Stress Optical Coefficient, Test Methodology, and Glass Standard Evaluation

DTIC Science & Technology

2016-05-01

identifying and mapping flaw size distributions on glass surfaces for predicting mechanical response. International Journal of Applied Glass ...ARL-TN-0756 ● MAY 2016 US Army Research Laboratory Stress Optical Coefficient, Test Methodology, and Glass Standard Evaluation...Stress Optical Coefficient, Test Methodology, and Glass Standard Evaluation by Clayton M Weiss Oak Ridge Institute for Science and Education

Constrained dipole oscillator strength distributions, sum rules, and dispersion coefficients for Br2 and BrCN

NASA Astrophysics Data System (ADS)

Kumar, Ashok; Thakkar, Ajit J.

2017-03-01

Dipole oscillator strength distributions for Br2 and BrCN are constructed from photoabsorption cross-sections combined with constraints provided by the Kuhn-Reiche-Thomas sum rule, the high-energy behavior of the dipole-oscillator-strength density and molar refractivity data when available. The distributions are used to predict dipole sum rules S (k) , mean excitation energies I (k) , and van der Waals C6 coefficients. Coupled-cluster calculations of the static dipole polarizabilities of Br2 and BrCN are reported for comparison with the values of S (- 2) extracted from the distributions.

Statistical procedures for evaluating daily and monthly hydrologic model predictions

USGS Publications Warehouse

Coffey, M.E.; Workman, S.R.; Taraba, J.L.; Fogle, A.W.

2004-01-01

The overall study objective was to evaluate the applicability of different qualitative and quantitative methods for comparing daily and monthly SWAT computer model hydrologic streamflow predictions to observed data, and to recommend statistical methods for use in future model evaluations. Statistical methods were tested using daily streamflows and monthly equivalent runoff depths. The statistical techniques included linear regression, Nash-Sutcliffe efficiency, nonparametric tests, t-test, objective functions, autocorrelation, and cross-correlation. None of the methods specifically applied to the non-normal distribution and dependence between data points for the daily predicted and observed data. Of the tested methods, median objective functions, sign test, autocorrelation, and cross-correlation were most applicable for the daily data. The robust coefficient of determination (CD*) and robust modeling efficiency (EF*) objective functions were the preferred methods for daily model results due to the ease of comparing these values with a fixed ideal reference value of one. Predicted and observed monthly totals were more normally distributed, and there was less dependence between individual monthly totals than was observed for the corresponding predicted and observed daily values. More statistical methods were available for comparing SWAT model-predicted and observed monthly totals. The 1995 monthly SWAT model predictions and observed data had a regression Rr2 of 0.70, a Nash-Sutcliffe efficiency of 0.41, and the t-test failed to reject the equal data means hypothesis. The Nash-Sutcliffe coefficient and the R r2 coefficient were the preferred methods for monthly results due to the ability to compare these coefficients to a set ideal value of one.

Modified Regression Correlation Coefficient for Poisson Regression Model

NASA Astrophysics Data System (ADS)

Kaengthong, Nattacha; Domthong, Uthumporn

2017-09-01

This study gives attention to indicators in predictive power of the Generalized Linear Model (GLM) which are widely used; however, often having some restrictions. We are interested in regression correlation coefficient for a Poisson regression model. This is a measure of predictive power, and defined by the relationship between the dependent variable (Y) and the expected value of the dependent variable given the independent variables [E(Y|X)] for the Poisson regression model. The dependent variable is distributed as Poisson. The purpose of this research was modifying regression correlation coefficient for Poisson regression model. We also compare the proposed modified regression correlation coefficient with the traditional regression correlation coefficient in the case of two or more independent variables, and having multicollinearity in independent variables. The result shows that the proposed regression correlation coefficient is better than the traditional regression correlation coefficient based on Bias and the Root Mean Square Error (RMSE).

High Reynolds number analysis of flat plate and separated afterbody flow using non-linear turbulence models

NASA Technical Reports Server (NTRS)

Carlson, John R.

1996-01-01

The ability of the three-dimensional Navier-Stokes method, PAB3D, to simulate the effect of Reynolds number variation using non-linear explicit algebraic Reynolds stress turbulence modeling was assessed. Subsonic flat plate boundary-layer flow parameters such as normalized velocity distributions, local and average skin friction, and shape factor were compared with DNS calculations and classical theory at various local Reynolds numbers up to 180 million. Additionally, surface pressure coefficient distributions and integrated drag predictions on an axisymmetric nozzle afterbody were compared with experimental data from 10 to 130 million Reynolds number. The high Reynolds data was obtained from the NASA Langley 0.3m Transonic Cryogenic Tunnel. There was generally good agreement of surface static pressure coefficients between the CFD and measurement. The change in pressure coefficient distributions with varying Reynolds number was similar to the experimental data trends, though slightly over-predicting the effect. The computational sensitivity of viscous modeling and turbulence modeling are shown. Integrated afterbody pressure drag was typically slightly lower than the experimental data. The change in afterbody pressure drag with Reynolds number was small both experimentally and computationally, even though the shape of the distribution was somewhat modified with Reynolds number.

A laser-induced heat flux technique for convective heat transfer measurements in high speed flows

NASA Technical Reports Server (NTRS)

Porro, A. R.; Keith, T. G., Jr.; Hingst, W. R.

1991-01-01

A technique is developed to measure the local convective heat transfer coefficient on a model surface in a supersonic flow field. The technique uses a laser to apply a discrete local heat flux at the model test surface, and an infrared camera system determines the local temperature distribution due to the heating. From this temperature distribution and an analysis of the heating process, a local convective heat transfer coefficient is determined. The technique was used to measure the local surface convective heat transfer coefficient distribution on a flat plate at nominal Mach numbers of 2.5, 3.0, 3.5, and 4.0. The flat plate boundary layer initially was laminar and became transitional in the measurement region. The experimentally determined convective heat transfer coefficients were generally higher than the theoretical predictions for flat plate laminar boundary layers. However, the results indicate that this nonintrusive optical measurement technique has the potential to measure surface convective heat transfer coefficients in high speed flow fields.

A laser-induced heat flux technique for convective heat transfer measurements in high speed flows

NASA Technical Reports Server (NTRS)

Porro, A. R.; Keith, T. G., Jr.; Hingst, W. R.

1991-01-01

A technique is developed to measure the local convective heat transfer coefficient on a model surface in a supersonic flow field. The technique uses a laser to apply a discrete local heat flux at the model test surface, and an infrared camera system determines the local temperature distribution due to the heating. From this temperature distribution and an analysis of the heating process, a local convective heat transfer coefficient is determined. The technique was used to measure the local surface convective heat transfer coefficient distribution on a flat plate at nominal Mach numbers of 2.5, 3.0, 3.5, and 4.0. The flat plate boundary layer initially was laminar and became transitional in the measurement region. The experimentally determined convective heat transfer coefficients were generally higher than the theoretical predictions for flat plate laminar boundary layers. However, the results indicate that this nonintrusive optical measurement technique has the potential to measure surface convective heat transfer coefficients in high-speed flowfields.

Calculation of distribution coefficients in the SAMPL5 challenge from atomic solvation parameters and surface areas.

PubMed

Santos-Martins, Diogo; Fernandes, Pedro Alexandrino; Ramos, Maria João

2016-11-01

In the context of SAMPL5, we submitted blind predictions of the cyclohexane/water distribution coefficient (D) for a series of 53 drug-like molecules. Our method is purely empirical and based on the additive contribution of each solute atom to the free energy of solvation in water and in cyclohexane. The contribution of each atom depends on the atom type and on the exposed surface area. Comparatively to similar methods in the literature, we used a very small set of atomic parameters: only 10 for solvation in water and 1 for solvation in cyclohexane. As a result, the method is protected from overfitting and the error in the blind predictions could be reasonably estimated. Moreover, this approach is fast: it takes only 0.5 s to predict the distribution coefficient for all 53 SAMPL5 compounds, allowing its application in virtual screening campaigns. The performance of our approach (submission 49) is modest but satisfactory in view of its efficiency: the root mean square error (RMSE) was 3.3 log D units for the 53 compounds, while the RMSE of the best performing method (using COSMO-RS) was 2.1 (submission 16). Our method is implemented as a Python script available at https://github.com/diogomart/SAMPL5-DC-surface-empirical .

Predictability of drug release from water-insoluble polymeric matrix tablets.

PubMed

Grund, Julia; Körber, Martin; Bodmeier, Roland

2013-11-01

The purpose of this study was to extend the predictability of an established solution of Fick's second law of diffusion with formulation-relevant parameters and including percolation theory. Kollidon SR (polyvinyl acetate/polyvinylpyrrolidone, 80/20 w/w) matrix tablets with various porosities (10-30% v/v) containing model drugs with different solubilities (Cs=10-170 mg/ml) and in different amounts (A=10-90% w/w) were prepared by direct compression and characterized by drug release and mass loss studies. Drug release was fitted to Fick's second law to obtain the apparent diffusion coefficient. Its changes were correlated with the total porosity of the matrix and the solubility of the drug. The apparent diffusion coefficient was best described by a cumulative normal distribution over the range of total porosities. The mean of the distribution coincided with the polymer percolation threshold, and the minimum and maximum of the distribution were represented by the diffusion coefficient in pore-free polymer and in aqueous medium, respectively. The derived model was verified, and the applicability further extended to a drug solubility range of 10-1000 mg/ml. The developed mathematical model accurately describes and predicts drug release from Kollidon SR matrix tablets. It can efficiently reduce experimental trials during formulation development. Copyright © 2013 Elsevier B.V. All rights reserved.

Precise predictions for the angular coefficients in Z-boson production at the LHC

NASA Astrophysics Data System (ADS)

Gauld, R.; Gehrmann-De Ridder, A.; Gehrmann, T.; Glover, E. W. N.; Huss, A.

2017-11-01

The angular distributions of lepton pairs in the Drell-Yan process can provide rich information on the underlying QCD production mechanisms. These dynamics can be parameterised in terms of a set of frame dependent angular coefficients, A i=0,…,7, which depend on the invariant mass, transverse momentum, and rapidity of the lepton pair. Motivated by recent measurements of these coefficients by ATLAS and CMS, and in particular by the apparent violation of the Lam-Tung relation A 0 - A 2 = 0, we perform a precision study of the angular coefficients at O({α}s^3) in perturbative QCD. We make predic-tions relevant for pp collisions at √{s}=8 TeV, and perform comparisons with the available ATLAS and CMS data as well as providing predictions for a prospective measurement at LHCb. To expose the violation of the Lam-Tung relationship we propose a new observable ΔLT = 1 - A 2 /A 0 that is more sensitive to the dynamics in the region where A 0 and A 2 are both small. We find that the O({α}s^3) corrections have an important impact on the p T,Z distributions for several of the angular coefficients, and are essential to provide an adequate description of the data. The compatibility of the available ATLAS and CMS data is reassessed by performing a partial χ 2 test with respect to the central theoretical prediction which shows that χ 2 /N data is significantly reduced by going from O({α}s^2) to O({α}s^3).

Prediction of pH-Dependent Hydrophobic Profiles of Small Molecules from Miertus-Scrocco-Tomasi Continuum Solvation Calculations.

PubMed

Zamora, William J; Curutchet, Carles; Campanera, Josep M; Luque, F Javier

2017-10-26

Hydrophobicity is a key physicochemical descriptor used to understand the biological profile of (bio)organic compounds as well as a broad variety of biochemical, pharmacological, and toxicological processes. This property is estimated from the partition coefficient between aqueous and nonaqueous environments for neutral compounds (P N ) and corrected for the pH-dependence of ionizable compounds as the distribution coefficient (D). Here, we have extended the parametrization of the Miertus-Scrocco-Tomasi continuum solvation model in n-octanol to nitrogen-containing heterocyclic compounds, as they are present in many biologically relevant molecules (e.g., purines and pyrimidines bases, amino acids, and drugs), to obtain accurate log P N values for these molecules. This refinement also includes solvation calculations for ionic species in n-octanol with the aim of reproducing the experimental partition of ionic compounds (P I ). Finally, the suitability of different formalisms to estimate the distribution coefficient for a wide range of pH values has been examined for a set of small acidic and basic compounds. The results indicate that in general the simple pH-dependence model of the ionizable compound in water suffices to predict the partitioning at or around physiological pH. However, at extreme pH values, where ionic species are predominant, more elaborate models provide a better prediction of the n-octanol/water distribution coefficient, especially for amino acid analogues. Finally, the results also show that these formalisms are better suited to reproduce the experimental pH-dependent distribution curves of log D for both acidic and basic compounds as well as for amino acid analogues.

Estimation of cesium ion exchange distribution coefficients for concentrated electrolytic solutions when using crystalline silicotitanates

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zheng, Z.; Gu, D.; Anthony, R.G.

1995-06-01

Polzer et al.`s method combined with Bromley`s method for estimating activity coefficients and a Langmuir isotherm for cesium in a simple simulated waste solution containing 5.1 M NaNO{sub 3} and 0.6 M NaOH was used to estimate distribution coefficients for cesium in a complex simulated waste solution characteristic of the radioactive tank wastes at Hanford and other US Department of energy sites. The ion exchange material was a hydrous sodium crystalline silicotitanate, labeled TAM-5, which is being developed by Texas A and M University, Sandia National Laboratories, and UOP Associates. Cesium distribution coefficients collected by Bray et al. on amore » NCAW simulated waste solution were predicted with deviations of less than 25% for solutions containing 1 M, 3 M, and 5 M Na{sup +} and Na:Cs ratios of 10{sup 3}--10{sup 8}. The deviations were less than 5% for the solutions with 1 M Na{sup +}. Cesium distribution coefficients were also predicted and compared with values measured by Egan et al. for TAM-5 and for a storage tank supernate and a newly generated waste solution. Excellent results were obtained for the newly generated waste simulated solution, which did not contain potassium or rubidium.The predictions for the other simulated waste solution were significantly greater than the measured values, because of the presence of large concentrations of potassium or rubidium. The effect of competitive ion exchange between Cs, Rb, and K was not included in the theory. However, the effect of competitive ion exchange between Cs, Rb, and K was not included in the theory. However, the effect of competitive exchange of Cs, Rb, and K appears to be greater for the Oak Ridge simulated waste solution than for the NCAW waste.« less

Experimental and theoretical rotordynamic stiffness coefficients for a three-stage brush seal

NASA Astrophysics Data System (ADS)

Pugachev, A. O.; Deckner, M.

2012-08-01

Experimental and theoretical results are presented for a multistage brush seal. Experimental stiffness is obtained from integrating circumferential pressure distribution measured in seal cavities. A CFD analysis is used to predict seal performance. Bristle packs are modeled by the porous medium approach. Leakage is predicted well by the CFD method. Theoretical stiffness coefficients are in reasonable agreement with the measurements. Experimental results are also compared with a three-teeth-on-stator labyrinth seal. The multistage brush seal gives about 60% leakage reduction over the labyrinth seal. Rotordynamic stiffness coefficients are also improved: the brush seal has positive direct stiffness and smaller cross-coupled stiffness.

Random-growth urban model with geographical fitness

NASA Astrophysics Data System (ADS)

Kii, Masanobu; Akimoto, Keigo; Doi, Kenji

2012-12-01

This paper formulates a random-growth urban model with a notion of geographical fitness. Using techniques of complex-network theory, we study our system as a type of preferential-attachment model with fitness, and we analyze its macro behavior to clarify the properties of the city-size distributions it predicts. First, restricting the geographical fitness to take positive values and using a continuum approach, we show that the city-size distributions predicted by our model asymptotically approach Pareto distributions with coefficients greater than unity. Then, allowing the geographical fitness to take negative values, we perform local coefficient analysis to show that the predicted city-size distributions can deviate from Pareto distributions, as is often observed in actual city-size distributions. As a result, the model we propose can generate a generic class of city-size distributions, including but not limited to Pareto distributions. For applications to city-population projections, our simple model requires randomness only when new cities are created, not during their subsequent growth. This property leads to smooth trajectories of city population growth, in contrast to other models using Gibrat’s law. In addition, a discrete form of our dynamical equations can be used to estimate past city populations based on present-day data; this fact allows quantitative assessment of the performance of our model. Further study is needed to determine appropriate formulas for the geographical fitness.

Comparison of experimental surface pressures with theoretical predictions on twin two-dimensional convergent-divergent nozzles

NASA Technical Reports Server (NTRS)

Carlson, J. R.; Pendergraft, O. C., Jr.; Burley, J. R., II

1986-01-01

A three-dimensional subsonic aerodynamic panel code (VSAERO) was used to predict the effects of upper and lower external nozzle flap geometry on the external afterbody/nozzle pressure coefficient distributions and external nozzle drag of nonaxisymmetric convergent-divergent exhaust nozzles having parallel external sidewalls installed on a generic twin-engine high performance aircraft model. Nozzle static pressure coefficient distributions along the upper and lower surfaces near the model centerline and near the outer edges (corner) of the two surfaces were calculated, and nozzle drag was predicted using these surface pressure distributions. A comparison between the theoretical predictions and experimental wind tunnel data is made to evaluate the utility of the code in calculating the flow about these types of non-axisymmetric afterbody configurations. For free-stream Mach numbers of 0.60 and 0.90, the conditions where the flows were attached on the boattails yielded the best comparison between the theoretical predictions and the experimental data. For the Boattail terminal angles of greater than 15 deg., the experimental data for M = 0.60 and 0.90 indicated areas of separated flow, so the theoretical predictions failed to match the experimental data. Even though calculations of regions of separated flows are within the capabilities of the theoretical method, acceptable solutions were not obtained.

Dipole polarizability, sum rules, mean excitation energies, and long-range dispersion coefficients for buckminsterfullerene C 60

NASA Astrophysics Data System (ADS)

Kumar, Ashok; Thakkar, Ajit J.

2011-11-01

Experimental photoabsorption cross-sections combined with constraints provided by the Kuhn-Reiche-Thomas sum rule and the high-energy behavior of the dipole-oscillator-strength density are used to construct dipole oscillator strength distributions for buckminsterfullerene (C60). The distributions are used to predict dipole sum rules Sk, mean excitation energies Ik, the frequency dependent polarizability, and C6 coefficients for the long-range dipole-dipole interactions of C60 with a variety of atoms and molecules.

A Method of Determining Aerodynamic-Influence Coefficients from Wind-Tunnel Data for Wings at Supersonic Speeds

NASA Technical Reports Server (NTRS)

Gainer, Patrick A.

1961-01-01

A method is described for determining aerodynamic-influence coefficients from wind-tunnel data for calculating the steady-state load distribution on a wing with arbitrary angle-of-attack distribution at supersonic speeds. The method combines linearized theory with empirical adjustments in order to give accurate results over a wide range of angles of attack. The experimented data required are pressure distributions measured on a flat wing of the desired planform at the desired Mach number and over the desired range of angles of attack. The method has been tested by applying it to wind-tunnel data measured at Mach numbers of 1.61 and 2.01 on wings of the same planform but of different surface shapes. Influence coefficients adjusted to fit the flat wing gave good predictions of the spanwise and chord-wise distributions of loadings measured on twisted and cambered wings.

Relevance of octanol-water distribution measurements to the potential ecological uptake of multi-walled carbon nanotubes.

PubMed

Petersen, Elijah J; Huang, Qingguo; Weber, Walter J

2010-05-01

Many potential applications of carbon nanotubes (CNTs) require various physicochemical modifications prior to use, suggesting that nanotubes having varied properties may pose risks in ecosystems. A means for estimating bioaccumulation potentials of variously modified CNTs for incorporation in predictive fate models would be highly valuable. An approach commonly used for sparingly soluble organic contaminants, and previously suggested for use as well with carbonaceous nanomaterials, involves measurement of their octanol-water partitioning coefficient (KOW) values. To test the applicability of this approach, a methodology was developed to measure apparent octanol-water distribution behaviors for purified multi-walled carbon nanotubes and those acid treated. Substantial differences in apparent distribution coefficients between the two types of CNTs were observed, but these differences did not influence accumulation by either earthworms (Eisenia foetida) or oligochaetes (Lumbriculus variegatus), both of which showed minimal nanotube uptake for both types of nanotubes. The results suggest that traditional distribution behavior-based KOW approaches are likely not appropriate for predicting CNT bioaccumulation. Copyright (c) 2010 SETAC.

Prediction model of dissolved oxygen in ponds based on ELM neural network

NASA Astrophysics Data System (ADS)

Li, Xinfei; Ai, Jiaoyan; Lin, Chunhuan; Guan, Haibin

2018-02-01

Dissolved oxygen in ponds is affected by many factors, and its distribution is unbalanced. In this paper, in order to improve the imbalance of dissolved oxygen distribution more effectively, the dissolved oxygen prediction model of Extreme Learning Machine (ELM) intelligent algorithm is established, based on the method of improving dissolved oxygen distribution by artificial push flow. Select the Lake Jing of Guangxi University as the experimental area. Using the model to predict the dissolved oxygen concentration of different voltage pumps, the results show that the ELM prediction accuracy is higher than the BP algorithm, and its mean square error is MSEELM=0.0394, the correlation coefficient RELM=0.9823. The prediction results of the 24V voltage pump push flow show that the discrete prediction curve can approximate the measured values well. The model can provide the basis for the artificial improvement of the dissolved oxygen distribution decision.

Computation of thermodynamic and transport properties to predict thermophoretic effects in an argon-krypton mixture

NASA Astrophysics Data System (ADS)

Miller, Nicholas A. T.; Daivis, Peter J.; Snook, Ian K.; Todd, B. D.

2013-10-01

Thermophoresis is the movement of molecules caused by a temperature gradient. Here we report the results of a study of thermophoresis using non-equilibrium molecular dynamics simulations of a confined argon-krypton fluid subject to two different temperatures at thermostated walls. The resulting temperature profile between the walls is used along with the Soret coefficient to predict the concentration profile that develops across the channel. We obtain the Soret coefficient by calculating the mutual diffusion and thermal diffusion coefficients. We report an appropriate method for calculating the transport coefficients for binary systems, using the Green-Kubo integrals and radial distribution functions obtained from equilibrium molecular dynamics simulations of the bulk fluid. Our method has the unique advantage of separating the mutual diffusion and thermal diffusion coefficients, and calculating the sign and magnitude of their individual contributions to thermophoresis in binary mixtures.

The influence of precipitation kinetics on trace element partitioning between solid and liquid solutions: A coupled fluid dynamics/thermodynamics framework to predict distribution coefficients

NASA Astrophysics Data System (ADS)

Kavner, A.

2017-12-01

In a multicomponent multiphase geochemical system undergoing a chemical reaction such as precipitation and/or dissolution, the partitioning of species between phases is determined by a combination of thermodynamic properties and transport processes. The interpretation of the observed distribution of trace elements requires models integrating coupled chemistry and mechanical transport. Here, a framework is presented that predicts the kinetic effects on the distribution of species between two reacting phases. Based on a perturbation theory combining Navier-Stokes fluid flow and chemical reactivity, the framework predicts rate-dependent partition coefficients in a variety of different systems. We present the theoretical framework, with applications to two systems: 1. species- and isotope-dependent Soret diffusion of species in a multicomponent silicate melt subjected to a temperature gradient, and 2. Elemental partitioning and isotope fractionation during precipitation of a multicomponent solid from a multicomponent liquid phase. Predictions will be compared with results from experimental studies. The approach has applications for understanding chemical exchange in at boundary layers such as the Earth's surface magmatic systems and at the core/mantle boundary.

Model of transient drug diffusion across cornea.

PubMed

Zhang, Wensheng; Prausnitz, Mark R; Edwards, Aurélie

2004-09-30

A mathematical model of solute transient diffusion across the cornea to the anterior chamber of the eye was developed for topical drug delivery. Solute bioavailability was predicted given solute molecular radius and octanol-to-water distribution coefficient (Phi), ocular membrane ultrastructural parameters, tear fluid hydrodynamics, as well as solute distribution volume (Vd) and clearance rate (Cla) in the anterior chamber. The results suggest that drug bioavailability is primarily determined by solute lipophilicity. In human eyes, bioavailability is predicted to range between 1% and 5% for lipophilic molecules (Phi>1), and to be less than 0.5% for hydrophilic molecules (Phi<0.01). The simulations indicate that the distribution coefficient that maximizes bioavailability is on the order of 10. It was also found that the maximum solute concentration in the anterior chamber (Cmax) and the time needed to reach Cmax significantly depend on Phi, Vd, and Cla. Consistent with experimental findings, model predictions suggest that drug bioavailability can be increased by lowering the conjunctival-to-corneal permeability ratio and reducing precorneal solute drainage. Because of its mechanistic basis, this model will be useful to predict drug transport kinetics and bioavailability for new compounds and in diseased eyes.

Backward deletion to minimize prediction errors in models from factorial experiments with zero to six center points

NASA Technical Reports Server (NTRS)

Holms, A. G.

1980-01-01

Population model coefficients were chosen to simulate a saturated 2 to the 4th fixed-effects experiment having an unfavorable distribution of relative values. Using random number studies, deletion strategies were compared that were based on the F-distribution, on an order statistics distribution of Cochran's, and on a combination of the two. The strategies were compared under the criterion of minimizing the maximum prediction error, wherever it occurred, among the two-level factorial points. The strategies were evaluated for each of the conditions of 0, 1, 2, 3, 4, 5, or 6 center points. Three classes of strategies were identified as being appropriate, depending on the extent of the experimenter's prior knowledge. In almost every case the best strategy was found to be unique according to the number of center points. Among the three classes of strategies, a security regret class of strategy was demonstrated as being widely useful in that over a range of coefficients of variation from 4 to 65%, the maximum predictive error was never increased by more than 12% over what it would have been if the best strategy had been used for the particular coefficient of variation. The relative efficiency of the experiment, when using the security regret strategy, was examined as a function of the number of center points, and was found to be best when the design used one center point.

Development of a laser-induced heat flux technique for measurement of convective heat transfer coefficients in a supersonic flowfield

NASA Technical Reports Server (NTRS)

Porro, A. Robert; Keith, Theo G., Jr.; Hingst, Warren R.; Chriss, Randall M.; Seablom, Kirk D.

1991-01-01

A technique is developed to measure the local convective heat transfer coefficient on a model surface in a supersonic flow field. The technique uses a laser to apply a discrete local heat flux at the model test surface, and an infrared camera system determines the local temperature distribution due to heating. From this temperature distribution and an analysis of the heating process, a local convective heat transfer coefficient is determined. The technique was used to measure the load surface convective heat transfer coefficient distribution on a flat plate at nominal Mach numbers of 2.5, 3.0, 3.5, and 4.0. The flat plate boundary layer initially was laminar and became transitional in the measurement region. The experimental results agreed reasonably well with theoretical predictions of convective heat transfer of flat plate laminar boundary layers. The results indicate that this non-intrusive optical measurement technique has the potential to obtain high quality surface convective heat transfer measurements in high speed flowfields.

Simulation of size-exclusion chromatography distribution coefficients of comb-shaped molecules in spherical pores comparison of simulation and experiment.

PubMed

Radke, Wolfgang

2004-03-05

Simulations of the distribution coefficients of linear polymers and regular combs with various spacings between the arms have been performed. The distribution coefficients were plotted as a function of the number of segments in order to compare the size exclusion chromatography (SEC)-elution behavior of combs relative to linear molecules. By comparing the simulated SEC-calibration curves it is possible to predict the elution behavior of comb-shaped polymers relative to linear ones. In order to compare the results obtained by computer simulations with experimental data, a variety of comb-shaped polymers varying in side chain length, spacing between the side chains and molecular weights of the backbone were analyzed by SEC with light-scattering detection. It was found that the computer simulations could predict the molecular weights of linear molecules having the same retention volume with an accuracy of about 10%, i.e. the error in the molecular weight obtained by calculating the molecular weight of the comb-polymer based on a calibration curve constructed using linear standards and the results of the computer simulations are of the same magnitude as the experimental error of absolute molecular weight determination.

Assessment of atmospheric distribution of polycyclic aromatic hydrocarbons using a molecular structure model

NASA Astrophysics Data System (ADS)

Turk Sekulić, Maja; Okuka, Marija; Šenk, Nevena; Radonić, Jelena; Vojinović Miloradov, Mirjana; Vidicki, Branko

2013-07-01

In this paper, a comparison of experimentally obtained and SPARC software v4.6 modelled values of gas/particle partitioning coefficients was conducted to determine whether the evaluation of atmospheric distribution of PAH molecules can be performed using a molecular structure model. Partitioning coefficients were calculated for sixteen EPA PAHs, in thirty-nine samples of ambient air collected at nineteen urban, industrial, highly contaminated and background sites in the Republic of Serbia and Bosnia and Herzegovina. For obtaining samples of ambient air, the conventional high volume (Hi-Vol) methodology was applied, whereby gaseous and particulate phase data collection was conducted simultaneously by glass fibre filters (GFFs) and polyurethane foam filters (PUFs). The best prediction was for PAHs with 5 or more rings (benzo(b)fluoranthene, benzo(k)fluoranthene, benzo(a)pyrene, indeno(1,2,3-cd)perylene and benzo(ghi)perylene). For evaluating the applicability of SPARC software predictions of gas/particle partitioning coefficients for the existing conditions, the results were compared with those obtained by applying other frequently used and highly ranked theoretical models of phase distributions, namely Junge-Pankow adsorption model, KOA absorption model, Dachs-Eisenreich dual model and PP-LFER model.

Aerodynamic parameters from distributed heterogeneous CNT hair sensors with a feedforward neural network.

PubMed

Magar, Kaman Thapa; Reich, Gregory W; Kondash, Corey; Slinker, Keith; Pankonien, Alexander M; Baur, Jeffery W; Smyers, Brian

2016-11-10

Distributed arrays of artificial hair sensors have bio-like sensing capabilities to obtain spatial and temporal surface flow information which is an important aspect of an effective fly-by-feel system. The spatiotemporal surface flow measurement enables further exploration of additional flow features such as flow stagnation, separation, and reattachment points. Due to their inherent robustness and fault tolerant capability, distributed arrays of hair sensors are well equipped to assess the aerodynamic and flow states in adverse conditions. In this paper, a local flow measurement from an array of artificial hair sensors in a wind tunnel experiment is used with a feedforward artificial neural network to predict aerodynamic parameters such as lift coefficient, moment coefficient, free-stream velocity, and angle of attack on an airfoil. We find the prediction error within 6% and 10% for lift and moment coefficients. The error for free-stream velocity and angle of attack were within 0.12 mph and 0.37 degrees. Knowledge of these parameters are key to finding the real time forces and moments which paves the way for effective control design to increase flight agility, stability, and maneuverability.

A model predicting the evolution of ice particle size spectra and radiative properties of cirrus clouds. Part 2: Dependence of absorption and extinction on ice crystal morphology

NASA Technical Reports Server (NTRS)

Mitchell, David L.; Arnott, W. Patrick

1994-01-01

This study builds upon the microphysical modeling described in Part 1 by deriving formulations for the extinction and absorption coefficients in terms of the size distribution parameters predicted from the micro-physical model. The optical depth and single scatter albedo of a cirrus cloud can then be determined, which, along with the asymmetry parameter, are the input parameters needed by cloud radiation models. Through the use of anomalous diffraction theory, analytical expressions were developed describing the absorption and extinction coefficients and the single scatter albedo as functions of size distribution parameters, ice crystal shapes (or habits), wavelength, and refractive index. The extinction coefficient was formulated in terms of the projected area of the size distribution, while the absorption coefficient was formulated in terms of both the projected area and mass of the size distribution. These properties were formulated as explicit functions of ice crystal geometry and were not based on an 'effective radius.' Based on simulations of the second cirrus case study described in Part 1, absorption coefficients predicted in the near infrared for hexagonal columns and rosettes were up to 47% and 71% lower, respectively, than absorption coefficients predicted by using equivalent area spheres. This resulted in single scatter albedos in the near-infrared that were considerably greater than those predicted by the equivalent area sphere method. Reflectances in this region should therefore be underestimated using the equivalent area sphere approach. Cloud optical depth was found to depend on ice crystal habit. When the simulated cirrus cloud contained only bullet rosettes, the optical depth was 142% greater than when the cloud contained only hexagonal columns. This increase produced a doubling in cloud albedo. In the near-infrared (IR), the single scatter albedo also exhibited a significant dependence on ice crystal habit. More research is needed on the geometrical properties of ice crystals before the influence of ice crystal shape on cirrus radiative properties can be adequately understood. This study provides a way of coupling the radiative properties of absorption, extinction, and single scatter albedo to the microphysical properties of cirrus clouds. The dependence of extinction and absorption on ice crystal shape was not just due to geometrical differences between crystal types, but was also due to the effect these differences had on the evolution of ice particle size spectra. The ice particle growth model in Part 1 and the radiative properties treated here are based on analytical formulations, and thus represent a computationally efficient means of modeling the microphysical and radiative properties of cirrus clouds.

The behavior of groundwater with dispersion in coastal aquifers

NASA Astrophysics Data System (ADS)

Kakinuma, Tadao; Kishi, Yosuke; Inouchi, Kunimitsu

1988-04-01

A three-dimensional steady-state hydrodynamic dispersion model is used to simulate seawater encroachment in the confined aquifers in the estuaries of the Naka and Kiki Rivers in Japan. Two expressions of the dispersion coefficient are considered; one is constant over the entire region of the aquifer and the other is dependent on the flow velocity of the groundwater. The magnitudes of the constant dispersion coefficients in the horizontal and vertical directions, Dxx and Dzz, as well as the longitudinal and lateral dispersivities, aL and aT, are determined so as to reproduce the regional distributions of salt concentration in the confined aquifers in both estuaries. It is found that Dxx = 5 cm 2s -1, Dzz = 5-0.5 cm 2s -1 and aL = 1000-1250 m, aT = 100-125 m in the estuary of the Naka River; and Dxx = 0.2 cm 2s -1, Dzz = 0.2-0.02 cm 2s -1 and aL = 200 m, aT = 200-20 m in the estuary of the Kiki River. Examining the local distributions of the dispersion coefficient computed from the dispersivity and velocity fields of groundwater in both estuaries, the same value as estimated in the analysis with the constant dispersion coefficient is located in the middle layer of the aquifer. In the estuary of the Naka River, the piezometric surface predicted with the dispersion model with the velocity-dependent dispersion coefficient is almost the same as that predicted with the dispersion model with the constant dispersion coefficient and they are 5 10% lower than that predicted with the interface model (Kakinuma et al., 1984). They are, however, about 1.3 times the observed one.

Sea Level Affecting Marshes Model (SLAMM) ‐ New functionality for predicting changes in distribution of submerged aquatic vegetation in response to sea level rise

USGS Publications Warehouse

Lee II, Henry; Reusser, Deborah A.; Frazier, Melanie R; McCoy, Lee M; Clinton, Patrick J.; Clough, Jonathan S.

2014-01-01

The “Sea‐Level Affecting Marshes Model” (SLAMM) is a moderate resolution model used to predict the effects of sea level rise on marsh habitats (Craft et al. 2009). SLAMM has been used extensively on both the west coast (e.g., Glick et al., 2007) and east coast (e.g., Geselbracht et al., 2011) of the United States to evaluate potential changes in the distribution and extent of tidal marsh habitats. However, a limitation of the current version of SLAMM, (Version 6.2) is that it lacks the ability to model distribution changes in seagrass habitat resulting from sea level rise. Because of the ecological importance of SAV habitats, U.S. EPA, USGS, and USDA partnered with Warren Pinnacle Consulting to enhance the SLAMM modeling software to include new functionality in order to predict changes in Zostera marina distribution within Pacific Northwest estuaries in response to sea level rise. Specifically, the objective was to develop a SAV model that used generally available GIS data and parameters that were predictive and that could be customized for other estuaries that have GIS layers of existing SAV distribution. This report describes the procedure used to develop the SAV model for the Yaquina Bay Estuary, Oregon, appends a statistical script based on the open source R software to generate a similar SAV model for other estuaries that have data layers of existing SAV, and describes how to incorporate the model coefficients from the site‐specific SAV model into SLAMM to predict the effects of sea level rise on Zostera marina distributions. To demonstrate the applicability of the R tools, we utilize them to develop model coefficients for Willapa Bay, Washington using site‐specific SAV data.

Interpretation of diffusion coefficients in nanostructured materials from random walk numerical simulation.

PubMed

Anta, Juan A; Mora-Seró, Iván; Dittrich, Thomas; Bisquert, Juan

2008-08-14

We make use of the numerical simulation random walk (RWNS) method to compute the "jump" diffusion coefficient of electrons in nanostructured materials via mean-square displacement. First, a summary of analytical results is given that relates the diffusion coefficient obtained from RWNS to those in the multiple-trapping (MT) and hopping models. Simulations are performed in a three-dimensional lattice of trap sites with energies distributed according to an exponential distribution and with a step-function distribution centered at the Fermi level. It is observed that once the stationary state is reached, the ensemble of particles follow Fermi-Dirac statistics with a well-defined Fermi level. In this stationary situation the diffusion coefficient obeys the theoretical predictions so that RWNS effectively reproduces the MT model. Mobilities can be also computed when an electrical bias is applied and they are observed to comply with the Einstein relation when compared with steady-state diffusion coefficients. The evolution of the system towards the stationary situation is also studied. When the diffusion coefficients are monitored along simulation time a transition from anomalous to trap-limited transport is observed. The nature of this transition is discussed in terms of the evolution of electron distribution and the Fermi level. All these results will facilitate the use of RW simulation and related methods to interpret steady-state as well as transient experimental techniques.

Evaluation of diffusion coefficients by means of an approximate steady-state condition in sedimentation velocity distributions.

PubMed

Scott, David J; Harding, Stephen E; Winzor, Donald J

2015-12-01

This investigation examined the feasibility of manipulating the rotor speed in sedimentation velocity experiments to spontaneously generate an approximate steady-state condition where the extent of diffusional spreading is matched exactly by the boundary sharpening arising from negative s-c dependence. Simulated sedimentation velocity distributions based on the sedimentation characteristics for a purified mucin preparation were used to illustrate a simple procedure for determining the diffusion coefficient from such steady-state distributions in situations where the concentration dependence of the sedimentation coefficient, s = s(0)/(1 + Kc), was quantified in terms of the limiting sedimentation coefficient as c → 0 (s(0)) and the concentration coefficient (K). Those simulations established that spontaneous generation of the approximate steady state could well be a feature of sedimentation velocity distributions for many unstructured polymer systems because the requirement that Kcoω(2)s(0)/D be between 46 and 183 cm(-2) is not unduly restrictive. Although spontaneous generation of the approximate steady state is also a theoretical prediction for structured macromolecular solutes exhibiting linear concentration dependence of the sedimentation coefficient, s = s(0)(1 - kc), the required value of k is far too large for any practical advantage to be taken of this approach with globular proteins. Copyright © 2015 Elsevier Inc. All rights reserved.

Atomistic modeling of dropwise condensation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sikarwar, B. S., E-mail: bssikarwar@amity.edu; Singh, P. L.; Muralidhar, K.

The basic aim of the atomistic modeling of condensation of water is to determine the size of the stable cluster and connect phenomena occurring at atomic scale to the macroscale. In this paper, a population balance model is described in terms of the rate equations to obtain the number density distribution of the resulting clusters. The residence time is taken to be large enough so that sufficient time is available for all the adatoms existing in vapor-phase to loose their latent heat and get condensed. The simulation assumes clusters of a given size to be formed from clusters of smallermore » sizes, but not by the disintegration of the larger clusters. The largest stable cluster size in the number density distribution is taken to be representative of the minimum drop radius formed in a dropwise condensation process. A numerical confirmation of this result against predictions based on a thermodynamic model has been obtained. Results show that the number density distribution is sensitive to the surface diffusion coefficient and the rate of vapor flux impinging on the substrate. The minimum drop radius increases with the diffusion coefficient and the impinging vapor flux; however, the dependence is weak. The minimum drop radius predicted from thermodynamic considerations matches the prediction of the cluster model, though the former does not take into account the effect of the surface properties on the nucleation phenomena. For a chemically passive surface, the diffusion coefficient and the residence time are dependent on the surface texture via the coefficient of friction. Thus, physical texturing provides a means of changing, within limits, the minimum drop radius. The study reveals that surface texturing at the scale of the minimum drop radius does not provide controllability of the macro-scale dropwise condensation at large timescales when a dynamic steady-state is reached.« less

Distribution of Animal Drugs between Skim Milk and Milk Fat Fractions in Spiked Whole Milk: Understanding the Potential Impact on Commercial Milk Products.

PubMed

Hakk, Heldur; Shappell, Nancy W; Lupton, Sara J; Shelver, Weilin L; Fanaselle, Wendy; Oryang, David; Yeung, Chi Yuen; Hoelzer, Karin; Ma, Yinqing; Gaalswyk, Dennis; Pouillot, Régis; Van Doren, Jane M

2016-01-13

Seven animal drugs [penicillin G (PENG), sulfadimethoxine (SDMX), oxytetracycline (OTET), erythromycin (ERY), ketoprofen (KETO), thiabendazole (THIA), and ivermectin (IVR)] were used to evaluate the drug distribution between milk fat and skim milk fractions of cow milk. More than 90% of the radioactivity was distributed into the skim milk fraction for ERY, KETO, OTET, PENG, and SDMX, approximately 80% for THIA, and 13% for IVR. The distribution of drug between milk fat and skim milk fractions was significantly correlated to the drug's lipophilicity (partition coefficient, log P, or distribution coefficient, log D, which includes ionization). Data were fit with linear mixed effects models; the best fit was obtained within this data set with log D versus observed drug distribution ratios. These candidate empirical models serve for assisting to predict the distribution and concentration of these drugs in a variety of milk and milk products.

Model for the ultrasound reflection from micro-beads and cells distributed in layers on a uniform surface

NASA Astrophysics Data System (ADS)

Couture, O.; Cherin, E.; Foster, F. S.

2007-07-01

A model predicting the reflection of ultrasound from multiple layers of small scattering spheres is developed. Predictions of the reflection coefficient, which takes into account the interferences between the different sphere layers, are compared to measurements performed in the 10-80 MHz and 15-35 MHz frequency range with layers of glass beads and spherical acute myeloid leukemia (AML) cells, respectively. For both types of scatterers, the reflection coefficient increases as a function of their density on the surface for less than three superimposed layers, at which point it saturates at 0.38 for glass beads and 0.02 for AML cells. Above three layers, oscillations of the reflection coefficient due to constructive or destructive interference between layers are observed experimentally and are accurately predicted by the model. The use of such a model could lead to a better understanding of the structures observed in layered tissue images.

Spatiotemporal Co-existence of Female Thyroid and Breast Cancers in Hangzhou, China

NASA Astrophysics Data System (ADS)

Fei, Xufeng; Christakos, George; Lou, Zhaohan; Ren, Yanjun; Liu, Qingmin; Wu, Jiaping

2016-06-01

Thyroid and breast cancers (TC, BC) are common female malignant tumors worldwide. Studies suggest that TC patients have a higher BC risk, and vice versa. However, it has not been investigated quantitatively if there is an association between the space-time TC and BC incidence distributions at the population level. This work aims to answer this question. 5358 TC and 8784 BC (female) cases were diagnosed in Hangzhou (China, 2008-2012). Pearson and Spearman rank correlation coefficients of the TC and BC incidences were high, and their patterns were geographically similar. The spatiotemporal co-existence of TC and BC distributions was investigated using the integrative disease predictability (IDP) criterion: if TC-BC association is part of the disease mapping knowledge bases, it should yield improved space-time incidence predictions. Improved TC (BC) incidence predictions were generated when integrating both TC and BC data than when using only TC (BC) data. IDP consistently demonstrated the spatiotemporal co-existence of TC and BC distributions throughout Hangzhou (2008-2012), which means that when the population experiences high incidences of one kind of cancer attention should be paid to the other kind of cancer too. The strength of TC-BC association was measured by the IDP coefficients and incidence prediction accuracy.

Spatiotemporal Co-existence of Female Thyroid and Breast Cancers in Hangzhou, China

PubMed Central

Fei, Xufeng; Christakos, George; Lou, Zhaohan; Ren, Yanjun; Liu, Qingmin; Wu, Jiaping

2016-01-01

Thyroid and breast cancers (TC, BC) are common female malignant tumors worldwide. Studies suggest that TC patients have a higher BC risk, and vice versa. However, it has not been investigated quantitatively if there is an association between the space-time TC and BC incidence distributions at the population level. This work aims to answer this question. 5358 TC and 8784 BC (female) cases were diagnosed in Hangzhou (China, 2008–2012). Pearson and Spearman rank correlation coefficients of the TC and BC incidences were high, and their patterns were geographically similar. The spatiotemporal co-existence of TC and BC distributions was investigated using the integrative disease predictability (IDP) criterion: if TC-BC association is part of the disease mapping knowledge bases, it should yield improved space-time incidence predictions. Improved TC (BC) incidence predictions were generated when integrating both TC and BC data than when using only TC (BC) data. IDP consistently demonstrated the spatiotemporal co-existence of TC and BC distributions throughout Hangzhou (2008–2012), which means that when the population experiences high incidences of one kind of cancer attention should be paid to the other kind of cancer too. The strength of TC-BC association was measured by the IDP coefficients and incidence prediction accuracy. PMID:27341638

Prediction of cyclohexane-water distribution coefficient for SAMPL5 drug-like compounds with the QMPFF3 and ARROW polarizable force fields.

PubMed

Kamath, Ganesh; Kurnikov, Igor; Fain, Boris; Leontyev, Igor; Illarionov, Alexey; Butin, Oleg; Olevanov, Michael; Pereyaslavets, Leonid

2016-11-01

We present the performance of blind predictions of water-cyclohexane distribution coefficients for 53 drug-like compounds in the SAMPL5 challenge by three methods currently in use within our group. Two of them utilize QMPFF3 and ARROW, polarizable force-fields of varying complexity, and the third uses the General Amber Force-Field (GAFF). The polarizable FF's are implemented in an in-house MD package, Arbalest. We find that when we had time to parametrize the functional groups with care (batch 0), the polarizable force-fields outperformed the non-polarizable one. Conversely, on the full set of 53 compounds, GAFF performed better than both QMPFF3 and ARROW. We also describe the torsion-restrain method we used to improve sampling of molecular conformational space and thus the overall accuracy of prediction. The SAMPL5 challenge highlighted several drawbacks of our force-fields, such as our significant systematic over-estimation of hydrophobic interactions, specifically for alkanes and aromatic rings.

A Numerical Analysis of Heat Transfer and Effectiveness on Film Cooled Turbine Blade Tip Models

NASA Technical Reports Server (NTRS)

Ameri, A. A.; Rigby, D. L.

1999-01-01

A computational study has been performed to predict the distribution of convective heat transfer coefficient on a simulated blade tip with cooling holes. The purpose of the examination was to assess the ability of a three-dimensional Reynolds-averaged Navier-Stokes solver to predict the rate of tip heat transfer and the distribution of cooling effectiveness. To this end, the simulation of tip clearance flow with blowing of Kim and Metzger was used. The agreement of the computed effectiveness with the data was quite good. The agreement with the heat transfer coefficient was not as good but improved away from the cooling holes. Numerical flow visualization showed that the uniformity of wetting of the surface by the film cooling jet is helped by the reverse flow due to edge separation of the main flow.

Evaluating imaging quality between different ghost imaging systems based on the coherent-mode representation

NASA Astrophysics Data System (ADS)

Shen, Qian; Bai, Yanfeng; Shi, Xiaohui; Nan, Suqin; Qu, Lijie; Li, Hengxing; Fu, Xiquan

2017-07-01

The difference in imaging quality between different ghost imaging schemes is studied by using coherent-mode representation of partially coherent fields. It is shown that the difference mainly relies on the distribution changes of the decomposition coefficients of the object imaged when the light source is fixed. For a new-designed imaging scheme, we only need to give the distribution of the decomposition coefficients and compare them with that of the existing imaging system, thus one can predict imaging quality. By choosing several typical ghost imaging systems, we theoretically and experimentally verify our results.

On the continuity of the stationary state distribution of DPCM

NASA Astrophysics Data System (ADS)

Naraghi-Pour, Morteza; Neuhoff, David L.

1990-03-01

Continuity and singularity properties of the stationary state distribution of differential pulse code modulation (DPCM) are explored. Two-level DPCM (i.e., delta modulation) operating on a first-order autoregressive source is considered, and it is shown that, when the magnitude of the DPCM prediciton coefficient is between zero and one-half, the stationary state distribution is singularly continuous; i.e., it is not discrete but concentrates on an uncountable set with a Lebesgue measure of zero. Consequently, it cannot be represented with a probability density function. For prediction coefficients with magnitude greater than or equal to one-half, the distribution is pure, i.e., either absolutely continuous and representable with a density function, or singular. This problem is compared to the well-known and still substantially unsolved problem of symmetric Bernoulli convolutions.

Uncertain Henry's law constants compromise equilibrium partitioning calculations of atmospheric oxidation products

NASA Astrophysics Data System (ADS)

Wang, Chen; Yuan, Tiange; Wood, Stephen A.; Goss, Kai-Uwe; Li, Jingyi; Ying, Qi; Wania, Frank

2017-06-01

Gas-particle partitioning governs the distribution, removal, and transport of organic compounds in the atmosphere and the formation of secondary organic aerosol (SOA). The large variety of atmospheric species and their wide range of properties make predicting this partitioning equilibrium challenging. Here we expand on earlier work and predict gas-organic and gas-aqueous phase partitioning coefficients for 3414 atmospherically relevant molecules using COSMOtherm, SPARC Performs Automated Reasoning in Chemistry (SPARC), and poly-parameter linear free-energy relationships. The Master Chemical Mechanism generated the structures by oxidizing primary emitted volatile organic compounds. Predictions for gas-organic phase partitioning coefficients (KWIOM/G) by different methods are on average within 1 order of magnitude of each other, irrespective of the numbers of functional groups, except for predictions by COSMOtherm and SPARC for compounds with more than three functional groups, which have a slightly higher discrepancy. Discrepancies between predictions of gas-aqueous partitioning (KW/G) are much larger and increase with the number of functional groups in the molecule. In particular, COSMOtherm often predicts much lower KW/G for highly functionalized compounds than the other methods. While the quantum-chemistry-based COSMOtherm accounts for the influence of intra-molecular interactions on conformation, highly functionalized molecules likely fall outside of the applicability domain of the other techniques, which at least in part rely on empirical data for calibration. Further analysis suggests that atmospheric phase distribution calculations are sensitive to the partitioning coefficient estimation method, in particular to the estimated value of KW/G. The large uncertainty in KW/G predictions for highly functionalized organic compounds needs to be resolved to improve the quantitative treatment of SOA formation.

Effects of calcium leaching on diffusion properties of hardened and altered cement pastes

NASA Astrophysics Data System (ADS)

Kurumisawa, Kiyofumi; Haga, Kazuko; Hayashi, Daisuke; Owada, Hitoshi

2017-06-01

It is very important to predict alterations in the concrete used for fabricating disposal containers for radioactive waste. Therefore, it is necessary to understand the alteration of cementitious materials caused by calcium leaching when they are in contact with ground water in the long term. To evaluate the long-term transport characteristics of cementitious materials, the microstructural behavior of these materials should be considered. However, many predictive models of transport characteristics focus on the pore structure, while only few such models consider both, the spatial distribution of calcium silicate hydrate (C-S-H), portlandite, and the pore spaces. This study focused on the spatial distribution of these cement phases. The auto-correlation function of each phase of cementitious materials was calculated from two-dimensional backscattered electron imaging, and the three-dimensional spatial image of the cementitious material was produced using these auto-correlation functions. An attempt was made to estimate the diffusion coefficient of chloride from the three-dimensional spatial image. The estimated diffusion coefficient of the altered sample from the three-dimensional spatial image was found to be comparable to the measured value. This demonstrated that it is possible to predict the diffusion coefficient of the altered cement paste by using the proposed model.

Correlation of spatial climate/weather maps and the advantages of using the Mahalanobis metric in predictions

NASA Astrophysics Data System (ADS)

Stephenson, D. B.

1997-10-01

The skill in predicting spatially varying weather/climate maps depends on the definition of the measure of similarity between the maps. Under the justifiable approximation that the anomaly maps are distributed multinormally, it is shown analytically that the choice of weighting metric, used in defining the anomaly correlation between spatial maps, can change the resulting probability distribution of the correlation coefficient. The estimate of the numbers of degrees of freedom based on the variance of the correlation distribution can vary from unity up to the number of grid points depending on the choice of weighting metric. The (pseudo-) inverse of the sample covariance matrix acts as a special choice for the metric in that it gives a correlation distribution which has minimal kurtosis and maximum dimension. Minimal kurtosis suggests that the average predictive skill might be improved due to the rarer occurrence of troublesome outlier patterns far from the mean state. Maximum dimension has a disadvantage for analogue prediction schemes in that it gives the minimum number of analogue states. This metric also has an advantage in that it allows one to powerfully test the null hypothesis of multinormality by examining the second and third moments of the correlation coefficient which were introduced by Mardia as invariant measures of multivariate kurtosis and skewness. For these reasons, it is suggested that this metric could be usefully employed in the prediction of weather/climate and in fingerprinting anthropogenic climate change. The ideas are illustrated using the bivariate example of the observed monthly mean sea-level pressures at Darwin and Tahitifrom 1866 1995.

Estimation of the minimum permeability coefficient in rats for perfusion-limited tissue distribution in whole-body physiologically-based pharmacokinetics.

PubMed

Jeong, Yoo-Seong; Yim, Chang-Soon; Ryu, Heon-Min; Noh, Chi-Kyoung; Song, Yoo-Kyung; Chung, Suk-Jae

2017-06-01

The objective of the current study was to determine the minimum permeability coefficient, P, needed for perfusion-limited distribution in PBPK. Two expanded kinetic models, containing both permeability and perfusion terms for the rate of tissue distribution, were considered: The resulting equations could be simplified to perfusion-limited distribution depending on tissue permeability. Integration plot analyses were carried out with theophylline in 11 typical tissues to determine their apparent distributional clearances and the model-dependent permeabilities of the tissues. Effective surface areas were calculated for 11 tissues from the tissue permeabilities of theophylline and its PAMPA P. Tissue permeabilities of other drugs were then estimated from their PAMPA P and the effective surface area of the tissues. The differences between the observed and predicted concentrations, as expressed by the sum of squared log differences with the present models were at least comparable to or less than the values obtained using the traditional perfusion-limited distribution model for 24 compounds with diverse PAMPA P values. These observations suggest that the use of a combination of the proposed models, PAMPA P and the effective surface area can be used to reasonably predict the pharmacokinetics of 22 out of 24 model compounds, and is potentially applicable to calculating the kinetics for other drugs. Assuming that the fractional distribution parameter of 80% of the perfusion rate is a reasonable threshold for perfusion-limited distribution in PBPK, our theoretical prediction indicates that the pharmacokinetics of drugs having an apparent PAMPA P of 1×10 -6 cm/s or more will follow the traditional perfusion-limited distribution in PBPK for major tissues in the body. Copyright © 2017 Elsevier B.V. All rights reserved.

Prediction of Sliding Friction Coefficient Based on a Novel Hybrid Molecular-Mechanical Model.

PubMed

Zhang, Xiaogang; Zhang, Yali; Wang, Jianmei; Sheng, Chenxing; Li, Zhixiong

2018-08-01

Sliding friction is a complex phenomenon which arises from the mechanical and molecular interactions of asperities when examined in a microscale. To reveal and further understand the effects of micro scaled mechanical and molecular components of friction coefficient on overall frictional behavior, a hybrid molecular-mechanical model is developed to investigate the effects of main factors, including different loads and surface roughness values, on the sliding friction coefficient in a boundary lubrication condition. Numerical modelling was conducted using a deterministic contact model and based on the molecular-mechanical theory of friction. In the contact model, with given external loads and surface topographies, the pressure distribution, real contact area, and elastic/plastic deformation of each single asperity contact were calculated. Then asperity friction coefficient was predicted by the sum of mechanical and molecular components of friction coefficient. The mechanical component was mainly determined by the contact width and elastic/plastic deformation, and the molecular component was estimated as a function of the contact area and interfacial shear stress. Numerical results were compared with experimental results and a good agreement was obtained. The model was then used to predict friction coefficients in different operating and surface conditions. Numerical results explain why applied load has a minimum effect on the friction coefficients. They also provide insight into the effect of surface roughness on the mechanical and molecular components of friction coefficients. It is revealed that the mechanical component dominates the friction coefficient when the surface roughness is large (Rq > 0.2 μm), while the friction coefficient is mainly determined by the molecular component when the surface is relatively smooth (Rq < 0.2 μm). Furthermore, optimal roughness values for minimizing the friction coefficient are recommended.

Qualitative and numerical analyses of the effects of river inflow variations on mixing diagrams in estuaries

USGS Publications Warehouse

Cifuentes, L.A.; Schemel, L.E.; Sharp, J.H.

1990-01-01

The effects of river inflow variations on alkalinity/salinity distributions in San Francisco Bay and nitrate/salinity distributions in Delaware Bay are described. One-dimensional, advective-dispersion equations for salinity and the dissolved constituents are solved numerically and are used to simulate mixing in the estuaries. These simulations account for time-varying river inflow, variations in estuarine cross-sectional area, and longitudinally varying dispersion coefficients. The model simulates field observations better than models that use constant hydrodynamic coefficients and uniform estuarine geometry. Furthermore, field observations and model simulations are consistent with theoretical 'predictions' that the curvature of propery-salinity distributions depends on the relation between the estuarine residence time and the period of river concentration variation. ?? 1990.

Prediction of crosslink density of solid propellant binders. [curing of elastomers

NASA Technical Reports Server (NTRS)

Marsh, H. E., Jr.

