909 resultados para flow-based
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Smart hydrogels for biomedical applications are highly researched materials. However, integrating them into a device for implantation is difficult. This paper investigates an integrated delivery device designed to deliver an electro-responsive hydrogel to a target location inside a blood vessel with the purpose of creating an occlusion. The paper describes the synthesis and characterization of a Pluronic/methacrylic acid sodium salt electro-responsive hydrogel. Application of an electrical bias decelerates the expansion of the hydrogel. An integrated delivery system was manufactured to deliver the hydrogel to the target location in the body. Ex vivo and in vivo experiments in the carotid artery of sheep were used to validate the concept. The hydrogel was able to completely occlude the blood vessel reducing the blood flow from 245 to 0 ml/min after implantation. Ex vivo experiments showed that the hydrogel was able to withstand physiological blood pressures of > 270 mm·Hg without dislodgement. The results showed that the electro-responsive hydrogel used in this paper can be used to create a long-term occlusion in a blood vessel without any apparent side effects. The delivery system developed is a promising device for the delivery of electro-responsive hydrogels.
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The goal of this research is to produce a system for powering medical implants to increase the lifetime of the implanted devices and reduce the battery size. The system consists of a number of elements – the piezoelectric material for generating power, the device design, the circuit for rectification and energy storage. The piezoelectric material is analysed and a process for producing a repeatable high quality piezoelectric material is described. A full width half maximum (FWHM) of the rocking curve X-Ray diffraction (XRD) scan of between ~1.5° to ~1.7° for test wafers was achieved. This is state of the art for AlN on silicon and means devices with good piezoelectric constants can be fabricated. Finite element modelling FEM) was used to design the structures for energy harvesting. The models developed in this work were established to have an accuracy better than 5% in terms of the difference between measured and modelled results. Devices made from this material were analysed for power harvesting ability as well as the effect that they have on the flow of liquid which is an important consideration for implantable devices. The FEM results are compared to experimental results from laser Doppler vibrometry (LDV), magnetic shaker and perfusion machine tests. The rectifying circuitry for the energy harvester was also investigated. The final solution uses multiple devices to provide the power to augment the battery and so this was a key feature to be considered. Many circuits were examined and a solution based on a fully autonomous circuit was advanced. This circuit was analysed for use with multiple low power inputs similar to the results from previous investigations into the energy harvesting devices. Polymer materials were also studied for use as a substitute for the piezoelectric material as well as the substrate because silicon is more brittle.
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This material is based upon work supported by the National Science Foundation through the Florida Coastal Everglades Long-Term Ecological Research program under Cooperative Agreements #DBI-0620409 and #DEB-9910514. This image is made available for non-commercial or educational use only.
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In this study we utilize two organic geochemical proxies, the Uk'37 index and TEX86, to examine past sea surface temperatures (SST) from a site located near the Nile River Delta in the eastern Mediterranean (EM) Sea. The Uk'37 and TEX86 records generally are in agreement and indicate SST ranges of 14°C-26°C and 14°C-28°C, respectively, during the last 27 cal ka. During the Holocene, TEX86-based SST estimates are usually higher than Uk'37-based SST estimates, which is likely due to seasonal differences between the timing of the haptophyte and crenarchaeota blooms in the EM and is related to the onset of the modern flow regime of the Nile River. Both records show that SST varied on centennial to millennial timescales in response to global climate events, i.e., cooling during the Last Glacial Maximum (LGM), Heinrich event 1 (H1), and the Younger Dryas (YD) and warming during the Bølling-Allerød and in the early Holocene during deposition of sapropel S1. The H1 cooling was particularly severe and is marked by a drop in SST of ~4.5°C in comparison to pre-H1 SST, with temperatures >1°C cooler than during the LGM. In contrast to high-latitude and western Mediterranean records, which indicate both an abrupt onset and termination of the YD event, the transition from the YD to the Holocene was much more gradual in the EM.
