study may not exhibit isotropic behaviour. Regardless, for the structural conditions investigated, horizontal heat transfer through the fuel bed was identified as the dominant heating mechanism within this quiescent flame spread scenario. However, the significance of heat transfer contributions from the above-bed flame generally increased with increasing ασδ value of the fuel bed. Using direct measurements of the heat flux magnitude and effective heating distance, close agreement was observed between experimentally observed spread rates and a simple thermal model considering only radiative heat transfer through the fuel bed, particularly at lower values of ασδ. Over-predictions occurred at higher ασδ values, or where other heat transfer terms were incorporated, which may highlight the need to include additional heat loss terms. A significant effect of fuel structure on the primary flow regimes, both within and above these porous fuel beds, was also observed, with important implications for the heat transfer and oxygen supply within the fuel bed. Independent effects of fuel loading and bulk density on both the buoyant and buoyancy-driven entrainment flow were observed, with a complex feedback cycle occurring between Heat Release Rate (HRR) and combustion behaviour. Generally, increases in fuel loading resulted in increased HRR, and therefore increased buoyant flow velocity, along with an increase in the velocity of flow entrained towards the combustion region. The complex effects of fuel structure in both the flaming and smouldering combustion phases may necessitate modifications to other common modelling approaches. The widely used Rothermel model under-predicted spread rate for higher bulk density and lower ασδ fuel beds. As previously suggested, an over-sensitivity to fuel bed height was observed, with experimental comparison indicating an under-prediction of reaction intensity at lower fuel heights. These findings have important implications particularly given the continuing widespread use of the Rothermel model, which continues to underpin elements of the BehavePlus fire modelling system and the US National Fire Danger Rating System. The physical insights, and modelling approaches, developed for this low-intensity, quiescent flame spread scenario, are applicable to common prescribed fire activities. It is hoped that this work (alongside complimentary laboratory and field experiments conducted by various authors as part of a wider multi-agency project (SERDP-RC2641)) will contribute to the emerging field of prescribed fire science, and help to address the pressing need for further development of fire prediction and modelling tools

    Statistical Learning for Gene Expression Biomarker Detection in Neurodegenerative Diseases

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    In this work, statistical learning approaches are used to detect biomarkers for neurodegenerative diseases (NDs). NDs are becoming increasingly prevalent as populations age, making understanding of disease and identification of biomarkers progressively important for facilitating early diagnosis and the screening of individuals for clinical trials. Advancements in gene expression profiling has enabled the exploration of disease biomarkers at an unprecedented scale. The work presented here demonstrates the value of gene expression data in understanding the underlying processes and detection of biomarkers of NDs. The value of novel approaches to previously collected -omics data is shown and it is demonstrated that new therapeutic targets can be identified. Additionally, the importance of meta-analysis to improve power of multiple small studies is demonstrated. The value of blood transcriptomics data is shown in applications to researching NDs to understand underlying processes using network analysis and a novel hub detection method. Finally, after demonstrating the value of blood gene expression data for investigating NDs, a combination of feature selection and classification algorithms were used to identify novel accurate biomarker signatures for the diagnosis and prognosis of Parkinson’s disease (PD) and Alzheimer’s disease (AD). Additionally, the use of feature pools based on previous knowledge of disease and the viability of neural networks in dimensionality reduction and biomarker detection is demonstrated and discussed. In summary, gene expression data is shown to be valuable for the investigation of ND and novel gene biomarker signatures for the diagnosis and prognosis of PD and AD

    Fiabilité de l’underfill et estimation de la durée de vie d’assemblages microélectroniques