1976-01-01

A quantitative theory is outlined which allows calculation of crosslink density of solid propellant binders from a small number of predetermined parameters such as the binder composition, the functionality distributions of the ingredients, and the extent of the curing reaction. The parameter which is partly dependent on process conditions is the extent of reaction. The proposed theoretical model is verified by independent measurement of effective chain concentration and sol and gel fractions in simple compositions prepared from model compounds. The model is shown to correlate tensile data with composition in the case of urethane-cured polyether and certain solid propellants. A formula for the branching coefficient is provided according to which if one knows the functionality distributions of the ingredients and the corresponding equivalent weights and can measure or predict the extent of reaction, he can calculate the branching coefficient of such a system for any desired composition.

Modification of Hazen's equation in coarse grained soils by soft computing techniques

NASA Astrophysics Data System (ADS)

Kaynar, Oguz; Yilmaz, Isik; Marschalko, Marian; Bednarik, Martin; Fojtova, Lucie

2013-04-01

Hazen first proposed a Relationship between coefficient of permeability (k) and effective grain size (d10) was first proposed by Hazen, and it was then extended by some other researchers. However many attempts were done for estimation of k, correlation coefficients (R2) of the models were generally lower than ~0.80 and whole grain size distribution curves were not included in the assessments. Soft computing techniques such as; artificial neural networks, fuzzy inference systems, genetic algorithms, etc. and their hybrids are now being successfully used as an alternative tool. In this study, use of some soft computing techniques such as Artificial Neural Networks (ANNs) (MLP, RBF, etc.) and Adaptive Neuro-Fuzzy Inference System (ANFIS) for prediction of permeability of coarse grained soils was described, and Hazen's equation was then modificated. It was found that the soft computing models exhibited high performance in prediction of permeability coefficient. However four different kinds of ANN algorithms showed similar prediction performance, results of MLP was found to be relatively more accurate than RBF models. The most reliable prediction was obtained from ANFIS model.

An analysis method for multi-component airfoils in separated flow

NASA Technical Reports Server (NTRS)

Rao, B. M.; Duorak, F. A.; Maskew, B.

1980-01-01

The multi-component airfoil program (Langley-MCARF) for attached flow is modified to accept the free vortex sheet separation-flow model program (Analytical Methods, Inc.-CLMAX). The viscous effects are incorporated into the calculation by representing the boundary layer displacement thickness with an appropriate source distribution. The separation flow model incorporated into MCARF was applied to single component airfoils. Calculated pressure distributions for angles of attack up to the stall are in close agreement with experimental measurements. Even at higher angles of attack beyond the stall, correct trends of separation, decrease in lift coefficients, and increase in pitching moment coefficients are predicted.

Numerical and experimental investigations for the evaluation of the wear coefficient of reverse total shoulder prostheses.

PubMed

Mattei, Lorenza; Di Puccio, Francesca; Joyce, Thomas J; Ciulli, Enrico

2015-03-01

In the present study, numerical and experimental wear investigations on reverse total shoulder arthroplasties (RTSAs) were combined in order to estimate specific wear coefficients, currently not available in the literature. A wear model previously developed by the authors for metal-on-plastic hip implants was adapted to RTSAs and applied in a double direction: firstly, to evaluate specific wear coefficients for RTSAs from experimental results and secondly, to predict wear distribution. In both cases, the Archard wear law (AR) and the wear law of UHMWPE (PE) were considered, assuming four different k functions. The results indicated that both the wear laws predict higher wear coefficients for RTSA with respect to hip implants, particularly the AR law, with k values higher than twofold the hip ones. Such differences can significantly affect predictive wear model results for RTSA, when non-specific wear coefficients are used. Moreover, the wear maps simulated with the two laws are markedly different, although providing the same wear volume. A higher wear depth (+51%) is obtained with the AR law, located at the dome of the cup, while with the PE law the most worn region is close to the edge. Taking advantage of the linear trend of experimental volume losses, the wear coefficients obtained with the AR law should be valid despite having neglected the geometry update in the model. Copyright © 2015 Elsevier Ltd. All rights reserved.

Mutual diffusion of binary liquid mixtures containing methanol, ethanol, acetone, benzene, cyclohexane, toluene, and carbon tetrachloride

DOE Office of Scientific and Technical Information (OSTI.GOV)

Guevara-Carrion, Gabriela; Janzen, Tatjana; Muñoz-Muñoz, Y. Mauricio

Mutual diffusion coefficients of all 20 binary liquid mixtures that can be formed out of methanol, ethanol, acetone, benzene, cyclohexane, toluene, and carbon tetrachloride without a miscibility gap are studied at ambient conditions of temperature and pressure in the entire composition range. The considered mixtures show a varying mixing behavior from almost ideal to strongly non-ideal. Predictive molecular dynamics simulations employing the Green-Kubo formalism are carried out. Radial distribution functions are analyzed to gain an understanding of the liquid structure influencing the diffusion processes. It is shown that cluster formation in mixtures containing one alcoholic component has a significant impactmore » on the diffusion process. The estimation of the thermodynamic factor from experimental vapor-liquid equilibrium data is investigated, considering three excess Gibbs energy models, i.e., Wilson, NRTL, and UNIQUAC. It is found that the Wilson model yields the thermodynamic factor that best suits the simulation results for the prediction of the Fick diffusion coefficient. Four semi-empirical methods for the prediction of the self-diffusion coefficients and nine predictive equations for the Fick diffusion coefficient are assessed and it is found that methods based on local composition models are more reliable. Finally, the shear viscosity and thermal conductivity are predicted and in most cases favorably compared with experimental literature values.« less

Backward deletion to minimize prediction errors in models from factorial experiments with zero to six center points

NASA Technical Reports Server (NTRS)

Holms, A. G.

1980-01-01

Population model coefficients were chosen to simulate a saturated 2 to the fourth power fixed effects experiment having an unfavorable distribution of relative values. Using random number studies, deletion strategies were compared that were based on the F distribution, on an order statistics distribution of Cochran's, and on a combination of the two. Results of the comparisons and a recommended strategy are given.

Accurate load prediction by BEM with airfoil data from 3D RANS simulations

NASA Astrophysics Data System (ADS)

Schneider, Marc S.; Nitzsche, Jens; Hennings, Holger

2016-09-01

In this paper, two methods for the extraction of airfoil coefficients from 3D CFD simulations of a wind turbine rotor are investigated, and these coefficients are used to improve the load prediction of a BEM code. The coefficients are extracted from a number of steady RANS simulations, using either averaging of velocities in annular sections, or an inverse BEM approach for determination of the induction factors in the rotor plane. It is shown that these 3D rotor polars are able to capture the rotational augmentation at the inner part of the blade as well as the load reduction by 3D effects close to the blade tip. They are used as input to a simple BEM code and the results of this BEM with 3D rotor polars are compared to the predictions of BEM with 2D airfoil coefficients plus common empirical corrections for stall delay and tip loss. While BEM with 2D airfoil coefficients produces a very different radial distribution of loads than the RANS simulation, the BEM with 3D rotor polars manages to reproduce the loads from RANS very accurately for a variety of load cases, as long as the blade pitch angle is not too different from the cases from which the polars were extracted.

Assessment of the reliability of protein-protein interactions and protein function prediction.

PubMed

Deng, Minghua; Sun, Fengzhu; Chen, Ting

2003-01-01

As more and more high-throughput protein-protein interaction data are collected, the task of estimating the reliability of different data sets becomes increasingly important. In this paper, we present our study of two groups of protein-protein interaction data, the physical interaction data and the protein complex data, and estimate the reliability of these data sets using three different measurements: (1) the distribution of gene expression correlation coefficients, (2) the reliability based on gene expression correlation coefficients, and (3) the accuracy of protein function predictions. We develop a maximum likelihood method to estimate the reliability of protein interaction data sets according to the distribution of correlation coefficients of gene expression profiles of putative interacting protein pairs. The results of the three measurements are consistent with each other. The MIPS protein complex data have the highest mean gene expression correlation coefficients (0.256) and the highest accuracy in predicting protein functions (70% sensitivity and specificity), while Ito's Yeast two-hybrid data have the lowest mean (0.041) and the lowest accuracy (15% sensitivity and specificity). Uetz's data are more reliable than Ito's data in all three measurements, and the TAP protein complex data are more reliable than the HMS-PCI data in all three measurements as well. The complex data sets generally perform better in function predictions than do the physical interaction data sets. Proteins in complexes are shown to be more highly correlated in gene expression. The results confirm that the components of a protein complex can be assigned to functions that the complex carries out within a cell. There are three interaction data sets different from the above two groups: the genetic interaction data, the in-silico data and the syn-express data. Their capability of predicting protein functions generally falls between that of the Y2H data and that of the MIPS protein complex data. The supplementary information is available at the following Web site: http://www-hto.usc.edu/-msms/AssessInteraction/.

Assessing the Chemical Accuracy of Protein Structures via Peptide Acidity

PubMed Central

Anderson, Janet S.; Hernández, Griselda; LeMaster, David M.

2012-01-01

Although the protein native state is a Boltzmann conformational ensemble, practical applications often require a representative model from the most populated region of that distribution. The acidity of the backbone amides, as reflected in hydrogen exchange rates, is exquisitely sensitive to the surrounding charge and dielectric volume distribution. For each of four proteins, three independently determined X-ray structures of differing crystallographic resolution were used to predict exchange for the static solvent-exposed amide hydrogens. The average correlation coefficients range from 0.74 for ubiquitin to 0.93 for Pyrococcus furiosus rubredoxin, reflecting the larger range of experimental exchange rates exhibited by the latter protein. The exchange prediction errors modestly correlate with the crystallographic resolution. MODELLER 9v6-derived homology models at ~60% sequence identity (36% identity for chymotrypsin inhibitor CI2) yielded correlation coefficients that are ~0.1 smaller than for the cognate X-ray structures. The most recently deposited NOE-based ubiquitin structure and the original NMR structure of CI2 fail to provide statistically significant predictions of hydrogen exchange. However, the more recent RECOORD refinement study of CI2 yielded predictions comparable to the X-ray and homology model-based analyses. PMID:23182463

A comparison of experimental and theoretical results for leakage, pressure distribution, and rotordynamic coefficients for annular gas seals

NASA Technical Reports Server (NTRS)

Nicks, C. O.; Childs, D. W.

1984-01-01

The importance of seal behavior in rotordynamics is discussed and current annular seal theory is reviewed. A Nelson's analytical-computational method for determining rotordynamic coefficients for this type of compressible-flow seal is outlined. Various means for the experimental identification of the dynamic coefficients are given, and the method employed at the Texas A and M University (TAMU) test facility is explained. The TAMU test apparatus is described, and the test procedures are discussed. Experimental results, including leakage, entrance-loss coefficients, pressure distributions, and rotordynamic coefficients for a smooth and a honeycomb constant-clearance seal are presented and compared to theoretical results from Nelson's analysis. The results for both seals show little sensitivity to the running speed over the test range. Agreement between test results and theory for leakage through the seal is satisfactory. Test results for direct stiffness show a greater sensitivity to fluid pre-rotation than predicted. Results also indicate that the deliberately roughened surface of the honeycomb seal provides improved stability versus the smooth seal.

Rolling moments in a trailing vortex flow field

NASA Technical Reports Server (NTRS)

Mcmillan, O. J.; Schwind, R. G.; Nielsen, J. N.; Dillenius, M. F. E.

1977-01-01

Pressure distributions are presented which were measured on a wing in close proximity to a tip vortex of known structure generated by a larger, upstream semispan wing. Overall loads calculated by integration of these pressures are checked by independent measurements made with an identical model mounted on a force balance. Several conventional methods of wing analysis are used to predict the loads on the following wing. Strip theory is shown to give uniformly poor results for loading distribution, although predictions of overall lift and rolling moment are sometimes acceptable. Good results are obtained for overall coefficients and loading distribution by using linearized pressures in vortex-lattice theory in conjunction with a rectilinear vortex. The equivalent relation from reverse-flow theory that can be used to give economic predictions for overall loads is presented.

Differential Higgs production at N3LO beyond threshold

NASA Astrophysics Data System (ADS)

Dulat, Falko; Mistlberger, Bernhard; Pelloni, Andrea

2018-01-01

We present several key steps towards the computation of differential Higgs boson cross sections at N3LO in perturbative QCD. Specifically, we work in the framework of Higgs-differential cross sections that allows to compute precise predictions for realistic LHC observables. We demonstrate how to perform an expansion of the analytic N3LO coefficient functions around the production threshold of the Higgs boson. Our framework allows us to compute to arbitrarily high order in the threshold expansion and we explicitly obtain the first two expansion coefficients in analytic form. Furthermore, we assess the phenomenological viability of threshold expansions for differential distributions. We find that while a few terms in the threshold expansion are sufficient to approximate the exact rapidity distribution well, transverse momentum distributions require a signficantly higher number of terms in the expansion to be adequately described. We find that to improve state of the art predictions for the rapidity distribution beyond NNLO even more sub-leading terms in the threshold expansion than presented in this article are required. In addition, we report on an interesting obstacle for the computation of N3LO corrections with LHAPDF parton distribution functions and our solution. We provide files containing the analytic expressions for the partonic cross sections as supplementary material attached to this paper.

Differential Higgs production at N 3LO beyond threshold

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dulat, Falko; Mistlberger, Bernhard; Pelloni, Andrea

We present several key steps towards the computation of differential Higgs boson cross sections at N 3LO in perturbative QCD. Specifically, we work in the framework of Higgs-differential cross sections that allows to compute precise predictions for realistic LHC observables. We demonstrate how to perform an expansion of the analytic N 3LO coefficient functions around the production threshold of the Higgs boson. Our framework allows us to compute to arbitrarily high order in the threshold expansion and we explicitly obtain the first two expansion coefficients in analytic form. Furthermore, we assess the phenomenological viability of threshold expansions for differential distributions.more » We find that while a few terms in the threshold expansion are sufficient to approximate the exact rapidity distribution well, transverse momentum distributions require a signficantly higher number of terms in the expansion to be adequately described. We find that to improve state of the art predictions for the rapidity distribution beyond NNLO even more sub-leading terms in the threshold expansion than presented in this article are required. In addition, we report on an interesting obstacle for the computation of N 3LO corrections with LHAPDF parton distribution functions and our solution. We provide files containing the analytic expressions for the partonic cross sections as supplementary material attached to this paper.« less

Differential Higgs production at N 3LO beyond threshold

DOE PAGES

Dulat, Falko; Mistlberger, Bernhard; Pelloni, Andrea

2018-01-29

We present several key steps towards the computation of differential Higgs boson cross sections at N 3LO in perturbative QCD. Specifically, we work in the framework of Higgs-differential cross sections that allows to compute precise predictions for realistic LHC observables. We demonstrate how to perform an expansion of the analytic N 3LO coefficient functions around the production threshold of the Higgs boson. Our framework allows us to compute to arbitrarily high order in the threshold expansion and we explicitly obtain the first two expansion coefficients in analytic form. Furthermore, we assess the phenomenological viability of threshold expansions for differential distributions.more » We find that while a few terms in the threshold expansion are sufficient to approximate the exact rapidity distribution well, transverse momentum distributions require a signficantly higher number of terms in the expansion to be adequately described. We find that to improve state of the art predictions for the rapidity distribution beyond NNLO even more sub-leading terms in the threshold expansion than presented in this article are required. In addition, we report on an interesting obstacle for the computation of N 3LO corrections with LHAPDF parton distribution functions and our solution. We provide files containing the analytic expressions for the partonic cross sections as supplementary material attached to this paper.« less

A comparison of experimental and theoretical results for leakage, pressure gradients, and rotordynamic coefficients for tapered annular gas seal

NASA Technical Reports Server (NTRS)

Elrod, D. A.; Childs, D. W.

1986-01-01

A brief review of current annular seal theory and a discussion of the predicted effect on stiffness of tapering the seal stator are presented. An outline of Nelson's analytical-computational method for determining rotordynamic coefficients for annular compressible-flow seals is included. Modifications to increase the maximum rotor speed of an existing air-seal test apparatus at Texas A&M University are described. Experimental results, including leakage, entrance-loss coefficients, pressure distributions, and normalized rotordynamic coefficients, are presented for four convergent-tapered, smooth-rotor, smooth-stator seals. A comparison of the test results shows that an inlet-to-exit clearance ratio of 1.5 to 2.0 provides the maximum direct stiffness, a clearance ratio of 2.5 provides the greatest stability, and a clearance ratio of 1.0 provides the least stability. The experimental results are compared to theoretical results from Nelson's analysis with good agreement. Test results for cross-coupled stiffness show less sensitivity of fluid prerotation than predicted.

Applicability of empirical data currently used in predicting solid propellant exhaust plumes

NASA Technical Reports Server (NTRS)

Tevepaugh, J. A.; Smith, S. D.; Penny, M. M.; Greenwood, T.; Roberts, B. B.

1977-01-01

Theoretical and experimental approaches to exhaust plume analysis are compared. A two-phase model is extended to include treatment of reacting gas chemistry, and thermodynamical modeling of the gaseous phase of the flow field is considered. The applicability of empirical data currently available to define particle drag coefficients, heat transfer coefficients, mean particle size, and particle size distributions is investigated. Experimental and analytical comparisons are presented for subscale solid rocket motors operating at three altitudes with attention to pitot total pressure and stagnation point heating rate measurements. The mathematical treatment input requirements are explained. The two-phase flow field solution adequately predicts gasdynamic properties in the inviscid portion of two-phase exhaust plumes. It is found that prediction of exhaust plume gas pressures requires an adequate model of flow field dynamics.

Predictive modelling of grain-size distributions from marine electromagnetic profiling data using end-member analysis and a radial basis function network

NASA Astrophysics Data System (ADS)

Baasch, B.; Müller, H.; von Dobeneck, T.

2018-07-01

In this work, we present a new methodology to predict grain-size distributions from geophysical data. Specifically, electric conductivity and magnetic susceptibility of seafloor sediments recovered from electromagnetic profiling data are used to predict grain-size distributions along shelf-wide survey lines. Field data from the NW Iberian shelf are investigated and reveal a strong relation between the electromagnetic properties and grain-size distribution. The here presented workflow combines unsupervised and supervised machine-learning techniques. Non-negative matrix factorization is used to determine grain-size end-members from sediment surface samples. Four end-members were found, which well represent the variety of sediments in the study area. A radial basis function network modified for prediction of compositional data is then used to estimate the abundances of these end-members from the electromagnetic properties. The end-members together with their predicted abundances are finally back transformed to grain-size distributions. A minimum spatial variation constraint is implemented in the training of the network to avoid overfitting and to respect the spatial distribution of sediment patterns. The predicted models are tested via leave-one-out cross-validation revealing high prediction accuracy with coefficients of determination (R2) between 0.76 and 0.89. The predicted grain-size distributions represent the well-known sediment facies and patterns on the NW Iberian shelf and provide new insights into their distribution, transition and dynamics. This study suggests that electromagnetic benthic profiling in combination with machine learning techniques is a powerful tool to estimate grain-size distribution of marine sediments.

Predictive modelling of grain size distributions from marine electromagnetic profiling data using end-member analysis and a radial basis function network

NASA Astrophysics Data System (ADS)

Baasch, B.; M"uller, H.; von Dobeneck, T.

2018-04-01

In this work we present a new methodology to predict grain-size distributions from geophysical data. Specifically, electric conductivity and magnetic susceptibility of seafloor sediments recovered from electromagnetic profiling data are used to predict grain-size distributions along shelf-wide survey lines. Field data from the NW Iberian shelf are investigated and reveal a strong relation between the electromagnetic properties and grain-size distribution. The here presented workflow combines unsupervised and supervised machine learning techniques. Nonnegative matrix factorisation is used to determine grain-size end-members from sediment surface samples. Four end-members were found which well represent the variety of sediments in the study area. A radial-basis function network modified for prediction of compositional data is then used to estimate the abundances of these end-members from the electromagnetic properties. The end-members together with their predicted abundances are finally back transformed to grain-size distributions. A minimum spatial variation constraint is implemented in the training of the network to avoid overfitting and to respect the spatial distribution of sediment patterns. The predicted models are tested via leave-one-out cross-validation revealing high prediction accuracy with coefficients of determination (R2) between 0.76 and 0.89. The predicted grain-size distributions represent the well-known sediment facies and patterns on the NW Iberian shelf and provide new insights into their distribution, transition and dynamics. This study suggests that electromagnetic benthic profiling in combination with machine learning techniques is a powerful tool to estimate grain-size distribution of marine sediments.

Copula based prediction models: an application to an aortic regurgitation study

PubMed Central

Kumar, Pranesh; Shoukri, Mohamed M

2007-01-01

Background: An important issue in prediction modeling of multivariate data is the measure of dependence structure. The use of Pearson's correlation as a dependence measure has several pitfalls and hence application of regression prediction models based on this correlation may not be an appropriate methodology. As an alternative, a copula based methodology for prediction modeling and an algorithm to simulate data are proposed. Methods: The method consists of introducing copulas as an alternative to the correlation coefficient commonly used as a measure of dependence. An algorithm based on the marginal distributions of random variables is applied to construct the Archimedean copulas. Monte Carlo simulations are carried out to replicate datasets, estimate prediction model parameters and validate them using Lin's concordance measure. Results: We have carried out a correlation-based regression analysis on data from 20 patients aged 17–82 years on pre-operative and post-operative ejection fractions after surgery and estimated the prediction model: Post-operative ejection fraction = - 0.0658 + 0.8403 (Pre-operative ejection fraction); p = 0.0008; 95% confidence interval of the slope coefficient (0.3998, 1.2808). From the exploratory data analysis, it is noted that both the pre-operative and post-operative ejection fractions measurements have slight departures from symmetry and are skewed to the left. It is also noted that the measurements tend to be widely spread and have shorter tails compared to normal distribution. Therefore predictions made from the correlation-based model corresponding to the pre-operative ejection fraction measurements in the lower range may not be accurate. Further it is found that the best approximated marginal distributions of pre-operative and post-operative ejection fractions (using q-q plots) are gamma distributions. The copula based prediction model is estimated as: Post -operative ejection fraction = - 0.0933 + 0.8907 × (Pre-operative ejection fraction); p = 0.00008 ; 95% confidence interval for slope coefficient (0.4810, 1.3003). For both models differences in the predicted post-operative ejection fractions in the lower range of pre-operative ejection measurements are considerably different and prediction errors due to copula model are smaller. To validate the copula methodology we have re-sampled with replacement fifty independent bootstrap samples and have estimated concordance statistics 0.7722 (p = 0.0224) for the copula model and 0.7237 (p = 0.0604) for the correlation model. The predicted and observed measurements are concordant for both models. The estimates of accuracy components are 0.9233 and 0.8654 for copula and correlation models respectively. Conclusion: Copula-based prediction modeling is demonstrated to be an appropriate alternative to the conventional correlation-based prediction modeling since the correlation-based prediction models are not appropriate to model the dependence in populations with asymmetrical tails. Proposed copula-based prediction model has been validated using the independent bootstrap samples. PMID:17573974

Aeroelasticity in Turbomachines. Comparison of Theoretical and Experimental Cascade Results.

DTIC Science & Technology

1986-01-01

Y~x)csn1#(x)) It should be noted here that, in computing the blade surface pressure distribution, only components, and not amplitudes or phase angles...oscillation, done on the system is obtained by computing -i ChV+Cc+rhU+c_,Vh (12) Expressed in this way, the aerodynamic work coefficients c., cVh, cva...predictions), so the aerodynamic damping coefficient can easily be computed and plotted. This information is useful to the turbomachine designer for

Comparison of concurrent strain gage- and pressure transducer-measured flight loads on a lifting reentry vehicle and correlation with wind tunnel predictions

NASA Technical Reports Server (NTRS)

Tang, M. H.; Sefic, W. J.; Sheldon, R. G.

1978-01-01

Concurrent strain gage and pressure transducer measured flight loads on a lifting reentry vehicle are compared and correlated with wind tunnel-predicted loads. Subsonic, transonic, and supersonic aerodynamic loads are presented for the left fin and control surfaces of the X-24B lifting reentry vehicle. Typical left fin pressure distributions are shown. The effects of variations in angle of attack, angle of sideslip, and Mach number on the left fin loads and rudder hinge moments are presented in coefficient form. Also presented are the effects of variations in angle of attack and Mach number on the upper flap, lower flap, and aileron hinge-moment coefficients. The effects of variations in lower flap hinge moments due to changes in lower flap deflection and Mach number are presented in terms of coefficient slopes.

Atomistic simulations of carbon diffusion and segregation in liquid silicon

NASA Astrophysics Data System (ADS)

Luo, Jinping; Alateeqi, Abdullah; Liu, Lijun; Sinno, Talid

2017-12-01

The diffusivity of carbon atoms in liquid silicon and their equilibrium distribution between the silicon melt and crystal phases are key, but unfortunately not precisely known parameters for the global models of silicon solidification processes. In this study, we apply a suite of molecular simulation tools, driven by multiple empirical potential models, to compute diffusion and segregation coefficients of carbon at the silicon melting temperature. We generally find good consistency across the potential model predictions, although some exceptions are identified and discussed. We also find good agreement with the range of available experimental measurements of segregation coefficients. However, the carbon diffusion coefficients we compute are significantly lower than the values typically assumed in continuum models of impurity distribution. Overall, we show that currently available empirical potential models may be useful, at least semi-quantitatively, for studying carbon (and possibly other impurity) transport in silicon solidification, especially if a multi-model approach is taken.

Combined experimental-numerical identification of radiative transfer coefficients in white LED phosphor layers

NASA Astrophysics Data System (ADS)

Akolkar, A.; Petrasch, J.; Finck, S.; Rahmatian, N.

2018-02-01

An inverse analysis of the phosphor layer of a commercially available, conformally coated, white LED is done based on tomographic and spectrometric measurements. The aim is to determine the radiative transfer coefficients of the phosphor layer from the measurements of the finished device, with minimal assumptions regarding the composition of the phosphor layer. These results can be used for subsequent opto-thermal modelling and optimization of the device. For this purpose, multiple integrating sphere and gonioradiometric measurements are done to obtain statistical bounds on spectral radiometric values and angular color distributions for ten LEDs belonging to the same color bin of the product series. Tomographic measurements of the LED package are used to generate a tetrahedral grid of the 3D LED geometry. A radiative transfer model using Monte Carlo Ray Tracing in the tetrahedral grid is developed. Using a two-wavelength model consisting of a blue emission wavelength and a yellow, Stokes-shifted re-emission wavelength, the angular color distribution of the LED is simulated over wide ranges of the absorption and scattering coefficients of the phosphor layer, for the blue and yellow wavelengths. Using a two-step, iterative space search, combinations of the radiative transfer coefficients are obtained for which the simulations are consistent with the integrating sphere and gonioradiometric measurements. The results show an inverse relationship between the scattering and absorption coefficients of the phosphor layer for blue light. Scattering of yellow light acts as a distribution and loss mechanism for yellow light and affects the shape of the angular color distribution significantly, especially at larger viewing angles. The spread of feasible coefficients indicates that measured optical behavior of the LEDs may be reproduced using a range of combinations of radiative coefficients. Given that coefficients predicted by the Mie theory usually must be corrected in order to reproduce experimental results, these results indicate that a more complete model of radiative transfer in phosphor layers is required.

Spatial distribution of CH3 and CH2 radicals in a methane rf discharge

NASA Astrophysics Data System (ADS)

Sugai, H.; Kojima, H.; Ishida, A.; Toyoda, H.

1990-06-01

Spatial distributions of neutral radicals CH3 and CH2 in a capacitively coupled rf glow discharge of methane were measured by threshold ionization mass spectrometry. A strong asymmetry of the density profile was found for the CH2 radical in the high-pressure (˜100 mTorr) discharge. In addition, comprehensive measurements of electron energy distribution, ionic composition, and radical sticking coefficient were made to use as inputs to theoretical modeling of radicals in the methane plasma. The model predictions agree substantially with the measured radical distributions.

Equations of prediction for abdominal fat in brown egg-laying hens fed different diets.

PubMed

Souza, C; Jaimes, J J B; Gewehr, C E

2017-06-01

The objective was to use noninvasive measurements to formulate equations for predicting the abdominal fat weight of laying hens in a noninvasive manner. Hens were fed with different diets; the external body measurements of birds were used as regressors. We used 288 Hy-Line Brown laying hens, distributed in a completely randomized design in a factorial arrangement, submitted for 16 wk to 2 metabolizable energy levels (2,550 and 2,800 kcal/kg) and 3 levels of crude protein in the diet (150, 160, and 170 g/kg), totaling 6 treatments, with 48 hens each. Sixteen hens per treatment of 92 wk age were utilized to evaluate body weight, bird length, tarsus and sternum, greater and lesser diameter of the tarsus, and abdominal fat weight, after slaughter. The equations were obtained by using measures evaluated with regressors through simple and multiple linear regression with the stepwise method of indirect elimination (backward), with P < 0.10 for all variables remaining in the model. The weight of abdominal fat as predicted by the equations and observed values for each bird were subjected to Pearson's correlation analysis. The equations generated by energy levels showed coefficients of determination of 0.50 and 0.74 for 2,800 and 2,550 kcal/kg of metabolizable energy, respectively, with correlation coefficients of 0.71 and 0.84, with a highly significant correlation between the calculated and observed values of abdominal fat. For protein levels of 150, 160, and 170 g/kg in the diet, it was possible to obtain coefficients of determination of 0.75, 0.57, and 0.61, with correlation coefficients of 0.86, 0.75, and 0.78, respectively. Regarding the general equation for predicting abdominal fat weight, the coefficient of determination was 0.62; the correlation coefficient was 0.79. The equations for predicting abdominal fat weight in laying hens, based on external measurements of the birds, showed positive coefficients of determination and correlation coefficients, thus allowing researchers to determine abdominal fat weight in vivo. © 2016 Poultry Science Association Inc.

Modeling Monthly Spatial Distribution of Ommastrephes bartramii CPUE in the Northwest Pacific and Its Spatially Nonstationary Relationships with the Marine Environment

NASA Astrophysics Data System (ADS)

Feng, Yongjiu; Liu, Yang; Chen, Xinjun

2018-06-01

There are substantial spatial variations in the relationships between catch-per-unit-effort (CPUE) and oceanographic conditions with respect to pelagic species. This study examines the monthly spatiotemporal distribution of CPUE of the neon flying squid, Ommastrephes bartramii, in the Northwest Pacific from July to November during 2004-2013, and analyzes the relationships with oceanographic conditions using a generalized additive model (GAM) and geographically weighted regression (GWR) model. The results show that most of the squids were harvested in waters with sea surface temperature (SST) between 7.6 and 24.6°C, chlorophyll- a (Chl- a) concentration below 1.0 mg m-3, sea surface salinity (SSS) between 32.7 and 34.6, and sea surface height (SSH) between -12.8 and 28.4 cm. The monthly spatial distribution patterns of O. bartramii predicted using GAM and GWR models are similar to observed patterns for all months. There are notable variations in the local coefficients of GWR, indicating the presence of spatial non-stationarity in the relationship between O. bartramii CPUE and oceanographic conditions. The statistical results show that there were nearly equal positive and negative coefficients for Chl- a, more positive than negative coefficients for SST, and more negative than positive coefficients for SSS and SSH. The overall accuracies of the hot spots predicted by GWR exceed 60% (except for October), indicating a good performance of this model and its improvement over GAM. Our study provides a better understanding of the ecological dynamics of O. bartramii CPUE and makes it possible to use GWR to study the spatially nonstationary characteristics of other pelagic species.

Observations of the directional distribution of the wind energy input function over swell waves

NASA Astrophysics Data System (ADS)

Shabani, Behnam; Babanin, Alex V.; Baldock, Tom E.

2016-02-01

Field measurements of wind stress over shallow water swell traveling in different directions relative to the wind are presented. The directional distribution of the measured stresses is used to confirm the previously proposed but unverified directional distribution of the wind energy input function. The observed wind energy input function is found to follow a much narrower distribution (β∝cos⁡3.6θ) than the Plant (1982) cosine distribution. The observation of negative stress angles at large wind-wave angles, however, indicates that the onset of negative wind shearing occurs at about θ≈ 50°, and supports the use of the Snyder et al. (1981) directional distribution. Taking into account the reverse momentum transfer from swell to the wind, Snyder's proposed parameterization is found to perform exceptionally well in explaining the observed narrow directional distribution of the wind energy input function, and predicting the wind drag coefficients. The empirical coefficient (ɛ) in Snyder's parameterization is hypothesised to be a function of the wave shape parameter, with ɛ value increasing as the wave shape changes between sinusoidal, sawtooth, and sharp-crested shoaling waves.

Application of the Junge- and Pankow-equation for estimating indoor gas/particle distribution and exposure to SVOCs

NASA Astrophysics Data System (ADS)

Salthammer, Tunga; Schripp, Tobias

2015-04-01

In the indoor environment, distribution and dynamics of an organic compound between gas phase, particle phase and settled dust must be known for estimating human exposure. This, however, requires a detailed understanding of the environmentally important compound parameters, their interrelation and of the algorithms for calculating partitioning coefficients. The parameters of major concern are: (I) saturation vapor pressure (PS) (of the subcooled liquid); (II) Henry's law constant (H); (III) octanol/water partition coefficient (KOW); (IV) octanol/air partition coefficient (KOA); (V) air/water partition coefficient (KAW) and (VI) settled dust properties like density and organic content. For most of the relevant compounds reliable experimental data are not available and calculated gas/particle distributions can widely differ due to the uncertainty in predicted Ps and KOA values. This is not a big problem if the target compound is of low (<10-6 Pa) or high (>10-2 Pa) volatility, but in the intermediate region even small changes in Ps or KOA will have a strong impact on the result. Moreover, the related physical processes might bear large uncertainties. The KOA value can only be used for particle absorption from the gas phase if the organic portion of the particle or dust is high. The Junge- and Pankow-equation for calculating the gas/particle distribution coefficient KP do not consider the physical and chemical properties of the particle surface area. It is demonstrated by error propagation theory and Monte-Carlo simulations that parameter uncertainties from estimation methods for molecular properties and variations of indoor conditions might strongly influence the calculated distribution behavior of compounds in the indoor environment.

Using ESAP Software for Predicting the Spatial Distributions of NDVI and Transpiration of Cotton

USDA-ARS?s Scientific Manuscript database

The normalized difference vegetation index (NDVI) has many applications in agricultural management, including monitoring real-time crop coefficients for estimating crop evapotranspiration (ET). However, frequent monitoring of NDVI as needed in such applications is generally not feasible from aerial ...

New best estimates for radionuclide solid-liquid distribution coefficients in soils. Part 2: naturally occurring radionuclides.

PubMed

Vandenhove, H; Gil-García, C; Rigol, A; Vidal, M

2009-09-01

Predicting the transfer of radionuclides in the environment for normal release, accidental, disposal or remediation scenarios in order to assess exposure requires the availability of an important number of generic parameter values. One of the key parameters in environmental assessment is the solid liquid distribution coefficient, K(d), which is used to predict radionuclide-soil interaction and subsequent radionuclide transport in the soil column. This article presents a review of K(d) values for uranium, radium, lead, polonium and thorium based on an extensive literature survey, including recent publications. The K(d) estimates were presented per soil groups defined by their texture and organic matter content (Sand, Loam, Clay and Organic), although the texture class seemed not to significantly affect K(d). Where relevant, other K(d) classification systems are proposed and correlations with soil parameters are highlighted. The K(d) values obtained in this compilation are compared with earlier review data.

Modelling the spreading rate of controlled communicable epidemics through an entropy-based thermodynamic model

NASA Astrophysics Data System (ADS)

Wang, WenBin; Wu, ZiNiu; Wang, ChunFeng; Hu, RuiFeng

2013-11-01

A model based on a thermodynamic approach is proposed for predicting the dynamics of communicable epidemics assumed to be governed by controlling efforts of multiple scales so that an entropy is associated with the system. All the epidemic details are factored into a single and time-dependent coefficient, the functional form of this coefficient is found through four constraints, including notably the existence of an inflexion point and a maximum. The model is solved to give a log-normal distribution for the spread rate, for which a Shannon entropy can be defined. The only parameter, that characterizes the width of the distribution function, is uniquely determined through maximizing the rate of entropy production. This entropy-based thermodynamic (EBT) model predicts the number of hospitalized cases with a reasonable accuracy for SARS in the year 2003. This EBT model can be of use for potential epidemics such as avian influenza and H7N9 in China.

Computational hydrodynamic comparison of a mini vessel and a USP 2 dissolution testing system to predict the dynamic operating conditions for similarity of dissolution performance.

PubMed

Wang, Bing; Bredael, Gerard; Armenante, Piero M

2018-03-25

The hydrodynamic characteristics of a mini vessel and a USP 2 dissolution testing system were obtained and compared to predict the tablet-liquid mass transfer coefficient from velocity distributions near the tablet and establish the dynamic operating conditions under which dissolution in mini vessels could be conducted to generate concentration profiles similar to those in the USP 2. Velocity profiles were obtained experimentally using Particle Image Velocimetry (PIV). Computational Fluid Dynamics (CFD) was used to predict the velocity distribution and strain rate around a model tablet. A CFD-based mass transfer model was also developed. When plotted against strain rate, the predicted tablet-liquid mass transfer coefficient was found to be independent of the system where it was obtained, implying that a tablet would dissolve at the same rate in both systems provided that the concentration gradient between the tablet surface and the bulk is the same, the tablet surface area per unit liquid volume is identical, and the two systems are operated at the appropriate agitation speeds specified in this work. The results of this work will help dissolution scientists operate mini vessels so as to predict the dissolution profiles in the USP 2, especially during the early stages of drug development. Copyright © 2018 Elsevier B.V. All rights reserved.

Simulating Osmotic Equilibria: A New Tool for Calculating Activity Coefficients in Concentrated Aqueous Salt Solutions.

PubMed

Bley, Michael; Duvail, Magali; Guilbaud, Philippe; Dufrêche, Jean-François

2017-10-19

Herein, a new theoretical method is presented for predicting osmotic equilibria and activities, where a bulk liquid and its corresponding vapor phase are simulated by means of molecular dynamics using explicit polarization. Calculated time-averaged number density profiles provide the amount of evaporated molecules present in the vapor phase and consequently the vapor-phase density. The activity of the solvent and the corresponding osmotic coefficient are determined by the vapor density at different solute concentrations with respect to the reference vapor density of the pure solvent. With the extended Debye-Hückel equation for the activity coefficient along with the corresponding Gibbs-Duhem relation, the activity coefficients of the solutes are calculated by fitting the osmotic coefficients. A simple model based on the combination of Poisson processes and Maxwell-Boltzmann velocity distributions is introduced to interpret statistical phenomena observed during the simulations, which are related to evaporation and recondensation. This method is applied to aqueous dysprosium nitrate [Dy(NO 3 ) 3 ] solutions at different concentrations. The obtained densities of the liquid bulk and the osmotic and activity coefficients are in good agreement with the experimental results for concentrated and saturated solutions. Density profiles of the liquid-vapor interface at different concentrations provide detailed insight into the spatial distributions of all compounds.

An improved numerical model suggests potential differences of wind-blown sand between on Earth and Mars

NASA Astrophysics Data System (ADS)

Bo, T. L.; Fu, L. T.; Liu, L.; Zheng, X. J.

2017-06-01

The studies on wind-blown sand are crucial for understanding the change of climate and landscape on Mars. However, the disadvantages of the saltation models may result in unreliable predictions. In this paper, the saltation model has been improved from two main aspects, the aerodynamic surface roughness and the lift-off parameters. The aerodynamic surface roughness is expressed as function of particle size, wind strength, air density, and air dynamic viscosity. The lift-off parameters are improved through including the dependence of restitution coefficient on incident parameters and the correlation between saltating speed and angle. The improved model proved to be capable of reproducing the observed data well in both stable stage and evolution process. The modeling of wind-blown sand is promoted by all improved aspects, and the dependence of restitution coefficient on incident parameters could not be ignored. The constant restitution coefficient and uncorrelated lift-off parameter distributions would lead to both the overestimation of the sand transport rate and apparent surface roughness and the delay of evolution process. The distribution of lift-off speed and the evolution of lift-off parameters on Mars are found to be different from those on Earth. This may thus suggest that it is inappropriate to predict the evolution of wind-blown sand by using the lift-off velocity obtained in steady state saltation. And it also may be problematic to predict the wind-blown sand on Mars through applying the lift-off velocity obtained upon terrestrial conditions directly.

Improved predictive modeling of white LEDs with accurate luminescence simulation and practical inputs with TracePro opto-mechanical design software

NASA Astrophysics Data System (ADS)

Tsao, Chao-hsi; Freniere, Edward R.; Smith, Linda

2009-02-01

The use of white LEDs for solid-state lighting to address applications in the automotive, architectural and general illumination markets is just emerging. LEDs promise greater energy efficiency and lower maintenance costs. However, there is a significant amount of design and cost optimization to be done while companies continue to improve semiconductor manufacturing processes and begin to apply more efficient and better color rendering luminescent materials such as phosphor and quantum dot nanomaterials. In the last decade, accurate and predictive opto-mechanical software modeling has enabled adherence to performance, consistency, cost, and aesthetic criteria without the cost and time associated with iterative hardware prototyping. More sophisticated models that include simulation of optical phenomenon, such as luminescence, promise to yield designs that are more predictive - giving design engineers and materials scientists more control over the design process to quickly reach optimum performance, manufacturability, and cost criteria. A design case study is presented where first, a phosphor formulation and excitation source are optimized for a white light. The phosphor formulation, the excitation source and other LED components are optically and mechanically modeled and ray traced. Finally, its performance is analyzed. A blue LED source is characterized by its relative spectral power distribution and angular intensity distribution. YAG:Ce phosphor is characterized by relative absorption, excitation and emission spectra, quantum efficiency and bulk absorption coefficient. Bulk scatter properties are characterized by wavelength dependent scatter coefficients, anisotropy and bulk absorption coefficient.

Implementation Intention and Reminder Effects on Behavior Change in a Mobile Health System: A Predictive Cognitive Model

PubMed Central

Mohan, Shiwali; Venkatakrishnan, Anusha; Nelson, Les; Silva, Michael; Springer, Aaron

2017-01-01

Background Implementation intentions are mental representations of simple plans to translate goal intentions into behavior under specific conditions. Studies show implementation intentions can produce moderate to large improvements in behavioral goal achievement. Human associative memory mechanisms have been implicated in the processes by which implementation intentions produce effects. On the basis of the adaptive control of thought-rational (ACT-R) theory of cognition, we hypothesized that the strength of implementation intention effect could be manipulated in predictable ways using reminders delivered by a mobile health (mHealth) app. Objective The aim of this experiment was to manipulate the effects of implementation intentions on daily behavioral goal success in ways predicted by the ACT-R theory concerning mHealth reminder scheduling. Methods An incomplete factorial design was used in this mHealth study. All participants were asked to choose a healthy behavior goal associated with eat slowly, walking, or eating more vegetables and were asked to set implementation intentions. N=64 adult participants were in the study for 28 days. Participants were stratified by self-efficacy and assigned to one of two reminder conditions: reminders-presented versus reminders-absent. Self-efficacy and reminder conditions were crossed. Nested within the reminders-presented condition was a crossing of frequency of reminders sent (high, low) by distribution of reminders sent (distributed, massed). Participants in the low frequency condition got 7 reminders over 28 days; those in the high frequency condition were sent 14. Participants in the distributed conditions were sent reminders at uniform intervals. Participants in the massed distribution conditions were sent reminders in clusters. Results There was a significant overall effect of reminders on achieving a daily behavioral goal (coefficient=2.018, standard error [SE]=0.572, odds ratio [OR]=7.52, 95% CI 0.9037-3.2594, P<.001). As predicted by ACT-R, using default theoretical parameters, there was an interaction of reminder frequency by distribution on daily goal success (coefficient=0.7994, SE=0.2215, OR=2.2242, 95% CI 0.3656-1.2341, P<.001). The total number of times a reminder was acknowledged as received by a participant had a marginal effect on daily goal success (coefficient=0.0694, SE=0.0410, OR=1.0717, 95% CI −0.01116 to 0.1505, P=.09), and the time since acknowledging receipt of a reminder was highly significant (coefficient=−0.0490, SE=0.0104, OR=0.9522, 95% CI −0.0700 to −0.2852], P<.001). A dual system ACT-R mathematical model was fit to individuals’ daily goal successes and reminder acknowledgments: a goal-striving system dependent on declarative memory plus a habit-forming system that acquires automatic procedures for performance of behavioral goals. Conclusions Computational cognitive theory such as ACT-R can be used to make precise quantitative predictions concerning daily health behavior goal success in response to implementation intentions and the dosing schedules of reminders. PMID:29191800

A diffusivity model for predicting VOC diffusion in porous building materials based on fractal theory.

PubMed

Liu, Yanfeng; Zhou, Xiaojun; Wang, Dengjia; Song, Cong; Liu, Jiaping

2015-12-15

Most building materials are porous media, and the internal diffusion coefficients of such materials have an important influences on the emission characteristics of volatile organic compounds (VOCs). The pore structure of porous building materials has a significant impact on the diffusion coefficient. However, the complex structural characteristics bring great difficulties to the model development. The existing prediction models of the diffusion coefficient are flawed and need to be improved. Using scanning electron microscope (SEM) observations and mercury intrusion porosimetry (MIP) tests of typical porous building materials, this study developed a new diffusivity model: the multistage series-connection fractal capillary-bundle (MSFC) model. The model considers the variable-diameter capillaries formed by macropores connected in series as the main mass transfer paths, and the diameter distribution of the capillary bundles obeys a fractal power law in the cross section. In addition, the tortuosity of the macrocapillary segments with different diameters is obtained by the fractal theory. Mesopores serve as the connections between the macrocapillary segments rather than as the main mass transfer paths. The theoretical results obtained using the MSFC model yielded a highly accurate prediction of the diffusion coefficients and were in a good agreement with the VOC concentration measurements in the environmental test chamber. Copyright © 2015 Elsevier B.V. All rights reserved.

Effects of cooling system parameters on heat transfer in PAFC stack. Ph.D. Thesis

NASA Technical Reports Server (NTRS)

Abdul-Aziz, Ali A.

1985-01-01

Analytical and experimental study for the effects of cooling system parameters on the heat transfer and temperature distribution in the electrode plates of a phosphoric acid fuel-cell has been conducted. An experimental set-up that simulates the operating conditions prevailing in a phosphoric-acid fuel-cell stack was designed and constructed. The set-up was then used to measure the overall heat transfer coefficient, the thermal contact resistance, and the electrode temperature distribution for two different cooling plate configurations. Two types of cooling plate configurations, serpentine and straight, were tested. Air, water, and oil were used as coolants. Measurements for the heat transfer coefficient and the thermal contact resistance were made for various flow rates ranging from 16 to 88 Kg/hr, and stack clamping pressure ranging from O to 3448 Kpa. The experimental results for the overall heat transfer coefficient were utilized to derive mathematical relations for the overall heat transfer coefficient as a function of stack clamping pressure and Reynolds number for the three coolants. The empirically derived formulas were incorporated in a previously developed computer program to predict electrodes temperature distribution and the performance of the stack cooling system. The results obtained were then compared with those available in the literature. The comparison showed maximum deviation of +/- 11%.

Extended solvent-contact model approach to blind SAMPL5 prediction challenge for the distribution coefficients of drug-like molecules

NASA Astrophysics Data System (ADS)

Chung, Kee-Choo; Park, Hwangseo

2016-11-01

The performance of the extended solvent-contact model has been addressed in the SAMPL5 blind prediction challenge for distribution coefficient (LogD) of drug-like molecules with respect to the cyclohexane/water partitioning system. All the atomic parameters defined for 41 atom types in the solvation free energy function were optimized by operating a standard genetic algorithm with respect to water and cyclohexane solvents. In the parameterizations for cyclohexane, the experimental solvation free energy (Δ G sol ) data of 15 molecules for 1-octanol were combined with those of 77 molecules for cyclohexane to construct a training set because Δ G sol values of the former were unavailable for cyclohexane in publicly accessible databases. Using this hybrid training set, we established the LogD prediction model with the correlation coefficient ( R), average error (AE), and root mean square error (RMSE) of 0.55, 1.53, and 3.03, respectively, for the comparison of experimental and computational results for 53 SAMPL5 molecules. The modest accuracy in LogD prediction could be attributed to the incomplete optimization of atomic solvation parameters for cyclohexane. With respect to 31 SAMPL5 molecules containing the atom types for which experimental reference data for Δ G sol were available for both water and cyclohexane, the accuracy in LogD prediction increased remarkably with the R, AE, and RMSE values of 0.82, 0.89, and 1.60, respectively. This significant enhancement in performance stemmed from the better optimization of atomic solvation parameters by limiting the element of training set to the molecules with experimental Δ G sol data for cyclohexane. Due to the simplicity in model building and to low computational cost for parameterizations, the extended solvent-contact model is anticipated to serve as a valuable computational tool for LogD prediction upon the enrichment of experimental Δ G sol data for organic solvents.

Influence of slosh baffles on thermodynamic performance in liquid hydrogen tank.

PubMed

Liu, Zhan; Li, Cui

2018-03-15

A calibrated CFD model is built to investigate the influence of slosh baffles on the pressurization performance in liquid hydrogen (LH 2 ) tank. The calibrated CFD model is proven to have great predictive ability by compared against the flight experimental results. The pressure increase, thermal stratification and wall heat transfer coefficient of LH 2 tank have been detailedly studied. The results indicate that slosh baffles have a great influence on tank pressure increase, fluid temperature distribution and wall heat transfer. Owning to the existence of baffles, the stratification thickness increases gradually with the distance from tank axis to tank wall. While for the tank without baffles, the stratification thickness decreases firstly and then increases with the increase of the distance from the axis. The "M" type stratified thickness distribution presents in tank without baffles. One modified heat transfer coefficient correlation has been proposed with the change of fluid temperature considered by multiplying a temperature correction factor. It has been proven that the average relative prediction errors of heat transfer coefficient reduced from 19.08% to 4.98% for the wet tank wall of the tank, from 8.93% to 4.27% for the dry tank wall, respectively, calculated by the modified correlation. Copyright © 2017 Elsevier B.V. All rights reserved.

Time domain simulation of the response of geometrically nonlinear panels subjected to random loading

NASA Technical Reports Server (NTRS)

Moyer, E. Thomas, Jr.

1988-01-01

The response of composite panels subjected to random pressure loads large enough to cause geometrically nonlinear responses is studied. A time domain simulation is employed to solve the equations of motion. An adaptive time stepping algorithm is employed to minimize intermittent transients. A modified algorithm for the prediction of response spectral density is presented which predicts smooth spectral peaks for discrete time histories. Results are presented for a number of input pressure levels and damping coefficients. Response distributions are calculated and compared with the analytical solution of the Fokker-Planck equations. RMS response is reported as a function of input pressure level and damping coefficient. Spectral densities are calculated for a number of examples.

Helicopter rotor rotational noise predictions based on measured high-frequency blade loads

NASA Technical Reports Server (NTRS)

Hosier, R. N.; Ramakrishnan, R.

1974-01-01

In tests conducted at the Langley helicopter rotor test facility, simultaneous measurements of up to 200 harmonics of the fluctuating aerodynamic blade surface pressures and far-field radiated noise were made on a full-scale nontranslating rotor system. After their characteristics were determined, the measured blade surface pressures were converted to loading coefficients and used in an existing theory to predict the far-field rotational noise. A comparison of the calculated and measured noise shows generally good agreement up to 300 to 600 Hz, depending on the discreteness of the loading spectrum. Specific attention is given to the effects of the blade loading coefficients, chordwise loading distributions, blade loading phases, and observer azimuthal position on the calculations.

Reynolds number scaling to predict droplet size distribution in dispersed and undispersed subsurface oil releases.

PubMed

Li, Pu; Weng, Linlu; Niu, Haibo; Robinson, Brian; King, Thomas; Conmy, Robyn; Lee, Kenneth; Liu, Lei

2016-12-15

This study was aimed at testing the applicability of modified Weber number scaling with Alaska North Slope (ANS) crude oil, and developing a Reynolds number scaling approach for oil droplet size prediction for high viscosity oils. Dispersant to oil ratio and empirical coefficients were also quantified. Finally, a two-step Rosin-Rammler scheme was introduced for the determination of droplet size distribution. This new approach appeared more advantageous in avoiding the inconsistency in interfacial tension measurements, and consequently delivered concise droplet size prediction. Calculated and observed data correlated well based on Reynolds number scaling. The relation indicated that chemical dispersant played an important role in reducing the droplet size of ANS under different seasonal conditions. The proposed Reynolds number scaling and two-step Rosin-Rammler approaches provide a concise, reliable way to predict droplet size distribution, supporting decision making in chemical dispersant application during an offshore oil spill. Copyright © 2016 Elsevier Ltd. All rights reserved.

Prediction of slant path rain attenuation statistics at various locations

NASA Technical Reports Server (NTRS)

Goldhirsh, J.

1977-01-01

The paper describes a method for predicting slant path attenuation statistics at arbitrary locations for variable frequencies and path elevation angles. The method involves the use of median reflectivity factor-height profiles measured with radar as well as the use of long-term point rain rate data and assumed or measured drop size distributions. The attenuation coefficient due to cloud liquid water in the presence of rain is also considered. Absolute probability fade distributions are compared for eight cases: Maryland (15 GHz), Texas (30 GHz), Slough, England (19 and 37 GHz), Fayetteville, North Carolina (13 and 18 GHz), and Cambridge, Massachusetts (13 and 18 GHz).

Investigations of Fluid-Structure-Coupling and Turbulence Model Effects on the DLR Results of the Fifth AIAA CFD Drag Prediction Workshop

NASA Technical Reports Server (NTRS)

Keye, Stefan; Togiti, Vamish; Eisfeld, Bernhard; Brodersen, Olaf P.; Rivers, Melissa B.

2013-01-01

The accurate calculation of aerodynamic forces and moments is of significant importance during the design phase of an aircraft. Reynolds-averaged Navier-Stokes (RANS) based Computational Fluid Dynamics (CFD) has been strongly developed over the last two decades regarding robustness, efficiency, and capabilities for aerodynamically complex configurations. Incremental aerodynamic coefficients of different designs can be calculated with an acceptable reliability at the cruise design point of transonic aircraft for non-separated flows. But regarding absolute values as well as increments at off-design significant challenges still exist to compute aerodynamic data and the underlying flow physics with the accuracy required. In addition to drag, pitching moments are difficult to predict because small deviations of the pressure distributions, e.g. due to neglecting wing bending and twisting caused by the aerodynamic loads can result in large discrepancies compared to experimental data. Flow separations that start to develop at off-design conditions, e.g. in corner-flows, at trailing edges, or shock induced, can have a strong impact on the predictions of aerodynamic coefficients too. Based on these challenges faced by the CFD community a working group of the AIAA Applied Aerodynamics Technical Committee initiated in 2001 the CFD Drag Prediction Workshop (DPW) series resulting in five international workshops. The results of the participants and the committee are summarized in more than 120 papers. The latest, fifth workshop took place in June 2012 in conjunction with the 30th AIAA Applied Aerodynamics Conference. The results in this paper will evaluate the influence of static aeroelastic wing deformations onto pressure distributions and overall aerodynamic coefficients based on the NASA finite element structural model and the common grids.

A surface renewal model for unsteady-state mass transfer using the generalized Danckwerts age distribution function.

PubMed

Horvath, Isabelle R; Chatterjee, Siddharth G

2018-05-01

The recently derived steady-state generalized Danckwerts age distribution is extended to unsteady-state conditions. For three different wind speeds used by researchers on air-water heat exchange on the Heidelberg Aeolotron, calculations reveal that the distribution has a sharp peak during the initial moments, but flattens out and acquires a bell-shaped character with process time, with the time taken to attain a steady-state profile being a strong and inverse function of wind speed. With increasing wind speed, the age distribution narrows significantly, its skewness decreases and its peak becomes larger. The mean eddy renewal time increases linearly with process time initially but approaches a final steady-state value asymptotically, which decreases dramatically with increased wind speed. Using the distribution to analyse the transient absorption of a gas into a large body of liquid, assuming negligible gas-side mass-transfer resistance, estimates are made of the gas-absorption and dissolved-gas transfer coefficients for oxygen absorption in water at 25°C for the three different wind speeds. Under unsteady-state conditions, these two coefficients show an inverse behaviour, indicating a heightened accumulation of dissolved gas in the surface elements, especially during the initial moments of absorption. However, the two mass-transfer coefficients start merging together as the steady state is approached. Theoretical predictions of the steady-state mass-transfer coefficient or transfer velocity are in fair agreement (average absolute error of prediction = 18.1%) with some experimental measurements of the same for the nitrous oxide-water system at 20°C that were made in the Heidelberg Aeolotron.

Quantitative prediction of ionization effect on human skin permeability.

PubMed

Baba, Hiromi; Ueno, Yusuke; Hashida, Mitsuru; Yamashita, Fumiyoshi

2017-04-30

Although skin permeability of an active ingredient can be severely affected by its ionization in a dose solution, most of the existing prediction models cannot predict such impacts. To provide reliable predictors, we curated a novel large dataset of in vitro human skin permeability coefficients for 322 entries comprising chemically diverse permeants whose ionization fractions can be calculated. Subsequently, we generated thousands of computational descriptors, including LogD (octanol-water distribution coefficient at a specific pH), and analyzed the dataset using nonlinear support vector regression (SVR) and Gaussian process regression (GPR) combined with greedy descriptor selection. The SVR model was slightly superior to the GPR model, with externally validated squared correlation coefficient, root mean square error, and mean absolute error values of 0.94, 0.29, and 0.21, respectively. These models indicate that Log D is effective for a comprehensive prediction of ionization effects on skin permeability. In addition, the proposed models satisfied the statistical criteria endorsed in recent model validation studies. These models can evaluate virtually generated compounds at any pH; therefore, they can be used for high-throughput evaluations of numerous active ingredients and optimization of their skin permeability with respect to permeant ionization. Copyright © 2017 Elsevier B.V. All rights reserved.

