848 resultados para PREDICT FLUID RESPONSIVENESS
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Report for the scientific sojourn at the James Cook University, Australia, between June to December 2007. Free convection in enclosed spaces is found widely in natural and industrial systems. It is a topic of primary interest because in many systems it provides the largest resistance to the heat transfer in comparison with other heat transfer modes. In such systems the convection is driven by a density gradient within the fluid, which, usually, is produced by a temperature difference between the fluid and surrounding walls. In the oil industry, the oil, which has High Prandtl, usually is stored and transported in large tanks at temperatures high enough to keep its viscosity and, thus the pumping requirements, to a reasonable level. A temperature difference between the fluid and the walls of the container may give rise to the unsteady buoyancy force and hence the unsteady natural convection. In the initial period of cooling the natural convection regime dominates over the conduction contribution. As the oil cools down it typically becomes more viscous and this increase of viscosity inhibits the convection. At this point the oil viscosity becomes very large and unloading of the tank becomes very difficult. For this reason it is of primary interest to be able to predict the cooling rate of the oil. The general objective of this work is to develop and validate a simulation tool able to predict the cooling rates of high Prandtl fluid considering the variable viscosity effects.
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Efavirenz (EFV) is principally metabolized by CYP2B6 to 8-hydroxy-efavirenz (8OH-EFV) and to a lesser extent by CYP2A6 to 7-hydroxy-efavirenz (7OH-EFV). So far, most metabolite profile analyses have been restricted to 8OH-EFV, 7OH-EFV, and EFV-N-glucuronide, even though these metabolites represent a minor percentage of EFV metabolites present in vivo. We have performed a quantitative phase I and II metabolite profile analysis by tandem mass spectrometry of plasma, cerebrospinal fluid (CSF), and urine samples in 71 human immunodeficiency virus patients taking efavirenz, prior to and after enzymatic (glucuronidase and sulfatase) hydrolysis. We have shown that phase II metabolites constitute the major part of the known circulating efavirenz species in humans. The 8OH-EFV-glucuronide (gln) and 8OH-EFV-sulfate (identified for the first time) in humans were found to be 64- and 7-fold higher than the parent 8OH-EFV, respectively. In individuals (n = 67) genotyped for CYP2B6, 2A6, and CYP3A metabolic pathways, 8OH-EFV/EFV ratios in plasma were an index of CYP2B6 phenotypic activity (P < 0.0001), which was also reflected by phase II metabolites 8OH-EFV-glucuronide/EFV and 8OH-EFV-sulfate/EFV ratios. Neither EFV nor 8OH-EFV, nor any other considered metabolites in plasma were associated with an increased risk of central nervous system (CNS) toxicity. In CSF, 8OH-EFV levels were not influenced by CYP2B6 genotypes and did not predict CNS toxicity. The phase II metabolites 8OH-EFV-gln, 8OH-EFV-sulfate, and 7OH-EFV-gln were present in CSF at 2- to 9-fold higher concentrations than 8OH-EFV. The potential contribution of known and previously unreported EFV metabolites in CSF to the neuropsychological effects of efavirenz needs to be further examined in larger cohort studies.
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The main objective of this research is to estimate and characterize heterogeneous mass transfer coefficients in bench- and pilot-scale fluidized bed processes by the means of computational fluid dynamics (CFD). A further objective is to benchmark the heterogeneous mass transfer coefficients predicted by fine-grid Eulerian CFD simulations against empirical data presented in the scientific literature. First, a fine-grid two-dimensional Eulerian CFD model with a solid and gas phase has been designed. The model is applied for transient two-dimensional simulations of char combustion in small-scale bubbling and turbulent fluidized beds. The same approach is used to simulate a novel fluidized bed energy conversion process developed for the carbon capture, chemical looping combustion operated with a gaseous fuel. In order to analyze the results of the CFD simulations, two one-dimensional fluidized bed models have been formulated. The single-phase and bubble-emulsion models were applied to derive the average gas-bed and interphase mass transfer coefficients, respectively. In the analysis, the effects of various fluidized bed operation parameters, such as fluidization, velocity, particle and bubble diameter, reactor size, and chemical kinetics, on the heterogeneous mass transfer coefficients in the lower fluidized bed are evaluated extensively. The analysis shows that the fine-grid Eulerian CFD model can predict the heterogeneous mass transfer coefficients quantitatively with acceptable accuracy. Qualitatively, the CFD-based research of fluidized bed process revealed several new scientific results, such as parametrical relationships. The huge variance of seven orders of magnitude within the bed Sherwood numbers presented in the literature could be explained by the change of controlling mechanisms in the overall heterogeneous mass transfer process with the varied process conditions. The research opens new process-specific insights into the reactive fluidized bed processes, such as a strong mass transfer control over heterogeneous reaction rate, a dominance of interphase mass transfer in the fine-particle fluidized beds and a strong chemical kinetic dependence of the average gas-bed mass transfer. The obtained mass transfer coefficients can be applied in fluidized bed models used for various engineering design, reactor scale-up and process research tasks, and they consequently provide an enhanced prediction accuracy of the performance of fluidized bed processes.