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    Abstract : In order to protect the interconnections in flip-chip packages, an underfill material layer is used to fill the volumes and provide mechanical support between the silicon chip and the substrate. Due to the chip corner geometry and the mismatch of coefficient of thermal expansion (CTE), the underfill suffers from a stress concentration at the chip corners when the temperature is lower than the curing temperature. This stress concentration leads to subsequent mechanical failures in flip-chip packages, such as chip-underfill interfacial delamination and underfill cracking. Local stresses and strains are the most important parameters for understanding the mechanism of underfill failures. As a result, the industry currently relies on the finite element method (FEM) to calculate the stress components, but the FEM may not be accurate enough compared to the actual stresses in underfill. FEM simulations require a careful consideration of important geometrical details and material properties. This thesis proposes a modeling approach that can accurately estimate the underfill delamination areas and crack trajectories, with the following three objectives. The first objective was to develop an experimental technique capable of measuring underfill deformations around the chip corner region. This technique combined confocal microscopy and the digital image correlation (DIC) method to enable tri-dimensional strain measurements at different temperatures, and was named the confocal-DIC technique. This techique was first validated by a theoretical analysis on thermal strains. In a test component similar to a flip-chip package, the strain distribution obtained by the FEM model was in good agreement with the results measured by the confocal-DIC technique, with relative errors less than 20% at chip corners. Then, the second objective was to measure the strain near a crack in underfills. Artificial cracks with lengths of 160 μm and 640 μm were fabricated from the chip corner along the 45° diagonal direction. The confocal-DIC-measured maximum hoop strains and first principal strains were located at the crack front area for both the 160 μm and 640 μm cracks. A crack model was developed using the extended finite element method (XFEM), and the strain distribution in the simulation had the same trend as the experimental results. The distribution of hoop strains were in good agreement with the measured values, when the model element size was smaller than 22 μm to capture the strong strain gradient near the crack tip. The third objective was to propose a modeling approach for underfill delamination and cracking with the effects of manufacturing variables. A deep thermal cycling test was performed on 13 test cells to obtain the reference chip-underfill delamination areas and crack profiles. An artificial neural network (ANN) was trained to relate the effects of manufacturing variables and the number of cycles to first delamination of each cell. The predicted numbers of cycles for all 6 cells in the test dataset were located in the intervals of experimental observations. The growth of delamination was carried out on FEM by evaluating the strain energy amplitude at the interface elements between the chip and underfill. For 5 out of 6 cells in validation, the delamination growth model was consistent with the experimental observations. The cracks in bulk underfill were modelled by XFEM without predefined paths. The directions of edge cracks were in good agreement with the experimental observations, with an error of less than 2.5°. This approach met the goal of the thesis of estimating the underfill initial delamination, areas of delamination and crack paths in actual industrial flip-chip assemblies.Afin de protéger les interconnexions dans les assemblages, une couche de matériau d’underfill est utilisée pour remplir le volume et fournir un support mécanique entre la puce de silicium et le substrat. En raison de la géométrie du coin de puce et de l’écart du coefficient de dilatation thermique (CTE), l’underfill souffre d’une concentration de contraintes dans les coins lorsque la température est inférieure à la température de cuisson. Cette concentration de contraintes conduit à des défaillances mécaniques dans les encapsulations de flip-chip, telles que la délamination interfaciale puce-underfill et la fissuration d’underfill. Les contraintes et déformations locales sont les paramètres les plus importants pour comprendre le mécanisme des ruptures de l’underfill. En conséquent, l’industrie utilise actuellement la méthode des éléments finis (EF) pour calculer les composantes de la contrainte, qui ne sont pas assez précises par rapport aux contraintes actuelles dans l’underfill. Ces simulations nécessitent un examen minutieux de détails géométriques importants et des propriétés des matériaux. Cette thèse vise à proposer une approche de modélisation permettant d’estimer avec précision les zones de délamination et les trajectoires des fissures dans l’underfill, avec les trois objectifs suivants. Le premier objectif est de mettre au point une technique expérimentale capable de mesurer la déformation de l’underfill dans la région du coin de puce. Cette technique, combine la microscopie confocale et la méthode de corrélation des images numériques (DIC) pour permettre des mesures tridimensionnelles des déformations à différentes températures, et a été nommée le technique confocale-DIC. Cette technique a d’abord été validée par une analyse théorique en déformation thermique. Dans un échantillon similaire à un flip-chip, la distribution de la déformation obtenues par le modèle EF était en bon accord avec les résultats de la technique confocal-DIC, avec des erreurs relatives inférieures à 20% au coin de puce. Ensuite, le second objectif est de mesurer la déformation autour d’une fissure dans l’underfill. Des fissures artificielles d’une longueuer de 160 μm et 640 μm ont été fabriquées dans l’underfill vers la direction diagonale de 45°. Les déformations circonférentielles maximales et principale maximale étaient situées aux pointes des fissures correspondantes. Un modèle de fissure a été développé en utilisant la méthode des éléments finis étendue (XFEM), et la distribution des contraintes dans la simuation a montré la même tendance que les résultats expérimentaux. La distribution des déformations circonférentielles maximales était en bon accord avec les valeurs mesurées lorsque la taille des éléments était plus petite que 22 μm, assez petit pour capturer le grand gradient de déformation près de la pointe de fissure. Le troisième objectif était d’apporter une approche de modélisation de la délamination et de la fissuration de l’underfill avec les effets des variables de fabrication. Un test de cyclage thermique a d’abord été effectué sur 13 cellules pour obtenir les zones délaminées entre la puce et l’underfill, et les profils de fissures dans l’underfill, comme référence. Un réseau neuronal artificiel (ANN) a été formé pour établir une liaison entre les effets des variables de fabrication et le nombre de cycles à la délamination pour chaque cellule. Les nombres de cycles prédits pour les 6 cellules de l’ensemble de test étaient situés dans les intervalles d’observations expérimentaux. La croissance de la délamination a été réalisée par l’EF en évaluant l’énergie de la déformation au niveau des éléments interfaciaux entre la puce et l’underfill. Pour 5 des 6 cellules de la validation, le modèle de croissance du délaminage était conforme aux observations expérimentales. Les fissures dans l’underfill ont été modélisées par XFEM sans chemins prédéfinis. Les directions des fissures de bord étaient en bon accord avec les observations expérimentales, avec une erreur inférieure à 2,5°. Cette approche a répondu à la problématique qui consiste à estimer l’initiation des délamination, les zones de délamination et les trajectoires de fissures dans l’underfill pour des flip-chips industriels