Anomalous diffusion and scaling in coupled stochastic processes

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bel, Golan; Nemenman, Ilya

2009-01-01

Inspired by problems in biochemical kinetics, we study statistical properties of an overdamped Langevin processes with the friction coefficient depending on the state of a similar, unobserved, process. Integrating out the latter, we derive the Pocker-Planck the friction coefficient of the first depends on the state of the second. Integrating out the latter, we derive the Focker-Planck equation for the probability distribution of the former. This has the fonn of diffusion equation with time-dependent diffusion coefficient, resulting in an anomalous diffusion. The diffusion exponent can not be predicted using a simple scaling argument, and anomalous scaling appears as well. Themore » diffusion exponent of the Weiss-Havlin comb model is derived as a special case, and the same exponent holds even for weakly coupled processes. We compare our theoretical predictions with numerical simulations and find an excellent agreement. The findings caution against treating biochemical systems with unobserved dynamical degrees of freedom by means of standandard, diffusive Langevin descritpion.« less

Scavenging of radioactive soluble gases from inhomogeneous atmosphere by evaporating rain droplets.

PubMed

Elperin, Tov; Fominykh, Andrew; Krasovitov, Boris

2015-05-01

We analyze effects of inhomogeneous concentration and temperature distributions in the atmosphere, rain droplet evaporation and radioactive decay of soluble gases on the rate of trace gas scavenging by rain. We employ a one-dimensional model of precipitation scavenging of radioactive soluble gaseous pollutants that is valid for small gradients and non-uniform initial altitudinal distributions of temperature and concentration in the atmosphere. We assume that conditions of equilibrium evaporation of rain droplets are fulfilled. It is demonstrated that transient altitudinal distribution of concentration under the influence of rain is determined by the linear wave equation that describes propagation of a scavenging wave front. The obtained equation is solved by the method of characteristics. Scavenging coefficients are calculated for wet removal of gaseous iodine-131 and tritiated water vapor (HTO) for the exponential initial distribution of trace gases concentration in the atmosphere and linear temperature distribution. Theoretical predictions of the dependence of the magnitude of the scavenging coefficient on rain intensity for tritiated water vapor are in good agreement with the available atmospheric measurements. Copyright © 2015 Elsevier Ltd. All rights reserved.

Nonperturbative Contributions to a Resummed Leptonic Angular Distribution in Inclusive Z/γ* Boson Production

NASA Astrophysics Data System (ADS)

Guzzi, Marco; Nadolsky, Pavel M.

We summarize a new analysis of the distribution φ η * of charged leptons produced in decays of Z and γ* bosons in the Collins-Soper-Sterman (CSS) formalism for transverse momentum resummation. By comparing the φ η * distribution measured at the Tevatron with the resummed CSS cross section with approximate {O}(α s2) Wilson coefficients, we constrain the magnitude of the nonperturbative Gaussian smearing factor and analyze its uncertainty caused by variations in scale parameters. We find excellent agreement between the φ η * data and our theoretical prediction, provided by the RESBOS resummation program. The nonperturbative factor that we obtained can be used to update resummed QCD predictions for precision measurements in inclusive W and Z production and for comparisons to various models of nonperturbative dynamics.

Nonlinear-drifted Brownian motion with multiple hidden states for remaining useful life prediction of rechargeable batteries

NASA Astrophysics Data System (ADS)

Wang, Dong; Zhao, Yang; Yang, Fangfang; Tsui, Kwok-Leung

2017-09-01

Brownian motion with adaptive drift has attracted much attention in prognostics because its first hitting time is highly relevant to remaining useful life prediction and it follows the inverse Gaussian distribution. Besides linear degradation modeling, nonlinear-drifted Brownian motion has been developed to model nonlinear degradation. Moreover, the first hitting time distribution of the nonlinear-drifted Brownian motion has been approximated by time-space transformation. In the previous studies, the drift coefficient is the only hidden state used in state space modeling of the nonlinear-drifted Brownian motion. Besides the drift coefficient, parameters of a nonlinear function used in the nonlinear-drifted Brownian motion should be treated as additional hidden states of state space modeling to make the nonlinear-drifted Brownian motion more flexible. In this paper, a prognostic method based on nonlinear-drifted Brownian motion with multiple hidden states is proposed and then it is applied to predict remaining useful life of rechargeable batteries. 26 sets of rechargeable battery degradation samples are analyzed to validate the effectiveness of the proposed prognostic method. Moreover, some comparisons with a standard particle filter based prognostic method, a spherical cubature particle filter based prognostic method and two classic Bayesian prognostic methods are conducted to highlight the superiority of the proposed prognostic method. Results show that the proposed prognostic method has lower average prediction errors than the particle filter based prognostic methods and the classic Bayesian prognostic methods for battery remaining useful life prediction.

Development of bovine serum albumin-water partition coefficients predictive models for ionogenic organic chemicals based on chemical form adjusted descriptors.

PubMed

Ding, Feng; Yang, Xianhai; Chen, Guosong; Liu, Jining; Shi, Lili; Chen, Jingwen

2017-10-01

The partition coefficients between bovine serum albumin (BSA) and water (K BSA/w ) for ionogenic organic chemicals (IOCs) were different greatly from those of neutral organic chemicals (NOCs). For NOCs, several excellent models were developed to predict their logK BSA/w . However, it was found that the conventional descriptors are inappropriate for modeling logK BSA/w of IOCs. Thus, alternative approaches are urgently needed to develop predictive models for K BSA/w of IOCs. In this study, molecular descriptors that can be used to characterize the ionization effects (e.g. chemical form adjusted descriptors) were calculated and used to develop predictive models for logK BSA/w of IOCs. The models developed had high goodness-of-fit, robustness, and predictive ability. The predictor variables selected to construct the models included the chemical form adjusted averages of the negative potentials on the molecular surface (V s-adj - ), the chemical form adjusted molecular dipole moment (dipolemoment adj ), the logarithm of the n-octanol/water distribution coefficient (logD). As these molecular descriptors can be calculated from their molecular structures directly, the developed model can be easily used to fill the logK BSA/w data gap for other IOCs within the applicability domain. Furthermore, the chemical form adjusted descriptors calculated in this study also could be used to construct predictive models on other endpoints of IOCs. Copyright © 2017 Elsevier Inc. All rights reserved.

A hybrid approach to advancing quantitative prediction of tissue distribution of basic drugs in human

DOE Office of Scientific and Technical Information (OSTI.GOV)

Poulin, Patrick, E-mail: patrick-poulin@videotron.ca; Ekins, Sean; Department of Pharmaceutical Sciences, School of Pharmacy, University of Maryland, 20 Penn Street, Baltimore, MD 21201

A general toxicity of basic drugs is related to phospholipidosis in tissues. Therefore, it is essential to predict the tissue distribution of basic drugs to facilitate an initial estimate of that toxicity. The objective of the present study was to further assess the original prediction method that consisted of using the binding to red blood cells measured in vitro for the unbound drug (RBCu) as a surrogate for tissue distribution, by correlating it to unbound tissue:plasma partition coefficients (Kpu) of several tissues, and finally to predict volume of distribution at steady-state (V{sub ss}) in humans under in vivo conditions. Thismore » correlation method demonstrated inaccurate predictions of V{sub ss} for particular basic drugs that did not follow the original correlation principle. Therefore, the novelty of this study is to provide clarity on the actual hypotheses to identify i) the impact of pharmacological mode of action on the generic correlation of RBCu-Kpu, ii) additional mechanisms of tissue distribution for the outlier drugs, iii) molecular features and properties that differentiate compounds as outliers in the original correlation analysis in order to facilitate its applicability domain alongside the properties already used so far, and finally iv) to present a novel and refined correlation method that is superior to what has been previously published for the prediction of human V{sub ss} of basic drugs. Applying a refined correlation method after identifying outliers would facilitate the prediction of more accurate distribution parameters as key inputs used in physiologically based pharmacokinetic (PBPK) and phospholipidosis models.« less

Longitudinal distribution of ozone and chlorine in the human respiratory tract: simulation of nasal and oral breathing with the single-path diffusion model.

PubMed

Bush, M L; Zhang, W; Ben-Jebria, A; Ultman, J S

2001-06-15

In the single-path model of the respiratory system, gas transport occurs within a conduit of progressively increasing cross-sectional and surface areas by a combination of flow, longitudinal dispersion, and lateral absorption. The purpose of this study was to use bolus inhalation data previously obtained for chlorine (Cl(2)) and for ozone (O(3)) to test the predictive capability of the single-path model and to adjust input parameters for applying the model to other exposure conditions. The data, consisting of uptake fraction as a function of bolus penetration volume, were recorded on 10 healthy nonsmokers breathing orally as well as nasally at alternative air flows of 150, 250, and 1000 ml/s. By employing published data for airway anatomy, gas-phase dispersion coefficients, and gas-phase mass transfer coefficients while neglecting diffusion limitations in the mucus phase, the single-path model was capable of predicting the uptake distribution for O(3) but not the steeper distribution that was observed for Cl(2). To simultaneously explain the data for these two gases, it was necessary to increase gas-phase mass transfer coefficients and to include a finite diffusion resistance of O(3) within the mucous layer. The O(3) reaction rate constants that accounted for this diffusion resistance, 2 x 10(6) s(-1) in the mouth and 8 x 10(6) s(-1) in the nose and lower airways, were much greater than previously reported reactivities of individual substrates found in mucus. Copyright 2001 Academic Press.

Analysis of a High-Lift Multi-Element Airfoil using a Navier-Stokes Code

NASA Technical Reports Server (NTRS)

Whitlock, Mark E.

1995-01-01

A thin-layer Navier-Stokes code, CFL3D, was utilized to compute the flow over a high-lift multi-element airfoil. This study was conducted to improve the prediction of high-lift flowfields using various turbulence models and improved glidding techniques. An overset Chimera grid system is used to model the three element airfoil geometry. The effects of wind tunnel wall modeling, changes to the grid density and distribution, and embedded grids are discussed. Computed pressure and lift coefficients using Spalart-Allmaras, Baldwin-Barth, and Menter's kappa-omega - Shear Stress Transport (SST) turbulence models are compared with experimental data. The ability of CFL3D to predict the effects on lift coefficient due to changes in Reynolds number changes is also discussed.

Analytical prediction of sub-surface thermal history in translucent tissue phantoms during plasmonic photo-thermotherapy (PPTT).

PubMed

Dhar, Purbarun; Paul, Anup; Narasimhan, Arunn; Das, Sarit K

2016-12-01

Knowledge of thermal history and/or distribution in biological tissues during laser based hyperthermia is essential to achieve necrosis of tumour/carcinoma cells. A semi-analytical model to predict sub-surface thermal distribution in translucent, soft, tissue mimics has been proposed. The model can accurately predict the spatio-temporal temperature variations along depth and the anomalous thermal behaviour in such media, viz. occurrence of sub-surface temperature peaks. Based on optical and thermal properties, the augmented temperature and shift of the peak positions in case of gold nanostructure mediated tissue phantom hyperthermia can be predicted. Employing inverse approach, the absorption coefficient of nano-graphene infused tissue mimics is determined from the peak temperature and found to provide appreciably accurate predictions along depth. Furthermore, a simplistic, dimensionally consistent correlation to theoretically determine the position of the peak in such media is proposed and found to be consistent with experiments and computations. The model shows promise in predicting thermal distribution induced by lasers in tissues and deduction of therapeutic hyperthermia parameters, thereby assisting clinical procedures by providing a priori estimates. Copyright © 2016 Elsevier Ltd. All rights reserved.

Sources of Bias in the Goodman-Kruskal Gamma Coefficient Measure of Association: Implications for Studies of Metacognitive Processes

ERIC Educational Resources Information Center

Masson, Michael E. J.; Rotello, Caren M.

2009-01-01

In many cognitive, metacognitive, and perceptual tasks, measurement of performance or prediction accuracy may be influenced by response bias. Signal detection theory provides a means of assessing discrimination accuracy independent of such bias, but its application crucially depends on distributional assumptions. The Goodman-Kruskal gamma…

Measured pressure distributions, aerodynamic coefficients and shock shapes on blunt bodies at incidence in hypersonic air and CF4

NASA Technical Reports Server (NTRS)

Miller, C. G., III

1982-01-01

Pressure distributions, aerodynamic coefficients, and shock shapes were measured on blunt bodies of revolution in Mach 6 CF4 and in Mach 6 and Mach 10 air. The angle of attack was varied from 0 deg to 20 deg in 4 deg increments. Configurations tested were a hyperboloid with an asymptotic angle of 45 deg, a sonic-corner paraboloid, a paraboloid with an angle of 27.6 deg at the base, a Viking aeroshell generated in a generalized orthogonal coordinate system, and a family of cones having a 45 deg half-angle with spherical, flattened, concave, and cusp nose shapes. Real-gas effects were simulated for the hperboloid and paraboloid models at Mach 6 by testing at a normal-shock density ratio of 5.3 in air and 12 CF4. Predictions from simple theories and numerical flow field programs are compared with measurement. It is anticipated that the data presented in this report will be useful for verification of analytical methods for predicting hypersonic flow fields about blunt bodies at incidence.

Measurement of the angular coefficients in Z-boson events using electron and muon pairs from data taken at √{s}=8 TeV with the ATLAS detector

NASA Astrophysics Data System (ADS)

Aad, G.; Abbott, B.; Abdallah, J.; Abdinov, O.; Abeloos, B.; Aben, R.; AbouZeid, O. S.; Abraham, N. L.; Abramowicz, H.; Abreu, H.; Abreu, R.; Abulaiti, Y.; Acharya, B. S.; Adamczyk, L.; Adams, D. L.; Adelman, J.; Adomeit, S.; Adye, T.; Affolder, A. A.; Agatonovic-Jovin, T.; Agricola, J.; Aguilar-Saavedra, J. A.; Ahlen, S. P.; Ahmadov, F.; Aielli, G.; Akerstedt, H.; Åkesson, T. P. A.; Akimov, A. V.; Alberghi, G. L.; Albert, J.; Albrand, S.; Alconada Verzini, M. J.; Aleksa, M.; Aleksandrov, I. N.; Alexa, C.; Alexander, G.; Alexopoulos, T.; Alhroob, M.; Aliev, M.; Alimonti, G.; Alison, J.; Alkire, S. P.; Allbrooke, B. M. M.; Allen, B. W.; Allport, P. P.; Aloisio, A.; Alonso, A.; Alonso, F.; Alpigiani, C.; Alstaty, M.; Alvarez Gonzalez, B.; Álvarez Piqueras, D.; Alviggi, M. G.; Amadio, B. T.; Amako, K.; Amaral Coutinho, Y.; Amelung, C.; Amidei, D.; Amor Dos Santos, S. P.; Amorim, A.; Amoroso, S.; Amundsen, G.; Anastopoulos, C.; Ancu, L. S.; Andari, N.; Andeen, T.; Anders, C. F.; Anders, G.; Anders, J. K.; Anderson, K. J.; Andreazza, A.; Andrei, V.; Angelidakis, S.; Angelozzi, I.; Anger, P.; Angerami, A.; Anghinolfi, F.; Anisenkov, A. V.; Anjos, N.; Annovi, A.; Antonelli, M.; Antonov, A.; Antos, J.; Anulli, F.; Aoki, M.; Aperio Bella, L.; Arabidze, G.; Arai, Y.; Araque, J. P.; Arce, A. T. H.; Arduh, F. A.; Arguin, J.-F.; Argyropoulos, S.; Arik, M.; Armbruster, A. J.; Armitage, L. J.; Arnaez, O.; Arnold, H.; Arratia, M.; Arslan, O.; Artamonov, A.; Artoni, G.; Artz, S.; Asai, S.; Asbah, N.; Ashkenazi, A.; Åsman, B.; Asquith, L.; Assamagan, K.; Astalos, R.; Atkinson, M.; Atlay, N. B.; Augsten, K.; Avolio, G.; Axen, B.; Ayoub, M. K.; Azuelos, G.; Baak, M. A.; Baas, A. E.; Baca, M. J.; Bachacou, H.; Bachas, K.; Backes, M.; Backhaus, M.; Bagiacchi, P.; Bagnaia, P.; Bai, Y.; Baines, J. T.; Baker, O. K.; Baldin, E. M.; Balek, P.; Balestri, T.; Balli, F.; Balunas, W. K.; Banas, E.; Banerjee, Sw.; Bannoura, A. A. E.; Barak, L.; Barberio, E. L.; Barberis, D.; Barbero, M.; Barillari, T.; Barklow, T.; Barlow, N.; Barnes, S. L.; Barnett, B. M.; Barnett, R. M.; Barnovska, Z.; Baroncelli, A.; Barone, G.; Barr, A. J.; Barranco Navarro, L.; Barreiro, F.; Barreiro Guimarães da Costa, J.; Bartoldus, R.; Barton, A. E.; Bartos, P.; Basalaev, A.; Bassalat, A.; Bates, R. L.; Batista, S. J.; Batley, J. R.; Battaglia, M.; Bauce, M.; Bauer, F.; Bawa, H. S.; Beacham, J. B.; Beattie, M. D.; Beau, T.; Beauchemin, P. H.; Bechtle, P.; Beck, H. P.; Becker, K.; Becker, M.; Beckingham, M.; Becot, C.; Beddall, A. J.; Beddall, A.; Bednyakov, V. A.; Bedognetti, M.; Bee, C. P.; Beemster, L. J.; Beermann, T. A.; Begel, M.; Behr, J. K.; Belanger-Champagne, C.; Bell, A. S.; Bella, G.; Bellagamba, L.; Bellerive, A.; Bellomo, M.; Belotskiy, K.; Beltramello, O.; Belyaev, N. L.; Benary, O.; Benchekroun, D.; Bender, M.; Bendtz, K.; Benekos, N.; Benhammou, Y.; Benhar Noccioli, E.; Benitez, J.; Benjamin, D. P.; Bensinger, J. R.; Bentvelsen, S.; Beresford, L.; Beretta, M.; Berge, D.; Bergeaas Kuutmann, E.; Berger, N.; Beringer, J.; Berlendis, S.; Bernard, N. R.; Bernius, C.; Bernlochner, F. U.; Berry, T.; Berta, P.; Bertella, C.; Bertoli, G.; Bertolucci, F.; Bertram, I. A.; Bertsche, C.; Bertsche, D.; Besjes, G. J.; Bessidskaia Bylund, O.; Bessner, M.; Besson, N.; Betancourt, C.; Bethke, S.; Bevan, A. J.; Bhimji, W.; Bianchi, R. M.; Bianchini, L.; Bianco, M.; Biebel, O.; Biedermann, D.; Bielski, R.; Biesuz, N. V.; Biglietti, M.; Bilbao De Mendizabal, J.; Bilokon, H.; Bindi, M.; Binet, S.; Bingul, A.; Bini, C.; Biondi, S.; Bjergaard, D. M.; Black, C. W.; Black, J. E.; Black, K. M.; Blackburn, D.; Blair, R. E.; Blanchard, J.-B.; Blanco, J. E.; Blazek, T.; Bloch, I.; Blocker, C.; Blum, W.; Blumenschein, U.; Blunier, S.; Bobbink, G. J.; Bobrovnikov, V. S.; Bocchetta, S. S.; Bocci, A.; Bock, C.; Boehler, M.; Boerner, D.; Bogaerts, J. A.; Bogavac, D.; Bogdanchikov, A. G.; Bohm, C.; Boisvert, V.; Bokan, P.; Bold, T.; Boldyrev, A. S.; Bomben, M.; Bona, M.; Boonekamp, M.; Borisov, A.; Borissov, G.; Bortfeldt, J.; Bortoletto, D.; Bortolotto, V.; Bos, K.; Boscherini, D.; Bosman, M.; Bossio Sola, J. D.; Boudreau, J.; Bouffard, J.; Bouhova-Thacker, E. V.; Boumediene, D.; Bourdarios, C.; Boutle, S. K.; Boveia, A.; Boyd, J.; Boyko, I. R.; Bracinik, J.; Brandt, A.; Brandt, G.; Brandt, O.; Bratzler, U.; Brau, B.; Brau, J. E.; Braun, H. M.; Breaden Madden, W. D.; Brendlinger, K.; Brennan, A. J.; Brenner, L.; Brenner, R.; Bressler, S.; Bristow, T. M.; Britton, D.; Britzger, D.; Brochu, F. M.; Brock, I.; Brock, R.; Brooijmans, G.; Brooks, T.; Brooks, W. K.; Brosamer, J.; Brost, E.; Broughton, J. H.; Bruckman de Renstrom, P. A.; Bruncko, D.; Bruneliere, R.; Bruni, A.; Bruni, G.; Brunt, BH; Bruschi, M.; Bruscino, N.; Bryant, P.; Bryngemark, L.; Buanes, T.; Buat, Q.; Buchholz, P.; Buckley, A. G.; Budagov, I. A.; Buehrer, F.; Bugge, M. K.; Bulekov, O.; Bullock, D.; Burckhart, H.; Burdin, S.; Burgard, C. D.; Burghgrave, B.; Burka, K.; Burke, S.; Burmeister, I.; Busato, E.; Büscher, D.; Büscher, V.; Bussey, P.; Butler, J. M.; Buttar, C. M.; Butterworth, J. M.; Butti, P.; Buttinger, W.; Buzatu, A.; Buzykaev, A. R.; Cabrera Urbán, S.; Caforio, D.; Cairo, V. M.; Cakir, O.; Calace, N.; Calafiura, P.; Calandri, A.; Calderini, G.; Calfayan, P.; Caloba, L. P.; Calvet, D.; Calvet, S.; Calvet, T. P.; Camacho Toro, R.; Camarda, S.; Camarri, P.; Cameron, D.; Caminal Armadans, R.; Camincher, C.; Campana, S.; Campanelli, M.; Camplani, A.; Campoverde, A.; Canale, V.; Canepa, A.; Cano Bret, M.; Cantero, J.; Cantrill, R.; Cao, T.; Capeans Garrido, M. D. M.; Caprini, I.; Caprini, M.; Capua, M.; Caputo, R.; Carbone, R. M.; Cardarelli, R.; Cardillo, F.; Carli, I.; Carli, T.; Carlino, G.; Carminati, L.; Caron, S.; Carquin, E.; Carrillo-Montoya, G. D.; Carter, J. R.; Carvalho, J.; Casadei, D.; Casado, M. P.; Casolino, M.; Casper, D. W.; Castaneda-Miranda, E.; Castelijn, R.; Castelli, A.; Castillo Gimenez, V.; Castro, N. F.; Catinaccio, A.; Catmore, J. R.; Cattai, A.; Caudron, J.; Cavaliere, V.; Cavallaro, E.; Cavalli, D.; Cavalli-Sforza, M.; Cavasinni, V.; Ceradini, F.; Cerda Alberich, L.; Cerio, B. C.; Cerqueira, A. S.; Cerri, A.; Cerrito, L.; Cerutti, F.; Cerv, M.; Cervelli, A.; Cetin, S. A.; Chafaq, A.; Chakraborty, D.; Chan, S. K.; Chan, Y. L.; Chang, P.; Chapman, J. D.; Charlton, D. G.; Chatterjee, A.; Chau, C. C.; Chavez Barajas, C. A.; Che, S.; Cheatham, S.; Chegwidden, A.; Chekanov, S.; Chekulaev, S. V.; Chelkov, G. A.; Chelstowska, M. A.; Chen, C.; Chen, H.; Chen, K.; Chen, S.; Chen, S.; Chen, X.; Chen, Y.; Cheng, H. C.; Cheng, H. J.; Cheng, Y.; Cheplakov, A.; Cheremushkina, E.; Cherkaoui El Moursli, R.; Chernyatin, V.; Cheu, E.; Chevalier, L.; Chiarella, V.; Chiarelli, G.; Chiodini, G.; Chisholm, A. S.; Chitan, A.; Chizhov, M. V.; Choi, K.; Chomont, A. R.; Chouridou, S.; Chow, B. K. B.; Christodoulou, V.; Chromek-Burckhart, D.; Chudoba, J.; Chuinard, A. J.; Chwastowski, J. J.; Chytka, L.; Ciapetti, G.; Ciftci, A. K.; Cinca, D.; Cindro, V.; Cioara, I. A.; Ciocio, A.; Cirotto, F.; Citron, Z. H.; Citterio, M.; Ciubancan, M.; Clark, A.; Clark, B. L.; Clark, M. R.; Clark, P. J.; Clarke, R. N.; Clement, C.; Coadou, Y.; Cobal, M.; Coccaro, A.; Cochran, J.; Coffey, L.; Colasurdo, L.; Cole, B.; Colijn, A. P.; Collot, J.; Colombo, T.; Compostella, G.; Conde Muiño, P.; Coniavitis, E.; Connell, S. H.; Connelly, I. A.; Consorti, V.; Constantinescu, S.; Conti, G.; Conventi, F.; Cooke, M.; Cooper, B. D.; Cooper-Sarkar, A. M.; Cormier, K. J. R.; Cornelissen, T.; Corradi, M.; Corriveau, F.; Corso-Radu, A.; Cortes-Gonzalez, A.; Cortiana, G.; Costa, G.; Costa, M. J.; Costanzo, D.; Cottin, G.; Cowan, G.; Cox, B. E.; Cranmer, K.; Crawley, S. J.; Cree, G.; Crépé-Renaudin, S.; Crescioli, F.; Cribbs, W. A.; Crispin Ortuzar, M.; Cristinziani, M.; Croft, V.; Crosetti, G.; Cuhadar Donszelmann, T.; Cummings, J.; Curatolo, M.; Cúth, J.; Cuthbert, C.; Czirr, H.; Czodrowski, P.; D'amen, G.; D'Auria, S.; D'Onofrio, M.; Da Cunha Sargedas De Sousa, M. J.; Da Via, C.; Dabrowski, W.; Dado, T.; Dai, T.; Dale, O.; Dallaire, F.; Dallapiccola, C.; Dam, M.; Dandoy, J. R.; Dang, N. P.; Daniells, A. C.; Dann, N. S.; Danninger, M.; Dano Hoffmann, M.; Dao, V.; Darbo, G.; Darmora, S.; Dassoulas, J.; Dattagupta, A.; Davey, W.; David, C.; Davidek, T.; Davies, M.; Davison, P.; Dawe, E.; Dawson, I.; Daya-Ishmukhametova, R. K.; De, K.; de Asmundis, R.; De Benedetti, A.; De Castro, S.; De Cecco, S.; De Groot, N.; de Jong, P.; De la Torre, H.; De Lorenzi, F.; De Maria, A.; De Pedis, D.; De Salvo, A.; De Sanctis, U.; De Santo, A.; De Vivie De Regie, J. B.; Dearnaley, W. J.; Debbe, R.; Debenedetti, C.; Dedovich, D. V.; Dehghanian, N.; Deigaard, I.; Del Gaudio, M.; Del Peso, J.; Del Prete, T.; Delgove, D.; Deliot, F.; Delitzsch, C. M.; Deliyergiyev, M.; Dell'Acqua, A.; Dell'Asta, L.; Dell'Orso, M.; Della Pietra, M.; della Volpe, D.; Delmastro, M.; Delsart, P. A.; Deluca, C.; DeMarco, D. A.; Demers, S.; Demichev, M.; Demilly, A.; Denisov, S. P.; Denysiuk, D.; Derendarz, D.; Derkaoui, J. E.; Derue, F.; Dervan, P.; Desch, K.; Deterre, C.; Dette, K.; Deviveiros, P. O.; Dewhurst, A.; Dhaliwal, S.; Di Ciaccio, A.; Di Ciaccio, L.; Di Clemente, W. K.; Di Donato, C.; Di Girolamo, A.; Di Girolamo, B.; Di Micco, B.; Di Nardo, R.; Di Simone, A.; Di Sipio, R.; Di Valentino, D.; Diaconu, C.; Diamond, M.; Dias, F. A.; Diaz, M. A.; Diehl, E. B.; Dietrich, J.; Diglio, S.; Dimitrievska, A.; Dingfelder, J.; Dita, P.; Dita, S.; Dittus, F.; Djama, F.; Djobava, T.; Djuvsland, J. I.; do Vale, M. A. B.; Dobos, D.; Dobre, M.; Doglioni, C.; Dohmae, T.; Dolejsi, J.; Dolezal, Z.; Dolgoshein, B. A.; Donadelli, M.; Donati, S.; Dondero, P.; Donini, J.; Dopke, J.; Doria, A.; Dova, M. T.; Doyle, A. T.; Drechsler, E.; Dris, M.; Du, Y.; Duarte-Campderros, J.; Duchovni, E.; Duckeck, G.; Ducu, O. A.; Duda, D.; Dudarev, A.; Duflot, L.; Duguid, L.; Dührssen, M.; Dumancic, M.; Dunford, M.; Duran Yildiz, H.; Düren, M.; Durglishvili, A.; Duschinger, D.; Dutta, B.; Dyndal, M.; Eckardt, C.; Ecker, K. M.; Edgar, R. C.; Edwards, N. C.; Eifert, T.; Eigen, G.; Einsweiler, K.; Ekelof, T.; El Kacimi, M.; Ellajosyula, V.; Ellert, M.; Elles, S.; Ellinghaus, F.; Elliot, A. A.; Ellis, N.; Elmsheuser, J.; Elsing, M.; Emeliyanov, D.; Enari, Y.; Endner, O. C.; Endo, M.; Ennis, J. S.; Erdmann, J.; Ereditato, A.; Ernis, G.; Ernst, J.; Ernst, M.; Errede, S.; Ertel, E.; Escalier, M.; Esch, H.; Escobar, C.; Esposito, B.; Etienvre, A. I.; Etzion, E.; Evans, H.; Ezhilov, A.; Fabbri, F.; Fabbri, L.; Facini, G.; Fakhrutdinov, R. M.; Falciano, S.; Falla, R. J.; Faltova, J.; Fang, Y.; Fanti, M.; Farbin, A.; Farilla, A.; Farina, C.; Farooque, T.; Farrell, S.; Farrington, S. M.; Farthouat, P.; Fassi, F.; Fassnacht, P.; Fassouliotis, D.; Faucci Giannelli, M.; Favareto, A.; Fawcett, W. J.; Fayard, L.; Fedin, O. L.; Fedorko, W.; Feigl, S.; Feligioni, L.; Feng, C.; Feng, E. J.; Feng, H.; Fenyuk, A. B.; Feremenga, L.; Fernandez Martinez, P.; Fernandez Perez, S.; Ferrando, J.; Ferrari, A.; Ferrari, P.; Ferrari, R.; Ferreira de Lima, D. E.; Ferrer, A.; Ferrere, D.; Ferretti, C.; Ferretto Parodi, A.; Fiedler, F.; Filipčič, A.; Filipuzzi, M.; Filthaut, F.; Fincke-Keeler, M.; Finelli, K. D.; Fiolhais, M. C. N.; Fiorini, L.; Firan, A.; Fischer, A.; Fischer, C.; Fischer, J.; Fisher, W. C.; Flaschel, N.; Fleck, I.; Fleischmann, P.; Fletcher, G. T.; Fletcher, R. R. M.; Flick, T.; Floderus, A.; Flores Castillo, L. R.; Flowerdew, M. J.; Forcolin, G. T.; Formica, A.; Forti, A.; Foster, A. G.; Fournier, D.; Fox, H.; Fracchia, S.; Francavilla, P.; Franchini, M.; Francis, D.; Franconi, L.; Franklin, M.; Frate, M.; Fraternali, M.; Freeborn, D.; Fressard-Batraneanu, S. M.; Friedrich, F.; Froidevaux, D.; Frost, J. A.; Fukunaga, C.; Fullana Torregrosa, E.; Fusayasu, T.; Fuster, J.; Gabaldon, C.; Gabizon, O.; Gabrielli, A.; Gabrielli, A.; Gach, G. P.; Gadatsch, S.; Gadomski, S.; Gagliardi, G.; Gagnon, L. G.; Gagnon, P.; Galea, C.; Galhardo, B.; Gallas, E. J.; Gallop, B. J.; Gallus, P.; Galster, G.; Gan, K. K.; Gao, J.; Gao, Y.; Gao, Y. S.; Garay Walls, F. M.; García, C.; García Navarro, J. E.; Garcia-Sciveres, M.; Gardner, R. W.; Garelli, N.; Garonne, V.; Gascon Bravo, A.; Gatti, C.; Gaudiello, A.; Gaudio, G.; Gaur, B.; Gauthier, L.; Gavrilenko, I. L.; Gay, C.; Gaycken, G.; Gazis, E. N.; Gecse, Z.; Gee, C. N. P.; Geich-Gimbel, Ch.; Geisler, M. P.; Gemme, C.; Genest, M. H.; Geng, C.; Gentile, S.; George, S.; Gerbaudo, D.; Gershon, A.; Ghasemi, S.; Ghazlane, H.; Ghneimat, M.; Giacobbe, B.; Giagu, S.; Giannetti, P.; Gibbard, B.; Gibson, S. M.; Gignac, M.; Gilchriese, M.; Gillam, T. P. S.; Gillberg, D.; Gilles, G.; Gingrich, D. M.; Giokaris, N.; Giordani, M. P.; Giorgi, F. M.; Giorgi, F. M.; Giraud, P. F.; Giromini, P.; Giugni, D.; Giuli, F.; Giuliani, C.; Giulini, M.; Gjelsten, B. K.; Gkaitatzis, S.; Gkialas, I.; Gkougkousis, E. L.; Gladilin, L. K.; Glasman, C.; Glatzer, J.; Glaysher, P. C. F.; Glazov, A.; Goblirsch-Kolb, M.; Godlewski, J.; Goldfarb, S.; Golling, T.; Golubkov, D.; Gomes, A.; Gonçalo, R.; Goncalves Pinto Firmino Da Costa, J.; Gonella, L.; Gongadze, A.; González de la Hoz, S.; Gonzalez Parra, G.; Gonzalez-Sevilla, S.; Goossens, L.; Gorbounov, P. A.; Gordon, H. A.; Gorelov, I.; Gorini, B.; Gorini, E.; Gorišek, A.; Gornicki, E.; Goshaw, A. T.; Gössling, C.; Gostkin, M. I.; Goudet, C. R.; Goujdami, D.; Goussiou, A. G.; Govender, N.; Gozani, E.; Graber, L.; Grabowska-Bold, I.; Gradin, P. O. J.; Grafström, P.; Gramling, J.; Gramstad, E.; Grancagnolo, S.; Gratchev, V.; Gray, H. M.; Graziani, E.; Greenwood, Z. D.; Grefe, C.; Gregersen, K.; Gregor, I. M.; Grenier, P.; Grevtsov, K.; Griffiths, J.; Grillo, A. A.; Grimm, K.; Grinstein, S.; Gris, Ph.; Grivaz, J.-F.; Groh, S.; Grohs, J. P.; Gross, E.; Grosse-Knetter, J.; Grossi, G. C.; Grout, Z. J.; Guan, L.; Guan, W.; Guenther, J.; Guescini, F.; Guest, D.; Gueta, O.; Guido, E.; Guillemin, T.; Guindon, S.; Gul, U.; Gumpert, C.; Guo, J.; Guo, Y.; Gupta, S.; Gustavino, G.; Gutierrez, P.; Gutierrez Ortiz, N. G.; Gutschow, C.; Guyot, C.; Gwenlan, C.; Gwilliam, C. B.; Haas, A.; Haber, C.; Hadavand, H. K.; Haddad, N.; Hadef, A.; Haefner, P.; Hageböck, S.; Hajduk, Z.; Hakobyan, H.; Haleem, M.; Haley, J.; Halladjian, G.; Hallewell, G. D.; Hamacher, K.; Hamal, P.; Hamano, K.; Hamilton, A.; Hamity, G. N.; Hamnett, P. G.; Han, L.; Hanagaki, K.; Hanawa, K.; Hance, M.; Haney, B.; Hanke, P.; Hanna, R.; Hansen, J. B.; Hansen, J. D.; Hansen, M. C.; Hansen, P. H.; Hara, K.; Hard, A. S.; Harenberg, T.; Hariri, F.; Harkusha, S.; Harrington, R. D.; Harrison, P. F.; Hartjes, F.; Hartmann, N. M.; Hasegawa, M.; Hasegawa, Y.; Hasib, A.; Hassani, S.; Haug, S.; Hauser, R.; Hauswald, L.; Havranek, M.; Hawkes, C. M.; Hawkings, R. J.; Hayden, D.; Hays, C. P.; Hays, J. M.; Hayward, H. S.; Haywood, S. J.; Head, S. J.; Heck, T.; Hedberg, V.; Heelan, L.; Heim, S.; Heim, T.; Heinemann, B.; Heinrich, J. J.; Heinrich, L.; Heinz, C.; Hejbal, J.; Helary, L.; Hellman, S.; Helsens, C.; Henderson, J.; Henderson, R. C. W.; Heng, Y.; Henkelmann, S.; Henriques Correia, A. M.; Henrot-Versille, S.; Herbert, G. H.; Hernández Jiménez, Y.; Herten, G.; Hertenberger, R.; Hervas, L.; Hesketh, G. G.; Hessey, N. P.; Hetherly, J. W.; Hickling, R.; Higón-Rodriguez, E.; Hill, E.; Hill, J. C.; Hiller, K. H.; Hillier, S. J.; Hinchliffe, I.; Hines, E.; Hinman, R. R.; Hirose, M.; Hirschbuehl, D.; Hobbs, J.; Hod, N.; Hodgkinson, M. C.; Hodgson, P.; Hoecker, A.; Hoeferkamp, M. R.; Hoenig, F.; Hohlfeld, M.; Hohn, D.; Holmes, T. R.; Homann, M.; Hong, T. M.; Hooberman, B. H.; Hopkins, W. H.; Horii, Y.; Horton, A. J.; Hostachy, J.-Y.; Hou, S.; Hoummada, A.; Howarth, J.; Hrabovsky, M.; Hristova, I.; Hrivnac, J.; Hryn'ova, T.; Hrynevich, A.; Hsu, C.; Hsu, P. J.; Hsu, S.-C.; Hu, D.; Hu, Q.; Huang, Y.; Hubacek, Z.; Hubaut, F.; Huegging, F.; Huffman, T. B.; Hughes, E. W.; Hughes, G.; Huhtinen, M.; Hülsing, T. A.; Huo, P.; Huseynov, N.; Huston, J.; Huth, J.; Iacobucci, G.; Iakovidis, G.; Ibragimov, I.; Iconomidou-Fayard, L.; Ideal, E.; Idrissi, Z.; Iengo, P.; Igonkina, O.; Iizawa, T.; Ikegami, Y.; Ikeno, M.; Ilchenko, Y.; Iliadis, D.; Ilic, N.; Ince, T.; Introzzi, G.; Ioannou, P.; Iodice, M.; Iordanidou, K.; Ippolito, V.; Ishino, M.; Ishitsuka, M.; Ishmukhametov, R.; Issever, C.; Istin, S.; Ito, F.; Iturbe Ponce, J. M.; Iuppa, R.; Iwanski, W.; Iwasaki, H.; Izen, J. M.; Izzo, V.; Jabbar, S.; Jackson, B.; Jackson, M.; Jackson, P.; Jain, V.; Jakobi, K. B.; Jakobs, K.; Jakobsen, S.; Jakoubek, T.; Jamin, D. O.; Jana, D. K.; Jansen, E.; Jansky, R.; Janssen, J.; Janus, M.; Jarlskog, G.; Javadov, N.; Javůrek, T.; Jeanneau, F.; Jeanty, L.; Jejelava, J.; Jeng, G.-Y.; Jennens, D.; Jenni, P.; Jentzsch, J.; Jeske, C.; Jézéquel, S.; Ji, H.; Jia, J.; Jiang, H.; Jiang, Y.; Jiggins, S.; Jimenez Pena, J.; Jin, S.; Jinaru, A.; Jinnouchi, O.; Johansson, P.; Johns, K. A.; Johnson, W. J.; Jon-And, K.; Jones, G.; Jones, R. W. L.; Jones, S.; Jones, T. J.; Jongmanns, J.; Jorge, P. M.; Jovicevic, J.; Ju, X.; Juste Rozas, A.; Köhler, M. K.; Kaczmarska, A.; Kado, M.; Kagan, H.; Kagan, M.; Kahn, S. J.; Kajomovitz, E.; Kalderon, C. W.; Kaluza, A.; Kama, S.; Kamenshchikov, A.; Kanaya, N.; Kaneti, S.; Kanjir, L.; Kantserov, V. A.; Kanzaki, J.; Kaplan, B.; Kaplan, L. S.; Kapliy, A.; Kar, D.; Karakostas, K.; Karamaoun, A.; Karastathis, N.; Kareem, M. J.; Karentzos, E.; Karnevskiy, M.; Karpov, S. N.; Karpova, Z. M.; Karthik, K.; Kartvelishvili, V.; Karyukhin, A. N.; Kasahara, K.; Kashif, L.; Kass, R. D.; Kastanas, A.; Kataoka, Y.; Kato, C.; Katre, A.; Katzy, J.; Kawagoe, K.; Kawamoto, T.; Kawamura, G.; Kazama, S.; Kazanin, V. F.; Keeler, R.; Kehoe, R.; Keller, J. S.; Kempster, J. J.; Kentaro, K.; Keoshkerian, H.; Kepka, O.; Kerševan, B. P.; Kersten, S.; Keyes, R. A.; Khalil-zada, F.; Khanov, A.; Kharlamov, A. G.; Khoo, T. J.; Khovanskiy, V.; Khramov, E.; Khubua, J.; Kido, S.; Kim, H. Y.; Kim, S. H.; Kim, Y. K.; Kimura, N.; Kind, O. M.; King, B. T.; King, M.; King, S. B.; Kirk, J.; Kiryunin, A. E.; Kishimoto, T.; Kisielewska, D.; Kiss, F.; Kiuchi, K.; Kivernyk, O.; Kladiva, E.; Klein, M. H.; Klein, M.; Klein, U.; Kleinknecht, K.; Klimek, P.; Klimentov, A.; Klingenberg, R.; Klinger, J. A.; Klioutchnikova, T.; Kluge, E.-E.; Kluit, P.; Kluth, S.; Knapik, J.; Kneringer, E.; Knoops, E. B. F. G.; Knue, A.; Kobayashi, A.; Kobayashi, D.; Kobayashi, T.; Kobel, M.; Kocian, M.; Kodys, P.; Koffas, T.; Koffeman, E.; Koi, T.; Kolanoski, H.; Kolb, M.; Koletsou, I.; Komar, A. A.; Komori, Y.; Kondo, T.; Kondrashova, N.; Köneke, K.; König, A. C.; Kono, T.; Konoplich, R.; Konstantinidis, N.; Kopeliansky, R.; Koperny, S.; Köpke, L.; Kopp, A. K.; Korcyl, K.; Kordas, K.; Korn, A.; Korol, A. A.; Korolkov, I.; Korolkova, E. V.; Kortner, O.; Kortner, S.; Kosek, T.; Kostyukhin, V. V.; Kotwal, A.; Kourkoumeli-Charalampidi, A.; Kourkoumelis, C.; Kouskoura, V.; Kowalewska, A. B.; Kowalewski, R.; Kowalski, T. Z.; Kozakai, C.; Kozanecki, W.; Kozhin, A. S.; Kramarenko, V. A.; Kramberger, G.; Krasnopevtsev, D.; Krasny, M. W.; Krasznahorkay, A.; Kraus, J. K.; Kravchenko, A.; Kretz, M.; Kretzschmar, J.; Kreutzfeldt, K.; Krieger, P.; Krizka, K.; Kroeninger, K.; Kroha, H.; Kroll, J.; Kroseberg, J.; Krstic, J.; Kruchonak, U.; Krüger, H.; Krumnack, N.; Kruse, A.; Kruse, M. C.; Kruskal, M.; Kubota, T.; Kucuk, H.; Kuday, S.; Kuechler, J. T.; Kuehn, S.; Kugel, A.; Kuger, F.; Kuhl, A.; Kuhl, T.; Kukhtin, V.; Kukla, R.; Kulchitsky, Y.; Kuleshov, S.; Kuna, M.; Kunigo, T.; Kupco, A.; Kurashige, H.; Kurochkin, Y. A.; Kus, V.; Kuwertz, E. S.; Kuze, M.; Kvita, J.; Kwan, T.; Kyriazopoulos, D.; La Rosa, A.; La Rosa Navarro, J. L.; La Rotonda, L.; Lacasta, C.; Lacava, F.; Lacey, J.; Lacker, H.; Lacour, D.; Lacuesta, V. R.; Ladygin, E.; Lafaye, R.; Laforge, B.; Lagouri, T.; Lai, S.; Lammers, S.; Lampl, W.; Lançon, E.; Landgraf, U.; Landon, M. P. J.; Lang, V. S.; Lange, J. C.; Lankford, A. J.; Lanni, F.; Lantzsch, K.; Lanza, A.; Laplace, S.; Lapoire, C.; Laporte, J. F.; Lari, T.; Lasagni Manghi, F.; Lassnig, M.; Laurelli, P.; Lavrijsen, W.; Law, A. T.; Laycock, P.; Lazovich, T.; Lazzaroni, M.; Le, B.; Le Dortz, O.; Le Guirriec, E.; Le Quilleuc, E. P.; LeBlanc, M.; LeCompte, T.; Ledroit-Guillon, F.; Lee, C. A.; Lee, S. C.; Lee, L.; Lefebvre, G.; Lefebvre, M.; Legger, F.; Leggett, C.; Lehan, A.; Lehmann Miotto, G.; Lei, X.; Leight, W. A.; Leisos, A.; Leister, A. G.; Leite, M. A. L.; Leitner, R.; Lellouch, D.; Lemmer, B.; Leney, K. J. C.; Lenz, T.; Lenzi, B.; Leone, R.; Leone, S.; Leonidopoulos, C.; Leontsinis, S.; Lerner, G.; Leroy, C.; Lesage, A. A. J.; Lester, C. G.; Levchenko, M.; Levêque, J.; Levin, D.; Levinson, L. J.; Levy, M.; Leyko, A. M.; Leyton, M.; Li, B.; Li, H.; Li, H. L.; Li, L.; Li, L.; Li, Q.; Li, S.; Li, X.; Li, Y.; Liang, Z.; Liberti, B.; Liblong, A.; Lichard, P.; Lie, K.; Liebal, J.; Liebig, W.; Limosani, A.; Lin, S. C.; Lin, T. H.; Lindquist, B. E.; Lionti, A. E.; Lipeles, E.; Lipniacka, A.; Lisovyi, M.; Liss, T. M.; Lister, A.; Litke, A. M.; Liu, B.; Liu, D.; Liu, H.; Liu, H.; Liu, J.; Liu, J. B.; Liu, K.; Liu, L.; Liu, M.; Liu, M.; Liu, Y. L.; Liu, Y.; Livan, M.; Lleres, A.; Llorente Merino, J.; Lloyd, S. L.; Lo Sterzo, F.; Lobodzinska, E.; Loch, P.; Lockman, W. S.; Loebinger, F. K.; Loevschall-Jensen, A. E.; Loew, K. M.; Loginov, A.; Lohse, T.; Lohwasser, K.; Lokajicek, M.; Long, B. A.; Long, J. D.; Long, R. E.; Longo, L.; Looper, K. A.; Lopes, L.; Lopez Mateos, D.; Lopez Paredes, B.; Lopez Paz, I.; Lopez Solis, A.; Lorenz, J.; Lorenzo Martinez, N.; Losada, M.; Lösel, P. J.; Lou, X.; Lounis, A.; Love, J.; Love, P. A.; Lu, H.; Lu, N.; Lubatti, H. J.; Luci, C.; Lucotte, A.; Luedtke, C.; Luehring, F.; Lukas, W.; Luminari, L.; Lundberg, O.; Lund-Jensen, B.; Lynn, D.; Lysak, R.; Lytken, E.; Lyubushkin, V.; Ma, H.; Ma, L. L.; Ma, Y.; Maccarrone, G.; Macchiolo, A.; Macdonald, C. M.; Maček, B.; Machado Miguens, J.; Madaffari, D.; Madar, R.; Maddocks, H. J.; Mader, W. F.; Madsen, A.; Maeda, J.; Maeland, S.; Maeno, T.; Maevskiy, A.; Magradze, E.; Mahlstedt, J.; Maiani, C.; Maidantchik, C.; Maier, A. A.; Maier, T.; Maio, A.; Majewski, S.; Makida, Y.; Makovec, N.; Malaescu, B.; Malecki, Pa.; Maleev, V. P.; Malek, F.; Mallik, U.; Malon, D.; Malone, C.; Maltezos, S.; Malyukov, S.; Mamuzic, J.; Mancini, G.; Mandelli, B.; Mandelli, L.; Mandić, I.; Maneira, J.; Manhaes de Andrade Filho, L.; Manjarres Ramos, J.; Mann, A.; Mansoulie, B.; Mansour, J. D.; Mantifel, R.; Mantoani, M.; Manzoni, S.; Mapelli, L.; Marceca, G.; March, L.; Marchiori, G.; Marcisovsky, M.; Marjanovic, M.; Marley, D. E.; Marroquim, F.; Marsden, S. P.; Marshall, Z.; Marti-Garcia, S.; Martin, B.; Martin, T. A.; Martin, V. J.; Martin dit Latour, B.; Martinez, M.; Martin-Haugh, S.; Martoiu, V. S.; Martyniuk, A. C.; Marx, M.; Marzin, A.; Masetti, L.; Mashimo, T.; Mashinistov, R.; Masik, J.; Maslennikov, A. L.; Massa, I.; Massa, L.; Mastrandrea, P.; Mastroberardino, A.; Masubuchi, T.; Mättig, P.; Mattmann, J.; Maurer, J.; Maxfield, S. J.; Maximov, D. A.; Mazini, R.; Mazza, S. M.; Mc Fadden, N. C.; Mc Goldrick, G.; Mc Kee, S. P.; McCarn, A.; McCarthy, R. L.; McCarthy, T. G.; McClymont, L. I.; McDonald, E. F.; McFarlane, K. W.; Mcfayden, J. A.; Mchedlidze, G.; McMahon, S. J.; McPherson, R. A.; Medinnis, M.; Meehan, S.; Mehlhase, S.; Mehta, A.; Meier, K.; Meineck, C.; Meirose, B.; Melini, D.; Mellado Garcia, B. R.; Melo, M.; Meloni, F.; Mengarelli, A.; Menke, S.; Meoni, E.; Mergelmeyer, S.; Mermod, P.; Merola, L.; Meroni, C.; Merritt, F. S.; Messina, A.; Metcalfe, J.; Mete, A. S.; Meyer, C.; Meyer, C.; Meyer, J.-P.; Meyer, J.; Meyer Zu Theenhausen, H.; Miano, F.; Middleton, R. P.; Miglioranzi, S.; Mijović, L.; Mikenberg, G.; Mikestikova, M.; Mikuž, M.; Milesi, M.; Milic, A.; Miller, D. W.; Mills, C.; Milov, A.; Milstead, D. A.; Minaenko, A. A.; Minami, Y.; Minashvili, I. A.; Mincer, A. I.; Mindur, B.; Mineev, M.; Ming, Y.; Mir, L. M.; Mistry, K. P.; Mitani, T.; Mitrevski, J.; Mitsou, V. A.; Miucci, A.; Miyagawa, P. S.; Mjörnmark, J. U.; Moa, T.; Mochizuki, K.; Mohapatra, S.; Molander, S.; Moles-Valls, R.; Monden, R.; Mondragon, M. C.; Mönig, K.; Monk, J.; Monnier, E.; Montalbano, A.; Montejo Berlingen, J.; Monticelli, F.; Monzani, S.; Moore, R. W.; Morange, N.; Moreno, D.; Moreno Llácer, M.; Morettini, P.; Mori, D.; Mori, T.; Morii, M.; Morinaga, M.; Morisbak, V.; Moritz, S.; Morley, A. K.; Mornacchi, G.; Morris, J. D.; Mortensen, S. S.; Morvaj, L.; Mosidze, M.; Moss, J.; Motohashi, K.; Mount, R.; Mountricha, E.; Mouraviev, S. V.; Moyse, E. J. W.; Muanza, S.; Mudd, R. D.; Mueller, F.; Mueller, J.; Mueller, R. S. P.; Mueller, T.; Muenstermann, D.; Mullen, P.; Mullier, G. A.; Munoz Sanchez, F. J.; Murillo Quijada, J. A.; Murray, W. J.; Musheghyan, H.; Muškinja, M.; Myagkov, A. G.; Myska, M.; Nachman, B. P.; Nackenhorst, O.; Nagai, K.; Nagai, R.; Nagano, K.; Nagasaka, Y.; Nagata, K.; Nagel, M.; Nagy, E.; Nairz, A. M.; Nakahama, Y.; Nakamura, K.; Nakamura, T.; Nakano, I.; Namasivayam, H.; Naranjo Garcia, R. F.; Narayan, R.; Narrias Villar, D. I.; Naryshkin, I.; Naumann, T.; Navarro, G.; Nayyar, R.; Neal, H. A.; Nechaeva, P. Yu.; Neep, T. J.; Nef, P. D.; Negri, A.; Negrini, M.; Nektarijevic, S.; Nellist, C.; Nelson, A.; Nemecek, S.; Nemethy, P.; Nepomuceno, A. A.; Nessi, M.; Neubauer, M. S.; Neumann, M.; Neves, R. M.; Nevski, P.; Newman, P. R.; Nguyen, D. H.; Nguyen Manh, T.; Nickerson, R. B.; Nicolaidou, R.; Nielsen, J.; Nikiforov, A.; Nikolaenko, V.; Nikolic-Audit, I.; Nikolopoulos, K.; Nilsen, J. K.; Nilsson, P.; Ninomiya, Y.; Nisati, A.; Nisius, R.; Nobe, T.; Nodulman, L.; Nomachi, M.; Nomidis, I.; Nooney, T.; Norberg, S.; Nordberg, M.; Norjoharuddeen, N.; Novgorodova, O.; Nowak, S.; Nozaki, M.; Nozka, L.; Ntekas, K.; Nurse, E.; Nuti, F.; O'grady, F.; O'Neil, D. C.; O'Rourke, A. A.; O'Shea, V.; Oakham, F. G.; Oberlack, H.; Obermann, T.; Ocariz, J.; Ochi, A.; Ochoa, I.; Ochoa-Ricoux, J. P.; Oda, S.; Odaka, S.; Ogren, H.; Oh, A.; Oh, S. H.; Ohm, C. C.; Ohman, H.; Oide, H.; Okawa, H.; Okumura, Y.; Okuyama, T.; Olariu, A.; Oleiro Seabra, L. F.; Olivares Pino, S. A.; Oliveira Damazio, D.; Olszewski, A.; Olszowska, J.; Onofre, A.; Onogi, K.; Onyisi, P. U. E.; Oreglia, M. J.; Oren, Y.; Orestano, D.; Orlando, N.; Orr, R. S.; Osculati, B.; Ospanov, R.; Otero y Garzon, G.; Otono, H.; Ouchrif, M.; Ould-Saada, F.; Ouraou, A.; Oussoren, K. P.; Ouyang, Q.; Owen, M.; Owen, R. E.; Ozcan, V. E.; Ozturk, N.; Pachal, K.; Pacheco Pages, A.; Padilla Aranda, C.; Pagáčová, M.; Pagan Griso, S.; Paige, F.; Pais, P.; Pajchel, K.; Palacino, G.; Palestini, S.; Palka, M.; Pallin, D.; Palma, A.; Panagiotopoulou, E. St.; Pandini, C. E.; Panduro Vazquez, J. G.; Pani, P.; Panitkin, S.; Pantea, D.; Paolozzi, L.; Papadopoulou, Th. D.; Papageorgiou, K.; Paramonov, A.; Paredes Hernandez, D.; Parker, A. J.; Parker, M. A.; Parker, K. A.; Parodi, F.; Parsons, J. A.; Parzefall, U.; Pascuzzi, V. R.; Pasqualucci, E.; Passaggio, S.; Pastore, F.; Pastore, Fr.; Pásztor, G.; Pataraia, S.; Pater, J. R.; Pauly, T.; Pearce, J.; Pearson, B.; Pedersen, L. E.; Pedersen, M.; Pedraza Lopez, S.; Pedro, R.; Peleganchuk, S. V.; Pelikan, D.; Penc, O.; Peng, C.; Peng, H.; Penwell, J.; Peralva, B. S.; Perego, M. M.; Perepelitsa, D. V.; Perez Codina, E.; Perini, L.; Pernegger, H.; Perrella, S.; Peschke, R.; Peshekhonov, V. D.; Peters, K.; Peters, R. F. Y.; Petersen, B. A.; Petersen, T. C.; Petit, E.; Petridis, A.; Petridou, C.; Petroff, P.; Petrolo, E.; Petrov, M.; Petrucci, F.; Pettersson, N. E.; Peyaud, A.; Pezoa, R.; Phillips, P. W.; Piacquadio, G.; Pianori, E.; Picazio, A.; Piccaro, E.; Piccinini, M.; Pickering, M. A.; Piegaia, R.; Pilcher, J. E.; Pilkington, A. D.; Pin, A. W. J.; Pinamonti, M.; Pinfold, J. L.; Pingel, A.; Pires, S.; Pirumov, H.; Pitt, M.; Plazak, L.; Pleier, M.-A.; Pleskot, V.; Plotnikova, E.; Plucinski, P.; Pluth, D.; Poettgen, R.; Poggioli, L.; Pohl, D.; Polesello, G.; Poley, A.; Policicchio, A.; Polifka, R.; Polini, A.; Pollard, C. S.; Polychronakos, V.; Pommès, K.; Pontecorvo, L.; Pope, B. G.; Popeneciu, G. A.; Popovic, D. S.; Poppleton, A.; Pospisil, S.; Potamianos, K.; Potrap, I. N.; Potter, C. J.; Potter, C. T.; Poulard, G.; Poveda, J.; Pozdnyakov, V.; Pozo Astigarraga, M. E.; Pralavorio, P.; Pranko, A.; Prell, S.; Price, D.; Price, L. E.; Primavera, M.; Prince, S.; Proissl, M.; Prokofiev, K.; Prokoshin, F.; Protopopescu, S.; Proudfoot, J.; Przybycien, M.; Puddu, D.; Puldon, D.; Purohit, M.; Puzo, P.; Qian, J.; Qin, G.; Qin, Y.; Quadt, A.; Quayle, W. B.; Queitsch-Maitland, M.; Quilty, D.; Raddum, S.; Radeka, V.; Radescu, V.; Radhakrishnan, S. K.; Radloff, P.; Rados, P.; Ragusa, F.; Rahal, G.; Raine, J. A.; Rajagopalan, S.; Rammensee, M.; Rangel-Smith, C.; Ratti, M. G.; Rauscher, F.; Rave, S.; Ravenscroft, T.; Ravinovich, I.; Raymond, M.; Read, A. L.; Readioff, N. P.; Reale, M.; Rebuzzi, D. M.; Redelbach, A.; Redlinger, G.; Reece, R.; Reeves, K.; Rehnisch, L.; Reichert, J.; Reisin, H.; Rembser, C.; Ren, H.; Rescigno, M.; Resconi, S.; Rezanova, O. L.; Reznicek, P.; Rezvani, R.; Richter, R.; Richter, S.; Richter-Was, E.; Ricken, O.; Ridel, M.; Rieck, P.; Riegel, C. J.; Rieger, J.; Rifki, O.; Rijssenbeek, M.; Rimoldi, A.; Rimoldi, M.; Rinaldi, L.; Ristić, B.; Ritsch, E.; Riu, I.; Rizatdinova, F.; Rizvi, E.; Rizzi, C.; Robertson, S. H.; Robichaud-Veronneau, A.; Robinson, D.; Robinson, J. E. M.; Robson, A.; Roda, C.; Rodina, Y.; Rodriguez Perez, A.; Rodriguez Rodriguez, D.; Roe, S.; Rogan, C. S.; Røhne, O.; Romaniouk, A.; Romano, M.; Romano Saez, S. M.; Romero Adam, E.; Rompotis, N.; Ronzani, M.; Roos, L.; Ros, E.; Rosati, S.; Rosbach, K.; Rose, P.; Rosenthal, O.; Rosien, N.-A.; Rossetti, V.; Rossi, E.; Rossi, L. P.; Rosten, J. H. N.; Rosten, R.; Rotaru, M.; Roth, I.; Rothberg, J.; Rousseau, D.; Royon, C. R.; Rozanov, A.; Rozen, Y.; Ruan, X.; Rubbo, F.; Rudolph, M. S.; Rühr, F.; Ruiz-Martinez, A.; Rurikova, Z.; Rusakovich, N. A.; Ruschke, A.; Russell, H. L.; Rutherfoord, J. P.; Ruthmann, N.; Ryabov, Y. F.; Rybar, M.; Rybkin, G.; Ryu, S.; Ryzhov, A.; Rzehorz, G. F.; Saavedra, A. F.; Sabato, G.; Sacerdoti, S.; Sadrozinski, H. F.-W.; Sadykov, R.; Safai Tehrani, F.; Saha, P.; Sahinsoy, M.; Saimpert, M.; Saito, T.; Sakamoto, H.; Sakurai, Y.; Salamanna, G.; Salamon, A.; Salazar Loyola, J. E.; Salek, D.; Sales De Bruin, P. H.; Salihagic, D.; Salnikov, A.; Salt, J.; Salvatore, D.; Salvatore, F.; Salvucci, A.; Salzburger, A.; Sammel, D.; Sampsonidis, D.; Sanchez, A.; Sánchez, J.; Sanchez Martinez, V.; Sandaker, H.; Sandbach, R. L.; Sander, H. G.; Sandhoff, M.; Sandoval, C.; Sandstroem, R.; Sankey, D. P. C.; Sannino, M.; Sansoni, A.; Santoni, C.; Santonico, R.; Santos, H.; Santoyo Castillo, I.; Sapp, K.; Sapronov, A.; Saraiva, J. G.; Sarrazin, B.; Sasaki, O.; Sasaki, Y.; Sato, K.; Sauvage, G.; Sauvan, E.; Savage, G.; Savard, P.; Sawyer, C.; Sawyer, L.; Saxon, J.; Sbarra, C.; Sbrizzi, A.; Scanlon, T.; Scannicchio, D. A.; Scarcella, M.; Scarfone, V.; Schaarschmidt, J.; Schacht, P.; Schachtner, B. M.; Schaefer, D.; Schaefer, R.; Schaeffer, J.; Schaepe, S.; Schaetzel, S.; Schäfer, U.; Schaffer, A. C.; Schaile, D.; Schamberger, R. D.; Scharf, V.; Schegelsky, V. A.; Scheirich, D.; Schernau, M.; Schiavi, C.; Schier, S.; Schillo, C.; Schioppa, M.; Schlenker, S.; Schmieden, K.; Schmitt, C.; Schmitt, S.; Schmitz, S.; Schneider, B.; Schnoor, U.; Schoeffel, L.; Schoening, A.; Schoenrock, B. D.; Schopf, E.; Schott, M.; Schovancova, J.; Schramm, S.; Schreyer, M.; Schuh, N.; Schultens, M. J.; Schultz-Coulon, H.-C.; Schulz, H.; Schumacher, M.; Schumm, B. A.; Schune, Ph.; Schwartzman, A.; Schwarz, T. A.; Schwegler, Ph.; Schweiger, H.; Schwemling, Ph.; Schwienhorst, R.; Schwindling, J.; Schwindt, T.; Sciolla, G.; Scuri, F.; Scutti, F.; Searcy, J.; Seema, P.; Seidel, S. C.; Seiden, A.; Seifert, F.; Seixas, J. M.; Sekhniaidze, G.; Sekhon, K.; Sekula, S. J.; Seliverstov, D. M.; Semprini-Cesari, N.; Serfon, C.; Serin, L.; Serkin, L.; Sessa, M.; Seuster, R.; Severini, H.; Sfiligoj, T.; Sforza, F.; Sfyrla, A.; Shabalina, E.; Shaikh, N. W.; Shan, L. Y.; Shang, R.; Shank, J. T.; Shapiro, M.; Shatalov, P. B.; Shaw, K.; Shaw, S. M.; Shcherbakova, A.; Shehu, C. Y.; Sherwood, P.; Shi, L.; Shimizu, S.; Shimmin, C. O.; Shimojima, M.; Shiyakova, M.; Shmeleva, A.; Shoaleh Saadi, D.; Shochet, M. J.; Shojaii, S.; Shrestha, S.; Shulga, E.; Shupe, M. A.; Sicho, P.; Sidebo, P. E.; Sidiropoulou, O.; Sidorov, D.; Sidoti, A.; Siegert, F.; Sijacki, Dj.; Silva, J.; Silverstein, S. B.; Simak, V.; Simard, O.; Simic, Lj.; Simion, S.; Simioni, E.; Simmons, B.; Simon, D.; Simon, M.; Sinervo, P.; Sinev, N. B.; Sioli, M.; Siragusa, G.; Sivoklokov, S. Yu.; Sjölin, J.; Sjursen, T. B.; Skinner, M. B.; Skottowe, H. P.; Skubic, P.; Slater, M.; Slavicek, T.; Slawinska, M.; Sliwa, K.; Slovak, R.; Smakhtin, V.; Smart, B. H.; Smestad, L.; Smiesko, J.; Smirnov, S. Yu.; Smirnov, Y.; Smirnova, L. N.; Smirnova, O.; Smith, M. N. K.; Smith, R. W.; Smizanska, M.; Smolek, K.; Snesarev, A. A.; Snyder, S.; Sobie, R.; Socher, F.; Soffer, A.; Soh, D. A.; Sokhrannyi, G.; Solans Sanchez, C. A.; Solar, M.; Soldatov, E. Yu.; Soldevila, U.; Solodkov, A. A.; Soloshenko, A.; Solovyanov, O. V.; Solovyev, V.; Sommer, P.; Son, H.; Song, H. Y.; Sood, A.; Sopczak, A.; Sopko, V.; Sorin, V.; Sosa, D.; Sotiropoulou, C. L.; Soualah, R.; Soukharev, A. M.; South, D.; Sowden, B. C.; Spagnolo, S.; Spalla, M.; Spangenberg, M.; Spanò, F.; Sperlich, D.; Spettel, F.; Spighi, R.; Spigo, G.; Spiller, L. A.; Spousta, M.; Denis, R. D. St.; Stabile, A.; Stamen, R.; Stamm, S.; Stanecka, E.; Stanek, R. W.; Stanescu, C.; Stanescu-Bellu, M.; Stanitzki, M. M.; Stapnes, S.; Starchenko, E. A.; Stark, G. H.; Stark, J.; Staroba, P.; Starovoitov, P.; Stärz, S.; Staszewski, R.; Steinberg, P.; Stelzer, B.; Stelzer, H. J.; Stelzer-Chilton, O.; Stenzel, H.; Stewart, G. A.; Stillings, J. A.; Stockton, M. C.; Stoebe, M.; Stoicea, G.; Stolte, P.; Stonjek, S.; Stradling, A. R.; Straessner, A.; Stramaglia, M. E.; Strandberg, J.; Strandberg, S.; Strandlie, A.; Strauss, M.; Strizenec, P.; Ströhmer, R.; Strom, D. M.; Stroynowski, R.; Strubig, A.; Stucci, S. A.; Stugu, B.; Styles, N. A.; Su, D.; Su, J.; Subramaniam, R.; Suchek, S.; Sugaya, Y.; Suk, M.; Sulin, V. V.; Sultansoy, S.; Sumida, T.; Sun, S.; Sun, X.; Sundermann, J. E.; Suruliz, K.; Susinno, G.; Sutton, M. R.; Suzuki, S.; Svatos, M.; Swiatlowski, M.; Sykora, I.; Sykora, T.; Ta, D.; Taccini, C.; Tackmann, K.; Taenzer, J.; Taffard, A.; Tafirout, R.; Taiblum, N.; Takai, H.; Takashima, R.; Takeshita, T.; Takubo, Y.; Talby, M.; Talyshev, A. A.; Tan, K. G.; Tanaka, J.; Tanaka, R.; Tanaka, S.; Tannenwald, B. B.; Tapia Araya, S.; Tapprogge, S.; Tarem, S.; Tartarelli, G. F.; Tas, P.; Tasevsky, M.; Tashiro, T.; Tassi, E.; Tavares Delgado, A.; Tayalati, Y.; Taylor, A. C.; Taylor, G. N.; Taylor, P. T. E.; Taylor, W.; Teischinger, F. A.; Teixeira-Dias, P.; Temming, K. K.; Temple, D.; Ten Kate, H.; Teng, P. K.; Teoh, J. J.; Tepel, F.; Terada, S.; Terashi, K.; Terron, J.; Terzo, S.; Testa, M.; Teuscher, R. J.; Theveneaux-Pelzer, T.; Thomas, J. P.; Thomas-Wilsker, J.; Thompson, E. N.; Thompson, P. D.; Thompson, A. S.; Thomsen, L. A.; Thomson, E.; Thomson, M.; Tibbetts, M. J.; Ticse Torres, R. E.; Tikhomirov, V. O.; Tikhonov, Yu. A.; Timoshenko, S.; Tipton, P.; Tisserant, S.; Todome, K.; Todorov, T.; Todorova-Nova, S.; Tojo, J.; Tokár, S.; Tokushuku, K.; Tolley, E.; Tomlinson, L.; Tomoto, M.; Tompkins, L.; Toms, K.; Tong, B.; Torrence, E.; Torres, H.; Torró Pastor, E.; Toth, J.; Touchard, F.; Tovey, D. R.; Trefzger, T.; Tricoli, A.; Trigger, I. M.; Trincaz-Duvoid, S.; Tripiana, M. F.; Trischuk, W.; Trocmé, B.; Trofymov, A.; Troncon, C.; Trottier-McDonald, M.; Trovatelli, M.; Truong, L.; Trzebinski, M.; Trzupek, A.; Tseng, J. C.-L.; Tsiareshka, P. V.; Tsipolitis, G.; Tsirintanis, N.; Tsiskaridze, S.; Tsiskaridze, V.; Tskhadadze, E. G.; Tsui, K. M.; Tsukerman, I. I.; Tsulaia, V.; Tsuno, S.; Tsybychev, D.; Tudorache, A.; Tudorache, V.; Tuna, A. N.; Tupputi, S. A.; Turchikhin, S.; Turecek, D.; Turgeman, D.; Turra, R.; Turvey, A. J.; Tuts, P. M.; Tyndel, M.; Ucchielli, G.; Ueda, I.; Ueno, R.; Ughetto, M.; Ukegawa, F.; Unal, G.; Undrus, A.; Unel, G.; Ungaro, F. C.; Unno, Y.; Unverdorben, C.; Urban, J.; Urquijo, P.; Urrejola, P.; Usai, G.; Usanova, A.; Vacavant, L.; Vacek, V.; Vachon, B.; Valderanis, C.; Valdes Santurio, E.; Valencic, N.; Valentinetti, S.; Valero, A.; Valery, L.; Valkar, S.; Vallecorsa, S.; Valls Ferrer, J. A.; Van Den Wollenberg, W.; Van Der Deijl, P. C.; van der Geer, R.; van der Graaf, H.; van Eldik, N.; van Gemmeren, P.; Van Nieuwkoop, J.; van Vulpen, I.; van Woerden, M. C.; Vanadia, M.; Vandelli, W.; Vanguri, R.; Vaniachine, A.; Vankov, P.; Vardanyan, G.; Vari, R.; Varnes, E. W.; Varol, T.; Varouchas, D.; Vartapetian, A.; Varvell, K. E.; Vasquez, J. G.; Vazeille, F.; Vazquez Schroeder, T.; Veatch, J.; Veloce, L. M.; Veloso, F.; Veneziano, S.; Ventura, A.; Venturi, M.; Venturi, N.; Venturini, A.; Vercesi, V.; Verducci, M.; Verkerke, W.; Vermeulen, J. C.; Vest, A.; Vetterli, M. C.; Viazlo, O.; Vichou, I.; Vickey, T.; Vickey Boeriu, O. E.; Viehhauser, G. H. A.; Viel, S.; Vigani, L.; Vigne, R.; Villa, M.; Villaplana Perez, M.; Vilucchi, E.; Vincter, M. G.; Vinogradov, V. B.; Vittori, C.; Vivarelli, I.; Vlachos, S.; Vlasak, M.; Vogel, M.; Vokac, P.; Volpi, G.; Volpi, M.; von der Schmitt, H.; von Toerne, E.; Vorobel, V.; Vorobev, K.; Vos, M.; Voss, R.; Vossebeld, J. H.; Vranjes, N.; Vranjes Milosavljevic, M.; Vrba, V.; Vreeswijk, M.; Vuillermet, R.; Vukotic, I.; Vykydal, Z.; Wagner, P.; Wagner, W.; Wahlberg, H.; Wahrmund, S.; Wakabayashi, J.; Walder, J.; Walker, R.; Walkowiak, W.; Wallangen, V.; Wang, C.; Wang, C.; Wang, F.; Wang, H.; Wang, H.; Wang, J.; Wang, J.; Wang, K.; Wang, R.; Wang, S. M.; Wang, T.; Wang, T.; Wang, X.; Wanotayaroj, C.; Warburton, A.; Ward, C. P.; Wardrope, D. R.; Washbrook, A.; Watkins, P. M.; Watson, A. T.; Watson, M. F.; Watts, G.; Watts, S.; Waugh, B. M.; Webb, S.; Weber, M. S.; Weber, S. W.; Webster, J. S.; Weidberg, A. R.; Weinert, B.; Weingarten, J.; Weiser, C.; Weits, H.; Wells, P. S.; Wenaus, T.; Wengler, T.; Wenig, S.; Wermes, N.; Werner, M.; Werner, P.; Wessels, M.; Wetter, J.; Whalen, K.; Whallon, N. L.; Wharton, A. M.; White, A.; White, M. J.; White, R.; Whiteson, D.; Wickens, F. J.; Wiedenmann, W.; Wielers, M.; Wienemann, P.; Wiglesworth, C.; Wiik-Fuchs, L. A. M.; Wildauer, A.; Wilk, F.; Wilkens, H. G.; Williams, H. H.; Williams, S.; Willis, C.; Willocq, S.; Wilson, J. A.; Wingerter-Seez, I.; Winklmeier, F.; Winston, O. J.; Winter, B. T.; Wittgen, M.; Wittkowski, J.; Wollstadt, S. J.; Wolter, M. W.; Wolters, H.; Wosiek, B. K.; Wotschack, J.; Woudstra, M. J.; Wozniak, K. W.; Wu, M.; Wu, M.; Wu, S. L.; Wu, X.; Wu, Y.; Wyatt, T. R.; Wynne, B. M.; Xella, S.; Xu, D.; Xu, L.; Yabsley, B.; Yacoob, S.; Yakabe, R.; Yamaguchi, D.; Yamaguchi, Y.; Yamamoto, A.; Yamamoto, S.; Yamanaka, T.; Yamauchi, K.; Yamazaki, Y.; Yan, Z.; Yang, H.; Yang, H.; Yang, Y.; Yang, Z.; Yao, W.-M.; Yap, Y. C.; Yasu, Y.; Yatsenko, E.; Yau Wong, K. H.; Ye, J.; Ye, S.; Yeletskikh, I.; Yen, A. L.; Yildirim, E.; Yorita, K.; Yoshida, R.; Yoshihara, K.; Young, C.; Young, C. J. S.; Youssef, S.; Yu, D. R.; Yu, J.; Yu, J. M.; Yu, J.; Yuan, L.; Yuen, S. P. Y.; Yusuff, I.; Zabinski, B.; Zaidan, R.; Zaitsev, A. M.; Zakharchuk, N.; Zalieckas, J.; Zaman, A.; Zambito, S.; Zanello, L.; Zanzi, D.; Zeitnitz, C.; Zeman, M.; Zemla, A.; Zeng, J. C.; Zeng, Q.; Zengel, K.; Zenin, O.; Ženiš, T.; Zerwas, D.; Zhang, D.; Zhang, F.; Zhang, G.; Zhang, H.; Zhang, J.; Zhang, L.; Zhang, R.; Zhang, R.; Zhang, X.; Zhang, Z.; Zhao, X.; Zhao, Y.; Zhao, Z.; Zhemchugov, A.; Zhong, J.; Zhou, B.; Zhou, C.; Zhou, L.; Zhou, L.; Zhou, M.; Zhou, N.; Zhu, C. G.; Zhu, H.; Zhu, J.; Zhu, Y.; Zhuang, X.; Zhukov, K.; Zibell, A.; Zieminska, D.; Zimine, N. I.; Zimmermann, C.; Zimmermann, S.; Zinonos, Z.; Zinser, M.; Ziolkowski, M.; Živković, L.; Zobernig, G.; Zoccoli, A.; zur Nedden, M.; Zurzolo, G.; Zwalinski, L.