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Fluid inteliigence has been defined as an innate ability to reason which is measured commonly by the Raven's Progressive Matrices (RPM). Individual differences in fluid intelligence are currently explained by the Cascade model (Fry & Hale, 1996) and the Controlled Attention hypothesis (Engle, Kane, & Tuholski, 1999; Kane & Engle, 2002). The first theory is based on a complex relation among age, speed, and working memory which is described as a Cascade. The alternative to this theory, the Controlled Attention hypothesis, is based on the proposition that it is the executive attention component of working memory that explains performance on fluid intelligence tests. The first goal of this study was to examine whether the Cascade model is consistent within the visuo-spatial and verbal-numerical modalities. The second goal was to examine whether the executive attention component ofworking memory accounts for the relation between working memory and fluid intelligence. Two hundred and six undergraduate students between the ages of 18 and 28 completed a battery of cognitive tests selected to measure processing speed, working memory, and controlled attention which were selected from two cognitive modalities, verbalnumerical and visuo-spatial. These were used to predict performance on two standard measures of fluid intelligence: the Raven's Progressive Matrices (RPM) and the Shipley Institute of Living Scales (SILS) subtests. Multiple regression and Structural Equation Modeling (SEM) were used to test the Cascade model and to determine the independent and joint effects of controlled attention and working memory on general fluid intelligence. Among the processing speed measures only spatial scan was related to the RPM. No other significant relations were observed between processing speed and fluid intelligence. As 1 a construct, working memory was related to the fluid intelligence tests. Consistent with the predictions for the RPM there was support for the Cascade model within the visuo-spatial modality but not within the verbal-numerical modality. There was no support for the Cascade model with respect to the SILS tests. SEM revealed that there was a direct path between controlled attention and RPM and between working memory and RPM. However, a significant path between set switching and RPM explained the relation between controlled attention and RPM. The prediction that controlled attention mediated the relation between working memory and RPM was therefore not supported. The findings support the view that the Cascade model may not adequately explain individual differences in fluid intelligence and this may be due to the differential relations observed between working memory and fluid intelligence across different modalities. The findings also show that working memory is not a domain-general construct and as a result its relation with fluid intelligence may be dependent on the nature of the working memory modality.
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Domestic gas burners are investigated experimentally and numerically in order to further understand the fluid dynamics processes that drive the cooking appliance performances. In particular, a numerical simulation tool has been developed in order to predict the onset of two flame instabilities which may deteriorate the performances of the burner: the flame back and flame lift. The numerical model has been firstly validated by comparing the simulated flow field with a data set of experimental measurements. A prediction criterion for the flame back instability has been formulated based on isothermal simulations without involving the combustion modelization. This analysis has been verified by a Design Of Experiments investigation performed on different burner prototype geometries. On the contrary, the formulation of a prediction criterion regarding the flame lift instability has required the use of a combustion model in the numerical code. In this analysis, the structure and aerodynamics of the flame generated by a cooking appliance has thus been characterized by experimental and numerical investigations, in which, by varying the flow inlet conditions, the flame behaviour was studied from a stable reference case toward a complete blow-out.
