99 resultados para Modified k-epsilon model


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The kinetics of drop penetration were studied by filming single drops of several different fluids (water, PEG200, PEG600, and HPC solutions) as they penetrated into loosely packed beds of glass ballotini, lactose, zinc oxide, and titanium dioxide powders. Measured times ranged from 0.45 to 126 s and depended on the powder particle size,viscosity, surface tensions, and contact angle. The experimental drop penetration times were compared to existing theoretical predictions by M. Denesuk et al. (J. Colloid Interface Sci. 158, 114, 1993) and S. Middleman (Modeling Axisymmetric Flows: Dynamics of Films, Jets, and Drops, Academic Press, San Diego, 1995) but did not agree. Loosely packed powder beds tend to have a heterogeneous bed structure containing large macrovoids which do not participate in liquid flow but are included implicitly in the existing approach to estimating powder pore size. A new two-phase model was proposed where the total volume of the macrovoids was assumed to be the difference between the bed porosity and the tap porosity. A new parameter, the effective porosity (epsilon)eff, was defined as the tap porosity multiplied by the fraction of pores that terminate at a macrovoid and are effectively blocked pores. The improved drop penetration model was much more successful at estimating the drop penetration time on all powders and the predicted times were generally within an order of magnitude of the experimental results. (C) 2002 Elsevier Science (USA).

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A comprehensive probabilistic model for simulating microstructure formation and evolution during solidification has been developed, based on coupling a Finite Differential Method (FDM) for macroscopic modelling of heat diffusion to a modified Cellular Automaton (mCA) for microscopic modelling of nucleation, growth of microstructures and solute diffusion. The mCA model is similar to Nastac's model for handling solute redistribution in the liquid and solid phases, curvature and growth anisotropy, but differs in the treatment of nucleation and growth. The aim is to improve understanding of the relationship between the solidification conditions and microstructure formation and evolution. A numerical algorithm used for FDM and mCA was developed. At each coarse scale, temperatures at FDM nodes were calculated while nucleation-growth simulation was done at a finer scale, with the temperature at the cell locations being interpolated from those at the coarser volumes. This model takes account of thermal, curvature and solute diffusion effects. Therefore, it can not only simulate microstructures of alloys both on the scale of grain size (macroscopic level) and the dendrite tip length (mesoscopic level), but also investigate nucleation mechanisms and growth kinetics of alloys solidified with various solute concentrations and solidification morphologies. The calculated results are compared with values of grain sizes and solidification morphologies of microstructures obtained from a set of casting experiments of Al-Si alloys in graphite crucibles.

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Magnetic resonance imaging (MRI) is an easily automated, reliable technique to investigate axial mixing within rotating drums. Moist bran can be clearly differentiated from dry bran using MRI allowing a non-segregating tracer for axial mixing. For a 20-cm diameter drum, the axial dispersion coefficient in the particle bed was 0.51 cm s(-2). Axial dispersion is scale-dependent.

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This article extends earlier research regarding the relationships between senior travelers’ participation in activities while on vacation, their overall satisfaction with their travel experiences, and their psychological well-being. A path model was developed to depict the direct and indirect relationships between these variables by using a sample of senior tourists traveling on North American escorted tour itineraries. Whereas the direct effect accounted for 98% of the relationships between the senior tourists’ levels of participation in activities and their psychological well-being, the indirect effect was negligible. The study concluded that senior tourists’activity levels were significantly related to their psychological well-being, but their satisfaction with the tours was not.

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The Agricultural Production Systems slMulator, APSIM, is a cropping system modelling environment that simulates the dynamics of soil-plant-management interactions within a single crop or a cropping system. Adaptation of previously developed crop models has resulted in multiple crop modules in APSIM, which have low scientific transparency and code efficiency. A generic crop model template (GCROP) has been developed to capture unifying physiological principles across crops (plant types) and to provide modular and efficient code for crop modelling. It comprises a standard crop interface to the APSIM engine, a generic crop model structure, a crop process library, and well-structured crop parameter files. The process library contains the major science underpinning the crop models and incorporates generic routines based on physiological principles for growth and development processes that are common across crops. It allows APSIM to simulate different crops using the same set of computer code. The generic model structure and parameter files provide an easy way to test, modify, exchange and compare modelling approaches at process level without necessitating changes in the code. The standard interface generalises the model inputs and outputs, and utilises a standard protocol to communicate with other APSIM modules through the APSIM engine. The crop template serves as a convenient means to test new insights and compare approaches to component modelling, while maintaining a focus on predictive capability. This paper describes and discusses the scientific basis, the design, implementation and future development of the crop template in APSIM. On this basis, we argue that the combination of good software engineering with sound crop science can enhance the rate of advance in crop modelling. Crown Copyright (C) 2002 Published by Elsevier Science B.V. All rights reserved.