2016-08-01

The angular distributions of Drell-Yan charged lepton pairs in the vicinity of the Z-boson mass peak probe the underlying QCD dynamics of Z-boson production. This paper presents a measurement of the complete set of angular coefficients A 0-7 describing these distributions in the Z-boson Collins-Soper frame. The data analysed correspond to 20.3 fb-1 of pp collisions at √{s}=8 TeV, collected by the ATLAS detector at the CERN LHC. The measurements are compared to the most precise fixed-order calculations currently available ({O}({α}s^2)) and with theoretical predictions embedded in Monte Carlo generators. The measurements are precise enough to probe QCD corrections beyond the formal accuracy of these calculations and to provide discrimination between different parton-shower models. A significant deviation from the ({O}({α}s^2)) predictions is observed for A 0 - A 2. Evidence is found for non-zero A 5,6,7, consistent with expectations. [Figure not available: see fulltext.

Measurement of the angular coefficients in Z-boson events using electron and muon pairs from data taken at $$ \\sqrt{s}=8 $$ TeV with the ATLAS detector

DOE PAGES

Aad, G.; Abbott, B.; Abdallah, J.; ...

2016-08-29

The angular distributions of Drell-Yan charged lepton pairs in the vicinity of the Z-boson mass peak probe the underlying QCD dynamics of Z-boson production. This paper presents a measurement of the complete set of angular coefficients A 0–7 describing these distributions in the Z-boson Collins-Soper frame. The data analysed correspond to 20.3 fb –1 of pp collisions at √s = 8 TeV, collected by the ATLAS detector at the CERN LHC. The measurements are compared to the most precise fixed-order calculations currently available (O(α2s)) and with theoretical predictions embedded in Monte Carlo generators. The measurements are precise enough to probemore » QCD corrections beyond the formal accuracy of these calculations and to provide discrimination between different parton-shower models. A significant deviation from the (O(α 2 s)) predictions is observed for A 0 – A 2. In conclusion, evidence is found for non-zero A 5,6,7, consistent with expectations.« less

Measurement of the angular coefficients in Z-boson events using electron and muon pairs from data taken at $$ \\sqrt{s}=8 $$ TeV with the ATLAS detector

DOE Office of Scientific and Technical Information (OSTI.GOV)

Aad, G.; Abbott, B.; Abdallah, J.

The angular distributions of Drell-Yan charged lepton pairs in the vicinity of the Z-boson mass peak probe the underlying QCD dynamics of Z-boson production. This paper presents a measurement of the complete set of angular coefficients A 0–7 describing these distributions in the Z-boson Collins-Soper frame. The data analysed correspond to 20.3 fb –1 of pp collisions at √s = 8 TeV, collected by the ATLAS detector at the CERN LHC. The measurements are compared to the most precise fixed-order calculations currently available (O(α2s)) and with theoretical predictions embedded in Monte Carlo generators. The measurements are precise enough to probemore » QCD corrections beyond the formal accuracy of these calculations and to provide discrimination between different parton-shower models. A significant deviation from the (O(α 2 s)) predictions is observed for A 0 – A 2. In conclusion, evidence is found for non-zero A 5,6,7, consistent with expectations.« less

Effect of the coefficient of friction and tightening speed on the preload induced at the dental implant complex with the finite element method.

PubMed

Bulaqi, Haddad Arabi; Mousavi Mashhadi, Mahmoud; Geramipanah, Farideh; Safari, Hamed; Paknejad, Mojgan

2015-05-01

To prevent screw loosening, a clear understanding of the factors influencing secure preload is necessary. The purpose of this study was to investigate the effect of coefficient of friction and tightening speed on screw tightening based on energy distribution method with exact geometric modeling and finite element analysis. To simulate the proper boundary conditions of the screw tightening process, the supporting bone of an implant was considered. The exact geometry of the implant complex, including the Straumann dental implant, direct crown attachment, and abutment screw were modeled with Solidworks software. Abutment screw/implant and implant/bone interfaces were designed as spiral thread helixes. The screw-tightening process was simulated with Abaqus software, and to achieve the target torque, an angular displacement was applied to the abutment screw head at different coefficients of friction and tightening speeds. The values of torque, preload, energy distribution, elastic energy, and efficiency were obtained at the target torque of 35 Ncm. Additionally, the torque distribution ratio and preload simulated values were compared to theoretically predicted values. Upon reducing the coefficient of friction and enhancing the tightening speed, the angle of turn increased at the target torque. As the angle of turn increased, the elastic energy and preload also increased. Additionally, by increasing the coefficient of friction, the frictional dissipation energy increased but the efficiency decreased, whereas the increase in tightening speed insignificantly affected efficiency. The results of this study indicate that the coefficient of friction is the most influential factor on efficiency. Increasing the tightening speed lowered the response rate to the frictional resistance, thus diminishing the coefficient of friction and slightly increasing the preload. Increasing the tightening speed has the same result as reducing the coefficient of friction. Copyright © 2015 Editorial Council for the Journal of Prosthetic Dentistry. Published by Elsevier Inc. All rights reserved.

Implementation Intention and Reminder Effects on Behavior Change in a Mobile Health System: A Predictive Cognitive Model.

PubMed

Pirolli, Peter; Mohan, Shiwali; Venkatakrishnan, Anusha; Nelson, Les; Silva, Michael; Springer, Aaron

2017-11-30

Implementation intentions are mental representations of simple plans to translate goal intentions into behavior under specific conditions. Studies show implementation intentions can produce moderate to large improvements in behavioral goal achievement. Human associative memory mechanisms have been implicated in the processes by which implementation intentions produce effects. On the basis of the adaptive control of thought-rational (ACT-R) theory of cognition, we hypothesized that the strength of implementation intention effect could be manipulated in predictable ways using reminders delivered by a mobile health (mHealth) app. The aim of this experiment was to manipulate the effects of implementation intentions on daily behavioral goal success in ways predicted by the ACT-R theory concerning mHealth reminder scheduling. An incomplete factorial design was used in this mHealth study. All participants were asked to choose a healthy behavior goal associated with eat slowly, walking, or eating more vegetables and were asked to set implementation intentions. N=64 adult participants were in the study for 28 days. Participants were stratified by self-efficacy and assigned to one of two reminder conditions: reminders-presented versus reminders-absent. Self-efficacy and reminder conditions were crossed. Nested within the reminders-presented condition was a crossing of frequency of reminders sent (high, low) by distribution of reminders sent (distributed, massed). Participants in the low frequency condition got 7 reminders over 28 days; those in the high frequency condition were sent 14. Participants in the distributed conditions were sent reminders at uniform intervals. Participants in the massed distribution conditions were sent reminders in clusters. There was a significant overall effect of reminders on achieving a daily behavioral goal (coefficient=2.018, standard error [SE]=0.572, odds ratio [OR]=7.52, 95% CI 0.9037-3.2594, P<.001). As predicted by ACT-R, using default theoretical parameters, there was an interaction of reminder frequency by distribution on daily goal success (coefficient=0.7994, SE=0.2215, OR=2.2242, 95% CI 0.3656-1.2341, P<.001). The total number of times a reminder was acknowledged as received by a participant had a marginal effect on daily goal success (coefficient=0.0694, SE=0.0410, OR=1.0717, 95% CI -0.01116 to 0.1505, P=.09), and the time since acknowledging receipt of a reminder was highly significant (coefficient=-0.0490, SE=0.0104, OR=0.9522, 95% CI -0.0700 to -0.2852], P<.001). A dual system ACT-R mathematical model was fit to individuals' daily goal successes and reminder acknowledgments: a goal-striving system dependent on declarative memory plus a habit-forming system that acquires automatic procedures for performance of behavioral goals. Computational cognitive theory such as ACT-R can be used to make precise quantitative predictions concerning daily health behavior goal success in response to implementation intentions and the dosing schedules of reminders. ©Peter Pirolli, Shiwali Mohan, Anusha Venkatakrishnan, Les Nelson, Michael Silva, Aaron Springer. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 30.11.2017.

Determination of variables in the prediction of strontium distribution coefficients for selected sediments

USGS Publications Warehouse

Pace, M.N.; Rosentreter, J.J.; Bartholomay, R.C.

2001-01-01

Idaho State University and the US Geological Survey, in cooperation with the US Department of Energy, conducted a study to determine and evaluate strontium distribution coefficients (Kds) of subsurface materials at the Idaho National Engineering and Environmental Laboratory (INEEL). The Kds were determined to aid in assessing the variability of strontium Kds and their effects on chemical transport of strontium-90 in the Snake River Plain aquifer system. Data from batch experiments done to determine strontium Kds of five sediment-infill samples and six standard reference material samples were analyzed by using multiple linear regression analysis and the stepwise variable-selection method in the statistical program, Statistical Product and Service Solutions, to derive an equation of variables that can be used to predict strontium Kds of sediment-infill samples. The sediment-infill samples were from basalt vesicles and fractures from a selected core at the INEEL; strontium Kds ranged from ???201 to 356 ml g-1. The standard material samples consisted of clay minerals and calcite. The statistical analyses of the batch-experiment results showed that the amount of strontium in the initial solution, the amount of manganese oxide in the sample material, and the amount of potassium in the initial solution are the most important variables in predicting strontium Kds of sediment-infill samples.

Design, synthesis, pharmacological evaluation and in silico ADMET prediction of novel substituted benzimidazole derivatives as angiotensin II-AT1 receptor antagonists based on predictive 3D QSAR models.

PubMed

Vyas, V K; Gupta, N; Ghate, M; Patel, S

2014-01-01

In this study we designed novel substituted benzimidazole derivatives and predicted their absorption, distribution, metabolism, excretion and toxicity (ADMET) properties, based on a predictive 3D QSAR study on 132 substituted benzimidazoles as AngII-AT1 receptor antagonists. The two best predicted compounds were synthesized and evaluated for AngII-AT1 receptor antagonism. Three different alignment tools for comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) were used. The best 3D QSAR models were obtained using the rigid body (Distill) alignment method. CoMFA and CoMSIA models were found to be statistically significant with leave-one-out correlation coefficients (q(2)) of 0.630 and 0.623, respectively, cross-validated coefficients (r(2)cv) of 0.651 and 0.630, respectively, and conventional coefficients of determination (r(2)) of 0.848 and 0.843, respectively. 3D QSAR models were validated using a test set of 24 compounds, giving satisfactory predicted results (r(2)pred) of 0.727 and 0.689 for the CoMFA and CoMSIA models, respectively. We have identified some key features in substituted benzimidazole derivatives, such as lipophilicity and H-bonding at the 2- and 5-positions of the benzimidazole nucleus, respectively, for AT1 receptor antagonistic activity. We designed 20 novel substituted benzimidazole derivatives and predicted their activity. In silico ADMET properties were also predicted for these designed molecules. Finally, the compounds with best predicted activity were synthesized and evaluated for in vitro angiotensin II-AT1 receptor antagonism.

Insect density-plant density relationships: a modified view of insect responses to resource concentrations.

PubMed

Andersson, Petter; Löfstedt, Christer; Hambäck, Peter A

2013-12-01

Habitat area is an important predictor of spatial variation in animal densities. However, the area often correlates with the quantity of resources within habitats, complicating our understanding of the factors shaping animal distributions. We addressed this problem by investigating densities of insect herbivores in habitat patches with a constant area but varying numbers of plants. Using a mathematical model, predictions of scale-dependent immigration and emigration rates for insects into patches with different densities of host plants were derived. Moreover, a field experiment was conducted where the scaling properties of odour-mediated attraction in relation to the number of odour sources were estimated, in order to derive a prediction of immigration rates of olfactory searchers. The theoretical model predicted that we should expect immigration rates of contact and visual searchers to be determined by patch area, with a steep scaling coefficient, μ = -1. The field experiment suggested that olfactory searchers should show a less steep scaling coefficient, with μ ≈ -0.5. A parameter estimation and analysis of published data revealed a correspondence between observations and predictions, and density-variation among groups could largely be explained by search behaviour. Aphids showed scaling coefficients corresponding to the prediction for contact/visual searchers, whereas moths, flies and beetles corresponded to the prediction for olfactory searchers. As density responses varied considerably among groups, and variation could be explained by a certain trait, we conclude that a general theory of insect responses to habitat heterogeneity should be based on shared traits, rather than a general prediction for all species.

Functional network architecture predicts psychologically mediated analgesia related to treatment in chronic knee pain patients.

PubMed

Hashmi, Javeria Ali; Kong, Jian; Spaeth, Rosa; Khan, Sheraz; Kaptchuk, Ted J; Gollub, Randy L

2014-03-12

Placebo analgesia is an indicator of how efficiently the brain translates psychological signals conveyed by a treatment procedure into pain relief. It has been demonstrated that functional connectivity between distributed brain regions predicts placebo analgesia in chronic back pain patients. Greater network efficiency in baseline brain networks may allow better information transfer and facilitate adaptive physiological responses to psychological aspects of treatment. Here, we theorized that topological network alignments in resting state scans predict psychologically conditioned analgesic responses to acupuncture treatment in chronic knee osteoarthritis pain patients (n = 45). Analgesia was induced by building positive expectations toward acupuncture treatment with verbal suggestion and heat pain conditioning on a test site of the arm. This procedure induced significantly more analgesia after sham or real acupuncture on the test site than in a control site. The psychologically conditioned analgesia was invariant to sham versus real treatment. Efficiency of information transfer within local networks calculated with graph-theoretic measures (local efficiency and clustering coefficients) significantly predicted conditioned analgesia. Clustering coefficients in regions associated with memory, motivation, and pain modulation were closely involved in predicting analgesia. Moreover, women showed higher clustering coefficients and marginally greater pain reduction than men. Overall, analgesic response to placebo cues can be predicted from a priori resting state data by observing local network topology. Such low-cost synchronizations may represent preparatory resources that facilitate subsequent performance of brain circuits in responding to adaptive environmental cues. This suggests a potential utility of network measures in predicting placebo response for clinical use.

A surface renewal model for unsteady-state mass transfer using the generalized Danckwerts age distribution function

PubMed Central

Horvath, Isabelle R.

2018-01-01

The recently derived steady-state generalized Danckwerts age distribution is extended to unsteady-state conditions. For three different wind speeds used by researchers on air–water heat exchange on the Heidelberg Aeolotron, calculations reveal that the distribution has a sharp peak during the initial moments, but flattens out and acquires a bell-shaped character with process time, with the time taken to attain a steady-state profile being a strong and inverse function of wind speed. With increasing wind speed, the age distribution narrows significantly, its skewness decreases and its peak becomes larger. The mean eddy renewal time increases linearly with process time initially but approaches a final steady-state value asymptotically, which decreases dramatically with increased wind speed. Using the distribution to analyse the transient absorption of a gas into a large body of liquid, assuming negligible gas-side mass-transfer resistance, estimates are made of the gas-absorption and dissolved-gas transfer coefficients for oxygen absorption in water at 25°C for the three different wind speeds. Under unsteady-state conditions, these two coefficients show an inverse behaviour, indicating a heightened accumulation of dissolved gas in the surface elements, especially during the initial moments of absorption. However, the two mass-transfer coefficients start merging together as the steady state is approached. Theoretical predictions of the steady-state mass-transfer coefficient or transfer velocity are in fair agreement (average absolute error of prediction = 18.1%) with some experimental measurements of the same for the nitrous oxide–water system at 20°C that were made in the Heidelberg Aeolotron. PMID:29892429

Developing a NIR multispectral imaging for prediction and visualization of peanut protein content using variable selection algorithms

NASA Astrophysics Data System (ADS)

Cheng, Jun-Hu; Jin, Huali; Liu, Zhiwei

2018-01-01

The feasibility of developing a multispectral imaging method using important wavelengths from hyperspectral images selected by genetic algorithm (GA), successive projection algorithm (SPA) and regression coefficient (RC) methods for modeling and predicting protein content in peanut kernel was investigated for the first time. Partial least squares regression (PLSR) calibration model was established between the spectral data from the selected optimal wavelengths and the reference measured protein content ranged from 23.46% to 28.43%. The RC-PLSR model established using eight key wavelengths (1153, 1567, 1972, 2143, 2288, 2339, 2389 and 2446 nm) showed the best predictive results with the coefficient of determination of prediction (R2P) of 0.901, and root mean square error of prediction (RMSEP) of 0.108 and residual predictive deviation (RPD) of 2.32. Based on the obtained best model and image processing algorithms, the distribution maps of protein content were generated. The overall results of this study indicated that developing a rapid and online multispectral imaging system using the feature wavelengths and PLSR analysis is potential and feasible for determination of the protein content in peanut kernels.

Estimation Methods for Non-Homogeneous Regression - Minimum CRPS vs Maximum Likelihood

NASA Astrophysics Data System (ADS)

Gebetsberger, Manuel; Messner, Jakob W.; Mayr, Georg J.; Zeileis, Achim

2017-04-01

Non-homogeneous regression models are widely used to statistically post-process numerical weather prediction models. Such regression models correct for errors in mean and variance and are capable to forecast a full probability distribution. In order to estimate the corresponding regression coefficients, CRPS minimization is performed in many meteorological post-processing studies since the last decade. In contrast to maximum likelihood estimation, CRPS minimization is claimed to yield more calibrated forecasts. Theoretically, both scoring rules used as an optimization score should be able to locate a similar and unknown optimum. Discrepancies might result from a wrong distributional assumption of the observed quantity. To address this theoretical concept, this study compares maximum likelihood and minimum CRPS estimation for different distributional assumptions. First, a synthetic case study shows that, for an appropriate distributional assumption, both estimation methods yield to similar regression coefficients. The log-likelihood estimator is slightly more efficient. A real world case study for surface temperature forecasts at different sites in Europe confirms these results but shows that surface temperature does not always follow the classical assumption of a Gaussian distribution. KEYWORDS: ensemble post-processing, maximum likelihood estimation, CRPS minimization, probabilistic temperature forecasting, distributional regression models

Differential pencil beam dose computation model for photons.

PubMed

Mohan, R; Chui, C; Lidofsky, L

1986-01-01

Differential pencil beam (DPB) is defined as the dose distribution relative to the position of the first collision, per unit collision density, for a monoenergetic pencil beam of photons in an infinite homogeneous medium of unit density. We have generated DPB dose distribution tables for a number of photon energies in water using the Monte Carlo method. The three-dimensional (3D) nature of the transport of photons and electrons is automatically incorporated in DPB dose distributions. Dose is computed by evaluating 3D integrals of DPB dose. The DPB dose computation model has been applied to calculate dose distributions for 60Co and accelerator beams. Calculations for the latter are performed using energy spectra generated with the Monte Carlo program. To predict dose distributions near the beam boundaries defined by the collimation system as well as blocks, we utilize the angular distribution of incident photons. Inhomogeneities are taken into account by attenuating the primary photon fluence exponentially utilizing the average total linear attenuation coefficient of intervening tissue, by multiplying photon fluence by the linear attenuation coefficient to yield the number of collisions in the scattering volume, and by scaling the path between the scattering volume element and the computation point by an effective density.

Development of a Thermodynamic Model for the Hanford Tank Waste Operations Simulator - 12193

DOE Office of Scientific and Technical Information (OSTI.GOV)

Carter, Robert; Seniow, Kendra

The Hanford Tank Waste Operations Simulator (HTWOS) is the current tool used by the Hanford Tank Operations Contractor for system planning and assessment of different operational strategies. Activities such as waste retrievals in the Hanford tank farms and washing and leaching of waste in the Waste Treatment and Immobilization Plant (WTP) are currently modeled in HTWOS. To predict phase compositions during these activities, HTWOS currently uses simple wash and leach factors that were developed many years ago. To improve these predictions, a rigorous thermodynamic framework has been developed based on the multi-component Pitzer ion interaction model for use with severalmore » important chemical species in Hanford tank waste. These chemical species are those with the greatest impact on high-level waste glass production in the WTP and whose solubility depends on the processing conditions. Starting with Pitzer parameter coefficients and species chemical potential coefficients collated from open literature sources, reconciliation with published experimental data led to a self-consistent set of coefficients known as the HTWOS Pitzer database. Using Gibbs energy minimization with the Pitzer ion interaction equations in Microsoft Excel,1 a number of successful predictions were made for the solubility of simple mixtures of the chosen species. Currently, this thermodynamic framework is being programmed into HTWOS as the mechanism for determining the solid-liquid phase distributions for the chosen species, replacing their simple wash and leach factors. Starting from a variety of open literature sources, a collection of Pitzer parameters and species chemical potentials, as functions of temperature, was tested for consistency and accuracy by comparison with available experimental thermodynamic data (e.g., osmotic coefficients and solubility). Reconciliation of the initial set of parameter coefficients with the experimental data led to the development of the self-consistent set known as the HTWOS Pitzer database. Using Microsoft Excel to formulate the Gibbs energy minimization method and the multi-component Pitzer ion interaction equations, several predictions of the solubility of solute mixtures at various temperatures were made using the HTWOS Pitzer database coefficients. Examples of these predictions are shown in Figure 3 and Figure 4. A listing of the entire HTWOS Pitzer database can be found in RPP-RPT-50703. Currently, work is underway to install the Pitzer ion interaction model in HTWOS as the mechanism for determining the solid-liquid phase distributions of select waste constituents during tank retrievals and subsequent washing and leaching of the waste. Validation of the Pitzer ion interaction model in HTWOS will be performed with analytical laboratory data of actual tank waste. This change in HTWOS is expected to elicit shifts in mission criteria, such as mission end date and quantity of high-level waste glass produced by WTP, as predicted by HTWOS. These improvements to the speciation calculations in HTWOS, however, will establish a better planning basis and facilitate more effective and efficient future operations of the WTP. (authors)« less

Limited distortion in LSB steganography

NASA Astrophysics Data System (ADS)

Kim, Younhee; Duric, Zoran; Richards, Dana

2006-02-01

It is well known that all information hiding methods that modify the least significant bits introduce distortions into the cover objects. Those distortions have been utilized by steganalysis algorithms to detect that the objects had been modified. It has been proposed that only coefficients whose modification does not introduce large distortions should be used for embedding. In this paper we propose an effcient algorithm for information hiding in the LSBs of JPEG coefficients. Our algorithm uses parity coding to choose the coefficients whose modifications introduce minimal additional distortion. We derive the expected value of the additional distortion as a function of the message length and the probability distribution of the JPEG quantization errors of cover images. Our experiments show close agreement between the theoretical prediction and the actual additional distortion.

Population Pharmacokinetics of Intravenous Paracetamol (Acetaminophen) in Preterm and Term Neonates: Model Development and External Evaluation.

PubMed

Cook, Sarah F; Roberts, Jessica K; Samiee-Zafarghandy, Samira; Stockmann, Chris; King, Amber D; Deutsch, Nina; Williams, Elaine F; Allegaert, Karel; Wilkins, Diana G; Sherwin, Catherine M T; van den Anker, John N

2016-01-01

The aims of this study were to develop a population pharmacokinetic model for intravenous paracetamol in preterm and term neonates and to assess the generalizability of the model by testing its predictive performance in an external dataset. Nonlinear mixed-effects models were constructed from paracetamol concentration-time data in NONMEM 7.2. Potential covariates included body weight, gestational age, postnatal age, postmenstrual age, sex, race, total bilirubin, and estimated glomerular filtration rate. An external dataset was used to test the predictive performance of the model through calculation of bias, precision, and normalized prediction distribution errors. The model-building dataset included 260 observations from 35 neonates with a mean gestational age of 33.6 weeks [standard deviation (SD) 6.6]. Data were well-described by a one-compartment model with first-order elimination. Weight predicted paracetamol clearance and volume of distribution, which were estimated as 0.348 L/h (5.5 % relative standard error; 30.8 % coefficient of variation) and 2.46 L (3.5 % relative standard error; 14.3 % coefficient of variation), respectively, at the mean subject weight of 2.30 kg. An external evaluation was performed on an independent dataset that included 436 observations from 60 neonates with a mean gestational age of 35.6 weeks (SD 4.3). The median prediction error was 10.1 % [95 % confidence interval (CI) 6.1-14.3] and the median absolute prediction error was 25.3 % (95 % CI 23.1-28.1). Weight predicted intravenous paracetamol pharmacokinetics in neonates ranging from extreme preterm to full-term gestational status. External evaluation suggested that these findings should be generalizable to other similar patient populations.

Population Pharmacokinetics of Intravenous Paracetamol (Acetaminophen) in Preterm and Term Neonates: Model Development and External Evaluation

PubMed Central

Cook, Sarah F.; Roberts, Jessica K.; Samiee-Zafarghandy, Samira; Stockmann, Chris; King, Amber D.; Deutsch, Nina; Williams, Elaine F.; Allegaert, Karel; Sherwin, Catherine M. T.; van den Anker, John N.

2017-01-01

Objectives The aims of this study were to develop a population pharmacokinetic model for intravenous paracetamol in preterm and term neonates and to assess the generalizability of the model by testing its predictive performance in an external dataset. Methods Nonlinear mixed-effects models were constructed from paracetamol concentration–time data in NONMEM 7.2. Potential covariates included body weight, gestational age, postnatal age, postmenstrual age, sex, race, total bilirubin, and estimated glomerular filtration rate. An external dataset was used to test the predictive performance of the model through calculation of bias, precision, and normalized prediction distribution errors. Results The model-building dataset included 260 observations from 35 neonates with a mean gestational age of 33.6 weeks [standard deviation (SD) 6.6]. Data were well-described by a one-compartment model with first-order elimination. Weight predicted paracetamol clearance and volume of distribution, which were estimated as 0.348 L/h (5.5 % relative standard error; 30.8 % coefficient of variation) and 2.46 L (3.5 % relative standard error; 14.3 % coefficient of variation), respectively, at the mean subject weight of 2.30 kg. An external evaluation was performed on an independent dataset that included 436 observations from 60 neonates with a mean gestational age of 35.6 weeks (SD 4.3). The median prediction error was 10.1 % [95 % confidence interval (CI) 6.1–14.3] and the median absolute prediction error was 25.3 % (95 % CI 23.1–28.1). Conclusions Weight predicted intravenous paracetamol pharmacokinetics in neonates ranging from extreme preterm to full-term gestational status. External evaluation suggested that these findings should be generalizable to other similar patient populations. PMID:26201306

Lithium manganese oxide spinel electrodes

NASA Astrophysics Data System (ADS)

Darling, Robert Mason

Batteries based oil intercalation eletrodes are currently being considered for a variety of applications including automobiles. This thesis is concerned with the simulation and experimental investigation of one such system: spinel LiyMn2O4. A mathematical model simulating the behavior of an electrochemical cell containing all intercalation electrode is developed and applied to Li yMn2O4 based systems. The influence of the exchange current density oil the propagation of the reaction through the depth of the electrode is examined theoretically. Galvanostatic cycling and relaxation phenomena on open circuit are simulated for different particle-size distributions. The electrode with uniformly sized particles shows the best performance when the current is on, and relaxes towards equilibrium most quickly. The impedance of a porous electrode containing a particle-size distribution at low frequencies is investigated with all analytic solution and a simplified version of the mathematical model. The presence of the particle-size distribution leads to an apparent diffusion coefficient which has all incorrect concentration dependence. A Li/1 M LiClO4 in propylene carbonate (PC)/ LiyMn 2O4 cell is used to investigate the influence of side reactions oil the current-potential behavior of intercalation electrodes. Slow cyclic voltammograms and self-discharge data are combined to estimate the reversible potential of the host material and the kinetic parameters for the side reaction. This information is then used, together with estimates of the solid-state diffusion coefficient and main-reaction exchange current density, in a mathematical model of the system. Predictions from the model compare favorably with continuous cycling results and galvanostatic experiments with periodic current interruptions. The variation with respect to composition of' the diffusion coefficient of lithium in LiyMn2O4 is estimated from incomplete galvanostatic discharges following open-circult periods. The results compared favorably with those available in the literature. Dynamic Monte Carlo simulations were conducted to investigate the concentration dependence of the diffusion coefficient fundamentally. The dynamic Monte Carlo predictions compare favorably with the experimental data.

Meta-analytical synthesis of regression coefficients under different categorization scheme of continuous covariates.

PubMed

Yoneoka, Daisuke; Henmi, Masayuki

2017-11-30

Recently, the number of clinical prediction models sharing the same regression task has increased in the medical literature. However, evidence synthesis methodologies that use the results of these regression models have not been sufficiently studied, particularly in meta-analysis settings where only regression coefficients are available. One of the difficulties lies in the differences between the categorization schemes of continuous covariates across different studies. In general, categorization methods using cutoff values are study specific across available models, even if they focus on the same covariates of interest. Differences in the categorization of covariates could lead to serious bias in the estimated regression coefficients and thus in subsequent syntheses. To tackle this issue, we developed synthesis methods for linear regression models with different categorization schemes of covariates. A 2-step approach to aggregate the regression coefficient estimates is proposed. The first step is to estimate the joint distribution of covariates by introducing a latent sampling distribution, which uses one set of individual participant data to estimate the marginal distribution of covariates with categorization. The second step is to use a nonlinear mixed-effects model with correction terms for the bias due to categorization to estimate the overall regression coefficients. Especially in terms of precision, numerical simulations show that our approach outperforms conventional methods, which only use studies with common covariates or ignore the differences between categorization schemes. The method developed in this study is also applied to a series of WHO epidemiologic studies on white blood cell counts. Copyright © 2017 John Wiley & Sons, Ltd.

Modelling the distribution of chickens, ducks, and geese in China

USGS Publications Warehouse

Prosser, Diann J.; Wu, Junxi; Ellis, Erie C.; Gale, Fred; Van Boeckel, Thomas P.; Wint, William; Robinson, Tim; Xiao, Xiangming; Gilbert, Marius

2011-01-01

Global concerns over the emergence of zoonotic pandemics emphasize the need for high-resolution population distribution mapping and spatial modelling. Ongoing efforts to model disease risk in China have been hindered by a lack of available species level distribution maps for poultry. The goal of this study was to develop 1 km resolution population density models for China's chickens, ducks, and geese. We used an information theoretic approach to predict poultry densities based on statistical relationships between poultry census data and high-resolution agro-ecological predictor variables. Model predictions were validated by comparing goodness of fit measures (root mean square error and correlation coefficient) for observed and predicted values for 1/4 of the sample data which were not used for model training. Final output included mean and coefficient of variation maps for each species. We tested the quality of models produced using three predictor datasets and 4 regional stratification methods. For predictor variables, a combination of traditional predictors for livestock mapping and land use predictors produced the best goodness of fit scores. Comparison of regional stratifications indicated that for chickens and ducks, a stratification based on livestock production systems produced the best results; for geese, an agro-ecological stratification produced best results. However, for all species, each method of regional stratification produced significantly better goodness of fit scores than the global model. Here we provide descriptive methods, analytical comparisons, and model output for China's first high resolution, species level poultry distribution maps. Output will be made available to the scientific and public community for use in a wide range of applications from epidemiological studies to livestock policy and management initiatives.

Modelling the distribution of chickens, ducks, and geese in China

PubMed Central

Prosser, Diann J.; Wu, Junxi; Ellis, Erle C.; Gale, Fred; Van Boeckel, Thomas P.; Wint, William; Robinson, Tim; Xiao, Xiangming; Gilbert, Marius

2011-01-01

Global concerns over the emergence of zoonotic pandemics emphasize the need for high-resolution population distribution mapping and spatial modelling. Ongoing efforts to model disease risk in China have been hindered by a lack of available species level distribution maps for poultry. The goal of this study was to develop 1 km resolution population density models for China’s chickens, ducks, and geese. We used an information theoretic approach to predict poultry densities based on statistical relationships between poultry census data and high-resolution agro-ecological predictor variables. Model predictions were validated by comparing goodness of fit measures (root mean square error and correlation coefficient) for observed and predicted values for ¼ of the sample data which was not used for model training. Final output included mean and coefficient of variation maps for each species. We tested the quality of models produced using three predictor datasets and 4 regional stratification methods. For predictor variables, a combination of traditional predictors for livestock mapping and land use predictors produced the best goodness of fit scores. Comparison of regional stratifications indicated that for chickens and ducks, a stratification based on livestock production systems produced the best results; for geese, an agro-ecological stratification produced best results. However, for all species, each method of regional stratification produced significantly better goodness of fit scores than the global model. Here we provide descriptive methods, analytical comparisons, and model output for China’s first high resolution, species level poultry distribution maps. Output will be made available to the scientific and public community for use in a wide range of applications from epidemiological studies to livestock policy and management initiatives. PMID:21765567

Integrating GLL-Weibull Distribution Within a Bayesian Framework for Life Prediction of Shape Memory Alloy Spring Undergoing Thermo-mechanical Fatigue

NASA Astrophysics Data System (ADS)

Kundu, Pradeep; Nath, Tameshwer; Palani, I. A.; Lad, Bhupesh K.

2018-06-01

The present paper tackles an important but unmapped problem of the reliability estimations of smart materials. First, an experimental setup is developed for accelerated life testing of the shape memory alloy (SMA) springs. Generalized log-linear Weibull (GLL-Weibull) distribution-based novel approach is then developed for SMA spring life estimation. Applied stimulus (voltage), elongation and cycles of operation are used as inputs for the life prediction model. The values of the parameter coefficients of the model provide better interpretability compared to artificial intelligence based life prediction approaches. In addition, the model also considers the effect of operating conditions, making it generic for a range of the operating conditions. Moreover, a Bayesian framework is used to continuously update the prediction with the actual degradation value of the springs, thereby reducing the uncertainty in the data and improving the prediction accuracy. In addition, the deterioration of material with number of cycles is also investigated using thermogravimetric analysis and scanning electron microscopy.

The prediction of rotor rotational noise using measured fluctuating blade loads

NASA Technical Reports Server (NTRS)

Hosier, R. N.; Pegg, R. J.; Ramakrishnan, R.

1974-01-01

In tests conducted at the NASA Langley Research Center Helicopter Rotor Test Facility, simultaneous measurements of the high-frequency fluctuating aerodynamic blade loads and far-field radiated noise were made on a full-scale, nontranslating rotor system. After their characteristics were determined, the measured blade loads were used in an existing theory to predict the far-field rotational noise. A comparison of the calculated and measured rotational noise is presented with specific attention given to the effect of blade loading coefficients, chordwise loading distributions, blade loading phases, and observer azimuthal position on the predictions.

A model for dispersion from area sources in convective turbulence. [for air pollution

NASA Technical Reports Server (NTRS)

Crane, G.; Panofsky, H. A.; Zeman, O.

1977-01-01

Four independent estimates of the vertical distribution of the eddy coefficient for dispersion of a passive contaminant from an extensive area source in a convective layer have been presented. The estimates were based on the following methods: (1) a second-order closure prediction, (2) field data of pollutant concentrations over Los Angeles, (3) lab measurements of particle dispersion, and (4) assumption of equality between momentum and mass transfer coefficients in the free convective limit. It is suggested that K-values estimated both from second-order closure theory and from Los Angeles measurements are systematically underestimated.

Scalar utility theory and proportional processing: what does it actually imply?

PubMed Central

Rosenström, Tom; Wiesner, Karoline; Houston, Alasdair I

2017-01-01

Scalar Utility Theory (SUT) is a model used to predict animal and human choice behaviour in the context of reward amount, delay to reward, and variability in these quantities (risk preferences). This article reviews and extends SUT, deriving novel predictions. We show that, contrary to what has been implied in the literature, (1) SUT can predict both risk averse and risk prone behaviour for both reward amounts and delays to reward depending on experimental parameters, (2) SUT implies violations of several concepts of rational behaviour (e.g. it violates strong stochastic transitivity and its equivalents, and leads to probability matching) and (3) SUT can predict, but does not always predict, a linear relationship between risk sensitivity in choices and coefficient of variation in the decision-making experiment. SUT derives from Scalar Expectancy Theory which models uncertainty in behavioural timing using a normal distribution. We show that the above conclusions also hold for other distributions, such as the inverse Gaussian distribution derived from drift-diffusion models. A straightforward way to test the key assumptions of SUT is suggested and possible extensions, future prospects and mechanistic underpinnings are discussed. PMID:27288541

[Spatial distribution prediction of surface soil Pb in a battery contaminated site].

PubMed

Liu, Geng; Niu, Jun-Jie; Zhang, Chao; Zhao, Xin; Guo, Guan-Lin

2014-12-01

In order to enhance the reliability of risk estimation and to improve the accuracy of pollution scope determination in a battery contaminated site with the soil characteristic pollutant Pb, four spatial interpolation models, including Combination Prediction Model (OK(LG) + TIN), kriging model (OK(BC)), Inverse Distance Weighting model (IDW), and Spline model were employed to compare their effects on the spatial distribution and pollution assessment of soil Pb. The results showed that Pb concentration varied significantly and the data was severely skewed. The variation coefficient of the site was higher in the local region. OK(LG) + TIN was found to be more accurate than the other three models in predicting the actual pollution situations of the contaminated site. The prediction accuracy of other models was lower, due to the effect of the principle of different models and datum feature. The interpolation results of OK(BC), IDW and Spline could not reflect the detailed characteristics of seriously contaminated areas, and were not suitable for mapping and spatial distribution prediction of soil Pb in this site. This study gives great contributions and provides useful references for defining the remediation boundary and making remediation decision of contaminated sites.

Scalar utility theory and proportional processing: What does it actually imply?

PubMed

Rosenström, Tom; Wiesner, Karoline; Houston, Alasdair I

2016-09-07

Scalar Utility Theory (SUT) is a model used to predict animal and human choice behaviour in the context of reward amount, delay to reward, and variability in these quantities (risk preferences). This article reviews and extends SUT, deriving novel predictions. We show that, contrary to what has been implied in the literature, (1) SUT can predict both risk averse and risk prone behaviour for both reward amounts and delays to reward depending on experimental parameters, (2) SUT implies violations of several concepts of rational behaviour (e.g. it violates strong stochastic transitivity and its equivalents, and leads to probability matching) and (3) SUT can predict, but does not always predict, a linear relationship between risk sensitivity in choices and coefficient of variation in the decision-making experiment. SUT derives from Scalar Expectancy Theory which models uncertainty in behavioural timing using a normal distribution. We show that the above conclusions also hold for other distributions, such as the inverse Gaussian distribution derived from drift-diffusion models. A straightforward way to test the key assumptions of SUT is suggested and possible extensions, future prospects and mechanistic underpinnings are discussed. Copyright © 2016 Elsevier Ltd. All rights reserved.

Comparisons of some scattering theories with recent scatterometer measurements. [sea roughness radar model

NASA Technical Reports Server (NTRS)

Fung, A. K.; Dome, G.; Moore, R. K.

1977-01-01

The paper compares the predictions of two different types of sea scatter theories with recent scatterometer measurements which indicate the variations of the backscattering coefficient with polarization, incident angle, wind speed, and azimuth angle. Wright's theory (1968) differs from that of Chan and Fung (1977) in two major aspects: (1) Wright uses Phillips' sea spectrum (1966) while Chan and Fung use that of Mitsuyasu and Honda, and (2) Wright uses a modified slick sea slope distribution by Cox and Munk (1954) while Chan and Fung use the slick sea slope distribution of Cox and Munk defined with respect to the plane perpendicular to the look direction. Satisfactory agreements between theory and experimental data are obtained when Chan and Fung's model is used to explain the wind and azimuthal dependence of the scattering coefficient.

