950 resultados para Fluid Flow Modeling


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Oxygen-deficient TiO2 films with enhanced visible and near-infrared optical absorption have been deposited by reactive sputtering using a planar diode radio frequency magnetron configuration. It is observed that the increase in the absorption coefficient is more effective when the O-2 gas supply is periodically interrupted rather than by a decrease of the partial O-2 gas pressure in the deposition plasma. The optical absorption coefficient at 1.5 eV increases from about 1 x 10(2) cm(-1) to more than 4 x 10(3) cm(-1) as a result of the gas flow discontinuity. A red-shift of similar to 0.24 eV in the optical absorption edge is also observed. High resolution transmission electron microscopy with composition analysis shows that the films present a dense columnar morphology, with estimated mean column width of 40nm. Moreover, the interruptions of the O-2 gas flow do not produce detectable variations in the film composition along its growing direction. X-ray diffraction and micro-Raman experiments indicate the presence of the TiO2 anatase, rutile, and brookite phases. The anatase phase is dominant, with a slight increment of the rutile and brookite phases in films deposited under discontinued O-2 gas flow. The increase of optical absorption in the visible and near-infrared regions has been attributed to a high density of defects in the TiO2 films, which is consistent with density functional theory calculations that place oxygen-related vacancy states in the upper third of the optical bandgap. The electronic structure calculation results, along with the adopted deposition method and experimental data, have been used to propose a mechanism to explain the formation of the observed oxygen-related defects in TiO2 thin films. The observed increase in sub-bandgap absorption and the modeling of the corresponding changes in the electronic structure are potentially useful concerning the optimization of efficiency of the photocatalytic activity and the magnetic doping of TiO2 films. (C) 2012 American Institute of Physics. [http://dx.doi.org/10.1063/1.4724334]

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The stratified oil-water flow pattern is common in the petroleum industry, especially in offshore directional wells and pipelines. Previous studies have shown that the phenomenon of flow pattern transition in stratified flow can be related to the interfacial wave structure (problem of hydrodynamic instability). The study of the wavy stratified flow pattern requires the characterization of the interfacial wave properties, i.e., average shape, celerity and geometric properties (amplitude and wavelength) as a function of holdup, inclination angle and phases' relative velocity. However, the data available in the literature on wavy stratified flow is scanty, especially in inclined pipes and when oil is viscous. This paper presents new geometric and kinematic interfacial wave properties as a function of a proposed two-phase Froude number in the wavy-stratified liquid-liquid flow. The experimental work was conducted in a glass test line of 12 m and 0.026 m id., oil (density and viscosity of 828 kg/m(3) and 0.3 Pa s at 20 degrees C, respectively) and water as the working fluids at several inclinations from horizontal (-20 degrees, -10 degrees, 0 degrees, 10 degrees, 20 degrees). The results suggest a physical relation between wave shape and the hydrodynamic stability of the stratified liquid-liquid flow pattern. (C) 2011 Elsevier Inc. All rights reserved.

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Abstract Background To understand the molecular mechanisms underlying important biological processes, a detailed description of the gene products networks involved is required. In order to define and understand such molecular networks, some statistical methods are proposed in the literature to estimate gene regulatory networks from time-series microarray data. However, several problems still need to be overcome. Firstly, information flow need to be inferred, in addition to the correlation between genes. Secondly, we usually try to identify large networks from a large number of genes (parameters) originating from a smaller number of microarray experiments (samples). Due to this situation, which is rather frequent in Bioinformatics, it is difficult to perform statistical tests using methods that model large gene-gene networks. In addition, most of the models are based on dimension reduction using clustering techniques, therefore, the resulting network is not a gene-gene network but a module-module network. Here, we present the Sparse Vector Autoregressive model as a solution to these problems. Results We have applied the Sparse Vector Autoregressive model to estimate gene regulatory networks based on gene expression profiles obtained from time-series microarray experiments. Through extensive simulations, by applying the SVAR method to artificial regulatory networks, we show that SVAR can infer true positive edges even under conditions in which the number of samples is smaller than the number of genes. Moreover, it is possible to control for false positives, a significant advantage when compared to other methods described in the literature, which are based on ranks or score functions. By applying SVAR to actual HeLa cell cycle gene expression data, we were able to identify well known transcription factor targets. Conclusion The proposed SVAR method is able to model gene regulatory networks in frequent situations in which the number of samples is lower than the number of genes, making it possible to naturally infer partial Granger causalities without any a priori information. In addition, we present a statistical test to control the false discovery rate, which was not previously possible using other gene regulatory network models.

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Abstract Introduction We conducted the present study to examine the effects of hypertonic saline solution (7.5%) on cardiovascular function and splanchnic perfusion in experimental sepsis. Methods Anesthetized and mechanically ventilated mongrel dogs received an intravenous infusion of live Escherichia coli over 30 minutes. After 30 minutes, they were randomized to receive lactated Ringer's solution 32 ml/kg (LR; n = 7) over 30 minutes or 7.5% hypertonic saline solution 4 ml/kg (HS; n = 8) over 5 minutes. They were observed without additional interventions for 120 minutes. Cardiac output (CO), mean arterial pressure (MAP), portal and renal blood flow (PBF and RBF, respectively), gastric partial pressure of CO2 (pCO2; gas tonometry), blood gases and lactate levels were assessed. Results E. coli infusion promoted significant reductions in CO, MAP, PBF and RBF (approximately 45%, 12%, 45% and 25%, respectively) accompanied by an increase in lactate levels and systemic and mesenteric oxygen extraction (sO2ER and mO2ER). Widening of venous-arterial (approximately 15 mmHg), portal-arterial (approximately 18 mmHg) and gastric mucosal-arterial (approximately 55 mmHg) pCO2 gradients were also observed. LR and HS infusion transiently improved systemic and regional blood flow. However, HS infusion was associated with a significant and sustained reduction of systemic (18 ± 2.6 versus 38 ± 5.9%) and mesenteric oxygen extraction (18.5 ± 1.9 versus 36.5 ± 5.4%), without worsening other perfusional markers. Conclusion A large volume of LR or a small volume of HS promoted similar transient hemodynamic benefits in this sepsis model. However, a single bolus of HS did promote sustained reduction of systemic and mesenteric oxygen extraction, suggesting that hypertonic saline solution could be used as a salutary intervention during fluid resuscitation in septic patients.

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Experimental two-phase frictional pressure drop and flow boiling heat transfer results are presented for a horizontal 2.32-mm ID stainless-steel tube using R245fa as working fluid. The frictional pressure drop data was obtained under adiabatic and diabatic conditions. Experiments were performed for mass velocities ranging from 100 to 700 kg m−2 s−1 , heat flux from 0 to 55 kW m−2 , exit saturation temperatures of 31 and 41◦C, and vapor qualities from 0.10 to 0.99. Pressures drop gradients and heat transfer coefficients ranging from 1 to 70 kPa m−1 and from 1 to 7 kW m−2 K−1 were measured. It was found that the heat transfer coefficient is a strong function of the heat flux, mass velocity, and vapor quality. Five frictional pressure drop predictive methods were compared against the experimental database. The Cioncolini et al. (2009) method was found to work the best. Six flow boiling heat transfer predictive methods were also compared against the present database. Liu and Winterton (1991), Zhang et al. (2004), and Saitoh et al. (2007) were ranked as the best methods. They predicted the experimental flow boiling heat transfer data with an average error around 19%.