Improved estimation of myelin water fractions with learned parameter distributions

Author(s):  
Yudu Li ◽  
Jiahui Xiong ◽  
Rong Guo ◽  
Yibo Zhao ◽  
Yao Li ◽  
...  
2021 ◽  
Vol 5 (1) ◽  
Author(s):  
Joyce C. C. Santos ◽  
Mariana C. Prado ◽  
Helane L. O. Morais ◽  
Samuel M. Sousa ◽  
Elisangela Silva-Pinto ◽  
...  

AbstractThe production of 2D material flakes in large quantities is a rapidly evolving field and a cornerstone for their industrial applicability. Although flake production has advanced in a fast pace, its statistical characterization is somewhat slower, with few examples in the literature which may lack either modelling uniformity and/or physical equivalence to actual flake dimensions. The present work brings a methodology for 2D material flake characterization with a threefold target: (i) propose a set of morphological shape parameters that correctly map to actual and relevant flake dimensions; (ii) find a single distribution function that efficiently describes all these parameter distributions; and (iii) suggest a representation system—topological vectors—that uniquely characterizes the statistical flake morphology within a given distribution. The applicability of such methodology is illustrated via the analysis of tens of thousands flakes of graphene/graphite and talc, which were submitted to different production protocols. The richness of information unveiled by this universal methodology may help the development of necessary standardization procedures for the imminent 2D-materials industry.


Author(s):  
Jose Plasencia ◽  
Nathanael Inkson ◽  
Ole Jørgen Nydal

AbstractThis paper reports experimental research on the flow behavior of oil-water surfactant stabilized emulsions in different pipe diameters along with theoretical and computational fluid dynamics (CFD) modeling of the relative viscosity and inversion properties. The pipe flow of emulsions was studied in turbulent and laminar conditions in four pipe diameters (16, 32, 60, and 90 mm) at different mixture velocities and increasing water fractions. Salt water (3.5% NaCl w/v, pH = 7.3) and a mineral oil premixed with a lipophilic surfactant (Exxsol D80 + 0.25% v/v of Span 80) were used as the test fluids. The formation of water-in-oil emulsions was observed from low water fractions up to the inversion point. After inversion, unstable water-in-oil in water multiple emulsions were observed under different flow regimes. These regimes depend on the mixture velocity and the local water fraction of the water-in-oil emulsion. The eddy turbulent viscosity calculated using an elliptic-blending k-ε model and the relative viscosity in combination act to explain the enhanced pressure drop observed in the experiments. The inversion process occurred at a constant water fraction (90%) and was triggered by an increase of mixture velocity. No drag reduction effect was detected for the water-in-oil emulsions obtained before inversion.


2020 ◽  
Vol 34 (12) ◽  
pp. 2725-2738 ◽  
Author(s):  
Paolo Benettin ◽  
Ophélie Fovet ◽  
Li Li

2016 ◽  
Vol 14 (3) ◽  
pp. 443-459 ◽  
Author(s):  
Keewook Kim ◽  
Gene Whelan ◽  
Marirosa Molina ◽  
S. Thomas Purucker ◽  
Yakov Pachepsky ◽  
...  

A series of simulated rainfall-runoff experiments with applications of different manure types (cattle solid pats, poultry dry litter, swine slurry) was conducted across four seasons on a field containing 36 plots (0.75 × 2 m each), resulting in 144 rainfall-runoff events. Simulating time-varying release of Escherichia coli, enterococci, and fecal coliforms from manures applied at typical agronomic rates evaluated the efficacy of the Bradford–Schijven model modified by adding terms for release efficiency and transportation loss. Two complementary, parallel approaches were used to calibrate the model and estimate microbial release parameters. The first was a four-step sequential procedure using the inverse model PEST, which provides appropriate initial parameter values. The second utilized a PEST/bootstrap procedure to estimate average parameters across plots, manure age, and microbe, and to provide parameter distributions. The experiment determined that manure age, microbe, and season had no clear relationship to the release curve. Cattle solid pats released microbes at a different, slower rate than did poultry dry litter or swine slurry, which had very similar release patterns. These findings were consistent with other published results for both bench- and field-scale, suggesting the modified Bradford–Schijven model can be applied to microbial release from manure.


2021 ◽  
pp. 1-18
Author(s):  
Gisela Vanegas ◽  
John Nejedlik ◽  
Pascale Neff ◽  
Torsten Clemens

Summary Forecasting production from hydrocarbon fields is challenging because of the large number of uncertain model parameters and the multitude of observed data that are measured. The large number of model parameters leads to uncertainty in the production forecast from hydrocarbon fields. Changing operating conditions [e.g., implementation of improved oil recovery or enhanced oil recovery (EOR)] results in model parameters becoming sensitive in the forecast that were not sensitive during the production history. Hence, simulation approaches need to be able to address uncertainty in model parameters as well as conditioning numerical models to a multitude of different observed data. Sampling from distributions of various geological and dynamic parameters allows for the generation of an ensemble of numerical models that could be falsified using principal-component analysis (PCA) for different observed data. If the numerical models are not falsified, machine-learning (ML) approaches can be used to generate a large set of parameter combinations that can be conditioned to the different observed data. The data conditioning is followed by a final step ensuring that parameter interactions are covered. The methodology was applied to a sandstone oil reservoir with more than 70 years of production history containing dozens of wells. The resulting ensemble of numerical models is conditioned to all observed data. Furthermore, the resulting posterior-model parameter distributions are only modified from the prior-model parameter distributions if the observed data are informative for the model parameters. Hence, changes in operating conditions can be forecast under uncertainty, which is essential if nonsensitive parameters in the history are sensitive in the forecast.


2014 ◽  
Vol 18 (11) ◽  
pp. 4391-4401 ◽  
Author(s):  
J. L. Salinas ◽  
A. Castellarin ◽  
S. Kohnová ◽  
T. R. Kjeldsen

Abstract. This study aims to better understand the effect of catchment scale and climate on the statistical properties of regional flood frequency distributions. A database of L-moment ratios of annual maximum series (AMS) of peak discharges from Austria, Italy and Slovakia, involving a total of 813 catchments with more than 25 yr of record length is presented, together with mean annual precipitation (MAP) and basin area as catchment descriptors surrogates of climate and scale controls. A purely data-based investigation performed on the database shows that the generalized extreme value (GEV) distribution provides a better representation of the averaged sample L-moment ratios compared to the other distributions considered, for catchments with medium to higher values of MAP independently of catchment area, while the three-parameter lognormal distribution is probably a more appropriate choice for drier (lower MAP) intermediate-sized catchments, which presented higher skewness values. Sample L-moment ratios do not follow systematically any of the theoretical two-parameter distributions. In particular, the averaged values of L-coefficient of skewness (L-Cs) are always larger than Gumbel's fixed L-Cs. The results presented in this paper contribute to the progress in defining a set of "process-driven" pan-European flood frequency distributions and to assess possible effects of environmental change on its properties.


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