Modelling of plasma-based dry reforming: how do uncertainties in the input data affect the calculation results?

NASA Astrophysics Data System (ADS)

Wang, Weizong; Berthelot, Antonin; Zhang, Quanzhi; Bogaerts, Annemie

2018-05-01

One of the main issues in plasma chemistry modeling is that the cross sections and rate coefficients are subject to uncertainties, which yields uncertainties in the modeling results and hence hinders the predictive capabilities. In this paper, we reveal the impact of these uncertainties on the model predictions of plasma-based dry reforming in a dielectric barrier discharge. For this purpose, we performed a detailed uncertainty analysis and sensitivity study. 2000 different combinations of rate coefficients, based on the uncertainty from a log-normal distribution, are used to predict the uncertainties in the model output. The uncertainties in the electron density and electron temperature are around 11% and 8% at the maximum of the power deposition for a 70% confidence level. Still, this can have a major effect on the electron impact rates and hence on the calculated conversions of CO2 and CH4, as well as on the selectivities of CO and H2. For the CO2 and CH4 conversion, we obtain uncertainties of 24% and 33%, respectively. For the CO and H2 selectivity, the corresponding uncertainties are 28% and 14%, respectively. We also identify which reactions contribute most to the uncertainty in the model predictions. In order to improve the accuracy and reliability of plasma chemistry models, we recommend using only verified rate coefficients, and we point out the need for dedicated verification experiments.

Comparing the structure of an emerging market with a mature one under global perturbation

NASA Astrophysics Data System (ADS)

Namaki, A.; Jafari, G. R.; Raei, R.

2011-09-01

In this paper we investigate the Tehran stock exchange (TSE) and Dow Jones Industrial Average (DJIA) in terms of perturbed correlation matrices. To perturb a stock market, there are two methods, namely local and global perturbation. In the local method, we replace a correlation coefficient of the cross-correlation matrix with one calculated from two Gaussian-distributed time series, whereas in the global method, we reconstruct the correlation matrix after replacing the original return series with Gaussian-distributed time series. The local perturbation is just a technical study. We analyze these markets through two statistical approaches, random matrix theory (RMT) and the correlation coefficient distribution. By using RMT, we find that the largest eigenvalue is an influence that is common to all stocks and this eigenvalue has a peak during financial shocks. We find there are a few correlated stocks that make the essential robustness of the stock market but we see that by replacing these return time series with Gaussian-distributed time series, the mean values of correlation coefficients, the largest eigenvalues of the stock markets and the fraction of eigenvalues that deviate from the RMT prediction fall sharply in both markets. By comparing these two markets, we can see that the DJIA is more sensitive to global perturbations. These findings are crucial for risk management and portfolio selection.

A computer program to predict rotor rotational noise of a stationary rotor from blade loading coefficient

NASA Technical Reports Server (NTRS)

Ramakrishnan, R.; Randall, D.; Hosier, R. N.

1976-01-01

The programing language used is FORTRAN IV. A description of all main and subprograms is provided so that any user possessing a FORTRAN compiler and random access capability can adapt the program to his facility. Rotor blade surface-pressure spectra can be used by the program to calculate: (1) blade station loading spectra, (2) chordwise and/or spanwise integrated blade-loading spectra, and (3) far-field rotational noise spectra. Any of five standard inline functions describing the chordwise distribution of the blade loading can be chosen in order to study parametrically the acoustic predictions. The program output consists of both printed and graphic descriptions of the blade-loading coefficient spectra and far-field acoustic spectrum. The results may also be written on binary file for future processing. Examples of the application of the program along with a description of the rotational noise prediction theory on which the program is based are also provided.

Angular decay coefficients of J/ψ mesons at forward rapidity from p+p collisions at √s = 510 GeV

DOE Office of Scientific and Technical Information (OSTI.GOV)

Adare, A.; Azmoun, B.; Aidala, C.

In this paper, we report the first measurement of the full angular distribution for inclusive J/ψ → μ +μ - decays in p+p collisions at √s = 510 GeV. The measurements are made for J/ψ transverse momentum 2 < p T < 10 GeV/c and rapidity 1.2 < y < 2.2 in the Helicity, Collins-Soper, and Gottfried-Jackson reference frames. In all frames the polar coefficient λ θ is strongly negative at low p T and becomes close to zero at high p T, while the azimuthal coefficient λ Φ is close to zero at low p T, and becomes slightlymore » negative at higher p T. The frame-independent coefficient λ ~ is strongly negative at all p T in all frames. Finally, the data are compared to the theoretical predictions provided by nonrelativistic quantum chromodynamics models.« less

Angular decay coefficients of J /ψ mesons at forward rapidity from p +p collisions at √{s }=510 GeV

NASA Astrophysics Data System (ADS)

Adare, A.; Aidala, C.; Ajitanand, N. N.; Akiba, Y.; Akimoto, R.; Alfred, M.; Andrieux, V.; Aoki, K.; Apadula, N.; Aramaki, Y.; Asano, H.; Atomssa, E. T.; Awes, T. C.; Ayuso, C.; Azmoun, B.; Babintsev, V.; Bai, M.; Bandara, N. S.; Bannier, B.; Barish, K. N.; Bathe, S.; Bazilevsky, A.; Beaumier, M.; Beckman, S.; Belmont, R.; Berdnikov, A.; Berdnikov, Y.; Black, D.; Blau, D. S.; Boer, M.; Bok, J. S.; Bownes, E. K.; Boyle, K.; Brooks, M. L.; Bryslawskyj, J.; Buesching, H.; Bumazhnov, V.; Butler, C.; Campbell, S.; Canoa Roman, V.; Cervantes, R.; Chen, C.-H.; Chi, C. Y.; Chiu, M.; Choi, I. J.; Choi, J. B.; Chujo, T.; Citron, Z.; Connors, M.; Cronin, N.; Csanád, M.; Csörgő, T.; Danley, T. W.; Datta, A.; Daugherity, M. S.; David, G.; Deblasio, K.; Dehmelt, K.; Denisov, A.; Deshpande, A.; Desmond, E. J.; Ding, L.; Dion, A.; Dixit, D.; Do, J. H.; Drees, A.; Drees, K. A.; Dumancic, M.; Durham, J. M.; Durum, A.; Dusing, J. P.; Elder, T.; Enokizono, A.; En'yo, H.; Esumi, S.; Fadem, B.; Fan, W.; Feege, N.; Fields, D. E.; Finger, M.; Finger, M.; Fokin, S. L.; Frantz, J. E.; Franz, A.; Frawley, A. D.; Fukuda, Y.; Gal, C.; Gallus, P.; Garg, P.; Ge, H.; Giordano, F.; Glenn, A.; Goto, Y.; Grau, N.; Greene, S. V.; Grosse Perdekamp, M.; Gu, Y.; Gunji, T.; Guragain, H.; Hachiya, T.; Haggerty, J. S.; Hahn, K. I.; Hamagaki, H.; Hamilton, H. F.; Han, S. Y.; Hanks, J.; Hasegawa, S.; Haseler, T. O. S.; He, X.; Hemmick, T. K.; Hill, J. C.; Hill, K.; Hollis, R. S.; Homma, K.; Hong, B.; Hoshino, T.; Hotvedt, N.; Huang, J.; Huang, S.; Ikeda, Y.; Imai, K.; Imazu, Y.; Imrek, J.; Inaba, M.; Iordanova, A.; Isenhower, D.; Ito, Y.; Ivanishchev, D.; Jacak, B. V.; Jeon, S. J.; Jezghani, M.; Ji, Z.; Jia, J.; Jiang, X.; Johnson, B. M.; Joo, E.; Joo, K. S.; Jorjadze, V.; Jouan, D.; Jumper, D. S.; Kang, J. H.; Kang, J. S.; Kapukchyan, D.; Karthas, S.; Kawall, D.; Kazantsev, A. V.; Kempel, T.; Key, J. A.; Khachatryan, V.; Khanzadeev, A.; Kihara, K.; Kim, C.; Kim, D. H.; Kim, D. J.; Kim, E.-J.; Kim, H.-J.; Kim, M.; Kim, M. H.; Kim, Y. K.; Kimball, M. L.; Kincses, D.; Kistenev, E.; Klatsky, J.; Kleinjan, D.; Kline, P.; Koblesky, T.; Kofarago, M.; Koster, J.; Kotler, J. R.; Kotov, D.; Kudo, S.; Kurita, K.; Kurosawa, M.; Kwon, Y.; Lacey, R.; Lajoie, J. G.; Lallow, E. O.; Lebedev, A.; Lee, K. B.; Lee, S.; Lee, S. H.; Leitch, M. J.; Leitgab, M.; Leung, Y. H.; Lewis, N. A.; Li, X.; Lim, S. H.; Liu, L. D.; Liu, M. X.; Loggins, V.-R.; Loggins, V.-R.; Lovasz, K.; Lynch, D.; Majoros, T.; Makdisi, Y. I.; Makek, M.; Malaev, M.; Manion, A.; Manko, V. I.; Mannel, E.; Masuda, H.; McCumber, M.; McGaughey, P. L.; McGlinchey, D.; McKinney, C.; Meles, A.; Mendez, A. R.; Mendoza, M.; Meredith, B.; Miake, Y.; Mignerey, A. C.; Mihalik, D. E.; Miller, A. J.; Milov, A.; Mishra, D. K.; Mitchell, J. T.; Mitsuka, G.; Miyasaka, S.; Mizuno, S.; Montuenga, P.; Moon, T.; Morrison, D. P.; Morrow, S. I. M.; Moukhanova, T. V.; Murakami, T.; Murata, J.; Mwai, A.; Nagai, K.; Nagamiya, S.; Nagashima, K.; Nagashima, T.; Nagle, J. L.; Nagy, M. I.; Nakagawa, I.; Nakagomi, H.; Nakano, K.; Nattrass, C.; Netrakanti, P. K.; Nihashi, M.; Niida, T.; Nouicer, R.; Novák, T.; Novitzky, N.; Novotny, R.; Nyanin, A. S.; O'Brien, E.; Ogilvie, C. A.; Orjuela Koop, J. D.; Osborn, J. D.; Oskarsson, A.; Ottino, G. J.; Ozawa, K.; Pak, R.; Pantuev, V.; Papavassiliou, V.; Park, J. S.; Park, S.; Pate, S. F.; Patel, L.; Patel, M.; Peng, J.-C.; Peng, W.; Perepelitsa, D. V.; Perera, G. D. N.; Peressounko, D. Yu.; Perezlara, C. E.; Perry, J.; Petti, R.; Phipps, M.; Pinkenburg, C.; Pinson, R.; Pisani, R. P.; Press, C. J.; Pun, A.; Purschke, M. L.; Rak, J.; Ravinovich, I.; Read, K. F.; Reynolds, D.; Riabov, V.; Riabov, Y.; Richford, D.; Rinn, T.; Riveli, N.; Roach, D.; Rolnick, S. D.; Rosati, M.; Rowan, Z.; Rubin, J. G.; Runchey, J.; Safonov, A. S.; Saito, N.; Sakaguchi, T.; Sako, H.; Samsonov, V.; Sarsour, M.; Sato, K.; Sato, S.; Sawada, S.; Schaefer, B.; Schmoll, B. K.; Sedgwick, K.; Seele, J.; Seidl, R.; Sen, A.; Seto, R.; Sett, P.; Sexton, A.; Sharma, D.; Shein, I.; Shibata, T.-A.; Shigaki, K.; Shimomura, M.; Shioya, T.; Shukla, P.; Sickles, A.; Silva, C. L.; Silva, J. A.; Silvermyr, D.; Singh, B. K.; Singh, C. P.; Singh, V.; Slunečka, M.; Smith, K. L.; Snowball, M.; Soltz, R. A.; Sondheim, W. E.; Sorensen, S. P.; Sourikova, I. V.; Stankus, P. W.; Stepanov, M.; Stien, H.; Stoll, S. P.; Sugitate, T.; Sukhanov, A.; Sumita, T.; Sun, J.; Syed, S.; Sziklai, J.; Takahara, A.; Takeda, A.; Taketani, A.; Tanida, K.; Tannenbaum, M. J.; Tarafdar, S.; Taranenko, A.; Tarnai, G.; Tieulent, R.; Timilsina, A.; Todoroki, T.; Tomášek, M.; Torii, H.; Towell, C. L.; Towell, M.; Towell, R.; Towell, R. S.; Tserruya, I.; Ueda, Y.; Ujvari, B.; van Hecke, H. W.; Vargyas, M.; Vazquez-Carson, S.; Velkovska, J.; Virius, M.; Vrba, V.; Vukman, N.; Vznuzdaev, E.; Wang, X. R.; Wang, Z.; Watanabe, D.; Watanabe, Y.; Watanabe, Y. S.; Wei, F.; Whitaker, S.; Wolin, S.; Wong, C. P.; Woody, C. L.; Wysocki, M.; Xia, B.; Xu, C.; Xu, Q.; Xue, L.; Yalcin, S.; Yamaguchi, Y. L.; Yamamoto, H.; Yanovich, A.; Yin, P.; Yoo, J. H.; Yoon, I.; Younus, I.; Yu, H.; Yushmanov, I. E.; Zajc, W. A.; Zelenski, A.; Zharko, S.; Zou, L.; Phenix Collaboration

2017-05-01

We report the first measurement of the full angular distribution for inclusive J /ψ →μ+μ- decays in p +p collisions at √{s }=510 GeV . The measurements are made for J /ψ transverse momentum 2

Angular decay coefficients of J/ψ mesons at forward rapidity from p+p collisions at √s = 510 GeV

DOE PAGES

Adare, A.; Azmoun, B.; Aidala, C.; ...

2017-04-13

In this paper, we report the first measurement of the full angular distribution for inclusive J/ψ → μ +μ - decays in p+p collisions at √s = 510 GeV. The measurements are made for J/ψ transverse momentum 2 < p T < 10 GeV/c and rapidity 1.2 < y < 2.2 in the Helicity, Collins-Soper, and Gottfried-Jackson reference frames. In all frames the polar coefficient λ θ is strongly negative at low p T and becomes close to zero at high p T, while the azimuthal coefficient λ Φ is close to zero at low p T, and becomes slightlymore » negative at higher p T. The frame-independent coefficient λ ~ is strongly negative at all p T in all frames. Finally, the data are compared to the theoretical predictions provided by nonrelativistic quantum chromodynamics models.« less

Some methodological aspects of tectonic stress reconstruction based on geological indicators

NASA Astrophysics Data System (ADS)

Sim, Lidiya A.

2012-03-01

The impact of the initial heterogeneity in rocks on the distribution of slickensides (slip planes), which are used to reconstruct local stress-state, is discussed. The stress-state was reconstructed by a graphic variant of the cinematic method. A new type of stress-state - Variation of Stress-State Type (VSST) - is introduced. The VSST is characterized by dislocation vectors originated both by uniaxial compression and uniaxial tension in the same rock volume, i.e. coefficient μσ = 1-2R varies from +1 to -1. The reasons for differences between slip planes from those predicted by the model are discussed. The distribution of slip planes depends on the stress-state type (μσ coefficient) and on the initial heterogeneity of the rocks. A criterion for the identification of tectonic stress rank is suggested. It is based on the models of tectonic stress distribution in the fracture vicinities. Examples of results of tectonic stress studies are given. Studies of tectonic stresses based on geological indicators are of methodological and practical importance.

Effective stress law for the permeability and deformation of four porous limestones

NASA Astrophysics Data System (ADS)

Wang, Y.; Meng, F.; Wang, X.; Baud, P.; Wong, T. F.

2017-12-01

The effective stress behavior of a rock is related to the geometric of its pore space. In a microscopically homogeneous assemblage, effective stress coefficients for permeability, volumetric strain and porosity change are predicted to be equal to or less than unity. Experimental measurements are in basic agreement with this prediction, with exceptions particularly in clay-rich sandstones, for which effective stress coefficient for permeability up to 7 was documented. Little is known about carbonates, but Ghabezloo et al. [2009] studied the permeability of an oolitic limestone (from Nimes, France) with 17% porosity and reported effective stress coefficients up to 2.4. We investigated this phenomenon in Indiana, Leitha, Purbeck, and Thala limestones with porosities of 13-30%. Measurements were made at room temperature on water-saturated samples at confining and pore pressures of 7-15 MPa and 1-3 MPa, respectively. Unlike previous studies limited to the permeability, we also determined the effective stress coefficients for volumetric strain and porosity change. Indiana limestone is oolitic, and not surprisingly its behaviour was similar to Nimes limestone, with an effective stress coefficient for permeability of 2.5. Our Indiana limestone data showed that whereas the effective stress coefficient for volumetric strain was <1, that for porosity change was >1. Measurements on Purbeck and Thala limestones are consistent with these inequalities, with effective stress coefficients for permeability and porosity change >1 and that for volumetric strain <1. Even though Purbeck and Thala limestones are micritic with appreciable amount of quartz and dolomite, microstructural and mercury porosimetry data showed that their pore spaces are similar to the oolitic limestones, in that the pore size distribution is bimodal with significant fractions of both macropores and micropores. Berryman [1992] analyzed theoretically a rock made up of two porous constituents. Our new data are in agreement with inequalities he derived for these effective stress coefficients. For comparison, we also studied Leitha limestone predominately made up of macropores. Our measurements showed that in this case all three effective stress coefficients were <1, as predicted for a microscopically homogeneous assemblage.

Correlation of porous and functional properties of food materials by NMR relaxometry and multivariate analysis.

PubMed

Haiduc, Adrian Marius; van Duynhoven, John

2005-02-01

The porous properties of food materials are known to determine important macroscopic parameters such as water-holding capacity and texture. In conventional approaches, understanding is built from a long process of establishing macrostructure-property relations in a rational manner. Only recently, multivariate approaches were introduced for the same purpose. The model systems used here are oil-in-water emulsions, stabilised by protein, and form complex structures, consisting of fat droplets dispersed in a porous protein phase. NMR time-domain decay curves were recorded for emulsions with varied levels of fat, protein and water. Hardness, dry matter content and water drainage were determined by classical means and analysed for correlation with the NMR data with multivariate techniques. Partial least squares can calibrate and predict these properties directly from the continuous NMR exponential decays and yields regression coefficients higher than 82%. However, the calibration coefficients themselves belong to the continuous exponential domain and do little to explain the connection between NMR data and emulsion properties. Transformation of the NMR decays into a discreet domain with non-negative least squares permits the use of multilinear regression (MLR) on the resulting amplitudes as predictors and hardness or water drainage as responses. The MLR coefficients show that hardness is highly correlated with the components that have T2 distributions of about 20 and 200 ms whereas water drainage is correlated with components that have T2 distributions around 400 and 1800 ms. These T2 distributions very likely correlate with water populations present in pores with different sizes and/or wall mobility. The results for the emulsions studied demonstrate that NMR time-domain decays can be employed to predict properties and to provide insight in the underlying microstructural features.

Discovery of the linear region of Near Infrared Diffuse Reflectance spectra using the Kubelka-Munk theory

NASA Astrophysics Data System (ADS)

Dai, Shengyun; Pan, Xiaoning; Ma, Lijuan; Huang, Xingguo; Du, Chenzhao; Qiao, Yanjiang; Wu, Zhisheng

2018-05-01

Particle size is of great importance for the quantitative model of the NIR diffuse reflectance. In this paper, the effect of sample particle size on the measurement of harpagoside in Radix Scrophulariae powder by near infrared diffuse (NIR) reflectance spectroscopy was explored. High-performance liquid chromatography (HPLC) was employed as a reference method to construct the quantitative particle size model. Several spectral preprocessing methods were compared, and particle size models obtained by different preprocessing methods for establishing the partial least-squares (PLS) models of harpagoside. Data showed that the particle size distribution of 125-150 μm for Radix Scrophulariae exhibited the best prediction ability with R2pre=0.9513, RMSEP=0.1029 mg·g-1, and RPD = 4.78. For the hybrid granularity calibration model, the particle size distribution of 90-180 μm exhibited the best prediction ability with R2pre=0.8919, RMSEP=0.1632 mg·g-1, and RPD = 3.09. Furthermore, the Kubelka-Munk theory was used to relate the absorption coefficient k (concentration-dependent) and scatter coefficient s (particle size-dependent). The scatter coefficient s was calculated based on the Kubelka-Munk theory to study the changes of s after being mathematically preprocessed. A linear relationship was observed between k/s and absorption A within a certain range and the value for k/s was greater than 4. According to this relationship, the model was more accurately constructed with the particle size distribution of 90-180 μm when s was kept constant or in a small linear region. This region provided a good reference for the linear modeling of diffuse reflectance spectroscopy. To establish a diffuse reflectance NIR model, further accurate assessment should be obtained in advance for a precise linear model.

Pulmonary blood flow redistribution by increased gravitational force

NASA Technical Reports Server (NTRS)

Hlastala, M. P.; Chornuk, M. A.; Self, D. A.; Kallas, H. J.; Burns, J. W.; Bernard, S.; Polissar, N. L.; Glenny, R. W.

1998-01-01

This study was undertaken to assess the influence of gravity on the distribution of pulmonary blood flow (PBF) using increased inertial force as a perturbation. PBF was studied in unanesthetized swine exposed to -Gx (dorsal-to-ventral direction, prone position), where G is the magnitude of the force of gravity at the surface of the Earth, on the Armstrong Laboratory Centrifuge at Brooks Air Force Base. PBF was measured using 15-micron fluorescent microspheres, a method with markedly enhanced spatial resolution. Each animal was exposed randomly to -1, -2, and -3 Gx. Pulmonary vascular pressures, cardiac output, heart rate, arterial blood gases, and PBF distribution were measured at each G level. Heterogeneity of PBF distribution as measured by the coefficient of variation of PBF distribution increased from 0.38 +/- 0.05 to 0.55 +/- 0.11 to 0.72 +/- 0.16 at -1, -2, and -3 Gx, respectively. At -1 Gx, PBF was greatest in the ventral and cranial and lowest in the dorsal and caudal regions of the lung. With increased -Gx, this gradient was augmented in both directions. Extrapolation of these values to 0 G predicts a slight dorsal (nondependent) region dominance of PBF and a coefficient of variation of 0.22 in microgravity. Analysis of variance revealed that a fixed component (vascular structure) accounted for 81% and nonstructure components (including gravity) accounted for the remaining 19% of the PBF variance across the entire experiment (all 3 gravitational levels). The results are inconsistent with the predictions of the zone model.

Numerical approach of the injection molding process of fiber-reinforced composite with considering fiber orientation

NASA Astrophysics Data System (ADS)

Nguyen Thi, T. B.; Yokoyama, A.; Ota, K.; Kodama, K.; Yamashita, K.; Isogai, Y.; Furuichi, K.; Nonomura, C.

2014-05-01

One of the most important challenges in the injection molding process of the short-glass fiber/thermoplastic composite parts is being able to predict the fiber orientation, since it controls the mechanical and the physical properties of the final parts. Folgar and Tucker included into the Jeffery equation a diffusive type of term, which introduces a phenomenological coefficient for modeling the randomizing effect of the mechanical interactions between the fibers, to predict the fiber orientation in concentrated suspensions. Their experiments indicated that this coefficient depends on the fiber volume fraction and aspect ratio. However, a definition of the fiber interaction coefficient, which is very necessary in the fiber orientation simulations, hasn't still been proven yet. Consequently, this study proposed a developed fiber interaction model that has been introduced a fiber dynamics simulation in order to obtain a global fiber interaction coefficient. This supposed that the coefficient is a sum function of the fiber concentration, aspect ratio, and angular velocity. The proposed model was incorporated into a computer aided engineering simulation package C-Mold. Short-glass fiber/polyamide-6 composites were produced in the injection molding with the fiber weight concentration of 30 wt.%, 50 wt.%, and 70 wt.%. The physical properties of these composites were examined, and their fiber orientation distributions were measured by micro-computed-tomography equipment μ-CT. The simulation results showed a good agreement with experiment results.

Predicting fundamental frequency from mel-frequency cepstral coefficients to enable speech reconstruction.

PubMed

Shao, Xu; Milner, Ben

2005-08-01

This work proposes a method to reconstruct an acoustic speech signal solely from a stream of mel-frequency cepstral coefficients (MFCCs) as may be encountered in a distributed speech recognition (DSR) system. Previous methods for speech reconstruction have required, in addition to the MFCC vectors, fundamental frequency and voicing components. In this work the voicing classification and fundamental frequency are predicted from the MFCC vectors themselves using two maximum a posteriori (MAP) methods. The first method enables fundamental frequency prediction by modeling the joint density of MFCCs and fundamental frequency using a single Gaussian mixture model (GMM). The second scheme uses a set of hidden Markov models (HMMs) to link together a set of state-dependent GMMs, which enables a more localized modeling of the joint density of MFCCs and fundamental frequency. Experimental results on speaker-independent male and female speech show that accurate voicing classification and fundamental frequency prediction is attained when compared to hand-corrected reference fundamental frequency measurements. The use of the predicted fundamental frequency and voicing for speech reconstruction is shown to give very similar speech quality to that obtained using the reference fundamental frequency and voicing.

Model averaging and muddled multimodel inferences.

PubMed

Cade, Brian S

2015-09-01

Three flawed practices associated with model averaging coefficients for predictor variables in regression models commonly occur when making multimodel inferences in analyses of ecological data. Model-averaged regression coefficients based on Akaike information criterion (AIC) weights have been recommended for addressing model uncertainty but they are not valid, interpretable estimates of partial effects for individual predictors when there is multicollinearity among the predictor variables. Multicollinearity implies that the scaling of units in the denominators of the regression coefficients may change across models such that neither the parameters nor their estimates have common scales, therefore averaging them makes no sense. The associated sums of AIC model weights recommended to assess relative importance of individual predictors are really a measure of relative importance of models, with little information about contributions by individual predictors compared to other measures of relative importance based on effects size or variance reduction. Sometimes the model-averaged regression coefficients for predictor variables are incorrectly used to make model-averaged predictions of the response variable when the models are not linear in the parameters. I demonstrate the issues with the first two practices using the college grade point average example extensively analyzed by Burnham and Anderson. I show how partial standard deviations of the predictor variables can be used to detect changing scales of their estimates with multicollinearity. Standardizing estimates based on partial standard deviations for their variables can be used to make the scaling of the estimates commensurate across models, a necessary but not sufficient condition for model averaging of the estimates to be sensible. A unimodal distribution of estimates and valid interpretation of individual parameters are additional requisite conditions. The standardized estimates or equivalently the t statistics on unstandardized estimates also can be used to provide more informative measures of relative importance than sums of AIC weights. Finally, I illustrate how seriously compromised statistical interpretations and predictions can be for all three of these flawed practices by critiquing their use in a recent species distribution modeling technique developed for predicting Greater Sage-Grouse (Centrocercus urophasianus) distribution in Colorado, USA. These model averaging issues are common in other ecological literature and ought to be discontinued if we are to make effective scientific contributions to ecological knowledge and conservation of natural resources.

Model averaging and muddled multimodel inferences

USGS Publications Warehouse

Cade, Brian S.

2015-01-01

Three flawed practices associated with model averaging coefficients for predictor variables in regression models commonly occur when making multimodel inferences in analyses of ecological data. Model-averaged regression coefficients based on Akaike information criterion (AIC) weights have been recommended for addressing model uncertainty but they are not valid, interpretable estimates of partial effects for individual predictors when there is multicollinearity among the predictor variables. Multicollinearity implies that the scaling of units in the denominators of the regression coefficients may change across models such that neither the parameters nor their estimates have common scales, therefore averaging them makes no sense. The associated sums of AIC model weights recommended to assess relative importance of individual predictors are really a measure of relative importance of models, with little information about contributions by individual predictors compared to other measures of relative importance based on effects size or variance reduction. Sometimes the model-averaged regression coefficients for predictor variables are incorrectly used to make model-averaged predictions of the response variable when the models are not linear in the parameters. I demonstrate the issues with the first two practices using the college grade point average example extensively analyzed by Burnham and Anderson. I show how partial standard deviations of the predictor variables can be used to detect changing scales of their estimates with multicollinearity. Standardizing estimates based on partial standard deviations for their variables can be used to make the scaling of the estimates commensurate across models, a necessary but not sufficient condition for model averaging of the estimates to be sensible. A unimodal distribution of estimates and valid interpretation of individual parameters are additional requisite conditions. The standardized estimates or equivalently the tstatistics on unstandardized estimates also can be used to provide more informative measures of relative importance than sums of AIC weights. Finally, I illustrate how seriously compromised statistical interpretations and predictions can be for all three of these flawed practices by critiquing their use in a recent species distribution modeling technique developed for predicting Greater Sage-Grouse (Centrocercus urophasianus) distribution in Colorado, USA. These model averaging issues are common in other ecological literature and ought to be discontinued if we are to make effective scientific contributions to ecological knowledge and conservation of natural resources.

A 3D analysis of oxygen transfer in a low-cost micro-bioreactor for animal cell suspension culture.

PubMed

Yu, P; Lee, T S; Zeng, Y; Low, H T

2007-01-01

A 3D numerical model was developed to study the flow field and oxygen transport in a micro-bioreactor with a rotating magnetic bar on the bottom to mix the culture medium. The Reynolds number (Re) was kept in the range of 100-716 to ensure laminar environment for animal cell culture. The volumetric oxygen transfer coefficient (k(L)a) was determined from the oxygen concentration distribution. It was found that the effect of the cell consumption on k(L)a could be negligible. A correlation was proposed to predict the liquid-phase oxygen transfer coefficient (k(Lm)) as a function of Re. The overall oxygen transfer coefficient (k(L)) was obtained by the two-resistance model. Another correlation, within an error of 15%, was proposed to estimate the minimum oxygen concentration to avoid cell hypoxia. By combination of the correlations, the maximum cell density, which the present micro-bioreactor could support, was predicted to be in the order of 10(12) cells m(-3). The results are comparable with typical values reported for animal cell growth in mechanically stirred bioreactors.

Extension of Weighted Sum of Gray Gas Data to Mathematical Simulation of Radiative Heat Transfer in a Boiler with Gas-Soot Media

PubMed Central

Nouri-Borujerdi, Ali; Kazi, Salim Newaz

2014-01-01

In this study an expression for soot absorption coefficient is introduced to extend the weighted-sum-of-gray gases data to the furnace medium containing gas-soot mixture in a utility boiler 150 MWe. Heat transfer and temperature distribution of walls and within the furnace space are predicted by zone method technique. Analyses have been done considering both cases of presence and absence of soot particles at 100% load. To validate the proposed soot absorption coefficient, the expression is coupled with the Taylor and Foster's data as well as Truelove's data for CO2-H2O mixture and the total emissivities are calculated and compared with the Truelove's parameters for 3-term and 4-term gray gases plus two soot absorption coefficients. In addition, some experiments were conducted at 100% and 75% loads to measure furnace exit gas temperature as well as the rate of steam production. The predicted results show good agreement with the measured data at the power plant site. PMID:25143981

Extension of weighted sum of gray gas data to mathematical simulation of radiative heat transfer in a boiler with gas-soot media.

PubMed

Gharehkhani, Samira; Nouri-Borujerdi, Ali; Kazi, Salim Newaz; Yarmand, Hooman

2014-01-01

In this study an expression for soot absorption coefficient is introduced to extend the weighted-sum-of-gray gases data to the furnace medium containing gas-soot mixture in a utility boiler 150 MWe. Heat transfer and temperature distribution of walls and within the furnace space are predicted by zone method technique. Analyses have been done considering both cases of presence and absence of soot particles at 100% load. To validate the proposed soot absorption coefficient, the expression is coupled with the Taylor and Foster's data as well as Truelove's data for CO2-H2O mixture and the total emissivities are calculated and compared with the Truelove's parameters for 3-term and 4-term gray gases plus two soot absorption coefficients. In addition, some experiments were conducted at 100% and 75% loads to measure furnace exit gas temperature as well as the rate of steam production. The predicted results show good agreement with the measured data at the power plant site.

Heat-Transfer and Pressure Measurements on a Flat-Face Cylinder at a Mach Number Range of 2.49 to 4.44

NASA Technical Reports Server (NTRS)

Burbank, Paige B.; Stallings, Robert L., Jr.

1959-01-01

Heat-transfer coefficients and pressure distributions were obtained on a 4-inch-diameter flat-face cylinder in the Langley Unitary Plan wind tunnel. The measured stagnation heat-transfer coefficient agrees well with 55 percent of the theoretical value predicted by the modified Sibulkin method for a hemisphere. Pressure measurements indicated the dimensionless velocity gradient parameter r du\\ a(sub t) dx, where x=0 at the stagnation point was approximately 0.3 and invariant throughout the Mach number range from 2.49 to 4.44 and the Reynolds number range from 0.77 x 10(exp 6) to 1.46 x 10(exp 6). The heat-transfer coefficients on the cylindrical afterbody could be predicted with reasonable accuracy by flat-plate theory at an angle of attack of 0 deg. At angles of attack the cylindrical afterbody stagnation-line heat transfer could be computed from swept-cylinder theory for large distances back of the nose when the Reynolds number is based on the distance from the flow reattachment points.

Effect of Particle Size Distribution on Wall Heat Flux in Pulverized-Coal Furnaces and Boilers

NASA Astrophysics Data System (ADS)

Lu, Jun

A mathematical model of combustion and heat transfer within a cylindrical enclosure firing pulverized coal has been developed and tested against two sets of measured data (one is 1993 WSU/DECO Pilot test data, the other one is the International Flame Research Foundation 1964 Test (Beer, 1964)) and one independent code FURN3D from the Argonne National Laboratory (Ahluwalia and IM, 1992). The model called PILC assumes that the system is a sequence of many well-stirred reactors. A char burnout model combining diffusion to the particle surface, pore diffusion, and surface reaction is employed for predicting the char reaction, heat release, and evolution of char. The ash formation model included relates the ash particle size distribution to the particle size distribution of pulverized coal. The optical constants of char and ash particles are calculated from dispersion relations derived from reflectivity, transmissivity and extinction measurements. The Mie theory is applied to determine the extinction and scattering coefficients. The radiation heat transfer is modeled using the virtual zone method, which leads to a set of simultaneous nonlinear algebraic equations for the temperature field within the furnace and on its walls. This enables the heat fluxes to be evaluated. In comparisons with the experimental data and one independent code, the model is successful in predicting gas temperature, wall temperature, and wall radiative flux. When the coal with greater fineness is burnt, the particle size of pulverized coal has a consistent influence on combustion performance: the temperature peak was higher and nearer to burner, the radiation flux to combustor wall increased, and also the absorption and scattering coefficients of the combustion products increased. The effect of coal particle size distribution on absorption and scattering coefficients and wall heat flux is significant. But there is only a small effect on gas temperature and fuel fraction burned; it is speculated that this may be a characteristic special to the test combustor used.

Quantitative broadband ultrasonic backscatter - An approach to nondestructive evaluation in acoustically inhomogeneous materials

NASA Technical Reports Server (NTRS)

Odonnell, M.; Miller, J. G.

1981-01-01

The use of a broadband backscatter technique to obtain the frequency dependence of the longitudinal-wave ultrasonic backscatter coefficient from a collection of scatterers in a solid is investigated. Measurements of the backscatter coefficient were obtained over the range of ultrasonic wave vector magnitude-glass sphere radius product between 0.1 and 3.0 from model systems consisting of dilute suspensions of randomly distributed crown glass spheres in hardened polyester resin. The results of these measurements were in good agreement with theoretical prediction. Consequently, broadband measurements of the ultrasonic backscatter coefficient may represent a useful approach toward characterizing the physical properties of scatterers in intrinsically inhomogeneous materials such as composites, metals, and ceramics, and may represent an approach toward nondestructive evaluation of these materials.

Kinetic modelling of a diesel-polluted clayey soil bioremediation process.

PubMed

Fernández, Engracia Lacasa; Merlo, Elena Moliterni; Mayor, Lourdes Rodríguez; Camacho, José Villaseñor

2016-07-01

A mathematical model is proposed to describe a diesel-polluted clayey soil bioremediation process. The reaction system under study was considered a completely mixed closed batch reactor, which initially contacted a soil matrix polluted with diesel hydrocarbons, an aqueous liquid-specific culture medium and a microbial inoculation. The model coupled the mass transfer phenomena and the distribution of hydrocarbons among four phases (solid, S; water, A; non-aqueous liquid, NAPL; and air, V) with Monod kinetics. In the first step, the model simulating abiotic conditions was used to estimate only the mass transfer coefficients. In the second step, the model including both mass transfer and biodegradation phenomena was used to estimate the biological kinetic and stoichiometric parameters. In both situations, the model predictions were validated with experimental data that corresponded to previous research by the same authors. A correct fit between the model predictions and the experimental data was observed because the modelling curves captured the major trends for the diesel distribution in each phase. The model parameters were compared to different previously reported values found in the literature. Pearson correlation coefficients were used to show the reproducibility level of the model. Copyright © 2016. Published by Elsevier B.V.

The directivity of the sound radiation from panels and openings.

PubMed

Davy, John L

2009-06-01

This paper presents a method for calculating the directivity of the radiation of sound from a panel or opening, whose vibration is forced by the incidence of sound from the other side. The directivity of the radiation depends on the angular distribution of the incident sound energy in the room or duct in whose wall or end the panel or opening occurs. The angular distribution of the incident sound energy is predicted using a model which depends on the sound absorption coefficient of the room or duct surfaces. If the sound source is situated in the room or duct, the sound absorption coefficient model is used in conjunction with a model for the directivity of the sound source. For angles of radiation approaching 90 degrees to the normal to the panel or opening, the effect of the diffraction by the panel or opening, or by the finite baffle in which the panel or opening is mounted, is included. A simple empirical model is developed to predict the diffraction of sound into the shadow zone when the angle of radiation is greater than 90 degrees to the normal to the panel or opening. The method is compared with published experimental results.

Directed and Elliptic Flow of Charged Hadrons in 62.4 GeV Au+Au Collisions

NASA Astrophysics Data System (ADS)

Oldenburg, Markus

2004-10-01

The measurement of the azimuthal momentum distribution of particles produced in heavy-ion collisions reveals insight into the early stage of the system's evolution [1]. It is quantified by the Fourier coefficients vn of the distribution of particle momentum azimuth angle [2]. Theoretical models predict the first Fourier coefficient v1 ("directed flow") to be sensitive to a possible phase transition of normal nuclear matter to a quark-gluon plasma [3]. The second Fourier component v2 ("elliptic flow") is believed to be a signal of early thermalization of the created system of hot and dense nuclear matter [4]. We present results of directed and elliptic flow at √s_NN = 62.4 GeV, as measured by the STAR experiment at RHIC. Comparisons to model predictions and different analysis techniques will be made. [1] P.F. Kolb, J. Sollfrank, and U. Heinz, Phys. Rev. C 62, 054909 (2000). [2] S.A. Voloshin and Y. Zhang, Z. Phys. C 70, 665 (1996). [3] L.P. Csernai and D. Röhrich, Phys. Lett. B 458, 454 (1999). [4] D. Teaney, J. Lauret and E. Shuryak, Phys. Rev. Lett. 86, 4783 (2001).

Laser induced heat source distribution in bio-tissues

NASA Astrophysics Data System (ADS)

Li, Xiaoxia; Fan, Shifu; Zhao, Youquan

2006-09-01

During numerical simulation of laser and tissue thermal interaction, the light fluence rate distribution should be formularized and constituted to the source term in the heat transfer equation. Usually the solution of light irradiative transport equation is given in extreme conditions such as full absorption (Lambert-Beer Law), full scattering (Lubelka-Munk theory), most scattering (Diffusion Approximation) et al. But in specific conditions, these solutions will induce different errors. The usually used Monte Carlo simulation (MCS) is more universal and exact but has difficulty to deal with dynamic parameter and fast simulation. Its area partition pattern has limits when applying FEM (finite element method) to solve the bio-heat transfer partial differential coefficient equation. Laser heat source plots of above methods showed much difference with MCS. In order to solve this problem, through analyzing different optical actions such as reflection, scattering and absorption on the laser induced heat generation in bio-tissue, a new attempt was made out which combined the modified beam broaden model and the diffusion approximation model. First the scattering coefficient was replaced by reduced scattering coefficient in the beam broaden model, which is more reasonable when scattering was treated as anisotropic scattering. Secondly the attenuation coefficient was replaced by effective attenuation coefficient in scattering dominating turbid bio-tissue. The computation results of the modified method were compared with Monte Carlo simulation and showed the model provided reasonable predictions of heat source term distribution than past methods. Such a research is useful for explaining the physical characteristics of heat source in the heat transfer equation, establishing effective photo-thermal model, and providing theory contrast for related laser medicine experiments.

Inferring the distribution of mutational effects on fitness in Drosophila.

PubMed

Loewe, Laurence; Charlesworth, Brian

2006-09-22

The properties of the distribution of deleterious mutational effects on fitness (DDME) are of fundamental importance for evolutionary genetics. Since it is extremely difficult to determine the nature of this distribution, several methods using various assumptions about the DDME have been developed, for the purpose of parameter estimation. We apply a newly developed method to DNA sequence polymorphism data from two Drosophila species and compare estimates of the parameters of the distribution of the heterozygous fitness effects of amino acid mutations for several different distribution functions. The results exclude normal and gamma distributions, since these predict too few effectively lethal mutations and power-law distributions as a result of predicting too many lethals. Only the lognormal distribution appears to fit both the diversity data and the frequency of lethals. This DDME arises naturally in complex systems when independent factors contribute multiplicatively to an increase in fitness-reducing damage. Several important parameters, such as the fraction of effectively neutral non-synonymous mutations and the harmonic mean of non-neutral selection coefficients, are robust to the form of the DDME. Our results suggest that the majority of non-synonymous mutations in Drosophila are under effective purifying selection.

Mode-independent attenuation in evanescent-field sensors

NASA Astrophysics Data System (ADS)

Gnewuch, Harald; Renner, Hagen

1995-03-01

Generally, the total power attenuation in multimode evanescent-field sensor waveguides is nonproportional to the bulk absorbance because the modal attenuation constants differ. Hence a direct measurement is difficult and is additionally aggravated because the waveguide absorbance is highly sensitive to the specific launching conditions at the waveguide input. A general asymptotic formula for the modal power attenuation in strongly asymmetric inhomogeneous planar waveguides with arbitrarily distributed weak absorption in the low-index superstrate is derived. Explicit expressions for typical refractive-index profiles are given. Except when very close to the cutoff, the predicted asymptotic attenuation behavior agrees well with exact calculations. The ratio of TM versus TE absorption has been derived to be (2 - n0 2/nf2 ) for arbitrary profiles. Waveguides with a linear refractive-index profile show mode-independent attenuation coefficients within each polarization. Further, the asymptotic sensitivity is independent of the wavelength, so that it should be possible to directly measure the spectral variation of the bulk absorption. The mode independence of the attenuation has been verified experimentally for a second-order polynomial profile, which is close to a linear refractive-index distribution. In contrast, the attenuation in the step-profile waveguide has been found to depend strongly on the mode number, as predicted by theory. A strong spread of the modal attenuation coefficients is also predicted for the parabolic-profile waveguide sensor.

Biotransformation and sorption of trace organic compounds in biological nutrient removal treatment systems.

PubMed

Lakshminarasimman, Narasimman; Quiñones, Oscar; Vanderford, Brett J; Campo-Moreno, Pablo; Dickenson, Eric V; McAvoy, Drew C

2018-05-28

This study determined biotransformation rates (k bio ) and sorption-distribution coefficients (K d ) for a select group of trace organic compounds (TOrCs) in anaerobic, anoxic, and aerobic activated sludge collected from two different biological nutrient removal (BNR) treatment systems located in Nevada (NV) and Ohio (OH) in the United States (US). The NV and OH facilities operated at solids retention times (SRTs) of 8 and 23 days, respectively. Using microwave-assisted extraction, the biotransformation rates of the chosen TOrCs were measured in the total mixed liquor. Sulfamethoxazole, trimethoprim, and atenolol biotransformed in all three redox regimes irrespective of the activated sludge source. The biotransformation of N, N-diethyl-3-methylbenzamide (DEET), triclosan, and benzotriazole was observed in aerobic activated sludge from both treatment plants; however, anoxic biotransformation of these three compounds was seen only in anoxic activated sludge from NV. Carbamazepine was recalcitrant in all three redox regimes and both sources of activated sludge. Atenolol and DEET had greater biotransformation rates in activated sludge with a higher SRT (23 days), while trimethoprim had a higher biotransformation rate in activated sludge with a lower SRT (8 days). The remaining compounds did not show any dependence on SRT. Lyophilized, heat inactivated sludge solids were used to determine the sorption-distribution coefficients. Triclosan was the most sorptive compound followed by carbamazepine, sulfamethoxazole, DEET, and benzotriazole. The sorption-distribution coefficients were similar across redox conditions and sludge sources. The biotransformation rates and sorption-distribution coefficients determined in this study can be used to improve fate prediction of the target TOrCs in BNR treatment systems. Copyright © 2018. Published by Elsevier B.V.

Extensively Parameterized Mutation-Selection Models Reliably Capture Site-Specific Selective Constraint.

PubMed

Spielman, Stephanie J; Wilke, Claus O

2016-11-01

The mutation-selection model of coding sequence evolution has received renewed attention for its use in estimating site-specific amino acid propensities and selection coefficient distributions. Two computationally tractable mutation-selection inference frameworks have been introduced: One framework employs a fixed-effects, highly parameterized maximum likelihood approach, whereas the other employs a random-effects Bayesian Dirichlet Process approach. While both implementations follow the same model, they appear to make distinct predictions about the distribution of selection coefficients. The fixed-effects framework estimates a large proportion of highly deleterious substitutions, whereas the random-effects framework estimates that all substitutions are either nearly neutral or weakly deleterious. It remains unknown, however, how accurately each method infers evolutionary constraints at individual sites. Indeed, selection coefficient distributions pool all site-specific inferences, thereby obscuring a precise assessment of site-specific estimates. Therefore, in this study, we use a simulation-based strategy to determine how accurately each approach recapitulates the selective constraint at individual sites. We find that the fixed-effects approach, despite its extensive parameterization, consistently and accurately estimates site-specific evolutionary constraint. By contrast, the random-effects Bayesian approach systematically underestimates the strength of natural selection, particularly for slowly evolving sites. We also find that, despite the strong differences between their inferred selection coefficient distributions, the fixed- and random-effects approaches yield surprisingly similar inferences of site-specific selective constraint. We conclude that the fixed-effects mutation-selection framework provides the more reliable software platform for model application and future development. © The Author 2016. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Evaluating the Applicability of Phi Coefficient in Indicating Habitat Preferences of Forest Soil Fauna Based on a Single Field Study in Subtropical China.

PubMed

Cui, Yang; Wang, Silong; Yan, Shaokui

2016-01-01

Phi coefficient directly depends on the frequencies of occurrence of organisms and has been widely used in vegetation ecology to analyse the associations of organisms with site groups, providing a characterization of ecological preference, but its application in soil ecology remains rare. Based on a single field experiment, this study assessed the applicability of phi coefficient in indicating the habitat preferences of soil fauna, through comparing phi coefficient-induced results with those of ordination methods in charactering soil fauna-habitat(factors) relationships. Eight different habitats of soil fauna were implemented by reciprocal transfer of defaunated soil cores between two types of subtropical forests. Canonical correlation analysis (CCorA) showed that ecological patterns of fauna-habitat relationships and inter-fauna taxa relationships expressed, respectively, by phi coefficients and predicted abundances calculated from partial redundancy analysis (RDA), were extremely similar, and a highly significant relationship between the two datasets was observed (Pillai's trace statistic = 1.998, P = 0.007). In addition, highly positive correlations between phi coefficients and predicted abundances for Acari, Collembola, Nematode and Hemiptera were observed using linear regression analysis. Quantitative relationships between habitat preferences and soil chemical variables were also obtained by linear regression, which were analogous to the results displayed in a partial RDA biplot. Our results suggest that phi coefficient could be applicable on a local scale in evaluating habitat preferences of soil fauna at coarse taxonomic levels, and that the phi coefficient-induced information, such as ecological preferences and the associated quantitative relationships with habitat factors, will be largely complementary to the results of ordination methods. The application of phi coefficient in soil ecology may extend our knowledge about habitat preferences and distribution-abundance relationships, which will benefit the understanding of biodistributions and variations in community compositions in the soil. Similar studies in other places and scales apart from our local site will be need for further evaluation of phi coefficient.

Evaluating the Applicability of Phi Coefficient in Indicating Habitat Preferences of Forest Soil Fauna Based on a Single Field Study in Subtropical China

PubMed Central

Cui, Yang; Wang, Silong; Yan, Shaokui

2016-01-01

Phi coefficient directly depends on the frequencies of occurrence of organisms and has been widely used in vegetation ecology to analyse the associations of organisms with site groups, providing a characterization of ecological preference, but its application in soil ecology remains rare. Based on a single field experiment, this study assessed the applicability of phi coefficient in indicating the habitat preferences of soil fauna, through comparing phi coefficient-induced results with those of ordination methods in charactering soil fauna-habitat(factors) relationships. Eight different habitats of soil fauna were implemented by reciprocal transfer of defaunated soil cores between two types of subtropical forests. Canonical correlation analysis (CCorA) showed that ecological patterns of fauna-habitat relationships and inter-fauna taxa relationships expressed, respectively, by phi coefficients and predicted abundances calculated from partial redundancy analysis (RDA), were extremely similar, and a highly significant relationship between the two datasets was observed (Pillai's trace statistic = 1.998, P = 0.007). In addition, highly positive correlations between phi coefficients and predicted abundances for Acari, Collembola, Nematode and Hemiptera were observed using linear regression analysis. Quantitative relationships between habitat preferences and soil chemical variables were also obtained by linear regression, which were analogous to the results displayed in a partial RDA biplot. Our results suggest that phi coefficient could be applicable on a local scale in evaluating habitat preferences of soil fauna at coarse taxonomic levels, and that the phi coefficient-induced information, such as ecological preferences and the associated quantitative relationships with habitat factors, will be largely complementary to the results of ordination methods. The application of phi coefficient in soil ecology may extend our knowledge about habitat preferences and distribution-abundance relationships, which will benefit the understanding of biodistributions and variations in community compositions in the soil. Similar studies in other places and scales apart from our local site will be need for further evaluation of phi coefficient. PMID:26930593

Predicting the Activity Coefficients of Free-Solvent for Concentrated Globular Protein Solutions Using Independently Determined Physical Parameters

PubMed Central

McBride, Devin W.; Rodgers, Victor G. J.

2013-01-01

The activity coefficient is largely considered an empirical parameter that was traditionally introduced to correct the non-ideality observed in thermodynamic systems such as osmotic pressure. Here, the activity coefficient of free-solvent is related to physically realistic parameters and a mathematical expression is developed to directly predict the activity coefficients of free-solvent, for aqueous protein solutions up to near-saturation concentrations. The model is based on the free-solvent model, which has previously been shown to provide excellent prediction of the osmotic pressure of concentrated and crowded globular proteins in aqueous solutions up to near-saturation concentrations. Thus, this model uses only the independently determined, physically realizable quantities: mole fraction, solvent accessible surface area, and ion binding, in its prediction. Predictions are presented for the activity coefficients of free-solvent for near-saturated protein solutions containing either bovine serum albumin or hemoglobin. As a verification step, the predictability of the model for the activity coefficient of sucrose solutions was evaluated. The predicted activity coefficients of free-solvent are compared to the calculated activity coefficients of free-solvent based on osmotic pressure data. It is observed that the predicted activity coefficients are increasingly dependent on the solute-solvent parameters as the protein concentration increases to near-saturation concentrations. PMID:24324733

Confined active Brownian particles: theoretical description of propulsion-induced accumulation

NASA Astrophysics Data System (ADS)

Das, Shibananda; Gompper, Gerhard; Winkler, Roland G.

2018-01-01

The stationary-state distribution function of confined active Brownian particles (ABPs) is analyzed by computer simulations and analytical calculations. We consider a radial harmonic as well as an anharmonic confinement potential. In the simulations, the ABP is propelled with a prescribed velocity along a body-fixed direction, which is changing in a diffusive manner. For the analytical approach, the Cartesian components of the propulsion velocity are assumed to change independently; active Ornstein-Uhlenbeck particle (AOUP). This results in very different velocity distribution functions. The analytical solution of the Fokker-Planck equation for an AOUP in a harmonic potential is presented and a conditional distribution function is provided for the radial particle distribution at a given magnitude of the propulsion velocity. This conditional probability distribution facilitates the description of the coupling of the spatial coordinate and propulsion, which yields activity-induced accumulation of particles. For the anharmonic potential, a probability distribution function is derived within the unified colored noise approximation. The comparison of the simulation results with theoretical predictions yields good agreement for large rotational diffusion coefficients, e.g. due to tumbling, even for large propulsion velocities (Péclet numbers). However, we find significant deviations already for moderate Péclet number, when the rotational diffusion coefficient is on the order of the thermal one.

Full-coverage film cooling on flat, isothermal surfaces: Data and predictions

NASA Technical Reports Server (NTRS)

Crawford, M. E.; Kays, W. M.; Moffat, R. J.

1980-01-01

The heat transfer and fluid mechanics characteristics of full-coverage film cooling were investigated. The results for flat, isothermal plates for three injection geometries (normal, slant, and compound angle) are summarized and data concerning the spanwise distribution of the heat transfer coefficient within the blowing region are presented. Data are also presented for two different numbers of rows of holes (6 and 11). The experimental results summarized can be predicted with a two dimensional boundary layer code, STANCOOL, by providing descriptors of the injection parameters as inputs.

Effect of Interfacial Turbulence and Accommodation Coefficient on CFD Predictions of Pressurization and Pressure Control in Cryogenic Storage Tank

NASA Technical Reports Server (NTRS)

Kassemi, Mohammad; Kartuzova, Olga; Hylton, Sonya

2015-01-01

Laminar models agree closely with the pressure evolution and vapor phase temperature stratification but under-predict liquid temperatures. Turbulent SST k-w and k-e models under-predict the pressurization rate and extent of stratification in the vapor but represent liquid temperature distributions fairly well. These conclusions seem to equally apply to large cryogenic tank simulations as well as small scale simulant fluid pressurization cases. Appropriate turbulent models that represent both interfacial and bulk vapor phase turbulence with greater fidelity are needed. Application of LES models to the tank pressurization problem can serve as a starting point.

Diffusion coefficients in organic-water solutions and comparison with Stokes-Einstein predictions

NASA Astrophysics Data System (ADS)

Evoy, E.; Kamal, S.; Bertram, A. K.

2017-12-01

Diffusion coefficients of organic species in particles containing secondary organic material (SOM) are necessary for predicting the growth and reactivity of these particles in the atmosphere. Previously, the Stokes-Einstein equation combined with viscosity measurements have been used to predict these diffusion coefficients. However, the accuracy of the Stokes-Einstein equation for predicting diffusion coefficients in SOM-water particles has not been quantified. To test the Stokes-Einstein equation, diffusion coefficients of fluorescent organic probe molecules were measured in citric acid-water and sorbitol-water solutions. These solutions were used as proxies for SOM-water particles found in the atmosphere. Measurements were performed as a function of water activity, ranging from 0.26-0.86, and as a function of viscosity ranging from 10-3 to 103 Pa s. Diffusion coefficients were measured using fluorescence recovery after photobleaching. The measured diffusion coefficients were compared with predictions made using the Stokes-Einstein equation combined with literature viscosity data. Within the uncertainties of the measurements, the measured diffusion coefficients agreed with the predicted diffusion coefficients, in all cases.

On the p, q-binomial distribution and the Ising model

NASA Astrophysics Data System (ADS)

Lundow, P. H.; Rosengren, A.

2010-08-01

We employ p, q-binomial coefficients, a generalisation of the binomial coefficients, to describe the magnetisation distributions of the Ising model. For the complete graph this distribution corresponds exactly to the limit case p = q. We apply our investigation to the simple d-dimensional lattices for d = 1, 2, 3, 4, 5 and fit p, q-binomial distributions to our data, some of which are exact but most are sampled. For d = 1 and d = 5, the magnetisation distributions are remarkably well-fitted by p,q-binomial distributions. For d = 4 we are only slightly less successful, while for d = 2, 3 we see some deviations (with exceptions!) between the p, q-binomial and the Ising distribution. However, at certain temperatures near T c the statistical moments of the fitted distribution agree with the moments of the sampled data within the precision of sampling. We begin the paper by giving results of the behaviour of the p, q-distribution and its moment growth exponents given a certain parameterisation of p, q. Since the moment exponents are known for the Ising model (or at least approximately for d = 3) we can predict how p, q should behave and compare this to our measured p, q. The results speak in favour of the p, q-binomial distribution's correctness regarding its general behaviour in comparison to the Ising model. The full extent to which they correctly model the Ising distribution, however, is not settled.

Static Aeroelastic Predictions for a Transonic Transport Model Using an Unstructured-Grid Flow Solver Coupled With a Structural Plate Technique

NASA Technical Reports Server (NTRS)

Allison, Dennis O.; Cavallo, Peter A.

2003-01-01

An equivalent-plate structural deformation technique was coupled with a steady-state unstructured-grid three-dimensional Euler flow solver and a two-dimensional strip interactive boundary-layer technique. The objective of the research was to assess the extent to which a simple accounting for static model deformations could improve correlations with measured wing pressure distributions and lift coefficients at transonic speeds. Results were computed and compared to test data for a wing-fuselage model of a generic low-wing transonic transport at a transonic cruise condition over a range of Reynolds numbers and dynamic pressures. The deformations significantly improved correlations with measured wing pressure distributions and lift coefficients. This method provided a means of quantifying the role of dynamic pressure in wind-tunnel studies of Reynolds number effects for transonic transport models.