    Water Circulation Driven by Cold Fronts in the Wax Lake Delta (Louisiana, USA)

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    : Atmospheric cold fronts can periodically generate storm surges and affect sediment transport in the Northern Gulf of Mexico (NGOM). In this paper, we evaluate water circulation spatiotemporal patterns induced by six atmospheric cold front events in the Wax Lake Delta (WLD) in coastal Louisiana using the 3-D hydrodynamic model ECOM-si. Model simulations show that channelized and inter-distributary water flow is significantly impacted by cold fronts. Water volume transport throughout the deltaic channel network is not just constrained to the main channels but also occurs laterally across channels accounting for about a quarter of the total flow. Results show that a significant landward flow occurs across the delta prior to the frontal passage, resulting in a positive storm surge on the coast. The along-channel current velocity dominates while cross-channel water transport occurs at the southwest lobe during the post-frontal stage. Depending on local weather conditions, the cold-front-induced flushing event lasts for 1.7 to 7 days and can flush 32–76% of the total water mass out of the system, a greater range of variability than previous reports. The magnitude of water flushed out of the system is not necessarily dependent on the duration of the frontal events. An energy partitioning analysis shows that the relative importance of subtidal energy (10–45% of the total) and tidal energy (20–70%) varies substantially from station to station and is linked to the weather impact. It is important to note that within the WLD region, the weather-induced subtidal energy (46–66% of the total) is much greater than the diurnal tidal energy (13–25% of the total). The wind associated with cold fronts in winter is the main factor controlling water circulation in the WLD and is a major driver in the spatial configuration of the channel network and delta progradation rates
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