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The purpose of this study was to determine the pharmacokinetics of [C-14]diclofenac, [C-14]salicylate and [H-3]clonidine using a single pass rat head perfusion preparation. The head was perfused with 3-[N-morpholino] propane-sulfonic acid-buffered Ringer's solution. Tc-99m-red blood cells and a drug were injected in a bolus into the internal carotid artery and collected from the posterior facial vein over 28 min. A two-barrier stochastic organ model was used to estimate the statistical moments of the solutes. Plasma, interstitial and cellular distribution volumes for the solutes ranged from 1.0 mL (diclofenac) to 1.6 mL (salicylate), 2.0 mL (diclofenac) to 4.2 mL (water) and 3.9 mL (salicylate) to 20.9 mL (diclofenac), respectively. A comparison of these volumes to water indicated some exclusion of the drugs from the interstitial space and salicylate from the cellular space. Permeability-surface area (PS) products calculated from plasma to interstitial fluid permeation clearances (CLPI) (range 0.02-0.40 mL s(-1)) and fractions of solute unbound in the perfusate were in the order: diclofenac>salicylate >clonidine>sucrose (from 41.8 to 0.10 mL s(-1)). The slow efflux of diclofenac, compared with clonidine and salicylate, may be related to its low average unbound fraction in the cells. This work accounts for the tail of disposition curves in describing pharmacokinetics in the head.

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Two peptides, textilinins 1 and 2, isolated from the venom of the Australian common brown snake, Pseudonaja textilis textilis, are effective in preventing blood loss. To further investigate the potential of textilinins as anti-haemorrhagic agents, we cloned cDNAs encoding these proteins. The isolated full-length cDNA (430 bp in size) was shown to code for a 59 amino acid protein, corresponding in size to the native peptide, plus an additional 24 amino acid propeptide. Six such cDNAs were identified, differing in nucleotide sequence in the coding region but with an identical propeptide. All six sequences predicted peptides containing six conserved cysteines common to Kunitz-type serine protease inhibitors. When expressed as glutathione S-transferase (GST) fusion proteins and released by cleavage with thrombin, only those peptides corresponding to textilinin 1 and 2 were active in inhibiting plasmin with K-i values similar to those of their native counterparts and in binding to plasmin less tightly than aprotinin by two orders of magnitude. Similarly, in the mouse tail vein blood loss model only recombinant textilinin 1 and 2 were effective in reducing blood loss. These recombinant textilinins have potential as therapeutic agents for reducing blood loss in humans, obviating the need for reliance on aprotinin, a bovine product with possible risk of transmissible disease, and compromising the fibrinolytic system in a less irreversible manner.

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The Agricultural Production Systems Simulator (APSIM) is a modular modelling framework that has been developed by the Agricultural Production Systems Research Unit in Australia. APSIM was developed to simulate biophysical process in farming systems, in particular where there is interest in the economic and ecological outcomes of management practice in the face of climatic risk. The paper outlines APSIM's structure and provides details of the concepts behind the different plant, soil and management modules. These modules include a diverse range of crops, pastures and trees, soil processes including water balance, N and P transformations, soil pH, erosion and a full range of management controls. Reports of APSIM testing in a diverse range of systems and environments are summarised. An example of model performance in a long-term cropping systems trial is provided. APSIM has been used in a broad range of applications, including support for on-farm decision making, farming systems design for production or resource management objectives, assessment of the value of seasonal climate forecasting, analysis of supply chain issues in agribusiness activities, development of waste management guidelines, risk assessment for government policy making and as a guide to research and education activity. An extensive citation list for these model testing and application studies is provided. Crown Copyright (C) 2002 Published by Elsevier Science B.V. All rights reserved.