NONLINEAR OPTICAL PHENOMENA: Self-reflection in a system of excitons and biexcitons in semiconductors

NASA Astrophysics Data System (ADS)

Khadzhi, P. I.; Lyakhomskaya, K. D.

1999-10-01

The characteristic features of the self-reflection of a powerful electromagnetic wave in a system of coherent excitons and biexcitons in semiconductors were investigated as one of the manifestations of the nonlinear optical skin effect. It was found that a monotonically decreasing standing wave with an exponentially falling spatial tail is formed in the surface region of a semiconductor. Under the influence of the field of a powerful pulse, an optically homogeneous medium is converted into one with distributed feedback. The appearance of spatially separated narrow peaks of the refractive index, extinction coefficient, and reflection coefficient is predicted.

Modelling the distribution of domestic ducks in Monsoon Asia

USGS Publications Warehouse

Van Bockel, Thomas P.; Prosser, Diann; Franceschini, Gianluca; Biradar, Chandra; Wint, William; Robinson, Tim; Gilbert, Marius

2011-01-01

Domestic ducks are considered to be an important reservoir of highly pathogenic avian influenza (HPAI), as shown by a number of geospatial studies in which they have been identified as a significant risk factor associated with disease presence. Despite their importance in HPAI epidemiology, their large-scale distribution in Monsoon Asia is poorly understood. In this study, we created a spatial database of domestic duck census data in Asia and used it to train statistical distribution models for domestic duck distributions at a spatial resolution of 1km. The method was based on a modelling framework used by the Food and Agriculture Organisation to produce the Gridded Livestock of the World (GLW) database, and relies on stratified regression models between domestic duck densities and a set of agro-ecological explanatory variables. We evaluated different ways of stratifying the analysis and of combining the prediction to optimize the goodness of fit of the predictions. We found that domestic duck density could be predicted with reasonable accuracy (mean RMSE and correlation coefficient between log-transformed observed and predicted densities being 0.58 and 0.80, respectively), using a stratification based on livestock production systems. We tested the use of artificially degraded data on duck distributions in Thailand and Vietnam as training data, and compared the modelled outputs with the original high-resolution data. This showed, for these two countries at least, that these approaches could be used to accurately disaggregate provincial level (administrative level 1) statistical data to provide high resolution model distributions.

Predicting the probability of slip in gait: methodology and distribution study.

PubMed

Gragg, Jared; Yang, James

2016-01-01

The likelihood of a slip is related to the available and required friction for a certain activity, here gait. Classical slip and fall analysis presumed that a walking surface was safe if the difference between the mean available and required friction coefficients exceeded a certain threshold. Previous research was dedicated to reformulating the classical slip and fall theory to include the stochastic variation of the available and required friction when predicting the probability of slip in gait. However, when predicting the probability of a slip, previous researchers have either ignored the variation in the required friction or assumed the available and required friction to be normally distributed. Also, there are no published results that actually give the probability of slip for various combinations of required and available frictions. This study proposes a modification to the equation for predicting the probability of slip, reducing the previous equation from a double-integral to a more convenient single-integral form. Also, a simple numerical integration technique is provided to predict the probability of slip in gait: the trapezoidal method. The effect of the random variable distributions on the probability of slip is also studied. It is shown that both the required and available friction distributions cannot automatically be assumed as being normally distributed. The proposed methods allow for any combination of distributions for the available and required friction, and numerical results are compared to analytical solutions for an error analysis. The trapezoidal method is shown to be highly accurate and efficient. The probability of slip is also shown to be sensitive to the input distributions of the required and available friction. Lastly, a critical value for the probability of slip is proposed based on the number of steps taken by an average person in a single day.

Assessment of natural attenuation of aromatic hydrocarbons in groundwater near a former manufactured-gas plant, South Carolina, USA

USGS Publications Warehouse

Landmeyer, J.E.; Chapelle, F.H.; Petkewich, M.D.; Bradley, P.M.

1998-01-01

Shallow, anaerobic groundwater near a former manufactured-gas plant (MGP) in Charleston, South Carolina, USA, contains mono- and polycyclic aromatic hydrocarbons (MAHs and PAHs, respectively). Between 1994 and 1997, a combination of field, laboratory, and numerical-flow and transport-model investigations were made to assess natural attenuation processes affecting MAH and PAH distributions. This assessment included determination of adsorption coefficients (K(ad)) and first-order biodegradation rate constants (K(bio)) using aquifer material from the MGP site and adjacent properties. Naphthalene adsorption (K(ad) = 1.35 x 10-7 m3/mg) to aquifer sediments was higher than toluene adsorption (K(ad) = 9.34 x 10-10 m3/mg), suggesting preferential toluene transport relative to naphthalene. However, toluene and benzene distributions measured in January 1994 were smaller than the naphthalene distribution. This scenario can be explained, in part, by the differences between biodegradation rates of the compounds. Aerobic first-order rate constants of 14C-toluene, 14C-benzene, and 14C-naphthalene degradation were similar (-0.84, -0.03, and 0.88 day-1, respectively), but anaerobic rate constants were higher for toluene and benzene (-0.002 and -0.00014 day-1, respectively) than for naphthalene (-0.000046 day-1). Both areal and cross-sectional numerical simulations were used to test the hypothesis suggested by these rate differences that MAH compounds will be contained relative to PAHs. Predictive simulations indicated that the distributions of toluene and benzene reach steady-state conditions before groundwater flow lines discharge to an adjacent surface-water body, but do discharge low concentrations of naphthalene. Numerical predictions were 'audited' by measuring concentrations of naphthalene, toluene, and benzene at the site in early 1997. Measured naphthalene and toluene concentrations were substantially reduced and the areal extent of contamination smaller than was both observed in January 1994 and predicted for 1997. Measured 1997 benzene concentrations and distribution were shown to be relatively unchanged from those measured in 1994, and similar to predictions for 1997.The natural attenuation processes affecting mono- and polycyclic aromatic hydrocarbons (MAHs and PAHs, respectively) distributions in groundwater near a former manufactured-gas plant in South Carolina, USA was evaluated. This assessment included determination of adsorption coefficients and first-order biodegradation rate constants. Detailed results obtained in the study are presented.

Bypass Flow Resistance in Prismatic Gas-Cooled Nuclear Reactors

DOE PAGES

McEligot, Donald M.; Johnson, Richard W.

2016-12-20

Available computational fluid dynamics (CFD) predictions of pressure distributions in the vertical bypass flow between blocks in a prismatic gas-cooled reactor (GCR) have been analyzed to deduce apparent friction factors and loss coefficients for systems and network codes. We performed calculations for vertical gap spacings "s" of 2, 6 and 10 mm, horizontal gaps between the blocks of two mm and two flow rates, giving a range of gap Reynolds numbers Re Dh of about 40 to 5300. Laminar predictions of the fully-developed friction factor f fd were about three to ten per cent lower than the classical infinitely-wide channelmore » In the entry region, the local apparent friction factor was slightly higher than the classic idealized case but the hydraulic entry length L hy was approximately the same. The per cent reduction in flow resistance was greater than the per cent increase in flow area at the vertical corners of the blocks. The standard k-ϵ model was employed for flows expected to be turbulent. Its predictions of f fd and flow resistance were significantly higher than direct numerical simulations for the classic case; the value of L hy was about thirty gap spacings. Initial quantitative information for entry coefficients and loss coefficients for the expansion-contraction junctions between blocks is also presented. Our study demonstrates how CFD predictions can be employed to provide integral quantities needed in systems and network codes.« less

Bypass Flow Resistance in Prismatic Gas-Cooled Nuclear Reactors

DOE Office of Scientific and Technical Information (OSTI.GOV)

McEligot, Donald M.; Johnson, Richard W.

Available computational fluid dynamics (CFD) predictions of pressure distributions in the vertical bypass flow between blocks in a prismatic gas-cooled reactor (GCR) have been analyzed to deduce apparent friction factors and loss coefficients for systems and network codes. We performed calculations for vertical gap spacings "s" of 2, 6 and 10 mm, horizontal gaps between the blocks of two mm and two flow rates, giving a range of gap Reynolds numbers Re Dh of about 40 to 5300. Laminar predictions of the fully-developed friction factor f fd were about three to ten per cent lower than the classical infinitely-wide channelmore » In the entry region, the local apparent friction factor was slightly higher than the classic idealized case but the hydraulic entry length L hy was approximately the same. The per cent reduction in flow resistance was greater than the per cent increase in flow area at the vertical corners of the blocks. The standard k-ϵ model was employed for flows expected to be turbulent. Its predictions of f fd and flow resistance were significantly higher than direct numerical simulations for the classic case; the value of L hy was about thirty gap spacings. Initial quantitative information for entry coefficients and loss coefficients for the expansion-contraction junctions between blocks is also presented. Our study demonstrates how CFD predictions can be employed to provide integral quantities needed in systems and network codes.« less

Six-Year Nitrogen-Water Interaction Shifts the Frequency Distribution and Size Inequality of the First-Order Roots of Fraxinus mandschurica in a Mixed Mature Pinus koraiensis Forest.

PubMed

Wang, Cunguo; Geng, Zhenzhen; Chen, Zhao; Li, Jiandong; Guo, Wei; Zhao, Tian-Hong; Cao, Ying; Shen, Si; Jin, Daming; Li, Mai-He

2017-01-01

The variation in fine root traits in terms of size inequality at the individual root level can be identified as a strategy for adapting to the drastic changes in soil water and nutrient availabilities. The Gini and Lorenz asymmetry coefficients have been applied to describe the overall degree of size inequality, which, however, are neglected when conventional statistical means are calculated. Here, we used the Gini coefficient, Lorenz asymmetry coefficient and statistical mean in an investigation of Fraxinus mandschurica roots in a mixed mature Pinus koraiensis forest on Changbai Mountain, China. We analyzed 967 individual roots to determine the responses of length, diameter and area of the first-order roots and of branching intensity to 6 years of nitrogen addition (N), rainfall reduction (W) and their combination (NW). We found that first-order roots had a significantly greater average length and area but had smaller Gini coefficients in NW plots compared to in control plots (CK). Furthermore, the relationship between first-order root length and branching intensity was negative in CK, N, and W plots but positive in NW plots. The Lorenz asymmetry coefficient was >1 for the first-order root diameter in NW and W plots as well as for branching intensity in N plots. The bimodal frequency distribution of the first-order root length in NW plots differed clearly from the unimodal one in CK, N, and W plots. These results demonstrate that not only the mean but also the variation and the distribution mode of the first-order roots of F. mandschurica respond to soil nitrogen and water availability. The changes in size inequality of the first-order root traits suggest that Gini and Lorenz asymmetry coefficients can serve as informative parameters in ecological investigations of roots to improve our ability to predict how trees will respond to a changing climate at the individual root level.

Six-Year Nitrogen–Water Interaction Shifts the Frequency Distribution and Size Inequality of the First-Order Roots of Fraxinus mandschurica in a Mixed Mature Pinus koraiensis Forest

PubMed Central

Wang, Cunguo; Geng, Zhenzhen; Chen, Zhao; Li, Jiandong; Guo, Wei; Zhao, Tian-Hong; Cao, Ying; Shen, Si; Jin, Daming; Li, Mai-He

2017-01-01

The variation in fine root traits in terms of size inequality at the individual root level can be identified as a strategy for adapting to the drastic changes in soil water and nutrient availabilities. The Gini and Lorenz asymmetry coefficients have been applied to describe the overall degree of size inequality, which, however, are neglected when conventional statistical means are calculated. Here, we used the Gini coefficient, Lorenz asymmetry coefficient and statistical mean in an investigation of Fraxinus mandschurica roots in a mixed mature Pinus koraiensis forest on Changbai Mountain, China. We analyzed 967 individual roots to determine the responses of length, diameter and area of the first-order roots and of branching intensity to 6 years of nitrogen addition (N), rainfall reduction (W) and their combination (NW). We found that first-order roots had a significantly greater average length and area but had smaller Gini coefficients in NW plots compared to in control plots (CK). Furthermore, the relationship between first-order root length and branching intensity was negative in CK, N, and W plots but positive in NW plots. The Lorenz asymmetry coefficient was >1 for the first-order root diameter in NW and W plots as well as for branching intensity in N plots. The bimodal frequency distribution of the first-order root length in NW plots differed clearly from the unimodal one in CK, N, and W plots. These results demonstrate that not only the mean but also the variation and the distribution mode of the first-order roots of F. mandschurica respond to soil nitrogen and water availability. The changes in size inequality of the first-order root traits suggest that Gini and Lorenz asymmetry coefficients can serve as informative parameters in ecological investigations of roots to improve our ability to predict how trees will respond to a changing climate at the individual root level. PMID:29018474

An Examination of Diameter Density Prediction with k-NN and Airborne Lidar

DOE PAGES

Strunk, Jacob L.; Gould, Peter J.; Packalen, Petteri; ...

2017-11-16

While lidar-based forest inventory methods have been widely demonstrated, performances of methods to predict tree diameters with airborne lidar (lidar) are not well understood. One cause for this is that the performance metrics typically used in studies for prediction of diameters can be difficult to interpret, and may not support comparative inferences between sampling designs and study areas. To help with this problem we propose two indices and use them to evaluate a variety of lidar and k nearest neighbor (k-NN) strategies for prediction of tree diameter distributions. The indices are based on the coefficient of determination ( R 2),more » and root mean square deviation (RMSD). Both of the indices are highly interpretable, and the RMSD-based index facilitates comparisons with alternative (non-lidar) inventory strategies, and with projects in other regions. K-NN diameter distribution prediction strategies were examined using auxiliary lidar for 190 training plots distribute across the 800 km 2 Savannah River Site in South Carolina, USA. In conclusion, we evaluate the performance of k-NN with respect to distance metrics, number of neighbors, predictor sets, and response sets. K-NN and lidar explained 80% of variability in diameters, and Mahalanobis distance with k = 3 neighbors performed best according to a number of criteria.« less

An Examination of Diameter Density Prediction with k-NN and Airborne Lidar

DOE Office of Scientific and Technical Information (OSTI.GOV)

Strunk, Jacob L.; Gould, Peter J.; Packalen, Petteri

While lidar-based forest inventory methods have been widely demonstrated, performances of methods to predict tree diameters with airborne lidar (lidar) are not well understood. One cause for this is that the performance metrics typically used in studies for prediction of diameters can be difficult to interpret, and may not support comparative inferences between sampling designs and study areas. To help with this problem we propose two indices and use them to evaluate a variety of lidar and k nearest neighbor (k-NN) strategies for prediction of tree diameter distributions. The indices are based on the coefficient of determination ( R 2),more » and root mean square deviation (RMSD). Both of the indices are highly interpretable, and the RMSD-based index facilitates comparisons with alternative (non-lidar) inventory strategies, and with projects in other regions. K-NN diameter distribution prediction strategies were examined using auxiliary lidar for 190 training plots distribute across the 800 km 2 Savannah River Site in South Carolina, USA. In conclusion, we evaluate the performance of k-NN with respect to distance metrics, number of neighbors, predictor sets, and response sets. K-NN and lidar explained 80% of variability in diameters, and Mahalanobis distance with k = 3 neighbors performed best according to a number of criteria.« less

Direct Breakthrough Curve Prediction From Statistics of Heterogeneous Conductivity Fields

NASA Astrophysics Data System (ADS)

Hansen, Scott K.; Haslauer, Claus P.; Cirpka, Olaf A.; Vesselinov, Velimir V.

2018-01-01

This paper presents a methodology to predict the shape of solute breakthrough curves in heterogeneous aquifers at early times and/or under high degrees of heterogeneity, both cases in which the classical macrodispersion theory may not be applicable. The methodology relies on the observation that breakthrough curves in heterogeneous media are generally well described by lognormal distributions, and mean breakthrough times can be predicted analytically. The log-variance of solute arrival is thus sufficient to completely specify the breakthrough curves, and this is calibrated as a function of aquifer heterogeneity and dimensionless distance from a source plane by means of Monte Carlo analysis and statistical regression. Using the ensemble of simulated groundwater flow and solute transport realizations employed to calibrate the predictive regression, reliability estimates for the prediction are also developed. Additional theoretical contributions include heuristics for the time until an effective macrodispersion coefficient becomes applicable, and also an expression for its magnitude that applies in highly heterogeneous systems. It is seen that the results here represent a way to derive continuous time random walk transition distributions from physical considerations rather than from empirical field calibration.

Comparison of various error functions in predicting the optimum isotherm by linear and non-linear regression analysis for the sorption of basic red 9 by activated carbon.

PubMed

Kumar, K Vasanth; Porkodi, K; Rocha, F

2008-01-15

A comparison of linear and non-linear regression method in selecting the optimum isotherm was made to the experimental equilibrium data of basic red 9 sorption by activated carbon. The r(2) was used to select the best fit linear theoretical isotherm. In the case of non-linear regression method, six error functions namely coefficient of determination (r(2)), hybrid fractional error function (HYBRID), Marquardt's percent standard deviation (MPSD), the average relative error (ARE), sum of the errors squared (ERRSQ) and sum of the absolute errors (EABS) were used to predict the parameters involved in the two and three parameter isotherms and also to predict the optimum isotherm. Non-linear regression was found to be a better way to obtain the parameters involved in the isotherms and also the optimum isotherm. For two parameter isotherm, MPSD was found to be the best error function in minimizing the error distribution between the experimental equilibrium data and predicted isotherms. In the case of three parameter isotherm, r(2) was found to be the best error function to minimize the error distribution structure between experimental equilibrium data and theoretical isotherms. The present study showed that the size of the error function alone is not a deciding factor to choose the optimum isotherm. In addition to the size of error function, the theory behind the predicted isotherm should be verified with the help of experimental data while selecting the optimum isotherm. A coefficient of non-determination, K(2) was explained and was found to be very useful in identifying the best error function while selecting the optimum isotherm.

The role of microstructure and phase distribution in the failure mechanisms and life prediction model for PSZ coatings

NASA Technical Reports Server (NTRS)

Sisson, R. D., Jr.; Sone, Ichiro; Biederman, R. R.

1985-01-01

Partially Stabilized Zirconia (PSZ) may become widely used for Thermal Barrier Coatings (TBC). Failure of these coatings can occur due to thermal fatigue in oxidizing atmospheres. The failure is due to the strains that develop due to thermal gradients, differences in thermal expansion coefficients, and oxidation of the bond coating. The role of microstructure and the cubic, tetragonal, and monoclinic phase distribution in the strain development and subsequent failure will be discussed. An X-ray diffraction technique for accurate determination of the fraction of each phase in PSZ will be applied to understanding the phase transformations and strain development. These results will be discussed in terms of developing a model for life prediction in PSZ coatings during thermal cycling.

Comparison of Methods for Characterizing Nonideal Solute Self-Association by Sedimentation Equilibrium

PubMed Central

Scott, David J.; Winzor, Donald J.

2009-01-01

Abstract We have examined in detail analytical solutions of expressions for sedimentation equilibrium in the analytical ultracentrifuge to describe self-association under nonideal conditions. We find that those containing the radial dependence of total solute concentration that incorporate the Adams-Fujita assumption for composition-dependence of activity coefficients reveal potential shortcomings for characterizing such systems. Similar deficiencies are shown in the use of the NONLIN software incorporating the same assumption about the interrelationship between activity coefficients for monomer and polymer species. These difficulties can be overcome by iterative analyses incorporating expressions for the composition-dependence of activity coefficients predicted by excluded volume considerations. A recommendation is therefore made for the replacement of current software packages by programs that incorporate rigorous statistical-mechanical allowance for thermodynamic nonideality in sedimentation equilibrium distributions reflecting solute self-association. PMID:19651047

Prediction of Very High Reynolds Number Compressible Skin Friction

NASA Technical Reports Server (NTRS)

Carlson, John R.

1998-01-01

Flat plate skin friction calculations over a range of Mach numbers from 0.4 to 3.5 at Reynolds numbers from 16 million to 492 million using a Navier Stokes method with advanced turbulence modeling are compared with incompressible skin friction coefficient correlations. The semi-empirical correlation theories of van Driest; Cope; Winkler and Cha; and Sommer and Short T' are used to transform the predicted skin friction coefficients of solutions using two algebraic Reynolds stress turbulence models in the Navier-Stokes method PAB3D. In general, the predicted skin friction coefficients scaled well with each reference temperature theory though, overall the theory by Sommer and Short appeared to best collapse the predicted coefficients. At the lower Reynolds number 3 to 30 million, both the Girimaji and Shih, Zhu and Lumley turbulence models predicted skin-friction coefficients within 2% of the semi-empirical correlation skin friction coefficients. At the higher Reynolds numbers of 100 to 500 million, the turbulence models by Shih, Zhu and Lumley and Girimaji predicted coefficients that were 6% less and 10% greater, respectively, than the semi-empirical coefficients.

Numerical approach of the injection molding process of fiber-reinforced composite with considering fiber orientation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Nguyen Thi, T. B., E-mail: thanhbinh.skku@gmail.com, E-mail: yokoyama@kit.ac.jp; Yokoyama, A., E-mail: thanhbinh.skku@gmail.com, E-mail: yokoyama@kit.ac.jp; Ota, K., E-mail: kei-ota@toyobo.jp, E-mail: katsuhiro-kodama@toyobo.jp, E-mail: katsuhisa-yamashita@toyobo.jp, E-mail: yumiko-isogai@toyobo.jp, E-mail: kenji-furuichi@toyobo.jp, E-mail: chisato-nonomura@toyobo.jp

2014-05-15

One of the most important challenges in the injection molding process of the short-glass fiber/thermoplastic composite parts is being able to predict the fiber orientation, since it controls the mechanical and the physical properties of the final parts. Folgar and Tucker included into the Jeffery equation a diffusive type of term, which introduces a phenomenological coefficient for modeling the randomizing effect of the mechanical interactions between the fibers, to predict the fiber orientation in concentrated suspensions. Their experiments indicated that this coefficient depends on the fiber volume fraction and aspect ratio. However, a definition of the fiber interaction coefficient, whichmore » is very necessary in the fiber orientation simulations, hasn't still been proven yet. Consequently, this study proposed a developed fiber interaction model that has been introduced a fiber dynamics simulation in order to obtain a global fiber interaction coefficient. This supposed that the coefficient is a sum function of the fiber concentration, aspect ratio, and angular velocity. The proposed model was incorporated into a computer aided engineering simulation package C-Mold. Short-glass fiber/polyamide-6 composites were produced in the injection molding with the fiber weight concentration of 30 wt.%, 50 wt.%, and 70 wt.%. The physical properties of these composites were examined, and their fiber orientation distributions were measured by micro-computed-tomography equipment μ-CT. The simulation results showed a good agreement with experiment results.« less

Modelling of gas-metal arc welding taking into account metal vapour

NASA Astrophysics Data System (ADS)

Schnick, M.; Fuessel, U.; Hertel, M.; Haessler, M.; Spille-Kohoff, A.; Murphy, A. B.

2010-11-01

The most advanced numerical models of gas-metal arc welding (GMAW) neglect vaporization of metal, and assume an argon atmosphere for the arc region, as is also common practice for models of gas-tungsten arc welding (GTAW). These models predict temperatures above 20 000 K and a temperature distribution similar to GTAW arcs. However, spectroscopic temperature measurements in GMAW arcs demonstrate much lower arc temperatures. In contrast to measurements of GTAW arcs, they have shown the presence of a central local minimum of the radial temperature distribution. This paper presents a GMAW model that takes into account metal vapour and that is able to predict the local central minimum in the radial distributions of temperature and electric current density. The influence of different values for the net radiative emission coefficient of iron vapour, which vary by up to a factor of hundred, is examined. It is shown that these net emission coefficients cause differences in the magnitudes, but not in the overall trends, of the radial distribution of temperature and current density. Further, the influence of the metal vaporization rate is investigated. We present evidence that, for higher vaporization rates, the central flow velocity inside the arc is decreased and can even change direction so that it is directed from the workpiece towards the wire, although the outer plasma flow is still directed towards the workpiece. In support of this thesis, we have attempted to reproduce the measurements of Zielińska et al for spray-transfer mode GMAW numerically, and have obtained reasonable agreement.

Predictive Simulation of Gas Adsorption in Fixed-Beds and Limitations due to the Ill-Posed Danckwerts Boundary Condition

NASA Technical Reports Server (NTRS)

Knox, James Clinton

2016-01-01

The 1-D axially dispersed plug flow model is a mathematical model widely used for the simulation of adsorption processes. Lumped mass transfer coefficients such as the Glueckauf linear driving force (LDF) term and the axial dispersion coefficient are generally obtained by fitting simulation results to the experimental breakthrough test data. An approach is introduced where these parameters, along with the only free parameter in the energy balance equations, are individually fit to specific test data that isolates the appropriate physics. It is shown that with this approach this model provides excellent simulation results for the C02 on zeolite SA sorbent/sorbate system; however, for the H20 on zeolite SA system, non-physical deviations from constant pattern behavior occur when fitting dispersive experimental results with a large axial dispersion coefficient. A method has also been developed that determines a priori what values of the LDF and axial dispersion terms will result in non-physical simulation results for a specific sorbent/sorbate system when using the one-dimensional axially dispersed plug flow model. A relationship between the steepness of the adsorption equilibrium isotherm as indicated by the distribution factor, the magnitude of the axial dispersion and mass transfer coefficient, and the resulting non-physical behavior is derived. This relationship is intended to provide a guide for avoiding non-physical behavior by limiting the magnitude of the axial dispersion term on the basis of the mass transfer coefficient and distribution factor.

A study of a diffusive model of asset returns and an empirical analysis of financial markets

NASA Astrophysics Data System (ADS)

Alejandro Quinones, Angel Luis

A diffusive model for market dynamics is studied and the predictions of the model are compared to real financial markets. The model has a non-constant diffusion coefficient which depends both on the asset value and the time. A general solution for the distribution of returns is obtained and shown to match the results of computer simulations for two simple cases, piecewise linear and quadratic diffusion. The effects of discreteness in the market dynamics on the model are also studied. For the quadratic diffusion case, a type of phase transition leading to fat tails is observed as the discrete distribution approaches the continuum limit. It is also found that the model captures some of the empirical stylized facts observed in real markets, including fat-tails and scaling behavior in the distribution of returns. An analysis of empirical data for the EUR/USD currency exchange rate and the S&P 500 index is performed. Both markets show time scaling behavior consistent with a value of 1/2 for the Hurst exponent. Finally, the results show that the distribution of returns for the two markets is well fitted by the model, and the corresponding empirical diffusion coefficients are determined.

An Investigation of the Sampling Distribution of the Congruence Coefficient.

ERIC Educational Resources Information Center

Broadbooks, Wendy J.; Elmore, Patricia B.

This study developed and investigated an empirical sampling distribution of the congruence coefficient. The effects of sample size, number of variables, and population value of the congruence coefficient on the sampling distribution of the congruence coefficient were examined. Sample data were generated on the basis of the common factor model and…

A distribution model for the aerial application of granular agricultural particles

NASA Technical Reports Server (NTRS)

Fernandes, S. T.; Ormsbee, A. I.

1978-01-01

A model is developed to predict the shape of the distribution of granular agricultural particles applied by aircraft. The particle is assumed to have a random size and shape and the model includes the effect of air resistance, distributor geometry and aircraft wake. General requirements for the maintenance of similarity of the distribution for scale model tests are derived and are addressed to the problem of a nongeneral drag law. It is shown that if the mean and variance of the particle diameter and density are scaled according to the scaling laws governing the system, the shape of the distribution will be preserved. Distributions are calculated numerically and show the effect of a random initial lateral position, particle size and drag coefficient. A listing of the computer code is included.

Nonplanar Method for Predicting Incompressible Aerodynamic Coefficients of Rectangular Wings with Circular-Arc Camber. Ph.D. Thesis - Virginia Polytechnic Institute

NASA Technical Reports Server (NTRS)

Lamar, J. E.

1971-01-01

The development of a nonplanar lifting surface method having a continuous distribution of singularities and satisfying the tangent flow boundary condition on the mean camber surface is given. The method predicts some incompressible longitudinal aerodynamic coefficients of rectangular wings which have circular-arc camber. The solution method is of the integral-equation type and the resulting surface integrals are evaluated by either using numerical or analytical techniques, as are appropriate. Applications are made and the results compared with those from an exact two-dimensional circular-arc camber solution, a three-dimensional flat-wing solution which represents the camber by a projected slope onto the flat surface, and a flat-wing experiment. From these comparisons, the present method is found to predict well the flat-wing experiment and limiting values, in addition to the center of pressure variation at an angle of attack of zero for any camber. For wings having camber ratios larger than about 1.25% and moderate to high aspect ratios, the results deterioriate due to the inadequacy of lifting pressure modes employed.

The influence of pressure relaxation on the structure of an axial vortex

NASA Astrophysics Data System (ADS)

Ash, Robert L.; Zardadkhan, Irfan; Zuckerwar, Allan J.

2011-07-01

Governing equations including the effects of pressure relaxation have been utilized to study an incompressible, steady-state viscous axial vortex with specified far-field circulation. When sound generation is attributed to a velocity gradient tensor-pressure gradient product, the modified conservation of momentum equations that result yield an exact solution for a steady, incompressible axial vortex. The vortex velocity profile has been shown to closely approximate experimental vortex measurements in air and water over a wide range of circulation-based Reynolds numbers. The influence of temperature and humidity on the pressure relaxation coefficient in air has been examined using theoretical and empirical approaches, and published axial vortex experiments have been employed to estimate the pressure relaxation coefficient in water. Non-equilibrium pressure gradient forces have been shown to balance the viscous stresses in the vortex core region, and the predicted pressure deficits that result from this non-equilibrium balance can be substantially larger than the pressure deficits predicted using a Bernoulli equation approach. Previously reported pressure deficit distributions for dust devils and tornados have been employed to validate the non-equilibrium pressure deficit predictions.

Gas/particle partitioning, particle-size distribution of atmospheric polybrominated diphenyl ethers in southeast Shanghai rural area and size-resolved predicting model.

PubMed

Su, Peng-Hao; Tomy, Gregg T; Hou, Chun-Yan; Yin, Fang; Feng, Dao-Lun; Ding, Yong-Sheng; Li, Yi-Fan

2018-04-01

A size-segregated gas/particle partitioning coefficient K Pi was proposed and evaluated in the predicting models on the basis of atmospheric polybrominated diphenyl ether (PBDE) field data comparing with the bulk coefficient K P . Results revealed that the characteristics of atmospheric PBDEs in southeast Shanghai rural area were generally consistent with previous investigations, suggesting that this investigation was representative to the present pollution status of atmospheric PBDEs. K Pi was generally greater than bulk K P , indicating an overestimate of TSP (the mass concentration of total suspended particles) in the expression of bulk K P . In predicting models, K Pi led to a significant shift in regression lines as compared to K P , thus it should be more cautious to investigate sorption mechanisms using the regression lines. The differences between the performances of K Pi and K P were helpful to explain some phenomenon in predicting investigations, such as P L 0 and K OA models overestimate the particle fractions of PBDEs and the models work better at high temperature than at low temperature. Our findings are important because they enabled an insight into the influence of particle size on predicting models. Copyright © 2018 Elsevier Ltd. All rights reserved.

Study of Parameters And Methods of LL-Ⅳ Distributed Hydrological Model in DMIP2

NASA Astrophysics Data System (ADS)

Li, L.; Wu, J.; Wang, X.; Yang, C.; Zhao, Y.; Zhou, H.

2008-05-01

: The Physics-based distributed hydrological model is considered as an important developing period from the traditional experience-hydrology to the physical hydrology. The Hydrology Laboratory of the NOAA National Weather Service proposes the first and second phase of the Distributed Model Intercomparison Project (DMIP)，that it is a great epoch-making work. LL distributed hydrological model has been developed to the fourth generation since it was established in 1997 on the Fengman-I district reservoir area (11000 km2).The LL-I distributed hydrological model was born with the applications of flood control system in the Fengman-I in China. LL-II was developed under the DMIP-I support, it is combined with GIS, RS, GPS, radar rainfall measurement.LL-III was established along with Applications of LL Distributed Model on Water Resources which was supported by the 973-projects of The Ministry of Science and Technology of the People's Republic of China. LL-Ⅳ was developed to face China's water problem. Combined with Blue River and the Baron Fork River basin of DMIP-II, the convection-diffusion equation of non-saturated and saturated seepage was derived from the soil water dynamics and continuous equation. In view of the technical characteristics of the model, the advantage of using convection-diffusion equation to compute confluence overall is longer period of predictable, saving memory space, fast budgeting, clear physical concepts, etc. The determination of parameters of hydrological model is the key, including experience coefficients and parameters of physical parameters. There are methods of experience, inversion, and the optimization to determine the model parameters, and each has advantages and disadvantages. This paper briefly introduces the LL-Ⅳ distribution hydrological model equations, and particularly introduces methods of parameters determination and simulation results on Blue River and Baron Fork River basin for DMIP-II. The soil moisture diffusion coefficient and coefficient of hydraulic conductivity are involved all through the LL-Ⅳ distribution of runoff and slope convergence model, used mainly empirical formula to determine. It's used optimization methods to calculate the two parameters of evaporation capacity (coefficient of bare land and vegetation land), two parameters of interception and wave velocity of Overland Flow, interflow and groundwater. The approach of determining wave velocity of River Network confluence and diffusion coefficient is: 1. Estimate roughness based mainly on digital information such as land use, soil texture, etc. 2.Establish the empirical formula. Another method is called convection-diffusion numerical inversion.

Investigation of oscillating cascade aerodynamics by an experimental influence coefficient technique

NASA Technical Reports Server (NTRS)

Buffum, Daniel H.; Fleeter, Sanford

1988-01-01

Fundamental experiments are performed in the NASA Lewis Transonic Oscillating Cascade Facility to investigate the torsion mode unsteady aerodynamics of a biconvex airfoil cascade at realistic values of the reduced frequency for all interblade phase angles at a specified mean flow condition. In particular, an unsteady aerodynamic influence coefficient technique is developed and utilized in which only one airfoil in the cascade is oscillated at a time and the resulting airfoil surface unsteady pressure distribution measured on one dynamically instrumented airfoil. The unsteady aerodynamics of an equivalent cascade with all airfoils oscillating at a specified interblade phase angle are then determined through a vector summation of these data. These influence coefficient determined oscillation cascade data are correlated with data obtained in this cascade with all airfoils oscillating at several interblade phase angle values. The influence coefficients are then utilized to determine the unsteady aerodynamics of the cascade for all interblade phase angles, with these unique data subsequently correlated with predictions from a linearized unsteady cascade model.

Interactions of satellite-speed helium atoms with satellite surfaces. 3: Drag coefficients from spatial and energy distributions of reflected helium atoms

NASA Technical Reports Server (NTRS)

Sharma, P. K.; Knuth, E. L.

1977-01-01

Spatial and energy distributions of helium atoms scattered from an anodized 1235-0 aluminum surface as well as the tangential and normal momentum accommodation coefficients calculated from these distributions are reported. A procedure for calculating drag coefficients from measured values of spatial and energy distributions is given. The drag coefficient calculated for a 6061 T-6 aluminum sphere is included.

Distribution coefficients of rare earth ions in cubic zirconium dioxide

NASA Astrophysics Data System (ADS)

Romer, H.; Luther, K.-D.; Assmus, W.

1994-08-01

Cubic zirconium dioxide crystals are grown with the skull melting technique. The effective distribution coefficients for Nd(exp 3+), Sm(exp 3+) and Er(sup 3+) as dopants are determined experimentally as a function of the crystal growth velocity. With the Burton-Prim-Slichter theory, the equilibrium distribution coefficients can be calculated. The distribution coefficients of all other trivalent rare earth ions can be estimated by applying the correlation towards the ionic radii.

A model for the spatial distribution of snow water equivalent parameterized from the spatial variability of precipitation

NASA Astrophysics Data System (ADS)

Skaugen, Thomas; Weltzien, Ingunn H.

2016-09-01

Snow is an important and complicated element in hydrological modelling. The traditional catchment hydrological model with its many free calibration parameters, also in snow sub-models, is not a well-suited tool for predicting conditions for which it has not been calibrated. Such conditions include prediction in ungauged basins and assessing hydrological effects of climate change. In this study, a new model for the spatial distribution of snow water equivalent (SWE), parameterized solely from observed spatial variability of precipitation, is compared with the current snow distribution model used in the operational flood forecasting models in Norway. The former model uses a dynamic gamma distribution and is called Snow Distribution_Gamma, (SD_G), whereas the latter model has a fixed, calibrated coefficient of variation, which parameterizes a log-normal model for snow distribution and is called Snow Distribution_Log-Normal (SD_LN). The two models are implemented in the parameter parsimonious rainfall-runoff model Distance Distribution Dynamics (DDD), and their capability for predicting runoff, SWE and snow-covered area (SCA) is tested and compared for 71 Norwegian catchments. The calibration period is 1985-2000 and validation period is 2000-2014. Results show that SDG better simulates SCA when compared with MODIS satellite-derived snow cover. In addition, SWE is simulated more realistically in that seasonal snow is melted out and the building up of "snow towers" and giving spurious positive trends in SWE, typical for SD_LN, is prevented. The precision of runoff simulations using SDG is slightly inferior, with a reduction in Nash-Sutcliffe and Kling-Gupta efficiency criterion of 0.01, but it is shown that the high precision in runoff prediction using SD_LN is accompanied with erroneous simulations of SWE.

Evaluation of Pharmacokinetic Assumptions Using a 443 ...

EPA Pesticide Factsheets

With the increasing availability of high-throughput and in vitro data for untested chemicals, there is a need for pharmacokinetic (PK) models for in vitro to in vivo extrapolation (IVIVE). Though some PBPK models have been created for individual compounds using in vivo data, we are now able to rapidly parameterize generic PBPK models using in vitro data to allow IVIVE for chemicals tested for bioactivity via high-throughput screening. However, these new models are expected to have limited accuracy due to their simplicity and generalization of assumptions. We evaluated the assumptions and performance of a generic PBPK model (R package “httk”) parameterized by a library of in vitro PK data for 443 chemicals. We evaluate and calibrate Schmitt’s method by comparing the predicted volume of distribution (Vd) and tissue partition coefficients to in vivo measurements. The partition coefficients are initially over predicted, likely due to overestimation of partitioning into phospholipids in tissues and the lack of lipid partitioning in the in vitro measurements of the fraction unbound in plasma. Correcting for phospholipids and plasma binding improved the predictive ability (R2 to 0.52 for partition coefficients and 0.32 for Vd). We lacked enough data to evaluate the accuracy of changing the model structure to include tissue blood volumes and/or separate compartments for richly/poorly perfused tissues, therefore we evaluated the impact of these changes on model

CFD Study of NACA 0018 Airfoil with Flow Control

NASA Technical Reports Server (NTRS)

Eggert, Christopher A.; Rumsey, Christopher L.

2017-01-01

The abilities of two different Reynolds-Averaged Navier-Stokes codes to predict the effects of an active flow control device are evaluated. The flow control device consists of a blowing slot located on the upper surface of an NACA 0018 airfoil, near the leading edge. A second blowing slot present on the airfoil near mid-chord is not evaluated here. Experimental results from a wind tunnel test show that a slot blowing with high momentum coefficient will increase the lift of the airfoil (compared to no blowing) and delay flow separation. A slot with low momentum coefficient will decrease the lift and induce separation even at low angles of attack. Two codes, CFL3D and FUN3D, are used in two-dimensional computations along with several different turbulence models. Two of these produced reasonable results for this flow, when run fully turbulent. A more advanced transition model failed to predict reasonable results, but warrants further study using different inputs. Including inviscid upper and lower tunnel walls in the simulations was found to be important in obtaining pressure distributions and lift coefficients that best matched experimental data. A limited number of three-dimensional computations were also performed.

Predicting a contact's sensitivity to initial conditions using metrics of frictional coupling

DOE PAGES

Flicek, Robert C.; Hills, David A.; Brake, Matthew Robert W.

2016-09-29

This paper presents a method for predicting how sensitive a frictional contact’s steady-state behavior is to its initial conditions. Previous research has proven that if a contact is uncoupled, i.e. if slip displacements do not influence the contact pressure distribution, then its steady-state response is independent of initial conditions, but if the contact is coupled, the steady-state response depends on initial conditions. In this paper, two metrics for quantifying coupling in discrete frictional systems are examined. These metrics suggest that coupling is dominated by material dissimilarity due to Dundurs’ composite material parameter β when β ≥ 0.2, but geometric mismatchmore » becomes the dominant source of coupling for smaller values of β. Based on a large set of numerical simulations with different contact geometries, material combinations, and friction coefficients, a contact’s sensitivity to initial conditions is found to be correlated with the product of the coupling metric and the friction coefficient. For cyclic shear loading, this correlation is maintained for simulations with different contact geometries, material combinations, and friction coefficients. Furthermore, for cyclic bulk loading, the correlation is only maintained when the contact edge angle is held constant.« less

Predicting a contact's sensitivity to initial conditions using metrics of frictional coupling

DOE Office of Scientific and Technical Information (OSTI.GOV)

Flicek, Robert C.; Hills, David A.; Brake, Matthew Robert W.

This paper presents a method for predicting how sensitive a frictional contact’s steady-state behavior is to its initial conditions. Previous research has proven that if a contact is uncoupled, i.e. if slip displacements do not influence the contact pressure distribution, then its steady-state response is independent of initial conditions, but if the contact is coupled, the steady-state response depends on initial conditions. In this paper, two metrics for quantifying coupling in discrete frictional systems are examined. These metrics suggest that coupling is dominated by material dissimilarity due to Dundurs’ composite material parameter β when β ≥ 0.2, but geometric mismatchmore » becomes the dominant source of coupling for smaller values of β. Based on a large set of numerical simulations with different contact geometries, material combinations, and friction coefficients, a contact’s sensitivity to initial conditions is found to be correlated with the product of the coupling metric and the friction coefficient. For cyclic shear loading, this correlation is maintained for simulations with different contact geometries, material combinations, and friction coefficients. Furthermore, for cyclic bulk loading, the correlation is only maintained when the contact edge angle is held constant.« less

Modeling stochastic frontier based on vine copulas

NASA Astrophysics Data System (ADS)

Constantino, Michel; Candido, Osvaldo; Tabak, Benjamin M.; da Costa, Reginaldo Brito

2017-11-01

This article models a production function and analyzes the technical efficiency of listed companies in the United States, Germany and England between 2005 and 2012 based on the vine copula approach. Traditional estimates of the stochastic frontier assume that data is multivariate normally distributed and there is no source of asymmetry. The proposed method based on vine copulas allow us to explore different types of asymmetry and multivariate distribution. Using data on product, capital and labor, we measure the relative efficiency of the vine production function and estimate the coefficient used in the stochastic frontier literature for comparison purposes. This production vine copula predicts the value added by firms with given capital and labor in a probabilistic way. It thereby stands in sharp contrast to the production function, where the output of firms is completely deterministic. The results show that, on average, S&P500 companies are more efficient than companies listed in England and Germany, which presented similar average efficiency coefficients. For comparative purposes, the traditional stochastic frontier was estimated and the results showed discrepancies between the coefficients obtained by the application of the two methods, traditional and frontier-vine, opening new paths of non-linear research.

Latin hypercube approach to estimate uncertainty in ground water vulnerability

USGS Publications Warehouse

Gurdak, J.J.; McCray, J.E.; Thyne, G.; Qi, S.L.

2007-01-01

A methodology is proposed to quantify prediction uncertainty associated with ground water vulnerability models that were developed through an approach that coupled multivariate logistic regression with a geographic information system (GIS). This method uses Latin hypercube sampling (LHS) to illustrate the propagation of input error and estimate uncertainty associated with the logistic regression predictions of ground water vulnerability. Central to the proposed method is the assumption that prediction uncertainty in ground water vulnerability models is a function of input error propagation from uncertainty in the estimated logistic regression model coefficients (model error) and the values of explanatory variables represented in the GIS (data error). Input probability distributions that represent both model and data error sources of uncertainty were simultaneously sampled using a Latin hypercube approach with logistic regression calculations of probability of elevated nonpoint source contaminants in ground water. The resulting probability distribution represents the prediction intervals and associated uncertainty of the ground water vulnerability predictions. The method is illustrated through a ground water vulnerability assessment of the High Plains regional aquifer. Results of the LHS simulations reveal significant prediction uncertainties that vary spatially across the regional aquifer. Additionally, the proposed method enables a spatial deconstruction of the prediction uncertainty that can lead to improved prediction of ground water vulnerability. ?? 2007 National Ground Water Association.

Experiment Design for Complex VTOL Aircraft with Distributed Propulsion and Tilt Wing

NASA Technical Reports Server (NTRS)

Murphy, Patrick C.; Landman, Drew

2015-01-01

Selected experimental results from a wind tunnel study of a subscale VTOL concept with distributed propulsion and tilt lifting surfaces are presented. The vehicle complexity and automated test facility were ideal for use with a randomized designed experiment. Design of Experiments and Response Surface Methods were invoked to produce run efficient, statistically rigorous regression models with minimized prediction error. Static tests were conducted at the NASA Langley 12-Foot Low-Speed Tunnel to model all six aerodynamic coefficients over a large flight envelope. This work supports investigations at NASA Langley in developing advanced configurations, simulations, and advanced control systems.

Type I and II β-turns prediction using NMR chemical shifts.

PubMed

Wang, Ching-Cheng; Lai, Wen-Chung; Chuang, Woei-Jer

2014-07-01

A method for predicting type I and II β-turns using nuclear magnetic resonance (NMR) chemical shifts is proposed. Isolated β-turn chemical-shift data were collected from 1,798 protein chains. One-dimensional statistical analyses on chemical-shift data of three classes β-turn (type I, II, and VIII) showed different distributions at four positions, (i) to (i + 3). Considering the central two residues of type I β-turns, the mean values of Cο, Cα, H(N), and N(H) chemical shifts were generally (i + 1) > (i + 2). The mean values of Cβ and Hα chemical shifts were (i + 1) < (i + 2). The distributions of the central two residues in type II and VIII β-turns were also distinguishable by trends of chemical shift values. Two-dimensional cluster analyses on chemical-shift data show positional distributions more clearly. Based on these propensities of chemical shift classified as a function of position, rules were derived using scoring matrices for four consecutive residues to predict type I and II β-turns. The proposed method achieves an overall prediction accuracy of 83.2 and 84.2% with the Matthews correlation coefficient values of 0.317 and 0.632 for type I and II β-turns, indicating that its higher accuracy for type II turn prediction. The results show that it is feasible to use NMR chemical shifts to predict the β-turn types in proteins. The proposed method can be incorporated into other chemical-shift based protein secondary structure prediction methods.

Application of the Shiono and Knight Method in asymmetric compound channels with different side slopes of the internal wall

NASA Astrophysics Data System (ADS)

Alawadi, Wisam; Al-Rekabi, Wisam S.; Al-Aboodi, Ali H.

2018-03-01

The Shiono and Knight Method (SKM) is widely used to predict the lateral distribution of depth-averaged velocity and boundary shear stress for flows in compound channels. Three calibrating coefficients need to be estimated for applying the SKM, namely eddy viscosity coefficient ( λ), friction factor ( f) and secondary flow coefficient ( k). There are several tested methods which can satisfactorily be used to estimate λ, f. However, the calibration of secondary flow coefficients k to account for secondary flow effects correctly is still problematic. In this paper, the calibration of secondary flow coefficients is established by employing two approaches to estimate correct values of k for simulating asymmetric compound channel with different side slopes of the internal wall. The first approach is based on Abril and Knight (2004) who suggest fixed values for main channel and floodplain regions. In the second approach, the equations developed by Devi and Khatua (2017) that relate the variation of the secondary flow coefficients with the relative depth ( β) and width ratio ( α) are used. The results indicate that the calibration method developed by Devi and Khatua (2017) is a better choice for calibrating the secondary flow coefficients than using the first approach which assumes a fixed value of k for different flow depths. The results also indicate that the boundary condition based on the shear force continuity can successfully be used for simulating rectangular compound channels, while the continuity of depth-averaged velocity and its gradient is accepted boundary condition in simulations of trapezoidal compound channels. However, the SKM performance for predicting the boundary shear stress over the shear layer region may not be improved by only imposing the suitable calibrated values of secondary flow coefficients. This is because difficulties of modelling the complex interaction that develops between the flows in the main channel and on the floodplain in this region.

The study of RMB exchange rate complex networks based on fluctuation mode

NASA Astrophysics Data System (ADS)

Yao, Can-Zhong; Lin, Ji-Nan; Zheng, Xu-Zhou; Liu, Xiao-Feng

2015-10-01

In the paper, we research on the characteristics of RMB exchange rate time series fluctuation with methods of symbolization and coarse gaining. First, based on fluctuation features of RMB exchange rate, we define the first type of fluctuation mode as one specific foreign currency against RMB in four days' fluctuating situations, and the second type as four different foreign currencies against RMB in one day's fluctuating situation. With the transforming method, we construct the unique-currency and multi-currency complex networks. Further, through analyzing the topological features including out-degree, betweenness centrality and clustering coefficient of fluctuation-mode complex networks, we find that the out-degree distribution of both types of fluctuation mode basically follows power-law distributions with exponents between 1 and 2. The further analysis reveals that the out-degree and the clustering coefficient generally obey the approximated negative correlation. With this result, we confirm previous observations showing that the RMB exchange rate exhibits a characteristic of long-range memory. Finally, we analyze the most probable transmission route of fluctuation modes, and provide probability prediction matrix. The transmission route for RMB exchange rate fluctuation modes exhibits the characteristics of partially closed loop, repeat and reversibility, which lays a solid foundation for predicting RMB exchange rate fluctuation patterns with large volume of data.

Soft Wall Ion Channel in Continuum Representation with Application to Modeling Ion Currents in α-Hemolysin

PubMed Central

Simakov, Nikolay A.

2010-01-01

A soft repulsion (SR) model of short range interactions between mobile ions and protein atoms is introduced in the framework of continuum representation of the protein and solvent. The Poisson-Nernst-Plank (PNP) theory of ion transport through biological channels is modified to incorporate this soft wall protein model. Two sets of SR parameters are introduced: the first is parameterized for all essential amino acid residues using all atom molecular dynamic simulations; the second is a truncated Lennard – Jones potential. We have further designed an energy based algorithm for the determination of the ion accessible volume, which is appropriate for a particular system discretization. The effects of these models of short-range interaction were tested by computing current-voltage characteristics of the α-hemolysin channel. The introduced SR potentials significantly improve prediction of channel selectivity. In addition, we studied the effect of choice of some space-dependent diffusion coefficient distributions on the predicted current-voltage properties. We conclude that the diffusion coefficient distributions largely affect total currents and have little effect on rectifications, selectivity or reversal potential. The PNP-SR algorithm is implemented in a new efficient parallel Poisson, Poisson-Boltzman and PNP equation solver, also incorporated in a graphical molecular modeling package HARLEM. PMID:21028776

Fast detection and visualization of minced lamb meat adulteration using NIR hyperspectral imaging and multivariate image analysis.

PubMed

Kamruzzaman, Mohammed; Sun, Da-Wen; ElMasry, Gamal; Allen, Paul

2013-01-15

Many studies have been carried out in developing non-destructive technologies for predicting meat adulteration, but there is still no endeavor for non-destructive detection and quantification of adulteration in minced lamb meat. The main goal of this study was to develop and optimize a rapid analytical technique based on near-infrared (NIR) hyperspectral imaging to detect the level of adulteration in minced lamb. Initial investigation was carried out using principal component analysis (PCA) to identify the most potential adulterate in minced lamb. Minced lamb meat samples were then adulterated with minced pork in the range 2-40% (w/w) at approximately 2% increments. Spectral data were used to develop a partial least squares regression (PLSR) model to predict the level of adulteration in minced lamb. Good prediction model was obtained using the whole spectral range (910-1700 nm) with a coefficient of determination (R(2)(cv)) of 0.99 and root-mean-square errors estimated by cross validation (RMSECV) of 1.37%. Four important wavelengths (940, 1067, 1144 and 1217 nm) were selected using weighted regression coefficients (Bw) and a multiple linear regression (MLR) model was then established using these important wavelengths to predict adulteration. The MLR model resulted in a coefficient of determination (R(2)(cv)) of 0.98 and RMSECV of 1.45%. The developed MLR model was then applied to each pixel in the image to obtain prediction maps to visualize the distribution of adulteration of the tested samples. The results demonstrated that the laborious and time-consuming tradition analytical techniques could be replaced by spectral data in order to provide rapid, low cost and non-destructive testing technique for adulterate detection in minced lamb meat. Copyright © 2012 Elsevier B.V. All rights reserved.

Finite-floe wave reflection and transmission coefficients from a semi-infinite model

NASA Astrophysics Data System (ADS)

Meylan, Michael; Squire, Vernon A.

1993-07-01

A model to describe the reflection and transmission of ocean waves by a single ice floe is developed from the semi-infinite model of Fox and Squire (1990, 1991). This is done by considering the coefficients for the transition from ice to water in the semi-infinite case in terms of those from water to ice. Finite-floe reflection and transmission coefficients, R and T, respectively, are then found as the solution of a set of four simple simultaneous equations. The properties of R and T are investigated, and examples of their absolute values are given for several geometries. |R| compares well with the predictions of a precise model in the case of deep water. These results suggest that the analytical model described has applications to defining the sea state within marginal ice zones, given the floe size and ice thickness distributions and the incoming sea wave spectrum.

An Experimental Evaluation of Advanced Rotorcraft Airfoils in the NASA Ames Eleven-foot Transonic Wind Tunnel

NASA Technical Reports Server (NTRS)

Flemming, Robert J.

1984-01-01

Five full scale rotorcraft airfoils were tested in the NASA Ames Eleven-Foot Transonic Wind Tunnel for full scale Reynolds numbers at Mach numbers from 0.3 to 1.07. The models, which spanned the tunnel from floor to ceiling, included two modern baseline airfoils, the SC1095 and SC1094 R8, which have been previously tested in other facilities. Three advanced transonic airfoils, designated the SSC-A09, SSC-A07, and SSC-B08, were tested to confirm predicted performance and provide confirmation of advanced airfoil design methods. The test showed that the eleven-foot tunnel is suited to two-dimensional airfoil testing. Maximum lift coefficients, drag coefficients, pitching moments, and pressure coefficient distributions are presented. The airfoil analysis codes agreed well with the data, with the Grumman GRUMFOIL code giving the best overall performance correlation.

Quantitative visualization of passive transport across bilayer lipid membranes

PubMed Central

Grime, John M. A.; Edwards, Martin A.; Rudd, Nicola C.; Unwin, Patrick R.

2008-01-01

The ability to predict and interpret membrane permeation coefficients is of critical importance, particularly because passive transport is crucial for the effective delivery of many pharmaceutical agents to intracellular targets. We present a method for the quantitative measurement of the permeation coefficients of protonophores by using laser confocal scanning microscopy coupled to microelectrochemistry, which is amenable to precise modeling with the finite element method. The technique delivers well defined and high mass transport rates and allows rapid visualization of the entire pH distribution on both the cis and trans side of model bilayer lipid membranes (BLMs). A homologous series of carboxylic acids was investigated as probe molecules for BLMs composed of soybean phosphatidylcholine. Significantly, the permeation coefficient decreased with acyl tail length contrary to previous work and to Overton's rule. The reasons for this difference are considered, and we suggest that the applicability of Overton's rule requires re-evaluation. PMID:18787114

Hierarchical spatial models for predicting pygmy rabbit distribution and relative abundance

USGS Publications Warehouse

Wilson, T.L.; Odei, J.B.; Hooten, M.B.; Edwards, T.C.

2010-01-01

Conservationists routinely use species distribution models to plan conservation, restoration and development actions, while ecologists use them to infer process from pattern. These models tend to work well for common or easily observable species, but are of limited utility for rare and cryptic species. This may be because honest accounting of known observation bias and spatial autocorrelation are rarely included, thereby limiting statistical inference of resulting distribution maps. We specified and implemented a spatially explicit Bayesian hierarchical model for a cryptic mammal species (pygmy rabbit Brachylagus idahoensis). Our approach used two levels of indirect sign that are naturally hierarchical (burrows and faecal pellets) to build a model that allows for inference on regression coefficients as well as spatially explicit model parameters. We also produced maps of rabbit distribution (occupied burrows) and relative abundance (number of burrows expected to be occupied by pygmy rabbits). The model demonstrated statistically rigorous spatial prediction by including spatial autocorrelation and measurement uncertainty. We demonstrated flexibility of our modelling framework by depicting probabilistic distribution predictions using different assumptions of pygmy rabbit habitat requirements. Spatial representations of the variance of posterior predictive distributions were obtained to evaluate heterogeneity in model fit across the spatial domain. Leave-one-out cross-validation was conducted to evaluate the overall model fit. Synthesis and applications. Our method draws on the strengths of previous work, thereby bridging and extending two active areas of ecological research: species distribution models and multi-state occupancy modelling. Our framework can be extended to encompass both larger extents and other species for which direct estimation of abundance is difficult. ?? 2010 The Authors. Journal compilation ?? 2010 British Ecological Society.

Inference for multivariate regression model based on multiply imputed synthetic data generated via posterior predictive sampling

NASA Astrophysics Data System (ADS)

Moura, Ricardo; Sinha, Bimal; Coelho, Carlos A.

2017-06-01

The recent popularity of the use of synthetic data as a Statistical Disclosure Control technique has enabled the development of several methods of generating and analyzing such data, but almost always relying in asymptotic distributions and in consequence being not adequate for small sample datasets. Thus, a likelihood-based exact inference procedure is derived for the matrix of regression coefficients of the multivariate regression model, for multiply imputed synthetic data generated via Posterior Predictive Sampling. Since it is based in exact distributions this procedure may even be used in small sample datasets. Simulation studies compare the results obtained from the proposed exact inferential procedure with the results obtained from an adaptation of Reiters combination rule to multiply imputed synthetic datasets and an application to the 2000 Current Population Survey is discussed.