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The research is aimed at contributing to the identification of reliable fully predictive Computational Fluid Dynamics (CFD) methods for the numerical simulation of equipment typically adopted in the chemical and process industries. The apparatuses selected for the investigation, specifically membrane modules, stirred vessels and fluidized beds, were characterized by a different and often complex fluid dynamic behaviour and in some cases the momentum transfer phenomena were coupled with mass transfer or multiphase interactions. Firs of all, a novel modelling approach based on CFD for the prediction of the gas separation process in membrane modules for hydrogen purification is developed. The reliability of the gas velocity field calculated numerically is assessed by comparison of the predictions with experimental velocity data collected by Particle Image Velocimetry, while the applicability of the model to properly predict the separation process under a wide range of operating conditions is assessed through a strict comparison with permeation experimental data. Then, the effect of numerical issues on the RANS-based predictions of single phase stirred tanks is analysed. The homogenisation process of a scalar tracer is also investigated and simulation results are compared to original passive tracer homogenisation curves determined with Planar Laser Induced Fluorescence. The capability of a CFD approach based on the solution of RANS equations is also investigated for describing the fluid dynamic characteristics of the dispersion of organics in water. Finally, an Eulerian-Eulerian fluid-dynamic model is used to simulate mono-disperse suspensions of Geldart A Group particles fluidized by a Newtonian incompressible fluid as well as binary segregating fluidized beds of particles differing in size and density. The results obtained under a number of different operating conditions are compared with literature experimental data and the effect of numerical uncertainties on axial segregation is also discussed.
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Biologische Membranen sind Fettmolekül-Doppelschichten, die sich wie zweidimensionale Flüssigkeiten verhalten. Die Energie einer solchen fluiden Oberfläche kann häufig mit Hilfe eines Hamiltonians beschrieben werden, der invariant unter Reparametrisierungen der Oberfläche ist und nur von ihrer Geometrie abhängt. Beiträge innerer Freiheitsgrade und der Umgebung können in den Formalismus mit einbezogen werden. Dieser Ansatz wird in der vorliegenden Arbeit dazu verwendet, die Mechanik fluider Membranen und ähnlicher Oberflächen zu untersuchen. Spannungen und Drehmomente in der Oberfläche lassen sich durch kovariante Tensoren ausdrücken. Diese können dann z. B. dazu verwendet werden, die Gleichgewichtsposition der Kontaktlinie zu bestimmen, an der sich zwei aneinander haftende Oberflächen voneinander trennen. Mit Ausnahme von Kapillarphänomenen ist die Oberflächenenergie nicht nur abhängig von Translationen der Kontaktlinie, sondern auch von Änderungen in der Steigung oder sogar Krümmung. Die sich ergebenden Randbedingungen entsprechen den Gleichgewichtsbedingungen an Kräfte und Drehmomente, falls sich die Kontaktlinie frei bewegen kann. Wenn eine der Oberflächen starr ist, muss die Variation lokal dieser Fläche folgen. Spannungen und Drehmomente tragen dann zu einer einzigen Gleichgewichtsbedingung bei; ihre Beiträge können nicht mehr einzeln identifiziert werden. Um quantitative Aussagen über das Verhalten einer fluiden Oberfläche zu machen, müssen ihre elastischen Eigenschaften bekannt sein. Der "Nanotrommel"-Versuchsaufbau ermöglicht es, Membraneigenschaften lokal zu untersuchen: Er besteht aus einer porenüberspannenden Membran, die während des Experiments durch die Spitze eines Rasterkraftmikroskops in die Pore gedrückt wird. Der lineare Verlauf der resultierenden Kraft-Abstands-Kurven kann mit Hilfe der in dieser Arbeit entwickelten Theorie reproduziert werden, wenn der Einfluss von Adhäsion zwischen Spitze und Membran vernachlässigt wird. Bezieht man diesen Effekt in die Rechnungen mit ein, ändert sich das Resultat erheblich: Kraft-Abstands-Kurven sind nicht länger linear, Hysterese und nichtverschwindende Trennkräfte treten auf. Die Voraussagen der Rechnungen könnten in zukünftigen Experimenten dazu verwendet werden, Parameter wie die Biegesteifigkeit der Membran mit einer Auflösung im Nanometerbereich zu bestimmen. Wenn die Materialeigenschaften bekannt sind, können Probleme der Membranmechanik genauer betrachtet werden. Oberflächenvermittelte Wechselwirkungen sind in diesem Zusammenhang ein interessantes Beispiel. Mit Hilfe des oben erwähnten Spannungstensors können analytische Ausdrücke für die krümmungsvermittelte Kraft zwischen zwei Teilchen, die z. B. Proteine repräsentieren, hergeleitet werden. Zusätzlich wird das Gleichgewicht der Kräfte und Drehmomente genutzt, um mehrere Bedingungen an die Geometrie der Membran abzuleiten. Für den Fall zweier unendlich langer Zylinder auf der Membran werden diese Bedingungen zusammen mit Profilberechnungen kombiniert, um quantitative Aussagen über die Wechselwirkung zu treffen. Theorie und Experiment stoßen an ihre Grenzen, wenn es darum geht, die Relevanz von krümmungsvermittelten Wechselwirkungen in der biologischen Zelle korrekt zu beurteilen. In einem solchen Fall bieten Computersimulationen einen alternativen Ansatz: Die hier präsentierten Simulationen sagen voraus, dass Proteine zusammenfinden und Membranbläschen (Vesikel) bilden können, sobald jedes der Proteine eine Mindestkrümmung in der Membran induziert. Der Radius der Vesikel hängt dabei stark von der lokal aufgeprägten Krümmung ab. Das Resultat der Simulationen wird in dieser Arbeit durch ein approximatives theoretisches Modell qualitativ bestätigt.