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Chest clapping, vibration, and shaking were studied in 10 physiotherapists who applied these techniques on an anesthetized animal model. Hemodynamic variables (such as heart rate, blood pressure, pulmonary artery pressure, and right atrial pressure) were measured during the application of these techniques to verify claims of adverse events. In addition, expired tidal volume and peak expiratory flow rate were measured to ascertain effects of these techniques. Physiotherapists in this study applied chest clapping at a rate of 6.2 +/- 0.9 Hz, vibration at 10.5 +/- 2.3 Hz, and shaking at 6.2 +/- 2.3 Hz. With the use of these rates, esophageal pressure swings of 8.8 +/- 5.0, 0.7 +/- 0.3, and 1.4 +/- 0.7 mmHg resulted from clapping, vibration, and shaking respectively. Variability in rates and forces generated by these techniques was 80% of variance in shaking force (P = 0.003). Application of these techniques by physiotherapists was found to have no significant effects on hemodynamic and most ventilatory variables in this study. From this study, we conclude that chest clapping, vibration, and shaking 1) can be consistently performed by physiotherapists; 2) are significantly related to physiotherapists' characteristics, particularly clinical experience; and 3) caused no significant hemodynamic effects.

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ATP-dependent K+ channels (K-ATP) account for most of the recycling of K+ which enters the proximal tubules cell via Na, K-ATPase. In the mitochondrial membrane, opening of these channels preserves mitochondrial viability and matrix volume during ischemia. We examined KATP channel modulation in renal ischemia-reperfusion injury (IRI), using an isolated perfused rat kidney (IPRK) model, in control, IRI, IRI + 200 muM diazoxide (a K-ATP opener), IRI + 10 muM glibenclamide (a K-ATP blocker) and IRI + 200 muM diazoxide + 10 muM glibenclamide groups. IRI was induced by 2 periods of warm ischemia, followed by 45 min of reperfusion. IRI significantly decreased glomerular filtration rate (GFR) and increased fractional excretion of sodium (FENa) (p < 0.01). Neither diazoxide nor glibenclamide had an effect on control kidney function other than an increase in renal vascular resistance produced by glibenclamide. Pretreatment with 200 muM diazoxide reduced the postischemic increase in FENa (p < 0.05). Adding 10 muM glibenclamide inhibited the diazoxide effect on postischemic FENa (p < 0.01). Histology showed that kidneys pretreated with glibenclamide demonstrated an increase in injure in the thick ascending limb of outer medulla (p < 0.05). Glibenclamide significantly decreased post ischemic renal vascular resistance (p < 0.05). but had no significant effect on other renal function parameters. Our results suggest that sodium reabsorption is improved by K-ATP activation and blockade of K-ATP channels during IRI has an injury enhancing effect on renal epithelial function and histology. This may be mediated through K-ATP modulation in cell and or mitochondrial inner membrane.

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We consider a mixture model approach to the regression analysis of competing-risks data. Attention is focused on inference concerning the effects of factors on both the probability of occurrence and the hazard rate conditional on each of the failure types. These two quantities are specified in the mixture model using the logistic model and the proportional hazards model, respectively. We propose a semi-parametric mixture method to estimate the logistic and regression coefficients jointly, whereby the component-baseline hazard functions are completely unspecified. Estimation is based on maximum likelihood on the basis of the full likelihood, implemented via an expectation-conditional maximization (ECM) algorithm. Simulation studies are performed to compare the performance of the proposed semi-parametric method with a fully parametric mixture approach. The results show that when the component-baseline hazard is monotonic increasing, the semi-parametric and fully parametric mixture approaches are comparable for mildly and moderately censored samples. When the component-baseline hazard is not monotonic increasing, the semi-parametric method consistently provides less biased estimates than a fully parametric approach and is comparable in efficiency in the estimation of the parameters for all levels of censoring. The methods are illustrated using a real data set of prostate cancer patients treated with different dosages of the drug diethylstilbestrol. Copyright (C) 2003 John Wiley Sons, Ltd.

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In microarray studies, the application of clustering techniques is often used to derive meaningful insights into the data. In the past, hierarchical methods have been the primary clustering tool employed to perform this task. The hierarchical algorithms have been mainly applied heuristically to these cluster analysis problems. Further, a major limitation of these methods is their inability to determine the number of clusters. Thus there is a need for a model-based approach to these. clustering problems. To this end, McLachlan et al. [7] developed a mixture model-based algorithm (EMMIX-GENE) for the clustering of tissue samples. To further investigate the EMMIX-GENE procedure as a model-based -approach, we present a case study involving the application of EMMIX-GENE to the breast cancer data as studied recently in van 't Veer et al. [10]. Our analysis considers the problem of clustering the tissue samples on the basis of the genes which is a non-standard problem because the number of genes greatly exceed the number of tissue samples. We demonstrate how EMMIX-GENE can be useful in reducing the initial set of genes down to a more computationally manageable size. The results from this analysis also emphasise the difficulty associated with the task of separating two tissue groups on the basis of a particular subset of genes. These results also shed light on why supervised methods have such a high misallocation error rate for the breast cancer data.