An Investigation of the Sampling Distributions of Equating Coefficients.

ERIC Educational Resources Information Center

Baker, Frank B.

1996-01-01

Using the characteristic curve method for dichotomously scored test items, the sampling distributions of equating coefficients were examined. Simulations indicate that for the equating conditions studied, the sampling distributions of the equating coefficients appear to have acceptable characteristics, suggesting confidence in the values obtained…

Nonlinear Recurrent Neural Network Predictive Control for Energy Distribution of a Fuel Cell Powered Robot

PubMed Central

Chen, Qihong; Long, Rong; Quan, Shuhai

2014-01-01

This paper presents a neural network predictive control strategy to optimize power distribution for a fuel cell/ultracapacitor hybrid power system of a robot. We model the nonlinear power system by employing time variant auto-regressive moving average with exogenous (ARMAX), and using recurrent neural network to represent the complicated coefficients of the ARMAX model. Because the dynamic of the system is viewed as operating- state- dependent time varying local linear behavior in this frame, a linear constrained model predictive control algorithm is developed to optimize the power splitting between the fuel cell and ultracapacitor. The proposed algorithm significantly simplifies implementation of the controller and can handle multiple constraints, such as limiting substantial fluctuation of fuel cell current. Experiment and simulation results demonstrate that the control strategy can optimally split power between the fuel cell and ultracapacitor, limit the change rate of the fuel cell current, and so as to extend the lifetime of the fuel cell. PMID:24707206

Inhomogeneous distribution of water droplets in cloud turbulence

NASA Astrophysics Data System (ADS)

Fouxon, Itzhak; Park, Yongnam; Harduf, Roei; Lee, Changhoon

2015-09-01

We consider sedimentation of small particles in the turbulent flow where fluid accelerations are much smaller than acceleration of gravity g . The particles are dragged by the flow by linear friction force. We demonstrate that the pair-correlation function of particles' concentration diverges with decreasing separation as a power law with negative exponent. This manifests fractal distribution of particles in space. We find that the exponent is proportional to ratio of integral of energy spectrum of turbulence times the wave number over g . The proportionality coefficient is a universal number independent of particle size. We derive the spectrum of Lyapunov exponents that describes the evolution of small patches of particles. It is demonstrated that particles separate dominantly in the horizontal plane. This provides a theory for the recently observed vertical columns formed by the particles. We confirm the predictions by direct numerical simulations of Navier-Stokes turbulence. The predictions include conditions that hold for water droplets in warm clouds thus providing a tool for the prediction of rain formation.

Sensitivity analysis of urban flood flows to hydraulic controls

NASA Astrophysics Data System (ADS)

Chen, Shangzhi; Garambois, Pierre-André; Finaud-Guyot, Pascal; Dellinger, Guilhem; Terfous, Abdelali; Ghenaim, Abdallah

2017-04-01

Flooding represents one of the most significant natural hazards on each continent and particularly in highly populated areas. Improving the accuracy and robustness of prediction systems has become a priority. However, in situ measurements of floods remain difficult while a better understanding of flood flow spatiotemporal dynamics along with dataset for model validations appear essential. The present contribution is based on a unique experimental device at the scale 1/200, able to produce urban flooding with flood flows corresponding to frequent to rare return periods. The influence of 1D Saint Venant and 2D Shallow water model input parameters on simulated flows is assessed using global sensitivity analysis (GSA). The tested parameters are: global and local boundary conditions (water heights and discharge), spatially uniform or distributed friction coefficient and or porosity respectively tested in various ranges centered around their nominal values - calibrated thanks to accurate experimental data and related uncertainties. For various experimental configurations a variance decomposition method (ANOVA) is used to calculate spatially distributed Sobol' sensitivity indices (Si's). The sensitivity of water depth to input parameters on two main streets of the experimental device is presented here. Results show that the closer from the downstream boundary condition on water height, the higher the Sobol' index as predicted by hydraulic theory for subcritical flow, while interestingly the sensitivity to friction decreases. The sensitivity indices of all lateral inflows, representing crossroads in 1D, are also quantified in this study along with their asymptotic trends along flow distance. The relationship between lateral discharge magnitude and resulting sensitivity index of water depth is investigated. Concerning simulations with distributed friction coefficients, crossroad friction is shown to have much higher influence on upstream water depth profile than street friction coefficients. This methodology could be applied to any urban flood configuration in order to better understand flow dynamics and repartition but also guide model calibration in the light of flow controls.

Distributed gain in plasmonic reflectors and its use for terahertz generation.

PubMed

Sydoruk, O; Syms, R R A; Solymar, L

2012-08-27

Semiconductor plasmons have potential for terahertz generation. Because practical device formats may be quasi-optical, we studied theoretically distributed plasmonic reflectors that comprise multiple interfaces between cascaded two-dimensional electron channels. Employing a mode-matching technique, we show that transmission through and reflection from a single interface depend on the magnitude and direction of a dc current flowing in the channels. As a result, plasmons can be amplified at an interface, and the cumulative effect of multiple interfaces increases the total gain, leading to plasmonic reflection coefficients exceeding unity. Reversing the current direction in a distributed reflector, however, has the opposite effect of plasmonic deamplification. Consequently, we propose structurally asymmetric resonators comprising two different distributed reflectors and predict that they are capable of terahertz oscillations at low threshold currents.

Modelling of PM10 concentration for industrialized area in Malaysia: A case study in Shah Alam

NASA Astrophysics Data System (ADS)

N, Norazian Mohamed; Abdullah, M. M. A.; Tan, Cheng-yau; Ramli, N. A.; Yahaya, A. S.; Fitri, N. F. M. Y.

In Malaysia, the predominant air pollutants are suspended particulate matter (SPM) and nitrogen dioxide (NO2). This research is on PM10 as they may trigger harm to human health as well as environment. Six distributions, namely Weibull, log-normal, gamma, Rayleigh, Gumbel and Frechet were chosen to model the PM10 observations at the chosen industrial area i.e. Shah Alam. One-year period hourly average data for 2006 and 2007 were used for this research. For parameters estimation, method of maximum likelihood estimation (MLE) was selected. Four performance indicators that are mean absolute error (MAE), root mean squared error (RMSE), coefficient of determination (R2) and prediction accuracy (PA), were applied to determine the goodness-of-fit criteria of the distributions. The best distribution that fits with the PM10 observations in Shah Alamwas found to be log-normal distribution. The probabilities of the exceedences concentration were calculated and the return period for the coming year was predicted from the cumulative density function (cdf) obtained from the best-fit distributions. For the 2006 data, Shah Alam was predicted to exceed 150 μg/m3 for 5.9 days in 2007 with a return period of one occurrence per 62 days. For 2007, the studied area does not exceed the MAAQG of 150 μg/m3

Confidence bounds and hypothesis tests for normal distribution coefficients of variation

Treesearch

Steve Verrill; Richard A. Johnson

2007-01-01

For normally distributed populations, we obtain confidence bounds on a ratio of two coefficients of variation, provide a test for the equality of k coefficients of variation, and provide confidence bounds on a coefficient of variation shared by k populations.

Hypo- and hyperglycemia in relation to the mean, standard deviation, coefficient of variation, and nature of the glucose distribution.

PubMed

Rodbard, David

2012-10-01

We describe a new approach to estimate the risks of hypo- and hyperglycemia based on the mean and SD of the glucose distribution using optional transformations of the glucose scale to achieve a more nearly symmetrical and Gaussian distribution, if necessary. We examine the correlation of risks of hypo- and hyperglycemia calculated using different glucose thresholds and the relationships of these risks to the mean glucose, SD, and percentage coefficient of variation (%CV). Using representative continuous glucose monitoring datasets, one can predict the risk of glucose values above or below any arbitrary threshold if the glucose distribution is Gaussian or can be transformed to be Gaussian. Symmetry and gaussianness can be tested objectively and used to optimize the transformation. The method performs well with excellent correlation of predicted and observed risks of hypo- or hyperglycemia for individual subjects by time of day or for a specified range of dates. One can compare observed and calculated risks of hypo- and hyperglycemia for a series of thresholds considering their uncertainties. Thresholds such as 80 mg/dL can be used as surrogates for thresholds such as 50 mg/dL. We observe a high correlation of risk of hypoglycemia with %CV and illustrate the theoretical basis for that relationship. One can estimate the historical risks of hypo- and hyperglycemia by time of day, date, day of the week, or range of dates, using any specified thresholds. Risks of hypoglycemia with one threshold (e.g., 80 mg/dL) can be used as an effective surrogate marker for hypoglycemia at other thresholds (e.g., 50 mg/dL). These estimates of risk can be useful in research studies and in the clinical care of patients with diabetes.

Refining calibration and predictions of a Bayesian statistical-dynamical model for long term avalanche forecasting using dendrochronological reconstructions

NASA Astrophysics Data System (ADS)

Eckert, Nicolas; Schläppy, Romain; Jomelli, Vincent; Naaim, Mohamed

2013-04-01

A crucial step for proposing relevant long-term mitigation measures in long term avalanche forecasting is the accurate definition of high return period avalanches. Recently, "statistical-dynamical" approach combining a numerical model with stochastic operators describing the variability of its inputs-outputs have emerged. Their main interests is to take into account the topographic dependency of snow avalanche runout distances, and to constrain the correlation structure between model's variables by physical rules, so as to simulate the different marginal distributions of interest (pressure, flow depth, etc.) with a reasonable realism. Bayesian methods have been shown to be well adapted to achieve model inference, getting rid of identifiability problems thanks to prior information. An important problem which has virtually never been considered before is the validation of the predictions resulting from a statistical-dynamical approach (or from any other engineering method for computing extreme avalanches). In hydrology, independent "fossil" data such as flood deposits in caves are sometimes confronted to design discharges corresponding to high return periods. Hence, the aim of this work is to implement a similar comparison between high return period avalanches obtained with a statistical-dynamical approach and independent validation data resulting from careful dendrogeomorphological reconstructions. To do so, an up-to-date statistical model based on the depth-averaged equations and the classical Voellmy friction law is used on a well-documented case study. First, parameter values resulting from another path are applied, and the dendrological validation sample shows that this approach fails in providing realistic prediction for the case study. This may be due to the strongly bounded behaviour of runouts in this case (the extreme of their distribution is identified as belonging to the Weibull attraction domain). Second, local calibration on the available avalanche chronicle is performed with various prior distributions resulting from expert knowledge and/or other paths. For all calibrations, a very successful convergence is obtained, which confirms the robustness of the used Metropolis-Hastings estimation algorithm. This also demonstrates the interest of the Bayesian framework for aggregating information by sequential assimilation in the frequently encountered case of limited data quantity. Confrontation with the dendrological sample stresses the predominant role of the Coulombian friction coefficient distribution's variance on predicted high magnitude runouts. The optimal fit is obtained for a strong prior reflecting the local bounded behavior, and results in a 10-40 m difference for return periods ranging between 10 and 300 years. Implementing predictive simulations shows that this is largely within the range of magnitude of uncertainties to be taken into account. On the other hand, the different priors tested for the turbulent friction coefficient influence predictive performances only slightly, but have a large influence on predicted velocity and flow depth distributions. This all may be of high interest to refine calibration and predictive use of the statistical-dynamical model for any engineering application.

Bio-Optical Properties of the Arabian Sea as Determined by In Situ and Sea WiFS Data

NASA Technical Reports Server (NTRS)

Trees, Charles C.

1997-01-01

The overall objective of this work was to characterize optical and fluorescence properties in the euphotic zone during two British Ocean Flux Study (BOFS) Arabian Sea cruises. This was later expanded in 1995 to include three U.S. JGOFS Arabian Sea Cruises. The region was to be divided into one or more "bio-optical provinces," within each of which a single set of regression models was to be developed to relate the vertical distribution of irradiance attenuation and normalized fluorescence (SF and NF) to remote sensing reflectance and diffuse attenuation coefficient. The working hypothesis was that over relatively large spatial and temporal scales, the vertical profiles of bio-optical properties were predictable. The specific technical objectives were: (1) To characterize the vertical distribution of the inherent and apparent optical properties by measuring downwelling and upwelling irradiances, upwelling radiances, scalar irradiance of PAR, and beam transmissions at each station - from these data, spectral diffuse attenuation coefficients, irradiance reflectances, remote sensing reflectances, surface-leaving radiances and beam attenuation coefficients were determined; (2) To characterize the spectral absorption of total particulate, detrital, and dissolved organic material at each station from discrete water samples; (3) To describe the vertical distribution of photoadaptive properties in the water column by measuring profiles of stimulated (SF) and natural (NF) fluorescence and examining relationships between SF and NF as a function of diffuse optical depth, pigment biomass and primary productivity; and (4) To establish locally derived, in-water algorithms relating remote sensing reflectance spectra to diffuse attenuation coefficients, phytoplankton pigment concentrations and primary productivity, through intercomparisons with in situ measurements, for application to SeaWiFS data.

Equilibrium sorption and diffusion rate studies with halogenated organic chemical and sandy aquifer material

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ball, W.P.

1990-01-01

Concepts for rate limitation of sorptive uptake of hydrophobic organic solutes by aquifer solids are reviewed, emphasizing physical diffusion models and in the context of effects on contaminant transport. Data for the sorption of tetrachloroethene (PCE) and 1,2,4,5-tetrachlorobenzene (TeCB) on Borden sand are presented, showing that equilibrium is attained very slowly, requiring equilibration times on the order of tens of days for PCE and hundreds of days for TeCB. The rate of approach to equilibrium decreased with increasing particle size and sorption distribution coefficient, in accordance with retarded intragranular diffusion models. Pulverization of the samples significantly decreased the required timemore » to equilibrium without changing the sorption capacity of the solids. Batch sorption methodology was refined to allow accurate measurement of long-term distribution coefficients, using purified {sup 14}C-labelled solute spikes and sealed glass ampules. Sorption isotherms for PCE and TeCB were conducted with size fractions of Borden sand over four to five orders of magnitude in aqueous concentration, and were found to be slightly nonlinear (Freundlich exponent = 0.8). A concentrated set of data in the low concentration range (<50 ug/L) revealed that sorption in this range could be equally well described by a linear isotherm. Distribution coefficients of the two solutes with seven size fractions of Borden sand, measured at low concentration and at full equilibrium, were between seven and sixty times the value predicted on the basis of recent correlations with organic carbon content. Rate results for coarse size fractions support a simple pore diffusion model, with pore diffusion coefficients estimated to be approximately 3 {times} 10{sup {minus}8} cm{sup 2}/sec, more than 200{times} lower than the aqueous diffusivities.« less

Numerical simulation of fiber interaction in short-fiber injection-molded composite using different cavity geometries

DOE Office of Scientific and Technical Information (OSTI.GOV)

Thi, Thanh Binh Nguyen, E-mail: nttbinh@kit.ac.jp; Yokoyama, Atsushi, E-mail: yokoyama@kit.ac.jp; Hamanaka, Senji

The theoretical fiber-interaction model for calculating the fiber orientation in the injection molded short fiber/thermoplastic composite parts was proposed. The proposed model included the fiber dynamics simulation in order to obtain an equation of the global interaction coefficient and accurate estimate of the fiber interacts at all orientation states. The steps to derive the equation for this coefficient in short fiber suspension as a function of the fiber aspect ratio, volume fraction and general shear rate are delineated. Simultaneously, the high-resolution 3D X-ray computed tomography system XVA-160α was used to observe fiber distribution of short-glass-fiber-reinforced polyamide specimens using different cavitymore » geometries. The fiber orientation tensor components are then calculated. Experimental orientation measurements of short-glass-fiber-reinforced polyamide is used to check the ability of present theory for predicting orientation. The experiments and predictions show a quantitative agreement and confirm the basic understanding of fiber orientation in injection-molded composites.« less

Numerical simulation of fiber interaction in short-fiber injection-molded composite using different cavity geometries

NASA Astrophysics Data System (ADS)

Thi, Thanh Binh Nguyen; Yokoyama, Atsushi; Hamanaka, Senji; Yamashita, Katsuhisa; Nonomura, Chisato

2016-03-01

The theoretical fiber-interaction model for calculating the fiber orientation in the injection molded short fiber/thermoplastic composite parts was proposed. The proposed model included the fiber dynamics simulation in order to obtain an equation of the global interaction coefficient and accurate estimate of the fiber interacts at all orientation states. The steps to derive the equation for this coefficient in short fiber suspension as a function of the fiber aspect ratio, volume fraction and general shear rate are delineated. Simultaneously, the high-resolution 3D X-ray computed tomography system XVA-160α was used to observe fiber distribution of short-glass-fiber-reinforced polyamide specimens using different cavity geometries. The fiber orientation tensor components are then calculated. Experimental orientation measurements of short-glass-fiber-reinforced polyamide is used to check the ability of present theory for predicting orientation. The experiments and predictions show a quantitative agreement and confirm the basic understanding of fiber orientation in injection-molded composites.

Analysis on the Oversize Blast Furnace Desulfurization and a Sulfide Capacity Prediction Model Based on Congregated Electron Phase

NASA Astrophysics Data System (ADS)

Zhenyang, Wang; Jianliang, Zhang; Gang, An; Zhengjian, Liu; Zhengming, Cheng; Junjie, Huang; Jingwei, Zhang

2016-02-01

Through analyzed and regressed the actual productive desulfurization data from the oversize blast furnace (5500 m3) in north China, the relationship between the sulfur distribution parameters and the slag composition in actual production situation was investigated. As the slag and hot metal phases have their own balance sulfur content or sulfur partial pressure in gas phase, respectively, the non-equilibrium of sulfur among gas, slag, and metal phases leads to the transmission and distribution of sulfur. Combined with sulfur transmission reactions between gas, slag and metal phases, C/CO pairs equilibrium, and Wagner model, the measured sulfide capacity can be acquired using sulfur distribution ratio, sulfur activity coefficient, and oxygen activity in hot metal. Based on the theory of congregated electron phase, a new sulfide capacity prediction model (CEPM) has been developed, which has a good liner relationship with the measured sulfide capacity. Thus, using the burden structure for BF, the ironmaking slag composition can be obtained simply and can be used to reliably predict the ironmaking slag desulfurization ability a few hours later after charging under a certain temperature by CEPM.

Predicting phenolic acid absorption in Caco-2 cells: a theoretical permeability model and mechanistic study.

PubMed

Farrell, Tracy L; Poquet, Laure; Dew, Tristan P; Barber, Stuart; Williamson, Gary

2012-02-01

There is a considerable need to rationalize the membrane permeability and mechanism of transport for potential nutraceuticals. The aim of this investigation was to develop a theoretical permeability equation, based on a reported descriptive absorption model, enabling calculation of the transcellular component of absorption across Caco-2 monolayers. Published data for Caco-2 permeability of 30 drugs transported by the transcellular route were correlated with the descriptors 1-octanol/water distribution coefficient (log D, pH 7.4) and size, based on molecular mass. Nonlinear regression analysis was used to derive a set of model parameters a', β', and b' with an integrated molecular mass function. The new theoretical transcellular permeability (TTP) model obtained a good fit of the published data (R² = 0.93) and predicted reasonably well (R² = 0.86) the experimental apparent permeability coefficient (P(app)) for nine non-training set compounds reportedly transported by the transcellular route. For the first time, the TTP model was used to predict the absorption characteristics of six phenolic acids, and this original investigation was supported by in vitro Caco-2 cell mechanistic studies, which suggested that deviation of the P(app) value from the predicted transcellular permeability (P(app)(trans)) may be attributed to involvement of active uptake, efflux transporters, or paracellular flux.

On the turbulent friction layer for rising pressure

NASA Technical Reports Server (NTRS)

Wieghardt, K; Tillmann, W

1951-01-01

Among the information presented are included displacement, momentum, and kinetic energy thicknesses, shearing stress distributions across boundary layer, and surface friction coefficients. The Gruschwitz method and its modifications are examined and tested. An energy theorem for the turbulent boundary layer is introduced and discussed but does not lead to a method for the prediction of the behavior of the turbulent boundary layer because relations for the shearing stress and the surface friction are lacking.

Experimental measurement of the dynamic pressure distribution in a squeeze film bearing damper executing circular centered orbits

NASA Technical Reports Server (NTRS)

Sanandres, L. A.; Vance, J. M.

1987-01-01

A review of previous experimental measurements of squeeze film damper (SFD) forces is given. Measurements by the authors of SFD pressure fields and force coefficients, for circular centered orbits with epsilon = 0.5, are described and compared with computer predictions. For Reynolds numbers over the range 2-6, the effect of fluid inertia on the pressure fields and forces is found to be significant.

Pressure Distributions for the GA(W)-2 Airfoil with 20% Aileron, 25% Slotted Flap and 30% Fowler Flap

NASA Technical Reports Server (NTRS)

Wentz, W. H., Jr.; Fiscko, K. A.

1978-01-01

Surface pressure distributions were measured for the 13% thick GA(W)-2 airfoil section fitted with 20% aileron, 25% slotted flap and 30% Fowler flap. All tests were conducted at a Reynolds number of 2.2 x 10 to the 6th power and a Mach number of 0.13. Pressure distribution and force and moment coefficient measurements are compared with theoretical results for a number of cases. Agreement between theory and experiment is generally good for low angles of attack and small flap deflections. For high angles and large flap deflections where regions of separation are present, the theory is inadequate. Theoretical drag predictions are poor for all flap-extended cases.

Predicting Salt Permeability Coefficients in Highly Swollen, Highly Charged Ion Exchange Membranes.

PubMed

Kamcev, Jovan; Paul, Donald R; Manning, Gerald S; Freeman, Benny D

2017-02-01

This study presents a framework for predicting salt permeability coefficients in ion exchange membranes in contact with an aqueous salt solution. The model, based on the solution-diffusion mechanism, was tested using experimental salt permeability data for a series of commercial ion exchange membranes. Equilibrium salt partition coefficients were calculated using a thermodynamic framework (i.e., Donnan theory), incorporating Manning's counterion condensation theory to calculate ion activity coefficients in the membrane phase and the Pitzer model to calculate ion activity coefficients in the solution phase. The model predicted NaCl partition coefficients in a cation exchange membrane and two anion exchange membranes, as well as MgCl 2 partition coefficients in a cation exchange membrane, remarkably well at higher external salt concentrations (>0.1 M) and reasonably well at lower external salt concentrations (<0.1 M) with no adjustable parameters. Membrane ion diffusion coefficients were calculated using a combination of the Mackie and Meares model, which assumes ion diffusion in water-swollen polymers is affected by a tortuosity factor, and a model developed by Manning to account for electrostatic effects. Agreement between experimental and predicted salt diffusion coefficients was good with no adjustable parameters. Calculated salt partition and diffusion coefficients were combined within the framework of the solution-diffusion model to predict salt permeability coefficients. Agreement between model and experimental data was remarkably good. Additionally, a simplified version of the model was used to elucidate connections between membrane structure (e.g., fixed charge group concentration) and salt transport properties.

Orbital transfer rocket engine technology program: Soft wear ring seal technology

NASA Technical Reports Server (NTRS)

Lariviere, Brian W.

1992-01-01

Liquid oxygen (LOX) compatibility tests, including autogenous ignition, promoted ignition, LOX impact tests, and friction and wear tests on different PV products were conducted for several polymer materials as verification for the implementation of soft wear ring seals in advanced rocket engine turbopumps. Thermoplastics, polyimide based materials, and polyimide-imide base materials were compared for oxygen compatibility, specific wear coefficient, wear debris production, and heat dissipation mechanisms. A thermal model was generated that simulated the frictional heating input and calculated the surface temperature and temperature distribution within the seal. The predictions were compared against measured values. Heat loads in the model were varied to better match the test data and determine the difference between the measured and the calculated coefficients of friction.

Comparison of neptunium sorption results using batch and column techniques

DOE Office of Scientific and Technical Information (OSTI.GOV)

Triay, I.R.; Furlano, A.C.; Weaver, S.C.

1996-08-01

We used crushed-rock columns to study the sorption retardation of neptunium by zeolitic, devitrified, and vitric tuffs typical of those at the site of the potential high-level nuclear waste repository at Yucca Mountain, Nevada. We used two sodium bicarbonate waters (groundwater from Well J-13 at the site and water prepared to simulate groundwater from Well UE-25p No. 1) under oxidizing conditions. It was found that values of the sorption distribution coefficient, Kd, obtained from these column experiments under flowing conditions, regardless of the water or the water velocity used, agreed well with those obtained earlier from batch sorption experiments undermore » static conditions. The batch sorption distribution coefficient can be used to predict the arrival time for neptunium eluted through the columns. On the other hand, the elution curves showed dispersivity, which implies that neptunium sorption in these tuffs may be nonlinear, irreversible, or noninstantaneous. As a result, use of a batch sorption distribution coefficient to calculate neptunium transport through Yucca Mountain tuffs would yield conservative values for neptunium release from the site. We also noted that neptunium (present as the anionic neptunyl carbonate complex) never eluted prior to tritiated water, which implies that charge exclusion does not appear to exclude neptunium from the tuff pores. The column experiments corroborated the trends observed in batch sorption experiments: neptunium sorption onto devitrified and vitric tuffs is minimal and sorption onto zeolitic tuffs decreases as the amount of sodium and bicarbonate/carbonate in the water increases.« less

Rapid assessment of nonlinear optical propagation effects in dielectrics

PubMed Central

Hoyo, J. del; de la Cruz, A. Ruiz; Grace, E.; Ferrer, A.; Siegel, J.; Pasquazi, A.; Assanto, G.; Solis, J.

2015-01-01

Ultrafast laser processing applications need fast approaches to assess the nonlinear propagation of the laser beam in order to predict the optimal range of processing parameters in a wide variety of cases. We develop here a method based on the simple monitoring of the nonlinear beam shaping against numerical prediction. The numerical code solves the nonlinear Schrödinger equation with nonlinear absorption under simplified conditions by employing a state-of-the art computationally efficient approach. By comparing with experimental results we can rapidly estimate the nonlinear refractive index and nonlinear absorption coefficients of the material. The validity of this approach has been tested in a variety of experiments where nonlinearities play a key role, like spatial soliton shaping or fs-laser waveguide writing. The approach provides excellent results for propagated power densities for which free carrier generation effects can be neglected. Above such a threshold, the peculiarities of the nonlinear propagation of elliptical beams enable acquiring an instantaneous picture of the deposition of energy inside the material realistic enough to estimate the effective nonlinear refractive index and nonlinear absorption coefficients that can be used for predicting the spatial distribution of energy deposition inside the material and controlling the beam in the writing process. PMID:25564243

Rapid assessment of nonlinear optical propagation effects in dielectrics.

PubMed

del Hoyo, J; de la Cruz, A Ruiz; Grace, E; Ferrer, A; Siegel, J; Pasquazi, A; Assanto, G; Solis, J

2015-01-07

Ultrafast laser processing applications need fast approaches to assess the nonlinear propagation of the laser beam in order to predict the optimal range of processing parameters in a wide variety of cases. We develop here a method based on the simple monitoring of the nonlinear beam shaping against numerical prediction. The numerical code solves the nonlinear Schrödinger equation with nonlinear absorption under simplified conditions by employing a state-of-the art computationally efficient approach. By comparing with experimental results we can rapidly estimate the nonlinear refractive index and nonlinear absorption coefficients of the material. The validity of this approach has been tested in a variety of experiments where nonlinearities play a key role, like spatial soliton shaping or fs-laser waveguide writing. The approach provides excellent results for propagated power densities for which free carrier generation effects can be neglected. Above such a threshold, the peculiarities of the nonlinear propagation of elliptical beams enable acquiring an instantaneous picture of the deposition of energy inside the material realistic enough to estimate the effective nonlinear refractive index and nonlinear absorption coefficients that can be used for predicting the spatial distribution of energy deposition inside the material and controlling the beam in the writing process.

Rapid assessment of nonlinear optical propagation effects in dielectrics

NASA Astrophysics Data System (ADS)

Hoyo, J. Del; de La Cruz, A. Ruiz; Grace, E.; Ferrer, A.; Siegel, J.; Pasquazi, A.; Assanto, G.; Solis, J.

2015-01-01

Ultrafast laser processing applications need fast approaches to assess the nonlinear propagation of the laser beam in order to predict the optimal range of processing parameters in a wide variety of cases. We develop here a method based on the simple monitoring of the nonlinear beam shaping against numerical prediction. The numerical code solves the nonlinear Schrödinger equation with nonlinear absorption under simplified conditions by employing a state-of-the art computationally efficient approach. By comparing with experimental results we can rapidly estimate the nonlinear refractive index and nonlinear absorption coefficients of the material. The validity of this approach has been tested in a variety of experiments where nonlinearities play a key role, like spatial soliton shaping or fs-laser waveguide writing. The approach provides excellent results for propagated power densities for which free carrier generation effects can be neglected. Above such a threshold, the peculiarities of the nonlinear propagation of elliptical beams enable acquiring an instantaneous picture of the deposition of energy inside the material realistic enough to estimate the effective nonlinear refractive index and nonlinear absorption coefficients that can be used for predicting the spatial distribution of energy deposition inside the material and controlling the beam in the writing process.

Music therapy career aptitude and generalized self-efficacy in music therapy students.

PubMed

Lim, Hayoung A; Befi, Cathy M

2014-01-01

While the Music Therapy Career Aptitude Test (MTCAT) provides a measure of student aptitude, measures of perceived self-efficacy may provide additional information about a students' suitability for a music therapy career. As a first step in determining whether future studies examining combined scores from the MTCAT and the Generalized Self-Efficacy (GSE) scale would be useful to help predict academic success in music therapy, we explored the internal reliability of these two measures in a sample of undergraduate students, and the relationship (concurrent validity) of the measures to one another. Eighty undergraduate music therapy students (14 male; 66 female) completed the MTCAT and GSE. To determine internal reliability we conducted tests of normality and calculated Cronbach's Coefficient Alpha for each measure. Pearson correlation coefficients were calculated to ascertain the strength of the relationship between the MTCAT and GSE. MTCAT scores were normally distributed and had high internal consistency (Cronbach's α = 0.706). GSE scores were not normally distributed, but had high internal consistency (Cronbach's α = 0.748). The correlation coefficient analysis revealed that MTCAT and GSE scores were moderately correlated ((r = 0.426, p < 0.0001). MTCAT scores can be used to partially determine perceived self-efficacy in undergraduate music therapy students; however, a more complete picture of student suitability for music therapy may be determined by administering the GSE alongside the MTCAT. Future studies are needed to determine whether combined MTCAT and GSE scores can be used to predict student success in an undergraduate music therapy program. © the American Music Therapy Association 2014. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Modeling Electronic Skin Response to Normal Distributed Force

PubMed Central

Seminara, Lucia

2018-01-01

The reference electronic skin is a sensor array based on PVDF (Polyvinylidene fluoride) piezoelectric polymers, coupled to a rigid substrate and covered by an elastomer layer. It is first evaluated how a distributed normal force (Hertzian distribution) is transmitted to an extended PVDF sensor through the elastomer layer. A simplified approach based on Boussinesq’s half-space assumption is used to get a qualitative picture and extensive FEM simulations allow determination of the quantitative response for the actual finite elastomer layer. The ultimate use of the present model is to estimate the electrical sensor output from a measure of a basic mechanical action at the skin surface. However this requires that the PVDF piezoelectric coefficient be known a-priori. This was not the case in the present investigation. However, the numerical model has been used to fit experimental data from a real skin prototype and to estimate the sensor piezoelectric coefficient. It turned out that this value depends on the preload and decreases as a result of PVDF aging and fatigue. This framework contains all the fundamental ingredients of a fully predictive model, suggesting a number of future developments potentially useful for skin design and validation of the fabrication technology. PMID:29401692

Modeling Electronic Skin Response to Normal Distributed Force.

PubMed

Seminara, Lucia

2018-02-03

The reference electronic skin is a sensor array based on PVDF (Polyvinylidene fluoride) piezoelectric polymers, coupled to a rigid substrate and covered by an elastomer layer. It is first evaluated how a distributed normal force (Hertzian distribution) is transmitted to an extended PVDF sensor through the elastomer layer. A simplified approach based on Boussinesq's half-space assumption is used to get a qualitative picture and extensive FEM simulations allow determination of the quantitative response for the actual finite elastomer layer. The ultimate use of the present model is to estimate the electrical sensor output from a measure of a basic mechanical action at the skin surface. However this requires that the PVDF piezoelectric coefficient be known a-priori. This was not the case in the present investigation. However, the numerical model has been used to fit experimental data from a real skin prototype and to estimate the sensor piezoelectric coefficient. It turned out that this value depends on the preload and decreases as a result of PVDF aging and fatigue. This framework contains all the fundamental ingredients of a fully predictive model, suggesting a number of future developments potentially useful for skin design and validation of the fabrication technology.

Experimental Verification Of The Osculating Cones Method For Two Waverider Forebodies At Mach 4 and 6

NASA Technical Reports Server (NTRS)

Miller, Rolf W.; Argrow, Brian M.; Center, Kenneth B.; Brauckmann, Gregory J.; Rhode, Matthew N.

1998-01-01

The NASA Langley Research Center Unitary Plan Wind Tunnel and the 20-Inch Mach 6 Tunnel were used to test two osculating cones waverider models. The Mach-4 and Mach-6 shapes were generated using the interactive design tool WIPAR. WIPAR performance predictions are compared to the experimental results. Vapor screen results for the Mach-4 model at the on- design Mach number provide visual verification that the shock is attached along the entire leading edge, within the limits of observation. WIPAR predictions of pressure distributions and aerodynamic coefficients show general agreement with the corresponding experimental values.

Diffusion Rates of Organic Molecules in Secondary Organic Aerosol Particle

NASA Astrophysics Data System (ADS)

Bertram, A. K.; Chenyakin, Y.; Song, M.; Grayson, J. W.; Ullmann, D.; Evoy, E.; Renbaum-Wolff, L.; Liu, P.; Zhang, Y.; Kamal, S.; Martin, S. T.

2016-12-01

Information on the diffusion rates of organic molecules in secondary organic aerosol (SOA) particles are needed when predicting their size distribution, growth rates, photochemistry and heterogeneous chemistry. We have used two approaches to determine diffusion rates of organic molecules in SOA particles and proxies of SOA. In the first approach, we measured viscosities and then predicted diffusion rates using the Stokes-Einstein relation. In the second approach, we measured diffusion rates directly using a technique referred to as fluorescence recovery after photobleaching. Results from these measurements, including diffusion coefficients as a function of water activity, will be presented and the implications discussed.

Microscopic prediction of speech intelligibility in spatially distributed speech-shaped noise for normal-hearing listeners.

PubMed

Geravanchizadeh, Masoud; Fallah, Ali

2015-12-01

A binaural and psychoacoustically motivated intelligibility model, based on a well-known monaural microscopic model is proposed. This model simulates a phoneme recognition task in the presence of spatially distributed speech-shaped noise in anechoic scenarios. In the proposed model, binaural advantage effects are considered by generating a feature vector for a dynamic-time-warping speech recognizer. This vector consists of three subvectors incorporating two monaural subvectors to model the better-ear hearing, and a binaural subvector to simulate the binaural unmasking effect. The binaural unit of the model is based on equalization-cancellation theory. This model operates blindly, which means separate recordings of speech and noise are not required for the predictions. Speech intelligibility tests were conducted with 12 normal hearing listeners by collecting speech reception thresholds (SRTs) in the presence of single and multiple sources of speech-shaped noise. The comparison of the model predictions with the measured binaural SRTs, and with the predictions of a macroscopic binaural model called extended equalization-cancellation, shows that this approach predicts the intelligibility in anechoic scenarios with good precision. The square of the correlation coefficient (r(2)) and the mean-absolute error between the model predictions and the measurements are 0.98 and 0.62 dB, respectively.

Revisiting crash spatial heterogeneity: A Bayesian spatially varying coefficients approach.

PubMed

Xu, Pengpeng; Huang, Helai; Dong, Ni; Wong, S C

2017-01-01

This study was performed to investigate the spatially varying relationships between crash frequency and related risk factors. A Bayesian spatially varying coefficients model was elaborately introduced as a methodological alternative to simultaneously account for the unstructured and spatially structured heterogeneity of the regression coefficients in predicting crash frequencies. The proposed method was appealing in that the parameters were modeled via a conditional autoregressive prior distribution, which involved a single set of random effects and a spatial correlation parameter with extreme values corresponding to pure unstructured or pure spatially correlated random effects. A case study using a three-year crash dataset from the Hillsborough County, Florida, was conducted to illustrate the proposed model. Empirical analysis confirmed the presence of both unstructured and spatially correlated variations in the effects of contributory factors on severe crash occurrences. The findings also suggested that ignoring spatially structured heterogeneity may result in biased parameter estimates and incorrect inferences, while assuming the regression coefficients to be spatially clustered only is probably subject to the issue of over-smoothness. Copyright © 2016 Elsevier Ltd. All rights reserved.

Hinge Moment Coefficient Prediction Tool and Control Force Analysis of Extra-300 Aerobatic Aircraft

NASA Astrophysics Data System (ADS)

Nurohman, Chandra; Arifianto, Ony; Barecasco, Agra

2018-04-01

This paper presents the development of tool that is applicable to predict hinge moment coefficients of subsonic aircraft based on Roskam’s method, including the validation and its application to predict hinge moment coefficient of an Extra-300. The hinge moment coefficients are used to predict the stick forces of the aircraft during several aerobatic maneuver i.e. inside loop, half cuban 8, split-s, and aileron roll. The maximum longitudinal stick force is 566.97 N occurs in inside loop while the maximum lateral stick force is 340.82 N occurs in aileron roll. Furthermore, validation hinge moment prediction method is performed using Cessna 172 data.

Measurement of the distribution coefficient of neodymium in cubic ZrO 2

NASA Astrophysics Data System (ADS)

Römer, H.; Luther, K.-D.; Assmus, W.

1993-05-01

The incorporation of solute elements into single crystals has been examined for many years. In this paper we investigate the distribution coefficient of Nd 2O 3 in cubic stabilized zirconiumdioxide crystals. The distribution coefficient is measured as a function of the growth velocity. The validity of the Burton-Prim-Slichter theory [J.A. Burton, R.C. Prim and W.P. Slichter, J. Chem. Phys. 21 (1953) 1987] for the system zirconium dioxide/yttrium oxide is confirmed by the experimental results. The value for the equilibrium distribution coefficient is evaluated as k0 = 0.426.

The SSME HPFTP interstage seals: Analysis and experiments for leakage and reaction-force coefficients

NASA Technical Reports Server (NTRS)

Childs, D. W.

1983-01-01

An improved theory for the prediction of the rotordynamic coefficients of turbulent annular seals was developed. Predictions from the theory are compared to the experimental results and an approach for the direct calculation of empirical turbulent coefficients from test data are introduced. An improved short seal solution is shown to do a better job of calculating effective stiffness and damping coefficients than either the original short seal solution or a finite length solution. However, the original short seal solution does a much better job of predicting equivalent added mass coefficient.

A wind-tunnel investigation of wind-turbine wakes in yawed conditions

NASA Astrophysics Data System (ADS)

Bastankhah, Majid; Porté-Agel, Fernando

2015-06-01

Wind-tunnel experiments were performed to study the performance of a model wind turbine and its wake characteristics in a boundary layer under different operating conditions, including different yaw angles and tip speed ratios. High-resolution particle image- velocimetry (PIV) was used to measure the three velocity components in a horizontal plane at hub height covering a broad streamwise range from upstream of the turbine to the far- wake region. Additionally, thrust and power coefficients of the turbine were measured under different conditions. These power and thrust measurements, together with the highly-resolved flow measurements, enabled us to systematically study different wake properties. The near-wake region is found to have a highly complex structure influenced by different factors such as tip speed ratio and wake rotation. In particular, for higher tip speed ratios, a noticeable speed-up region is observed in the central part of near wake, which greatly affects the flow distribution in this region. In this regard, the behavior of the near wake for turbines with similar thrust coefficients but different tip speed ratios can vary widely. In contrast, it is shown that the mean streamwise velocity in the far wake of the turbine with zero yaw angle has a self-similar Gaussian distribution, and the strength of wake in this region is consistent with the magnitude of the thrust coefficient. With increasing yaw angle, as expected, the power and thrust coefficients decrease, and the wake deflection increases. The measurements also reveal that, in addition to turbulent momentum flux, lateral mean momentum flux boosts the flow entrainment in only one side of the wake, which results in a faster wake recovery in that side. It is also found that the induced velocity upstream of a yawed turbine has a non-symmetric distribution, and its distribution is in agreement with the available model in the literature. Moreover, the results suggest that in order to accurately predict the load distribution in yawed conditions, both normal and tangential (with respect to the rotor plane) components of the induced velocity upstream of the turbine should be taken into account.

Quantitative models for predicting adsorption of oxytetracycline, ciprofloxacin and sulfamerazine to swine manures with contrasting properties.

PubMed

Cheng, Dengmiao; Feng, Yao; Liu, Yuanwang; Li, Jinpeng; Xue, Jianming; Li, Zhaojun

2018-09-01

Understanding antibiotic adsorption in livestock manures is crucial to assess the fate and risk of antibiotics in the environment. In this study, three quantitative models developed with swine manure-water distribution coefficients (LgK d ) for oxytetracycline (OTC), ciprofloxacin (CIP) and sulfamerazine (SM1) in swine manures. Physicochemical parameters (n=12) of the swine manure were used as independent variables using partial least-squares (PLSs) analysis. The cumulative cross-validated regression coefficients (Q 2 cum ) values, standard deviations (SDs) and external validation coefficient (Q 2 ext ) ranged from 0.761 to 0.868, 0.027 to 0.064, and 0.743 to 0.827 for the three models; as such, internal and external predictability of the models were strong. The pH, soluble organic carbon (SOC) and nitrogen (SON), and Ca were important explanatory variables for the OTC-Model, pH, SOC, and SON for the CIP-model, and pH, total organic nitrogen (TON), and SOC for the SM1-model. The high VIPs (variable importance in the projections) of pH (1.178-1.396), SOC (0.968-1.034), and SON (0.822 and 0.865) established these physicochemical parameters as likely being dominant (associatively) in affecting transport of antibiotics in swine manures. Copyright © 2018 Elsevier B.V. All rights reserved.

Population pharmacokinetics of phenytoin in critically ill children.

PubMed

Hennig, Stefanie; Norris, Ross; Tu, Quyen; van Breda, Karin; Riney, Kate; Foster, Kelly; Lister, Bruce; Charles, Bruce

2015-03-01

The objective was to study the population pharmacokinetics of bound and unbound phenytoin in critically ill children, including influences on the protein binding profile. A population pharmacokinetic approach was used to analyze paired protein-unbound and total phenytoin plasma concentrations (n = 146 each) from 32 critically ill children (0.08-17 years of age) who were admitted to a pediatric hospital, primarily intensive care unit. The pharmacokinetics of unbound and bound phenytoin and the influence of possible influential covariates were modeled and evaluated using visual predictive checks and bootstrapping. The pharmacokinetics of protein-unbound phenytoin was described satisfactorily by a 1-compartment model with first-order absorption in conjunction with a linear partition coefficient parameter to describe the binding of phenytoin to albumin. The partitioning coefficient describing protein binding and distribution to bound phenytoin was estimated to be 8.22. Nonlinear elimination of unbound phenytoin was not supported in this patient group. Weight, allometrically scaled for clearance and volume of distribution for the unbound and bound compartments, and albumin concentration significantly influenced the partition coefficient for protein binding of phenytoin. The population model can be applied to estimate the fraction of unbound phenytoin in critically ill children given an individual's albumin concentration. © 2014, The American College of Clinical Pharmacology.

Influence of the pressure dependent coefficient of friction on deep drawing springback predictions

NASA Astrophysics Data System (ADS)

Gil, Imanol; Galdos, Lander; Mendiguren, Joseba; Mugarra, Endika; Sáenz de Argandoña, Eneko

2016-10-01

This research studies the effect of considering an advanced variable friction coefficient on the springback prediction of stamping processes. Traditional constant coefficient of friction considerations are being replaced by more advanced friction coefficient definitions. The aim of this work is to show the influence of defining a pressure dependent friction coefficient on numerical springback predictions of a DX54D mild steel, a HSLA380 and a DP780 high strength steel. The pressure dependent friction model of each material was fitted to the experimental data obtained by Strip Drawing tests. Then, these friction models were implemented in a numerical simulation of a drawing process of an industrial automotive part. The results showed important differences between defining a pressure dependent friction coefficient or a constant friction coefficient.

Internal field distribution of a radially inhomogeneous droplet illuminated by an arbitrary shaped beam

NASA Astrophysics Data System (ADS)

Wang, Jia Jie; Wriedt, Thomas; Han, Yi Ping; Mädler, Lutz; Jiao, Yong Chang

2018-05-01

Light scattering of a radially inhomogeneous droplet, which is modeled by a multilayered sphere, is investigated within the framework of Generalized Lorenz-Mie Theory (GLMT), with particular efforts devoted to the analysis of the internal field distribution in the cases of shaped beam illumination. To circumvent numerical difficulties in the computation of internal field for an absorbing/non-absorbing droplet with pretty large size parameter, a recursive algorithm is proposed by reformulation of the equations for the expansion coefficients. Two approaches are proposed for the prediction of the internal field distribution, namely a rigorous method and an approximation method. The developed computer code is tested to be stable in a wide range of size parameters. Numerical computations are implemented to simulate the internal field distributions of a radially inhomogeneous droplet illuminated by a focused Gaussian beam.

Prediction of mass transfer coefficient in rotating bed contactor (Higee) using artificial neural network

NASA Astrophysics Data System (ADS)

Saha, Dipendu

2009-02-01

The feasibility of drastically reducing the contactor size in mass transfer processes utilizing centrifugal field has generated a lot of interest in rotating packed bed (Higee). Various investigators have proposed correlations to predict mass transfer coefficients in Higee, but, none of the correlations was more than 20-30% accurate. In this work, artificial neural network (ANN) is employed for predicting mass transfer coefficient data. Results show that ANN provides better estimation of mass transfer coefficient with accuracy 5-15%.

Vertical mass transfer in open channel flow

USGS Publications Warehouse

Jobson, Harvey E.

1968-01-01

The vertical mass transfer coefficient and particle fall velocity were determined in an open channel shear flow. Three dispersants, dye, fine sand and medium sand, were used with each of three flow conditions. The dispersant was injected as a continuous line source across the channel and downstream concentration profiles were measured. From these profiles along with the measured velocity distribution both the vertical mass transfer coefficient and the local particle fall velocity were determined.The effects of secondary currents on the vertical mixing process were discussed. Data was taken and analyzed in such a way as to largely eliminate the effects of these currents on the measured values. A procedure was developed by which the local value of the fall velocity of sand sized particles could be determined in an open channel flow. The fall velocity of the particles in the turbulent flow was always greater than their fall velocity in quiescent water. Reynolds analogy between the transfer of momentum and marked fluid particles was further substantiated. The turbulent Schmidt number was shown to be approximately 1.03 for an open channel flow with a rough boundary. Eulerian turbulence measurements were not sufficient to predict the vertical transfer coefficient. Vertical mixing of sediment is due to three semi-independent processes. These processes are: secondary currents, diffusion due to tangential velocity fluctuations and diffusion due to the curvature of the fluid particle path lines. The diffusion coefficient due to tangential velocity fluctuations is approximately proportional to the transfer coefficient of marked fluid particles. The proportionality constant is less than or equal to 1.0 and decreases with increasing particle size. The diffusion coefficient due to the curvature of the fluid particle path lines is not related to the diffusion coefficient for marked fluid particles and increases with particle size, at least for sediment particles in the sand size range. The total sediment transfer coefficient is equal to the sum of the coefficient due to tangential velocity fluctuations and the coefficient due to the curvature of the fluid particle path lines. A numerical solution to the conservation of mass equation is given. The effects of the transfer coefficient, fall velocity and bed conditions on the predicted concentration profiles are illustrated.

Calibration of the 2D Hydrodynamic Model Floodos and Implications of Distributed Friction on Sediment Transport Capacity

NASA Astrophysics Data System (ADS)

Croissant, T.; Lague, D.; Davy, P.

2014-12-01

Numerical models of floodplain dynamics often use a simplified 1D description of flow hydraulics and sediment transport that cannot fully account for differential friction between vegetated banks and low friction in the main channel. Key parameters of such models are the friction coefficient and the description of the channel bathymetry which strongly influence predicted water depth and velocity, and therefore sediment transport capacity. In this study, we use a newly developed 2D hydrodynamic model, Floodos, whose efficiency is a major advantage for exploring channel morphodynamics from a flood event to millennial time scales. We evaluate the quality of Floodos predictions in the Whataroa river, New Zealand and assess the effect of a spatially distributed friction coefficient (SDFC) on long term sediment transport. Predictions from the model are compared to water depth data from a gauging station located on the Whataroa River in Southern Alps, New Zealand. The Digital Elevation Model (DEM) of the 2.5 km long studied reach is derived from a 2010 LiDAR acquisition with 2 m resolution and an interpolated bathymetry. The several large floods experienced by this river during 2010 allow us to access water depth for a wide range of possible river discharges and to retrieve the scaling between these two parameters. The high resolution DEM used has a non-negligible part of submerged bathymetry that airborne LiDAR was not able to capture. Bathymetry can be reconstructed by interpolation methods that introduce several uncertainties concerning water depth predictions. We address these uncertainties inherent to the interpolation using a simplified channel with a geometry (slope and width) similar to the Whataroa river. We then explore the effect of a SDFC on velocity pattern, water depth and sediment transport capacity and discuss its relevance on long term predictions of sediment transport and channel morphodynamics.

Equilibrium distribution of rare earth elements between molten KCl-LiCl eutectic salt and liquid cadmium

NASA Astrophysics Data System (ADS)

Sakata, Masahiro; Kurata, Masaki; Hijikata, Takatoshi; Inoue, Tadashi

1991-11-01

Distribution experiments for several rare earth elements (La, Ce, Pr, Nd and Y) between molten KCl-LiCl eutectic salt and liquid Cd were carried out at 450, 500 and 600°C. The material balance of rare earth elements after reaching the equilibrium and their distribution and chemical states in a Cd sample frozen after the experiment were examined. The results suggested the formation of solid intermetallic compounds at the lower concentrations of rare earth metals dissolved in liquid Cd than those solubilities measured in the binary alloy system. The distribution coefficients of rare earth elements between two phases (mole fraction in the Cd phase divided by mole fraction in the salt phase) were determined at each temperature. These distribution coefficients were explained satisfactorily by using the activity coefficients of chlorides and metals in salt and Cd. Both the activity coefficients of metal and chloride caused a much smaller distribution coefficient of Y relative to those of other elements.

Assessment of critical path analyses of the relationship between permeability and electrical conductivity of pore networks

NASA Astrophysics Data System (ADS)

Skaggs, Todd H.

2011-10-01

Critical path analysis (CPA) is a method for estimating macroscopic transport coefficients of heterogeneous materials that are highly disordered at the micro-scale. Developed originally to model conduction in semiconductors, numerous researchers have noted that CPA might also have relevance to flow and transport processes in porous media. However, the results of several numerical investigations of critical path analysis on pore network models raise questions about the applicability of CPA to porous media. Among other things, these studies found that (i) in well-connected 3D networks, CPA predictions were inaccurate and became worse when heterogeneity was increased; and (ii) CPA could not fully explain the transport properties of 2D networks. To better understand the applicability of CPA to porous media, we made numerical computations of permeability and electrical conductivity on 2D and 3D networks with differing pore-size distributions and geometries. A new CPA model for the relationship between the permeability and electrical conductivity was found to be in good agreement with numerical data, and to be a significant improvement over a classical CPA model. In sufficiently disordered 3D networks, the new CPA prediction was within ±20% of the true value, and was nearly optimal in terms of minimizing the squared prediction errors across differing network configurations. The agreement of CPA predictions with 2D network computations was similarly good, although 2D networks are in general not well-suited for evaluating CPA. Numerical transport coefficients derived for regular 3D networks of slit-shaped pores were found to be in better agreement with experimental data from rock samples than were coefficients derived for networks of cylindrical pores.

QCD evolution of (un)polarized gluon TMDPDFs and the Higgs q T -distribution

NASA Astrophysics Data System (ADS)

Echevarria, Miguel G.; Kasemets, Tomas; Mulders, Piet J.; Pisano, Cristian

2015-07-01

We provide the proper definition of all the leading-twist (un)polarized gluon transverse momentum dependent parton distribution functions (TMDPDFs), by considering the Higgs boson transverse momentum distribution in hadron-hadron collisions and deriving the factorization theorem in terms of them. We show that the evolution of all the (un)polarized gluon TMDPDFs is driven by a universal evolution kernel, which can be resummed up to next-to-next-to-leading-logarithmic accuracy. Considering the proper definition of gluon TMDPDFs, we perform an explicit next-to-leading-order calculation of the unpolarized ( f {1/ g }), linearly polarized ( h {1/⊥ g }) and helicity ( g {1/L g }) gluon TMDPDFs, and show that, as expected, they are free from rapidity divergences. As a byproduct, we obtain the Wilson coefficients of the refactorization of these TMDPDFs at large transverse momentum. In particular, the coefficient of g {1/L g }, which has never been calculated before, constitutes a new and necessary ingredient for a reliable phenomenological extraction of this quantity, for instance at RHIC or the future AFTER@LHC or Electron-Ion Collider. The coefficients of f {1/ g } and h {1/⊥ g } have never been calculated in the present formalism, although they could be obtained by carefully collecting and recasting previous results in the new TMD formalism. We apply these results to analyze the contribution of linearly polarized gluons at different scales, relevant, for instance, for the inclusive production of the Higgs boson and the C-even pseudoscalar bottomonium state η b . Applying our resummation scheme we finally provide predictions for the Higgs boson q T -distribution at the LHC.

Gas-surface interactions using accommodation coefficients for a dilute and a dense gas in a micro- or nanochannel: heat flux predictions using combined molecular dynamics and Monte Carlo techniques.

PubMed

Nedea, S V; van Steenhoven, A A; Markvoort, A J; Spijker, P; Giordano, D

2014-05-01

The influence of gas-surface interactions of a dilute gas confined between two parallel walls on the heat flux predictions is investigated using a combined Monte Carlo (MC) and molecular dynamics (MD) approach. The accommodation coefficients are computed from the temperature of incident and reflected molecules in molecular dynamics and used as effective coefficients in Maxwell-like boundary conditions in Monte Carlo simulations. Hydrophobic and hydrophilic wall interactions are studied, and the effect of the gas-surface interaction potential on the heat flux and other characteristic parameters like density and temperature is shown. The heat flux dependence on the accommodation coefficient is shown for different fluid-wall mass ratios. We find that the accommodation coefficient is increasing considerably when the mass ratio is decreased. An effective map of the heat flux depending on the accommodation coefficient is given and we show that MC heat flux predictions using Maxwell boundary conditions based on the accommodation coefficient give good results when compared to pure molecular dynamics heat predictions. The accommodation coefficients computed for a dilute gas for different gas-wall interaction parameters and mass ratios are transferred to compute the heat flux predictions for a dense gas. Comparison of the heat fluxes derived using explicit MD, MC with Maxwell-like boundary conditions based on the accommodation coefficients, and pure Maxwell boundary conditions are discussed. A map of the heat flux dependence on the accommodation coefficients for a dense gas, and the effective accommodation coefficients for different gas-wall interactions are given. In the end, this approach is applied to study the gas-surface interactions of argon and xenon molecules on a platinum surface. The derived accommodation coefficients are compared with values of experimental results.

[Research on Kalman interpolation prediction model based on micro-region PM2.5 concentration].

PubMed

Wang, Wei; Zheng, Bin; Chen, Binlin; An, Yaoming; Jiang, Xiaoming; Li, Zhangyong

2018-02-01

In recent years, the pollution problem of particulate matter, especially PM2.5, is becoming more and more serious, which has attracted many people's attention from all over the world. In this paper, a Kalman prediction model combined with cubic spline interpolation is proposed, which is applied to predict the concentration of PM2.5 in the micro-regional environment of campus, and to realize interpolation simulation diagram of concentration of PM2.5 and simulate the spatial distribution of PM2.5. The experiment data are based on the environmental information monitoring system which has been set up by our laboratory. And the predicted and actual values of PM2.5 concentration data have been checked by the way of Wilcoxon signed-rank test. We find that the value of bilateral progressive significance probability was 0.527, which is much greater than the significant level α = 0.05. The mean absolute error (MEA) of Kalman prediction model was 1.8 μg/m 3 , the average relative error (MER) was 6%, and the correlation coefficient R was 0.87. Thus, the Kalman prediction model has a better effect on the prediction of concentration of PM2.5 than those of the back propagation (BP) prediction and support vector machine (SVM) prediction. In addition, with the combination of Kalman prediction model and the spline interpolation method, the spatial distribution and local pollution characteristics of PM2.5 can be simulated.

A robust holographic autofocusing criterion based on edge sparsity: comparison of Gini index and Tamura coefficient for holographic autofocusing based on the edge sparsity of the complex optical wavefront

NASA Astrophysics Data System (ADS)

Tamamitsu, Miu; Zhang, Yibo; Wang, Hongda; Wu, Yichen; Ozcan, Aydogan

2018-02-01

The Sparsity of the Gradient (SoG) is a robust autofocusing criterion for holography, where the gradient modulus of the complex refocused hologram is calculated, on which a sparsity metric is applied. Here, we compare two different choices of sparsity metrics used in SoG, specifically, the Gini index (GI) and the Tamura coefficient (TC), for holographic autofocusing on dense/connected or sparse samples. We provide a theoretical analysis predicting that for uniformly distributed image data, TC and GI exhibit similar behavior, while for naturally sparse images containing few high-valued signal entries and many low-valued noisy background pixels, TC is more sensitive to distribution changes in the signal and more resistive to background noise. These predictions are also confirmed by experimental results using SoG-based holographic autofocusing on dense and connected samples (such as stained breast tissue sections) as well as highly sparse samples (such as isolated Giardia lamblia cysts). Through these experiments, we found that ToG and GoG offer almost identical autofocusing performance on dense and connected samples, whereas for naturally sparse samples, GoG should be calculated on a relatively small region of interest (ROI) closely surrounding the object, while ToG offers more flexibility in choosing a larger ROI containing more background pixels.