Field data, numerical simulations and probability analyses to assess lava flow hazards at Mount Etna
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Improving lava flow hazard assessment is one of the most important and challenging fields of volcanology, and has an immediate and practical impact on society. Here, we present a methodology for the quantitative assessment of lava flow hazards based on a combination of field data, numerical simulations and probability analyses. With the extensive data available on historic eruptions of Mt. Etna, going back over 2000 years, it has been possible to construct two hazard maps, one for flank and the other for summit eruptions, allowing a quantitative analysis of the most likely future courses of lava flows. The effective use of hazard maps of Etna may help in minimizing the damage from volcanic eruptions through correct land use in densely urbanized area with a population of almost one million people. Although this study was conducted on Mt. Etna, the approach used is designed to be applicable to other volcanic areas.
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Methane hydrate is an ice-like substance that is stable at high-pressure and low temperature in continental margin sediments. Since the discovery of a large number of gas flares at the landward termination of the gas hydrate stability zone off Svalbard, there has been concern that warming bottom waters have started to dissociate large amounts of gas hydrate and that the resulting methane release may possibly accelerate global warming. Here, we can corroborate that hydrates play a role in the observed seepage of gas, but we present evidence that seepage off Svalbard has been ongoing for at least three thousand years and that seasonal fluctuations of 1-2°C in the bottom-water temperature cause periodic gas hydrate formation and dissociation, which focus seepage at the observed sites.
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En route speed reduction can be used for air traffic flow management (ATFM), e.g., delaying aircraft while airborne or realizing metering at an arrival fix. In previous publications, the authors identified the flight conditions that maximize the airborne delay without incurring extra fuel consumption with respect to the nominal (not delayed) flight. In this paper, the effect of wind on this strategy is studied, and the sensitivity to wind forecast errors is also assessed. A case study done in Chicago O’Hare airport (ORD) is presented, showing that wind has a significant effect on the airborne delay that can be realized and that, in some cases, even tailwinds might lead to an increase in the maximum amount of airborne delay. The values of airborne delay are representative enough to suggest that this speed reduction technique might be useful in a real operational scenario. Moreover, the speed reduction strategy is more robust than nominal operations against fuel consumption in the presence of wind forecast uncertainties.
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Adjoint methods have proven to be an efficient way of calculating the gradient of an objective function with respect to a shape parameter for optimisation, with a computational cost nearly independent of the number of the design variables [1]. The approach in this paper links the adjoint surface sensitivities (gradient of objective function with respect to the surface movement) with the parametric design velocities (movement of the surface due to a CAD parameter perturbation) in order to compute the gradient of the objective function with respect to CAD variables.
For a successful implementation of shape optimization strategies in practical industrial cases, the choice of design variables or parameterisation scheme used for the model to be optimized plays a vital role. Where the goal is to base the optimization on a CAD model the choices are to use a NURBS geometry generated from CAD modelling software, where the position of the NURBS control points are the optimisation variables [2] or to use the feature based CAD model with all of the construction history to preserve the design intent [3]. The main advantage of using the feature based model is that the optimized model produced can be directly used for the downstream applications including manufacturing and process planning.
This paper presents an approach for optimization based on the feature based CAD model, which uses CAD parameters defining the features in the model geometry as the design variables. In order to capture the CAD surface movement with respect to the change in design variable, the “Parametric Design Velocity” is calculated, which is defined as the movement of the CAD model boundary in the normal direction due to a change in the parameter value.
The approach presented here for calculating the design velocities represents an advancement in terms of capability and robustness of that described by Robinson et al. [3]. The process can be easily integrated to most industrial optimisation workflows and is immune to the topology and labelling issues highlighted by other CAD based optimisation processes. It considers every continuous (“real value”) parameter type as an optimisation variable, and it can be adapted to work with any CAD modelling software, as long as it has an API which provides access to the values of the parameters which control the model shape and allows the model geometry to be exported. To calculate the movement of the boundary the methodology employs finite differences on the shape of the 3D CAD models before and after the parameter perturbation. The implementation procedure includes calculating the geometrical movement along a normal direction between two discrete representations of the original and perturbed geometry respectively. Parametric design velocities can then be directly linked with adjoint surface sensitivities to extract the gradients to use in a gradient-based optimization algorithm.
The optimisation of a flow optimisation problem is presented, in which the power dissipation of the flow in an automotive air duct is to be reduced by changing the parameters of the CAD geometry created in CATIA V5. The flow sensitivities are computed with the continuous adjoint method for a laminar and turbulent flow [4] and are combined with the parametric design velocities to compute the cost function gradients. A line-search algorithm is then used to update the design variables and proceed further with optimisation process.