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This study develops an automated analysis tool by combining total internal reflection fluorescence microscopy (TIRFM), an evanescent wave microscopic imaging technique to capture time-sequential images and the corresponding image processing Matlab code to identify movements of single individual particles. The developed code will enable us to examine two dimensional hindered tangential Brownian motion of nanoparticles with a sub-pixel resolution (nanoscale). The measured mean square displacements of nanoparticles are compared with theoretical predictions to estimate particle diameters and fluid viscosity using a nonlinear regression technique. These estimated values will be confirmed by the diameters and viscosities given by manufacturers to validate this analysis tool. Nano-particles used in these experiments are yellow-green polystyrene fluorescent nanospheres (200 nm, 500 nm and 1000 nm in diameter (nominal); 505 nm excitation and 515 nm emission wavelengths). Solutions used in this experiment are de-ionized (DI) water, 10% d-glucose and 10% glycerol. Mean square displacements obtained near the surface shows significant deviation from theoretical predictions which are attributed to DLVO forces in the region but it conforms to theoretical predictions after ~125 nm onwards. The proposed automation analysis tool will be powerfully employed in the bio-application fields needed for examination of single protein (DNA and/or vesicle) tracking, drug delivery, and cyto-toxicity unlike the traditional measurement techniques that require fixing the cells. Furthermore, this tool can be also usefully applied for the microfluidic areas of non-invasive thermometry, particle tracking velocimetry (PTV), and non-invasive viscometry.
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Self-regulation plays an important role in successful adaptation to preschool and school contexts as well as in later academic achievement. The current study relates different aspects of self-regulation such as temperamental effortful control and executive functions (updating, inhibition, and shifting) to different aspects of adaptation to school such as learning-related behavior, school grades, and performance in standardized achievement tests. The relationship between executive functions/effortful control and academic achievement has been established in previous studies; however, little is known about their unique contributions to different aspects of adaptation to school and the interplay of these factors in young school children. Results of a 1-year longitudinal study (N = 459) revealed that unique contributions of effortful control (parental report) to school grades were fully mediated by children’s learning-related behavior. On the other hand, the unique contributions of executive functions (performance on tasks) to school grades were only partially mediated by children’s learning-related behavior. Moreover, executive functions predicted performance in standardized achievement tests exclusively, with comparable predictive power for mathematical and reading/writing skills. Controlling for fluid intelligence did not change the pattern of prediction substantially, and fluid intelligence did not explain any variance above that of the two included aspects of self-regulation. Although effortful control and executive functions were not significantly related to each other, both aspects of self-regulation were shown to be important for fostering early learning and good classroom adjustment in children around transition to school.
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Two factors that have been suggested as key in explaining individual differences in fluid intelligence are working memory and sensory discrimination ability. A latent variable approach was used to explore the relative contributions of these two variables to individual differences in fluid intelligence in middle to late childhood. A sample of 263 children aged 7–12 years was examined. Correlational analyses showed that general discrimination ability (GDA)and working memory (WM) were related to each other and to fluid intelligence. Structural equation modeling showed that within both younger and older age groups and the sample as a whole, the relation between GDA and fluid intelligence could be accounted for by WM. While WM was able to predict variance in fluid intelligence above and beyond GDA, GDA was not able to explain significant amounts of variance in fluid intelligence, either in the whole sample or within the younger or older age group. We concluded that compared to GDA, WM should be considered the better predictor of individual differences in fluid intelligence in childhood. WM and fluid intelligence, while not being separable in middle childhood, develop at different rates, becoming more separable with age.