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With security and surveillance, there is an increasing need to process image data efficiently and effectively either at source or in a large data network. Whilst a Field-Programmable Gate Array (FPGA) has been seen as a key technology for enabling this, the design process has been viewed as problematic in terms of the time and effort needed for implementation and verification. The work here proposes a different approach of using optimized FPGA-based soft-core processors which allows the user to exploit the task and data level parallelism to achieve the quality of dedicated FPGA implementations whilst reducing design time. The paper also reports some preliminary
progress on the design flow to program the structure. An implementation for a Histogram of Gradients algorithm is also reported which shows that a performance of 328 fps can be achieved with this design approach, whilst avoiding the long design time, verification and debugging steps associated with conventional FPGA implementations.
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Combined conduction–convection–radiation heat transfer is investigated numerically in a micro-channel filled with a saturated cellular porous medium, with the channel walls held at a constant heat flux. Invoking the velocity slip and temperature jump, the thermal behaviour of the porous–fluid system are studied by considering hydrodynamically fully developed flow and applying the Darcy–Brinkman flow model. One energy equation model based on the local thermal equilibrium condition is adopted to evaluate the temperature field within the porous medium. Combined conduction and radiation heat transfer is treated as an effective conduction process with a temperature-dependent effective thermal conductivity. Results are reported in terms of the average Nusselt number and dimensionless temperature distribution, as a function of velocity slip coefficient, temperature jump coefficient, porous medium shape parameter and radiation parameters. Results show that increasing the radiation parameter (Tr)(Tr) and the temperature jump coefficient flattens the dimensionless temperature profile. The Nusselt numbers are more sensitive to the variation in the temperature jump coefficient rather than to the velocity slip coefficient. Such that for high porous medium shape parameter, the Nusselt number is found to be independent of velocity slip. Furthermore, it is found that as the temperature jump coefficient increases, the Nusselt number decrease. In addition, for high temperature jump coefficients, the Nusselt number is found to be insensitive to the radiation parameters and porous medium shape parameter. It is also concluded that compared with the conventional macro-channels, wherein using a porous material enhances the rate of heat transfer (up to about 40 % compared to the clear channel), insertion of a porous material inside a micro-channel in slip regime does not effectively enhance the rate of heat transfer that is about 2 %.
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Current trends in the automotive industry have placed increased importance on engine downsizing for passenger vehicles. Engine downsizing often results in reduced power output and turbochargers have been relied upon to restore the power output and maintain drivability. As improved power output is required across a wide range of engine operating conditions, it is necessary for the turbocharger to operate effectively at both design and off-design conditions. One off-design condition of considerable importance for turbocharger turbines is low velocity ratio operation, which refers to the combination of high exhaust gas velocity and low turbine rotational speed. Conventional radial flow turbines are constrained to achieve peak efficiency at the relatively high velocity ratio of 0.7, due the requirement to maintain a zero inlet blade angle for structural reasons. Several methods exist to potentially shift turbine peak efficiency to lower velocity ratios. One method is to utilize a mixed flow turbine as an alternative to a radial flow turbine. In addition to radial and circumferential components, the flow entering a mixed flow turbine also has an axial component. This allows the flow to experience a non-zero inlet blade angle, potentially shifting peak efficiency to a lower velocity ratio when compared to an equivalent radial flow turbine.
This study examined the effects of varying the flow conditions at the inlet to a mixed flow turbine and evaluated the subsequent impact on performance. The primary parameters examined were average inlet flow angle, the spanwise distribution of flow angle across the inlet and inlet flow cone angle. The results have indicated that the inlet flow angle significantly influenced the degree of reaction across the rotor and the turbine efficiency. The rotor studied was a custom in-house design based on a state-of-the-art radial flow turbine design. A numerical approach was used as the basis for this investigation and the numerical model has been validated against experimental data obtained from the cold flow turbine test rig at Queen’s University Belfast. The results of the study have provided a useful insight into how the flow conditions at rotor inlet influence the performance of a mixed flow turbine.