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The clinical course of rhinovirus (RV)-associated wheezing illnesses is difficult to predict. We measured lactate dehydrogenase concentrations, RV load, antiviral and proinflammatory cytokines in nasal washes obtained from 126 preschool children with RV wheezy bronchitis. lactate dehydrogenase values were inversely associated with subsequent need for oxygen therapy. lactate dehydrogenase may be a useful biomarker predicting disease severity in RV wheezy bronchitis.
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Early atherosclerotic lesions develop in a topographical pattern that strongly suggests involvement of hemodynamic forces in their pathogenesis. We hypothesized that certain endothelial genes, which exhibit differential responsiveness to distinct fluid mechanical stimuli, may participate in the atherogenic process by modulating, on a local level within the arterial wall, the effects of systemic risk factors. A differential display strategy using cultured human endothelial cells has identified two genes, manganese superoxide dismutase and cyclooxygenase-2, that exhibit selective and sustained up-regulation by steady laminar shear stress (LSS). Turbulent shear stress, a nonlaminar fluid mechanical stimulus, does not induce these genes. The endothelial form of nitric oxide synthase also demonstrates a similar LSS-selective pattern of induction. Thus, three genes with potential atheroprotective (antioxidant, antithrombotic, and antiadhesive) activities manifest a differential response to distinct fluid mechanical stimuli, providing a possible mechanistic link between endothelial gene expression and early events in atherogenesis. The activities of these and other LSS-responsive genes may have important implications for the pathogenesis and prevention of atherosclerosis.
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In recent years structured packings have become more widely used in the process industries because of their improved volumetric efficiency. Most structured packings consist of corrugated sheets placed in the vertical plane The corrugations provide a regular network of channels for vapour liquid contact. Until recently it has been necessary to develop new packings by trial and error, testing new shapes in the laboratory. The orderly repetitive nature of the channel network produced by a structured packing suggests it may be possible to develop improved structured packings by the application of computational fluid dynamics (CFD) to calculate the packing performance and evaluate changes in shape so as to reduce the need for laboratory testing. In this work the CFD package PHOENICS has been used to predict the flow patterns produced in the vapour phase as it passes through the channel network. A particular novelty of the approach is to set up a method of solving the Navier Stokes equations for any particular intersection of channels. The flow pattern of the streams leaving the intersection is then made the input to the downstream intersection. In this way the flow pattern within a section of packing can be calculated. The resulting heat or mass transfer performance can be calculated by other standard CFD procedures. The CFD predictions revealed a circulation developing within the channels which produce a loss in mass transfer efficiency The calculations explained and predicted a change in mass transfer efficiency with depth of the sheets. This effect was also shown experimentally. New shapes of packing were proposed to remove the circulation and these were evaluated using CFD. A new shape was chosen and manufactured. This was tested experimentally and found to have a higher mass transfer efficiency than the standard packing.
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Compact thermal-fluid systems are found in many industries from aerospace to microelectronics where a combination of small size, light weight, and high surface area to volume ratio fluid networks are necessary. These devices are typically designed with fluid networks consisting of many small parallel channels that effectively pack a large amount of heat transfer surface area in a very small volume but do so at the cost of increased pumping power requirements. ^ To offset this cost the use of a branching fluid network for the distribution of coolant within a heat sink is investigated. The goal of the branch design technique is to minimize the entropy generation associated with the combination of viscous dissipation and convection heat transfer experienced by the coolant in the heat sink while maintaining compact high heat transfer surface area to volume ratios. ^ The derivation of Murray's Law, originally developed to predict the geometry of physiological transport systems, is extended to heat sink designs which minimze entropy generation. Two heat sink designs at different scales are built, and tested experimentally and analytically. The first uses this new derivation of Murray's Law. The second uses a combination of Murray's Law and Constructal Theory. The results of the experiments were used to verify the analytical and numerical models. These models were then used to compare the performance of the heat sink with other compact high performance heat sink designs. The results showed that the techniques used to design branching fluid networks significantly improves the performance of active heat sinks. The design experience gained was then used to develop a set of geometric relations which optimize the heat transfer to pumping power ratio of a single cooling channel element. Each element can be connected together using a set of derived geometric guidelines which govern branch diameters and angles. The methodology can be used to design branching fluid networks which can fit any geometry. ^