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Les organismes aquatiques sont adaptés à une grande variabilité hydrique et thermique des rivières. Malgré ceci, la régulation des eaux suscite des changements aux débits qui peuvent provoquer des impacts négatifs sur la biodiversité et les processus écologiques en rivière. Celle-ci peut aussi causer des modifications au niveau des régimes thermiques et des caractéristiques de l’habitat du poisson. Des données environnementales et biologiques décrivant l’habitat du poisson existent, mais elles sont incomplètes pour plusieurs rivières au Canada et de faible qualité, limitant les relations quantitatives débit-température-poissons à un petit nombre de rivières ou à une région étudiée. La recherche menée dans le cadre de mon doctorat concerne les impacts de la génération d'hydroélectricité sur les rivières; soit les changements aux régimes hydriques et thermiques reliés à la régulation des eaux sur la variation des communautés ichtyologiques qui habitent les rivières régulées et naturelles au Canada. Suite à une comparaison d’échantillonnage de pêche, une méthode constante pour obtenir des bons estimés de poisson (richesse, densité et biomasse des espèces) a été établie pour évaluer la structure de la communauté de poissons pour l’ensemble des rivières ciblées par l’étude. Afin de mieux comprendre ces changements environnementaux, les principales composantes décrivant ces régimes ont été identifiées et l’altération des régimes hydriques pour certaines rivières régulées a été quantifiée. Ces résultats ont servi à établir la relation significative entre le degré de changement biotique et le degré de changement hydrique pour illustrer les différences entre les régimes de régulation. Pour faire un complément aux indices biotiques déjà calculés pour l’ensemble des communautés de poissons (diversité, densité et biomasse des espèces par rivière), les différences au niveau des guildes de poissons ont été quantifiées pour expliquer les divers effets écologiques dus aux changements de régimes hydriques et thermiques provenant de la gestion des barrages. Ces derniers résultats servent à prédire pour quels traits écologiques ou groupes d’espèces de poissons les composantes hydriques et thermiques sont importantes. De plus, ces derniers résultats ont servi à mettre en valeur les variables décrivant les régimes thermiques qui ne sont pas toujours inclues dans les études hydro-écologiques. L’ensemble des résultats de cette thèse ont des retombées importantes sur la gestion des rivières en évaluant, de façon cohérente, l’impact de la régulation des rivières sur les communautés de poissons et en développant des outils de prévision pour la restauration des écosystèmes riverains.
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This paper presents flow regimes identification methodology in multiphase system in annular, stratified and homogeneous oil-water-gas regimes. The principle is based on recognition of the pulse height distributions (PHD) from gamma-ray with supervised artificial neural network (ANN) systems. The detection geometry simulation comprises of two NaI(Tl) detectors and a dual-energy gamma-ray source. The measurement of scattered radiation enables the dual modality densitometry (DMD) measurement principle to be explored. Its basic principle is to combine the measurement of scattered and transmitted radiation in order to acquire information about the different flow regimes. The PHDs obtained by the detectors were used as input to ANN. The data sets required for training and testing the ANN were generated by the MCNP-X code from static and ideal theoretical models of multiphase systems. The ANN correctly identified the three different flow regimes for all data set evaluated. The results presented show that PHDs examined by ANN may be applied in the successfully flow regime identification.
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Thesis (Master's)--University of Washington, 2016-08
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One of the biggest challenges that contaminant hydrogeology is facing, is how to adequately address the uncertainty associated with model predictions. Uncertainty arise from multiple sources, such as: interpretative error, calibration accuracy, parameter sensitivity and variability. This critical issue needs to be properly addressed in order to support environmental decision-making processes. In this study, we perform Global Sensitivity Analysis (GSA) on a contaminant transport model for the assessment of hydrocarbon concentration in groundwater. We provide a quantification of the environmental impact and, given the incomplete knowledge of hydrogeological parameters, we evaluate which are the most influential, requiring greater accuracy in the calibration process. Parameters are treated as random variables and a variance-based GSA is performed in a optimized numerical Monte Carlo framework. The Sobol indices are adopted as sensitivity measures and they are computed by employing meta-models to characterize the migration process, while reducing the computational cost of the analysis. The proposed methodology allows us to: extend the number of Monte Carlo iterations, identify the influence of uncertain parameters and lead to considerable saving computational time obtaining an acceptable accuracy.