Prediction of Carbohydrate Binding Sites on Protein Surfaces with 3-Dimensional Probability Density Distributions of Interacting Atoms

PubMed Central

Tsai, Keng-Chang; Jian, Jhih-Wei; Yang, Ei-Wen; Hsu, Po-Chiang; Peng, Hung-Pin; Chen, Ching-Tai; Chen, Jun-Bo; Chang, Jeng-Yih; Hsu, Wen-Lian; Yang, An-Suei

2012-01-01

Non-covalent protein-carbohydrate interactions mediate molecular targeting in many biological processes. Prediction of non-covalent carbohydrate binding sites on protein surfaces not only provides insights into the functions of the query proteins; information on key carbohydrate-binding residues could suggest site-directed mutagenesis experiments, design therapeutics targeting carbohydrate-binding proteins, and provide guidance in engineering protein-carbohydrate interactions. In this work, we show that non-covalent carbohydrate binding sites on protein surfaces can be predicted with relatively high accuracy when the query protein structures are known. The prediction capabilities were based on a novel encoding scheme of the three-dimensional probability density maps describing the distributions of 36 non-covalent interacting atom types around protein surfaces. One machine learning model was trained for each of the 30 protein atom types. The machine learning algorithms predicted tentative carbohydrate binding sites on query proteins by recognizing the characteristic interacting atom distribution patterns specific for carbohydrate binding sites from known protein structures. The prediction results for all protein atom types were integrated into surface patches as tentative carbohydrate binding sites based on normalized prediction confidence level. The prediction capabilities of the predictors were benchmarked by a 10-fold cross validation on 497 non-redundant proteins with known carbohydrate binding sites. The predictors were further tested on an independent test set with 108 proteins. The residue-based Matthews correlation coefficient (MCC) for the independent test was 0.45, with prediction precision and sensitivity (or recall) of 0.45 and 0.49 respectively. In addition, 111 unbound carbohydrate-binding protein structures for which the structures were determined in the absence of the carbohydrate ligands were predicted with the trained predictors. The overall prediction MCC was 0.49. Independent tests on anti-carbohydrate antibodies showed that the carbohydrate antigen binding sites were predicted with comparable accuracy. These results demonstrate that the predictors are among the best in carbohydrate binding site predictions to date. PMID:22848404

A Pilot Comparative Study of Quantitative Ultrasound, Conventional Ultrasound, and MRI for Predicting Histology-Determined Steatosis Grade in Adult Nonalcoholic Fatty Liver Disease

PubMed Central

Paige, Jeremy S.; Bernstein, Gregory S.; Heba, Elhamy; Costa, Eduardo A. C.; Fereirra, Marilia; Wolfson, Tanya; Gamst, Anthony C.; Valasek, Mark A.; Lin, Grace Y.; Han, Aiguo; Erdman, John W.; O’Brien, William D.; Andre, Michael P.; Loomba, Rohit; Sirlin, Claude B.

2017-01-01

OBJECTIVE The purpose of this study is to explore the diagnostic performance of two investigational quantitative ultrasound (QUS) parameters, attenuation coefficient and backscatter coefficient, in comparison with conventional ultrasound (CUS) and MRI-estimated proton density fat fraction (PDFF) for predicting histology-confirmed steatosis grade in adults with nonalcoholic fatty liver disease (NAFLD). SUBJECTS AND METHODS In this prospectively designed pilot study, 61 adults with histology-confirmed NAFLD were enrolled from September 2012 to February 2014. Subjects underwent QUS, CUS, and MRI examinations within 100 days of clinical-care liver biopsy. QUS parameters (attenuation coefficient and backscatter coefficient) were estimated using a reference phantom technique by two analysts independently. Three-point ordinal CUS scores intended to predict steatosis grade (1, 2, or 3) were generated independently by two radiologists on the basis of QUS features. PDFF was estimated using an advanced chemical shift–based MRI technique. Using histologic examination as the reference standard, ROC analysis was performed. Optimal attenuation coefficient, backscatter coefficient, and PDFF cutoff thresholds were identified, and the accuracy of attenuation coefficient, backscatter coefficient, PDFF, and CUS to predict steatosis grade was determined. Interobserver agreement for attenuation coefficient, backscatter coefficient, and CUS was analyzed. RESULTS CUS had 51.7% grading accuracy. The raw and cross-validated steatosis grading accuracies were 61.7% and 55.0%, respectively, for attenuation coefficient, 68.3% and 68.3% for backscatter coefficient, and 76.7% and 71.3% for MRI-estimated PDFF. Interobserver agreements were 53.3% for CUS (κ = 0.61), 90.0% for attenuation coefficient (κ = 0.87), and 71.7% for backscatter coefficient (κ = 0.82) (p < 0.0001 for all). CONCLUSION Preliminary observations suggest that QUS parameters may be more accurate and provide higher interobserver agreement than CUS for predicting hepatic steatosis grade in patients with NAFLD. PMID:28267360

A Pilot Comparative Study of Quantitative Ultrasound, Conventional Ultrasound, and MRI for Predicting Histology-Determined Steatosis Grade in Adult Nonalcoholic Fatty Liver Disease.

PubMed

Paige, Jeremy S; Bernstein, Gregory S; Heba, Elhamy; Costa, Eduardo A C; Fereirra, Marilia; Wolfson, Tanya; Gamst, Anthony C; Valasek, Mark A; Lin, Grace Y; Han, Aiguo; Erdman, John W; O'Brien, William D; Andre, Michael P; Loomba, Rohit; Sirlin, Claude B

2017-05-01

The purpose of this study is to explore the diagnostic performance of two investigational quantitative ultrasound (QUS) parameters, attenuation coefficient and backscatter coefficient, in comparison with conventional ultrasound (CUS) and MRI-estimated proton density fat fraction (PDFF) for predicting histology-confirmed steatosis grade in adults with nonalcoholic fatty liver disease (NAFLD). In this prospectively designed pilot study, 61 adults with histology-confirmed NAFLD were enrolled from September 2012 to February 2014. Subjects underwent QUS, CUS, and MRI examinations within 100 days of clinical-care liver biopsy. QUS parameters (attenuation coefficient and backscatter coefficient) were estimated using a reference phantom technique by two analysts independently. Three-point ordinal CUS scores intended to predict steatosis grade (1, 2, or 3) were generated independently by two radiologists on the basis of QUS features. PDFF was estimated using an advanced chemical shift-based MRI technique. Using histologic examination as the reference standard, ROC analysis was performed. Optimal attenuation coefficient, backscatter coefficient, and PDFF cutoff thresholds were identified, and the accuracy of attenuation coefficient, backscatter coefficient, PDFF, and CUS to predict steatosis grade was determined. Interobserver agreement for attenuation coefficient, backscatter coefficient, and CUS was analyzed. CUS had 51.7% grading accuracy. The raw and cross-validated steatosis grading accuracies were 61.7% and 55.0%, respectively, for attenuation coefficient, 68.3% and 68.3% for backscatter coefficient, and 76.7% and 71.3% for MRI-estimated PDFF. Interobserver agreements were 53.3% for CUS (κ = 0.61), 90.0% for attenuation coefficient (κ = 0.87), and 71.7% for backscatter coefficient (κ = 0.82) (p < 0.0001 for all). Preliminary observations suggest that QUS parameters may be more accurate and provide higher interobserver agreement than CUS for predicting hepatic steatosis grade in patients with NAFLD.

An ex vivo investigation into the transurothelial permeability and bladder wall distribution of the nonsteroidal anti-inflammatory ketorolac.

PubMed

Williams, Nicholas A; Bowen, Jenna L; Al-Jayyoussi, Ghaith; Gumbleton, Mark; Allender, Chris J; Li, Jamie; Harrah, Tim; Raja, Aditya; Joshi, Hrishi B

2014-03-03

Transurothelial drug delivery continues to be an attractive treatment option for a range of urological conditions; however, dosing regimens remain largely empirical. Recently, intravesical delivery of the nonsteroidal anti-inflammatory ketorolac has been shown to significantly reduce ureteral stent-related pain. While this latest development provides an opportunity for advancing the management of stent-related pain, clinical translation will undoubtedly require an understanding of the rate and extent of delivery of ketorolac into the bladder wall. Using an ex vivo porcine model, we evaluate the urothelial permeability and bladder wall distribution of ketorolac. The subsequent application of a pharmacokinetic (PK) model enables prediction of concentrations achieved in vivo. Ketorolac was applied to the urothelium and a transurothelial permeability coefficient (Kp) calculated. Relative drug distribution into the bladder wall after 90 min was determined. Ketorolac was able to permeate the urothelium (Kp = 2.63 × 10(-6) cm s(-1)), and after 90 min average concentrations of 400, 141 and 21 μg g(-1) were achieved in the urothelium, lamina propria and detrusor respectively. An average concentration of 87 μg g(-1) was achieved across the whole bladder wall. PK simulations (STELLA) were then carried out, using ex vivo values for Kp and muscle/saline partition coefficient (providing an estimation of vascular clearance), to predict 90 min in vivo ketorolac tissue concentrations. When dilution of the drug solution with urine and vascular clearance were taken into account, a reduced ketorolac concentration of 37 μg g(-1) across the whole bladder wall was predicted. These studies reveal crucial information about the urothelium's permeability to agents such as ketorolac and the concentrations achievable in the bladder wall. It would appear that levels of ketorolac delivered to the bladder wall intravesically would be sufficient to provide an anti-inflammatory effect. The combination of such ex vivo data and PK modeling provides an insight into the likelihood of achieving clinically relevant concentrations of drug following intravesical administration.

Using remote sensing, ecological niche modeling, and Geographic Information Systems for Rift Valley fever risk assessment in the United States

NASA Astrophysics Data System (ADS)

Tedrow, Christine Atkins

The primary goal in this study was to explore remote sensing, ecological niche modeling, and Geographic Information Systems (GIS) as aids in predicting candidate Rift Valley fever (RVF) competent vector abundance and distribution in Virginia, and as means of estimating where risk of establishment in mosquitoes and risk of transmission to human populations would be greatest in Virginia. A second goal in this study was to determine whether the remotely-sensed Normalized Difference Vegetation Index (NDVI) can be used as a proxy variable of local conditions for the development of mosquitoes to predict mosquito species distribution and abundance in Virginia. As part of this study, a mosquito surveillance database was compiled to archive the historical patterns of mosquito species abundance in Virginia. In addition, linkages between mosquito density and local environmental and climatic patterns were spatially and temporally examined. The present study affirms the potential role of remote sensing imagery for species distribution prediction, and it demonstrates that ecological niche modeling is a valuable predictive tool to analyze the distributions of populations. The MaxEnt ecological niche modeling program was used to model predicted ranges for potential RVF competent vectors in Virginia. The MaxEnt model was shown to be robust, and the candidate RVF competent vector predicted distribution map is presented. The Normalized Difference Vegetation Index (NDVI) was found to be the most useful environmental-climatic variable to predict mosquito species distribution and abundance in Virginia. However, these results indicate that a more robust prediction is obtained by including other environmental-climatic factors correlated to mosquito densities (e.g., temperature, precipitation, elevation) with NDVI. The present study demonstrates that remote sensing and GIS can be used with ecological niche and risk modeling methods to estimate risk of virus establishment in mosquitoes and transmission to humans. Maps delineating the geographic areas in Virginia with highest risk for RVF establishment in mosquito populations and RVF disease transmission to human populations were generated in a GIS using human, domestic animal, and white-tailed deer population estimates and the MaxEnt potential RVF competent vector species distribution prediction. The candidate RVF competent vector predicted distribution and RVF risk maps presented in this study can help vector control agencies and public health officials focus Rift Valley fever surveillance efforts in geographic areas with large co-located populations of potential RVF competent vectors and human, domestic animal, and wildlife hosts. Keywords. Rift Valley fever, risk assessment, Ecological Niche Modeling, MaxEnt, Geographic Information System, remote sensing, Pearson's Product-Moment Correlation Coefficient, vectors, mosquito distribution, mosquito density, mosquito surveillance, United States, Virginia, domestic animals, white-tailed deer, ArcGIS

An Improved Method of Predicting Extinction Coefficients for the Determination of Protein Concentration.

PubMed

Hilario, Eric C; Stern, Alan; Wang, Charlie H; Vargas, Yenny W; Morgan, Charles J; Swartz, Trevor E; Patapoff, Thomas W

2017-01-01

Concentration determination is an important method of protein characterization required in the development of protein therapeutics. There are many known methods for determining the concentration of a protein solution, but the easiest to implement in a manufacturing setting is absorption spectroscopy in the ultraviolet region. For typical proteins composed of the standard amino acids, absorption at wavelengths near 280 nm is due to the three amino acid chromophores tryptophan, tyrosine, and phenylalanine in addition to a contribution from disulfide bonds. According to the Beer-Lambert law, absorbance is proportional to concentration and path length, with the proportionality constant being the extinction coefficient. Typically the extinction coefficient of proteins is experimentally determined by measuring a solution absorbance then experimentally determining the concentration, a measurement with some inherent variability depending on the method used. In this study, extinction coefficients were calculated based on the measured absorbance of model compounds of the four amino acid chromophores. These calculated values for an unfolded protein were then compared with an experimental concentration determination based on enzymatic digestion of proteins. The experimentally determined extinction coefficient for the native proteins was consistently found to be 1.05 times the calculated value for the unfolded proteins for a wide range of proteins with good accuracy and precision under well-controlled experimental conditions. The value of 1.05 times the calculated value was termed the predicted extinction coefficient. Statistical analysis shows that the differences between predicted and experimentally determined coefficients are scattered randomly, indicating no systematic bias between the values among the proteins measured. The predicted extinction coefficient was found to be accurate and not subject to the inherent variability of experimental methods. We propose the use of a predicted extinction coefficient for determining the protein concentration of therapeutic proteins starting from early development through the lifecycle of the product. LAY ABSTRACT: Knowing the concentration of a protein in a pharmaceutical solution is important to the drug's development and posology. There are many ways to determine the concentration, but the easiest one to use in a testing lab employs absorption spectroscopy. Absorbance of ultraviolet light by a protein solution is proportional to its concentration and path length; the proportionality constant is the extinction coefficient. The extinction coefficient of a protein therapeutic is usually determined experimentally during early product development and has some inherent method variability. In this study, extinction coefficients of several proteins were calculated based on the measured absorbance of model compounds. These calculated values for an unfolded protein were then compared with experimental concentration determinations based on enzymatic digestion of the proteins. The experimentally determined extinction coefficient for the native protein was 1.05 times the calculated value for the unfolded protein with good accuracy and precision under controlled experimental conditions, so the value of 1.05 times the calculated coefficient was called the predicted extinction coefficient. Comparison of predicted and measured extinction coefficients indicated that the predicted value was very close to the experimentally determined values for the proteins. The predicted extinction coefficient was accurate and removed the variability inherent in experimental methods. © PDA, Inc. 2017.

The interplay of various sources of noise on reliability of species distribution models hinges on ecological specialisation.

PubMed

Soultan, Alaaeldin; Safi, Kamran

2017-01-01

Digitized species occurrence data provide an unprecedented source of information for ecologists and conservationists. Species distribution model (SDM) has become a popular method to utilise these data for understanding the spatial and temporal distribution of species, and for modelling biodiversity patterns. Our objective is to study the impact of noise in species occurrence data (namely sample size and positional accuracy) on the performance and reliability of SDM, considering the multiplicative impact of SDM algorithms, species specialisation, and grid resolution. We created a set of four 'virtual' species characterized by different specialisation levels. For each of these species, we built the suitable habitat models using five algorithms at two grid resolutions, with varying sample sizes and different levels of positional accuracy. We assessed the performance and reliability of the SDM according to classic model evaluation metrics (Area Under the Curve and True Skill Statistic) and model agreement metrics (Overall Concordance Correlation Coefficient and geographic niche overlap) respectively. Our study revealed that species specialisation had by far the most dominant impact on the SDM. In contrast to previous studies, we found that for widespread species, low sample size and low positional accuracy were acceptable, and useful distribution ranges could be predicted with as few as 10 species occurrences. Range predictions for narrow-ranged species, however, were sensitive to sample size and positional accuracy, such that useful distribution ranges required at least 20 species occurrences. Against expectations, the MAXENT algorithm poorly predicted the distribution of specialist species at low sample size.

Threshold resummation of the rapidity distribution for Higgs production at NNLO +NNLL

NASA Astrophysics Data System (ADS)

Banerjee, Pulak; Das, Goutam; Dhani, Prasanna K.; Ravindran, V.

2018-03-01

We present a formalism that resums threshold-enhanced logarithms to all orders in perturbative QCD for the rapidity distribution of any colorless particle produced in hadron colliders. We achieve this by exploiting the factorization properties and K +G equations satisfied by the soft and virtual parts of the cross section. We compute for the first time compact and most general expressions in two-dimensional Mellin space for the resummed coefficients. Using various state-of-the-art multiloop and multileg results, we demonstrate the numerical impact of our resummed results up to next-to-next-to-leading order for the rapidity distribution of the Higgs boson at the LHC. We find that inclusion of these threshold logs through resummation improves the reliability of perturbative predictions.

Modified sedimentation-dispersion model for solids in a three-phase slurry column

DOE Office of Scientific and Technical Information (OSTI.GOV)

Smith, D.N.; Ruether, J.A.; Shah, Y.T.

1986-03-01

Solids distribution data for a three-phase, batch-fluidized slurry bubble column (SBC) are presented, using air as the gas phase, pure liquids and solutions as the liquid phase, and glass beads and carborundum catalyst powder as the solid phase. Solids distribution data for the three-phase SBC operated in a continuous mode of operation are also presented, using nitrogen as the gas phase, water as the liquid phase, and glass beads as the solid phase. A new model to provide a reasonable approach to predict solids concentration distributions for systems containing polydispersed solids is presented. The model is a modification of standardmore » sedimentation-dispersion model published earlier. Empirical correlations for prediction of hindered settling velocity and solids dispersion coefficient for systems containing polydispersed solids are presented. A new method of evaluating critical gas velocity (CGV) from concentrations of the sample withdrawn at the same port of the SBC is presented. Also presented is a new mapping for CGV which separates the two regimes in the SBC, namely, incomplete fluidization and complete fluidization.« less

Shoe-Floor Interactions in Human Walking With Slips: Modeling and Experiments.

PubMed

Trkov, Mitja; Yi, Jingang; Liu, Tao; Li, Kang

2018-03-01

Shoe-floor interactions play a crucial role in determining the possibility of potential slip and fall during human walking. Biomechanical and tribological parameters influence the friction characteristics between the shoe sole and the floor and the existing work mainly focus on experimental studies. In this paper, we present modeling, analysis, and experiments to understand slip and force distributions between the shoe sole and floor surface during human walking. We present results for both soft and hard sole material. The computational approaches for slip and friction force distributions are presented using a spring-beam networks model. The model predictions match the experimentally observed sole deformations with large soft sole deformation at the beginning and the end stages of the stance, which indicates the increased risk for slip. The experiments confirm that both the previously reported required coefficient of friction (RCOF) and the deformation measurements in this study can be used to predict slip occurrence. Moreover, the deformation and force distribution results reported in this study provide further understanding and knowledge of slip initiation and termination under various biomechanical conditions.

Confidence bounds and hypothesis tests for normal distribution coefficients of variation

Treesearch

Steve P. Verrill; Richard A. Johnson

2007-01-01

For normally distributed populations, we obtain confidence bounds on a ratio of two coefficients of variation, provide a test for the equality of k coefficients of variation, and provide confidence bounds on a coefficient of variation shared by k populations. To develop these confidence bounds and test, we first establish that estimators based on Newton steps from n-...

Transmission near-infrared (NIR) and photon time-of-flight (PTOF) spectroscopy in a comparative analysis of pharmaceuticals.

PubMed

Kamran, Faisal; Abildgaard, Otto H A; Sparén, Anders; Svensson, Olof; Johansson, Jonas; Andersson-Engels, Stefan; Andersen, Peter E; Khoptyar, Dmitry

2015-03-01

We present a comprehensive study of the application of photon time-of-flight spectroscopy (PTOFS) in the wavelength range 1050-1350 nm as a spectroscopic technique for the evaluation of the chemical composition and structural properties of pharmaceutical tablets. PTOFS is compared to transmission near-infrared spectroscopy (NIRS). In contrast to transmission NIRS, PTOFS is capable of directly and independently determining the absorption and reduced scattering coefficients of the medium. Chemometric models were built on the evaluated absorption spectra for predicting tablet drug concentration. Results are compared to corresponding predictions built on transmission NIRS measurements. The predictive ability of PTOFS and transmission NIRS is comparable when models are based on uniformly distributed tablet sets. For non-uniform distribution of tablets based on particle sizes, the prediction ability of PTOFS is better than that of transmission NIRS. Analysis of reduced scattering spectra shows that PTOFS is able to characterize tablet microstructure and manufacturing process parameters. In contrast to the chemometric pseudo-variables provided by transmission NIRS, PTOFS provides physically meaningful quantities such as scattering strength and slope of particle size. The ability of PTOFS to quantify the reduced scattering spectra, together with its robustness in predicting drug content, makes it suitable for such evaluations in the pharmaceutical industry.

Surfactant enhanced recovery of tetrachloroethylene from a porous medium containing low permeability lenses. 2. Numerical simulation.

PubMed

Rathfelder, K M; Abriola, L M; Taylor, T P; Pennell, K D

2001-04-01

A numerical model of surfactant enhanced solubilization was developed and applied to the simulation of nonaqueous phase liquid recovery in two-dimensional heterogeneous laboratory sand tank systems. Model parameters were derived from independent, small-scale, batch and column experiments. These parameters included viscosity, density, solubilization capacity, surfactant sorption, interfacial tension, permeability, capillary retention functions, and interphase mass transfer correlations. Model predictive capability was assessed for the evaluation of the micellar solubilization of tetrachloroethylene (PCE) in the two-dimensional systems. Predicted effluent concentrations and mass recovery agreed reasonably well with measured values. Accurate prediction of enhanced solubilization behavior in the sand tanks was found to require the incorporation of pore-scale, system-dependent, interphase mass transfer limitations, including an explicit representation of specific interfacial contact area. Predicted effluent concentrations and mass recovery were also found to depend strongly upon the initial NAPL entrapment configuration. Numerical results collectively indicate that enhanced solubilization processes in heterogeneous, laboratory sand tank systems can be successfully simulated using independently measured soil parameters and column-measured mass transfer coefficients, provided that permeability and NAPL distributions are accurately known. This implies that the accuracy of model predictions at the field scale will be constrained by our ability to quantify soil heterogeneity and NAPL distribution.

OH-PRED: prediction of protein hydroxylation sites by incorporating adapted normal distribution bi-profile Bayes feature extraction and physicochemical properties of amino acids.

PubMed

Jia, Cang-Zhi; He, Wen-Ying; Yao, Yu-Hua

2017-03-01

Hydroxylation of proline or lysine residues in proteins is a common post-translational modification event, and such modifications are found in many physiological and pathological processes. Nonetheless, the exact molecular mechanism of hydroxylation remains under investigation. Because experimental identification of hydroxylation is time-consuming and expensive, bioinformatics tools with high accuracy represent desirable alternatives for large-scale rapid identification of protein hydroxylation sites. In view of this, we developed a supporter vector machine-based tool, OH-PRED, for the prediction of protein hydroxylation sites using the adapted normal distribution bi-profile Bayes feature extraction in combination with the physicochemical property indexes of the amino acids. In a jackknife cross validation, OH-PRED yields an accuracy of 91.88% and a Matthew's correlation coefficient (MCC) of 0.838 for the prediction of hydroxyproline sites, and yields an accuracy of 97.42% and a MCC of 0.949 for the prediction of hydroxylysine sites. These results demonstrate that OH-PRED increased significantly the prediction accuracy of hydroxyproline and hydroxylysine sites by 7.37 and 14.09%, respectively, when compared with the latest predictor PredHydroxy. In independent tests, OH-PRED also outperforms previously published methods.

Matrimonial distance, inbreeding coefficient and population size: Dhangar data.

PubMed

Majumder, P P; Malhotra, K C

1979-01-01

Data on the distance between the birthplaces of spouses (matrimonial distance) were collected from 2,260 married individuals belonging to 21 endogamous castes of the Dhangar (shepherd) cast-cluster of Maharashtra, India. The general form of the distribution of matrimonial distances is one which is extremely positively skewed and leptokurtic. The percentage of intra-village marriages generally decreases from the southern areas of Maharashtra to the northern areas of the state, as does the inbreeding coefficient. This situation is in conformity with the socio-cultural norms regulating matrimonial choice in south and north India. An attempt has been made to relate the degree of inbreeding to the mean matrimonial distance and population size. The mean matrimonial distance is more useful in predicting the degree of inbreeding than population size.

Stochastic or statistic? Comparing flow duration curve models in ungauged basins and changing climates

NASA Astrophysics Data System (ADS)

Müller, M. F.; Thompson, S. E.

2015-09-01

The prediction of flow duration curves (FDCs) in ungauged basins remains an important task for hydrologists given the practical relevance of FDCs for water management and infrastructure design. Predicting FDCs in ungauged basins typically requires spatial interpolation of statistical or model parameters. This task is complicated if climate becomes non-stationary, as the prediction challenge now also requires extrapolation through time. In this context, process-based models for FDCs that mechanistically link the streamflow distribution to climate and landscape factors may have an advantage over purely statistical methods to predict FDCs. This study compares a stochastic (process-based) and statistical method for FDC prediction in both stationary and non-stationary contexts, using Nepal as a case study. Under contemporary conditions, both models perform well in predicting FDCs, with Nash-Sutcliffe coefficients above 0.80 in 75 % of the tested catchments. The main drives of uncertainty differ between the models: parameter interpolation was the main source of error for the statistical model, while violations of the assumptions of the process-based model represented the main source of its error. The process-based approach performed better than the statistical approach in numerical simulations with non-stationary climate drivers. The predictions of the statistical method under non-stationary rainfall conditions were poor if (i) local runoff coefficients were not accurately determined from the gauge network, or (ii) streamflow variability was strongly affected by changes in rainfall. A Monte Carlo analysis shows that the streamflow regimes in catchments characterized by a strong wet-season runoff and a rapid, strongly non-linear hydrologic response are particularly sensitive to changes in rainfall statistics. In these cases, process-based prediction approaches are strongly favored over statistical models.

Comparing statistical and process-based flow duration curve models in ungauged basins and changing rain regimes

NASA Astrophysics Data System (ADS)

Müller, M. F.; Thompson, S. E.

2016-02-01

The prediction of flow duration curves (FDCs) in ungauged basins remains an important task for hydrologists given the practical relevance of FDCs for water management and infrastructure design. Predicting FDCs in ungauged basins typically requires spatial interpolation of statistical or model parameters. This task is complicated if climate becomes non-stationary, as the prediction challenge now also requires extrapolation through time. In this context, process-based models for FDCs that mechanistically link the streamflow distribution to climate and landscape factors may have an advantage over purely statistical methods to predict FDCs. This study compares a stochastic (process-based) and statistical method for FDC prediction in both stationary and non-stationary contexts, using Nepal as a case study. Under contemporary conditions, both models perform well in predicting FDCs, with Nash-Sutcliffe coefficients above 0.80 in 75 % of the tested catchments. The main drivers of uncertainty differ between the models: parameter interpolation was the main source of error for the statistical model, while violations of the assumptions of the process-based model represented the main source of its error. The process-based approach performed better than the statistical approach in numerical simulations with non-stationary climate drivers. The predictions of the statistical method under non-stationary rainfall conditions were poor if (i) local runoff coefficients were not accurately determined from the gauge network, or (ii) streamflow variability was strongly affected by changes in rainfall. A Monte Carlo analysis shows that the streamflow regimes in catchments characterized by frequent wet-season runoff and a rapid, strongly non-linear hydrologic response are particularly sensitive to changes in rainfall statistics. In these cases, process-based prediction approaches are favored over statistical models.

Fisher information framework for time series modeling

NASA Astrophysics Data System (ADS)

Venkatesan, R. C.; Plastino, A.

2017-08-01

A robust prediction model invoking the Takens embedding theorem, whose working hypothesis is obtained via an inference procedure based on the minimum Fisher information principle, is presented. The coefficients of the ansatz, central to the working hypothesis satisfy a time independent Schrödinger-like equation in a vector setting. The inference of (i) the probability density function of the coefficients of the working hypothesis and (ii) the establishing of constraint driven pseudo-inverse condition for the modeling phase of the prediction scheme, is made, for the case of normal distributions, with the aid of the quantum mechanical virial theorem. The well-known reciprocity relations and the associated Legendre transform structure for the Fisher information measure (FIM, hereafter)-based model in a vector setting (with least square constraints) are self-consistently derived. These relations are demonstrated to yield an intriguing form of the FIM for the modeling phase, which defines the working hypothesis, solely in terms of the observed data. Cases for prediction employing time series' obtained from the: (i) the Mackey-Glass delay-differential equation, (ii) one ECG signal from the MIT-Beth Israel Deaconess Hospital (MIT-BIH) cardiac arrhythmia database, and (iii) one ECG signal from the Creighton University ventricular tachyarrhythmia database. The ECG samples were obtained from the Physionet online repository. These examples demonstrate the efficiency of the prediction model. Numerical examples for exemplary cases are provided.

A dynamic Monte Carlo model for predicting radiant exposure distribution in dental composites: model development and verifications

NASA Astrophysics Data System (ADS)

Chen, Yin-Chu; Ferracane, Jack L.; Prahl, Scott A.

2005-03-01

Photo-cured dental composites are widely used in dental practices to restore teeth due to the esthetic appearance of the composites and the ability to cure in situ. However, their complex optical characteristics make it difficult to understand the light transport within the composites and to predict the depth of cure. Our previous work showed that the absorption and scattering coefficients of the composite changed after the composite was cured. The static Monte Carlo simulation showed that the penetration of radiant exposures differed significantly for cured and uncured optical properties. This means that a dynamic model is required for accurate prediction of radiant exposure in the composites. The purpose of this study was to develop and verify a dynamic Monte Carlo (DMC) model simulating light propagation in dental composites that have dynamic optical properties while photons are absorbed. The composite was divided into many small cubes, each of which had its own scattering and absorption coefficients. As light passed through the composite, the light was scattered and absorbed. The amount of light absorbed in each cube was calculated using Beer's Law and was used to determine the next optical properties in that cube. Finally, the predicted total reflectance and transmittance as well as the optical property during curing were verified numerically and experimentally. Our results showed that the model predicted values agreed with the theoretical values within 1% difference. The DMC model results are comparable with experimental results within 5% differences.

Stochastic Fermi Energization of Coronal Plasma during Explosive Magnetic Energy Release

NASA Astrophysics Data System (ADS)

Pisokas, Theophilos; Vlahos, Loukas; Isliker, Heinz; Tsiolis, Vassilis; Anastasiadis, Anastasios

2017-02-01

The aim of this study is to analyze the interaction of charged particles (ions and electrons) with randomly formed particle scatterers (e.g., large-scale local “magnetic fluctuations” or “coherent magnetic irregularities”) using the setup proposed initially by Fermi. These scatterers are formed by the explosive magnetic energy release and propagate with the Alfvén speed along the irregular magnetic fields. They are large-scale local fluctuations (δB/B ≈ 1) randomly distributed inside the unstable magnetic topology and will here be called Alfvénic Scatterers (AS). We constructed a 3D grid on which a small fraction of randomly chosen grid points are acting as AS. In particular, we study how a large number of test particles evolves inside a collection of AS, analyzing the evolution of their energy distribution and their escape-time distribution. We use a well-established method to estimate the transport coefficients directly from the trajectories of the particles. Using the estimated transport coefficients and solving the Fokker-Planck equation numerically, we can recover the energy distribution of the particles. We have shown that the stochastic Fermi energization of mildly relativistic and relativistic plasma can heat and accelerate the tail of the ambient particle distribution as predicted by Parker & Tidman and Ramaty. The temperature of the hot plasma and the tail of the energetic particles depend on the mean free path (λsc) of the particles between the scatterers inside the energization volume.

Body frame size in school children is related to the amount of adipose tissue in different depots but not to adipose distribution.

PubMed

Guzmán-de la Garza, Francisco J; González Ayala, Alejandra E; Gómez Nava, Marisol; Martínez Monsiváis, Leislie I; Salinas Martínez, Ana M; Ramírez López, Erik; Mathiew Quirós, Alvaro; Garcia Quintanilla, Francisco

2017-09-10

The main aim of this study was to test the hypothesis that body frame size is related to the amount of fat in different adipose tissue depots and to fat distribution in schoolchildren. Children aged between 5 and 10 years were included in this cross-sectional study (n = 565). Body frame size, adiposity markers (anthropometric, skinfolds thickness, and ultrasound measures), and fat distribution indices were analyzed. Correlation coefficients adjusted by reliability were estimated and analyzed by sex; the significance of the difference between two correlation coefficients was assessed using the Fisher z-transformation. The sample included primarily urban children; 58.6% were normal weight, 16.1% overweight, 19.6% obese, and the rest were underweight. Markers of subcutaneous adiposity, fat mass and fat-free mass, and preperitoneal adiposity showed higher and significant correlations with the sum of the biacromial + bitrochanteric diameter than with the elbow diameter, regardless of sex. The fat distribution conicity index presented significant but weak correlations; and visceral adipose tissue, hepatic steatosis, and the waist-for-hip ratio were not significantly correlated with body frame size measures. Body frame size in school children was related to the amount of adipose tissue in different depots, but not adipose distribution. More studies are needed to confirm this relationship and its importance to predict changes in visceral fat deposition during growth. © 2017 Wiley Periodicals, Inc.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pisokas, Theophilos; Vlahos, Loukas; Isliker, Heinz

The aim of this study is to analyze the interaction of charged particles (ions and electrons) with randomly formed particle scatterers (e.g., large-scale local “magnetic fluctuations” or “coherent magnetic irregularities”) using the setup proposed initially by Fermi. These scatterers are formed by the explosive magnetic energy release and propagate with the Alfvén speed along the irregular magnetic fields. They are large-scale local fluctuations ( δB / B ≈ 1) randomly distributed inside the unstable magnetic topology and will here be called Alfvénic Scatterers (AS). We constructed a 3D grid on which a small fraction of randomly chosen grid points aremore » acting as AS. In particular, we study how a large number of test particles evolves inside a collection of AS, analyzing the evolution of their energy distribution and their escape-time distribution. We use a well-established method to estimate the transport coefficients directly from the trajectories of the particles. Using the estimated transport coefficients and solving the Fokker–Planck equation numerically, we can recover the energy distribution of the particles. We have shown that the stochastic Fermi energization of mildly relativistic and relativistic plasma can heat and accelerate the tail of the ambient particle distribution as predicted by Parker and Tidman and Ramaty. The temperature of the hot plasma and the tail of the energetic particles depend on the mean free path ( λ {sub sc}) of the particles between the scatterers inside the energization volume.« less

Prediction of stream volatilization coefficients

USGS Publications Warehouse

Rathbun, Ronald E.

1990-01-01

Equations are developed for predicting the liquid-film and gas-film reference-substance parameters for quantifying volatilization of organic solutes from streams. Molecular weight and molecular-diffusion coefficients of the solute are used as correlating parameters. Equations for predicting molecular-diffusion coefficients of organic solutes in water and air are developed, with molecular weight and molal volume as parameters. Mean absolute errors of prediction for diffusion coefficients in water are 9.97% for the molecular-weight equation, 6.45% for the molal-volume equation. The mean absolute error for the diffusion coefficient in air is 5.79% for the molal-volume equation. Molecular weight is not a satisfactory correlating parameter for diffusion in air because two equations are necessary to describe the values in the data set. The best predictive equation for the liquid-film reference-substance parameter has a mean absolute error of 5.74%, with molal volume as the correlating parameter. The best equation for the gas-film parameter has a mean absolute error of 7.80%, with molecular weight as the correlating parameter.

Limits of the memory coefficient in measuring correlated bursts

NASA Astrophysics Data System (ADS)

Jo, Hang-Hyun; Hiraoka, Takayuki

2018-03-01

Temporal inhomogeneities in event sequences of natural and social phenomena have been characterized in terms of interevent times and correlations between interevent times. The inhomogeneities of interevent times have been extensively studied, while the correlations between interevent times, often called correlated bursts, are far from being fully understood. For measuring the correlated bursts, two relevant approaches were suggested, i.e., memory coefficient and burst size distribution. Here a burst size denotes the number of events in a bursty train detected for a given time window. Empirical analyses have revealed that the larger memory coefficient tends to be associated with the heavier tail of the burst size distribution. In particular, empirical findings in human activities appear inconsistent, such that the memory coefficient is close to 0, while burst size distributions follow a power law. In order to comprehend these observations, by assuming the conditional independence between consecutive interevent times, we derive the analytical form of the memory coefficient as a function of parameters describing interevent time and burst size distributions. Our analytical result can explain the general tendency of the larger memory coefficient being associated with the heavier tail of burst size distribution. We also find that the apparently inconsistent observations in human activities are compatible with each other, indicating that the memory coefficient has limits to measure the correlated bursts.

The Impact of Variable Wind Shear Coefficients on Risk Reduction of Wind Energy Projects

PubMed Central

Thomson, Allan; Yoonesi, Behrang; McNutt, Josiah

2016-01-01

Estimation of wind speed at proposed hub heights is typically achieved using a wind shear exponent or wind shear coefficient (WSC), variation in wind speed as a function of height. The WSC is subject to temporal variation at low and high frequencies, ranging from diurnal and seasonal variations to disturbance caused by weather patterns; however, in many cases, it is assumed that the WSC remains constant. This assumption creates significant error in resource assessment, increasing uncertainty in projects and potentially significantly impacting the ability to control gird connected wind generators. This paper contributes to the body of knowledge relating to the evaluation and assessment of wind speed, with particular emphasis on the development of techniques to improve the accuracy of estimated wind speed above measurement height. It presents an evaluation of the use of a variable wind shear coefficient methodology based on a distribution of wind shear coefficients which have been implemented in real time. The results indicate that a VWSC provides a more accurate estimate of wind at hub height, ranging from 41% to 4% reduction in root mean squared error (RMSE) between predicted and actual wind speeds when using a variable wind shear coefficient at heights ranging from 33% to 100% above the highest actual wind measurement. PMID:27872898

Calm water resistance prediction of a bulk carrier using Reynolds averaged Navier-Stokes based solver

NASA Astrophysics Data System (ADS)

Rahaman, Md. Mashiur; Islam, Hafizul; Islam, Md. Tariqul; Khondoker, Md. Reaz Hasan

2017-12-01

Maneuverability and resistance prediction with suitable accuracy is essential for optimum ship design and propulsion power prediction. This paper aims at providing some of the maneuverability characteristics of a Japanese bulk carrier model, JBC in calm water using a computational fluid dynamics solver named SHIP Motion and OpenFOAM. The solvers are based on the Reynolds average Navier-Stokes method (RaNS) and solves structured grid using the Finite Volume Method (FVM). This paper comprises the numerical results of calm water test for the JBC model with available experimental results. The calm water test results include the total drag co-efficient, average sinkage, and trim data. Visualization data for pressure distribution on the hull surface and free water surface have also been included. The paper concludes that the presented solvers predict the resistance and maneuverability characteristics of the bulk carrier with reasonable accuracy utilizing minimum computational resources.

Analyzing degradation data with a random effects spline regression model

DOE PAGES

Fugate, Michael Lynn; Hamada, Michael Scott; Weaver, Brian Phillip

2017-03-17

This study proposes using a random effects spline regression model to analyze degradation data. Spline regression avoids having to specify a parametric function for the true degradation of an item. A distribution for the spline regression coefficients captures the variation of the true degradation curves from item to item. We illustrate the proposed methodology with a real example using a Bayesian approach. The Bayesian approach allows prediction of degradation of a population over time and estimation of reliability is easy to perform.

Determination of thermal contact conductance in vacuum-bagged thermoplastic prepreg stacks using infrared thermography

NASA Astrophysics Data System (ADS)

Baumard, Théo; De Almeida, Olivier; Menary, Gary; Le Maoult, Yannick; Schmidt, Fabrice; Bikard, Jérôme

2016-10-01

The infrared heating of a vacuum-bagged, thermoplastic prepreg stack of glass/PA66 was studied to investigate the influence of vacuum level on thermal contact resistance between plies. A higher vacuum level was shown experimentally to decrease the transverse heat transfer efficiency, indicating that considering only the effect of heat conduction at the plies interfaces is not sufficient to predict the temperature distribution. An inverse analysis was used to retrieve the contact resistance coefficients as a function of vacuum pressure.

Analyzing degradation data with a random effects spline regression model

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fugate, Michael Lynn; Hamada, Michael Scott; Weaver, Brian Phillip

This study proposes using a random effects spline regression model to analyze degradation data. Spline regression avoids having to specify a parametric function for the true degradation of an item. A distribution for the spline regression coefficients captures the variation of the true degradation curves from item to item. We illustrate the proposed methodology with a real example using a Bayesian approach. The Bayesian approach allows prediction of degradation of a population over time and estimation of reliability is easy to perform.

Parameterization of the middle and upper tropospheric water vapor from ATOVS observations over a tropical climate region

NASA Astrophysics Data System (ADS)

Makama, Ezekiel Kaura; Lim, Hwee San; Abdullah, Khiruddin

2018-01-01

Precipitable water vapor (PWV) is a highly variable, but important greenhouse gas that regulates the radiation budget of the earth. Its variability in time and space makes it difficult to quantify. Knowledge of its vertical distribution, in particular, is crucial for many reasons. In this study, empirical relationships between isobaric layers of PWV over Peninsular Malaysia are examined. Analysis of variance (ANOVA) technique on Advanced Television and Infrared Observation Satellite Operational Vertical Sounder (ATOVS) observations, from 2005 to 2011, has been used to propose a relationship of the form, W=α(WL)β for the middle (MW) and upper (UW) layers PWV. W is either MW or UW with α and β as regression coefficients, which are functions of latitude. Coefficients of determination (R2) and root mean square error (RMSE) of respective values between 0.75-0.86 and 1.65-2.38 mm, across the zones, were obtained for both the MW and UW predictions, with a mean bias (MB) below ±1 mm.The predicted and observed PWV presented a better agreement northerly. Initial predictability test for each model was done on two independent data sets: ATOVS (2012-2015), and radiosonde (2010-2011) at Penang, Kuantan and Sepang stations, with very good outcomes. The results of the tests revealed remarkable performances, when compared with two previously reported models. The inclusion of variable regression coefficients, and the utilization of satellite-derived data, which provide soundings of data-void regions between radiosonde networks, proved to have optimized the results.

SU-F-19A-10: Recalculation and Reporting Clinical HDR 192-Ir Head and Neck Dose Distributions Using Model Based Dose Calculation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Carlsson Tedgren, A; Persson, M; Nilsson, J

Purpose: To retrospectively re-calculate dose distributions for selected head and neck cancer patients, earlier treated with HDR 192Ir brachytherapy, using Monte Carlo (MC) simulations and compare results to distributions from the planning system derived using TG43 formalism. To study differences between dose to medium (as obtained with the MC code) and dose to water in medium as obtained through (1) ratios of stopping powers and (2) ratios of mass energy absorption coefficients between water and medium. Methods: The MC code Algebra was used to calculate dose distributions according to earlier actual treatment plans using anonymized plan data and CT imagesmore » in DICOM format. Ratios of stopping power and mass energy absorption coefficients for water with various media obtained from 192-Ir spectra were used in toggling between dose to water and dose to media. Results: Differences between initial planned TG43 dose distributions and the doses to media calculated by MC are insignificant in the target volume. Differences are moderate (within 4–5 % at distances of 3–4 cm) but increase with distance and are most notable in bone and at the patient surface. Differences between dose to water and dose to medium are within 1-2% when using mass energy absorption coefficients to toggle between the two quantities but increase to above 10% for bone using stopping power ratios. Conclusion: MC predicts target doses for head and neck cancer patients in close agreement with TG43. MC yields improved dose estimations outside the target where a larger fraction of dose is from scattered photons. It is important with awareness and a clear reporting of absorbed dose values in using model based algorithms. Differences in bone media can exceed 10% depending on how dose to water in medium is defined.« less

Experimental Determination and Prediction of the Fitness Effects of Random Point Mutations in the Biosynthetic Enzyme HisA

PubMed Central

Lundin, Erik; Tang, Po-Cheng; Guy, Lionel; Näsvall, Joakim; Andersson, Dan I

2018-01-01

Abstract The distribution of fitness effects of mutations is a factor of fundamental importance in evolutionary biology. We determined the distribution of fitness effects of 510 mutants that each carried between 1 and 10 mutations (synonymous and nonsynonymous) in the hisA gene, encoding an essential enzyme in the l-histidine biosynthesis pathway of Salmonella enterica. For the full set of mutants, the distribution was bimodal with many apparently neutral mutations and many lethal mutations. For a subset of 81 single, nonsynonymous mutants most mutations appeared neutral at high expression levels, whereas at low expression levels only a few mutations were neutral. Furthermore, we examined how the magnitude of the observed fitness effects was correlated to several measures of biophysical properties and phylogenetic conservation.We conclude that for HisA: (i) The effect of mutations can be masked by high expression levels, such that mutations that are deleterious to the function of the protein can still be neutral with regard to organism fitness if the protein is expressed at a sufficiently high level; (ii) the shape of the fitness distribution is dependent on the extent to which the protein is rate-limiting for growth; (iii) negative epistatic interactions, on an average, amplified the combined effect of nonsynonymous mutations; and (iv) no single sequence-based predictor could confidently predict the fitness effects of mutations in HisA, but a combination of multiple predictors could predict the effect with a SD of 0.04 resulting in 80% of the mutations predicted within 12% of their observed selection coefficients. PMID:29294020

Species distribution models predict temporal but not spatial variation in forest growth.

PubMed

van der Maaten, Ernst; Hamann, Andreas; van der Maaten-Theunissen, Marieke; Bergsma, Aldo; Hengeveld, Geerten; van Lammeren, Ron; Mohren, Frits; Nabuurs, Gert-Jan; Terhürne, Renske; Sterck, Frank

2017-04-01

Bioclimate envelope models have been widely used to illustrate the discrepancy between current species distributions and their potential habitat under climate change. However, the realism and correct interpretation of such projections has been the subject of considerable discussion. Here, we investigate whether climate suitability predictions correlate to tree growth, measured in permanent inventory plots and inferred from tree-ring records. We use the ensemble classifier RandomForest and species occurrence data from ~200,000 inventory plots to build species distribution models for four important European forestry species: Norway spruce, Scots pine, European beech, and pedunculate oak. We then correlate climate-based habitat suitability with volume measurements from ~50-year-old stands, available from ~11,000 inventory plots. Secondly, habitat projections based on annual historical climate are compared with ring width from ~300 tree-ring chronologies. Our working hypothesis is that habitat suitability projections from species distribution models should to some degree be associated with temporal or spatial variation in these growth records. We find that the habitat projections are uncorrelated with spatial growth records (inventory plot data), but they do predict interannual variation in tree-ring width, with an average correlation of .22. Correlation coefficients for individual chronologies range from values as high as .82 or as low as -.31. We conclude that tree responses to projected climate change are highly site-specific and that local suitability of a species for reforestation is difficult to predict. That said, projected increase or decrease in climatic suitability may be interpreted as an average expectation of increased or reduced growth over larger geographic scales.

A Modified Isotropic-Kinematic Hardening Model to Predict the Defects in Tube Hydroforming Process

NASA Astrophysics Data System (ADS)

Jin, Kai; Guo, Qun; Tao, Jie; Guo, Xun-zhong

2017-11-01

Numerical simulations of tube hydroforming process of hollow crankshafts were conducted by using finite element analysis method. Moreover, the modified model involving the integration of isotropic-kinematic hardening model with ductile criteria model was used to more accurately optimize the process parameters such as internal pressure, feed distance and friction coefficient. Subsequently, hydroforming experiments were performed based on the simulation results. The comparison between experimental and simulation results indicated that the prediction of tube deformation, crack and wrinkle was quite accurate for the tube hydroforming process. Finally, hollow crankshafts with high thickness uniformity were obtained and the thickness distribution between numerical and experimental results was well consistent.

An entropy method for induced drag minimization

NASA Technical Reports Server (NTRS)

Greene, George C.

1989-01-01

A fundamentally new approach to the aircraft minimum induced drag problem is presented. The method, a 'viscous lifting line', is based on the minimum entropy production principle and does not require the planar wake assumption. An approximate, closed form solution is obtained for several wing configurations including a comparison of wing extension, winglets, and in-plane wing sweep, with and without a constraint on wing-root bending moment. Like the classical lifting-line theory, this theory predicts that induced drag is proportional to the square of the lift coefficient and inversely proportioinal to the wing aspect ratio. Unlike the classical theory, it predicts that induced drag is Reynolds number dependent and that the optimum spanwise circulation distribution is non-elliptic.

Application to rotary wings of a simplified aerodynamic lifting surface theory for unsteady compressible flow

NASA Technical Reports Server (NTRS)

Rao, B. M.; Jones, W. P.

1974-01-01

A general method of predicting airloads is applied to helicopter rotor blades on a full three-dimensional basis using the general theory developed for a rotor blade at the psi = pi/2 position where flutter is most likely to occur. Calculations of aerodynamic coefficients for use in flutter analysis are made for forward and hovering flight with low inflow. The results are compared with values given by two-dimensional strip theory for a rigid rotor hinged at its root. The comparisons indicate the inadequacies of strip theory for airload prediction. One important conclusion drawn from this study is that the curved wake has a substantial effect on the chordwise load distribution.

Structured Set Intra Prediction With Discriminative Learning in a Max-Margin Markov Network for High Efficiency Video Coding

PubMed Central

Dai, Wenrui; Xiong, Hongkai; Jiang, Xiaoqian; Chen, Chang Wen

2014-01-01

This paper proposes a novel model on intra coding for High Efficiency Video Coding (HEVC), which simultaneously predicts blocks of pixels with optimal rate distortion. It utilizes the spatial statistical correlation for the optimal prediction based on 2-D contexts, in addition to formulating the data-driven structural interdependences to make the prediction error coherent with the probability distribution, which is desirable for successful transform and coding. The structured set prediction model incorporates a max-margin Markov network (M3N) to regulate and optimize multiple block predictions. The model parameters are learned by discriminating the actual pixel value from other possible estimates to maximize the margin (i.e., decision boundary bandwidth). Compared to existing methods that focus on minimizing prediction error, the M3N-based model adaptively maintains the coherence for a set of predictions. Specifically, the proposed model concurrently optimizes a set of predictions by associating the loss for individual blocks to the joint distribution of succeeding discrete cosine transform coefficients. When the sample size grows, the prediction error is asymptotically upper bounded by the training error under the decomposable loss function. As an internal step, we optimize the underlying Markov network structure to find states that achieve the maximal energy using expectation propagation. For validation, we integrate the proposed model into HEVC for optimal mode selection on rate-distortion optimization. The proposed prediction model obtains up to 2.85% bit rate reduction and achieves better visual quality in comparison to the HEVC intra coding. PMID:25505829

Application of Statistical Thermodynamics To Predict the Adsorption Properties of Polypeptides in Reversed-Phase HPLC.

PubMed

Tarasova, Irina A; Goloborodko, Anton A; Perlova, Tatyana Y; Pridatchenko, Marina L; Gorshkov, Alexander V; Evreinov, Victor V; Ivanov, Alexander R; Gorshkov, Mikhail V

2015-07-07

The theory of critical chromatography for biomacromolecules (BioLCCC) describes polypeptide retention in reversed-phase HPLC using the basic principles of statistical thermodynamics. However, whether this theory correctly depicts a variety of empirical observations and laws introduced for peptide chromatography over the last decades remains to be determined. In this study, by comparing theoretical results with experimental data, we demonstrate that the BioLCCC: (1) fits the empirical dependence of the polypeptide retention on the amino acid sequence length with R(2) > 0.99 and allows in silico determination of the linear regression coefficients of the log-length correction in the additive model for arbitrary sequences and lengths and (2) predicts the distribution coefficients of polypeptides with an accuracy from 0.98 to 0.99 R(2). The latter enables direct calculation of the retention factors for given solvent compositions and modeling of the migration dynamics of polypeptides separated under isocratic or gradient conditions. The obtained results demonstrate that the suggested theory correctly relates the main aspects of polypeptide separation in reversed-phase HPLC.

The computation of lipophilicities of ⁶⁴Cu PET systems based on a novel approach for fluctuating charges.

PubMed

Comba, Peter; Martin, Bodo; Sanyal, Avik; Stephan, Holger

2013-08-21

A QSPR scheme for the computation of lipophilicities of ⁶⁴Cu complexes was developed with a training set of 24 tetraazamacrocylic and bispidine-based Cu(II) compounds and their experimentally available 1-octanol-water distribution coefficients. A minimum number of physically meaningful parameters were used in the scheme, and these are primarily based on data available from molecular mechanics calculations, using an established force field for Cu(II) complexes and a recently developed scheme for the calculation of fluctuating atomic charges. The developed model was also applied to an independent validation set and was found to accurately predict distribution coefficients of potential ⁶⁴Cu PET (positron emission tomography) systems. A possible next step would be the development of a QSAR-based biodistribution model to track the uptake of imaging agents in different organs and tissues of the body. It is expected that such simple, empirical models of lipophilicity and biodistribution will be very useful in the design and virtual screening of positron emission tomography (PET) imaging agents.

Dipole oscillator strength distributions with improved high-energy behavior: Dipole sum rules and dispersion coefficients for Ne, Ar, Kr, and Xe revisited

NASA Astrophysics Data System (ADS)

Kumar, Ashok; Thakkar, Ajit J.

2010-02-01

The construction of the dipole oscillator strength distribution (DOSD) from theoretical and experimental photoabsorption cross sections combined with constraints provided by the Kuhn-Reiche-Thomas sum rule and molar refractivity data is a well-established technique that has been successfully applied to more than 50 species. Such DOSDs are insufficiently accurate at large photon energies. A novel iterative procedure is developed that rectifies this deficiency by using the high-energy asymptotic behavior of the dipole oscillator strength density as an additional constraint. Pilot applications are made for the neon, argon, krypton, and xenon atoms. The resulting DOSDs improve the agreement of the predicted S2 and S1 sum rules with ab initio calculations while preserving the accuracy of the remainder of the moments. Our DOSDs exploit new and more accurate experimental data. Improved estimates of dipole properties for these four atoms and of dipole-dipole C6 and triple-dipole C9 dispersion coefficients for the interactions among them are reported.

The implementation of rare events logistic regression to predict the distribution of mesophotic hard corals across the main Hawaiian Islands.

PubMed

Veazey, Lindsay M; Franklin, Erik C; Kelley, Christopher; Rooney, John; Frazer, L Neil; Toonen, Robert J

2016-01-01

Predictive habitat suitability models are powerful tools for cost-effective, statistically robust assessment of the environmental drivers of species distributions. The aim of this study was to develop predictive habitat suitability models for two genera of scleractinian corals (Leptoserisand Montipora) found within the mesophotic zone across the main Hawaiian Islands. The mesophotic zone (30-180 m) is challenging to reach, and therefore historically understudied, because it falls between the maximum limit of SCUBA divers and the minimum typical working depth of submersible vehicles. Here, we implement a logistic regression with rare events corrections to account for the scarcity of presence observations within the dataset. These corrections reduced the coefficient error and improved overall prediction success (73.6% and 74.3%) for both original regression models. The final models included depth, rugosity, slope, mean current velocity, and wave height as the best environmental covariates for predicting the occurrence of the two genera in the mesophotic zone. Using an objectively selected theta ("presence") threshold, the predicted presence probability values (average of 0.051 for Leptoseris and 0.040 for Montipora) were translated to spatially-explicit habitat suitability maps of the main Hawaiian Islands at 25 m grid cell resolution. Our maps are the first of their kind to use extant presence and absence data to examine the habitat preferences of these two dominant mesophotic coral genera across Hawai'i.

Prediction of random-regression coefficient for daily milk yield after 305 days in milk by using the regression-coefficient estimates from the first 305 days.

PubMed

Yamazaki, Takeshi; Takeda, Hisato; Hagiya, Koichi; Yamaguchi, Satoshi; Sasaki, Osamu

2018-03-13

Because lactation periods in dairy cows lengthen with increasing total milk production, it is important to predict individual productivities after 305 days in milk (DIM) to determine the optimal lactation period. We therefore examined whether the random regression (RR) coefficient from 306 to 450 DIM (M2) can be predicted from those during the first 305 DIM (M1) by using a random regression model. We analyzed test-day milk records from 85690 Holstein cows in their first lactations and 131727 cows in their later (second to fifth) lactations. Data in M1 and M2 were analyzed separately by using different single-trait RR animal models. We then performed a multiple regression analysis of the RR coefficients of M2 on those of M1 during the first and later lactations. The first-order Legendre polynomials were practical covariates of random regression for the milk yields of M2. All RR coefficients for the additive genetic (AG) effect and the intercept for the permanent environmental (PE) effect of M2 had moderate to strong correlations with the intercept for the AG effect of M1. The coefficients of determination for multiple regression of the combined intercepts for the AG and PE effects of M2 on the coefficients for the AG effect of M1 were moderate to high. The daily milk yields of M2 predicted by using the RR coefficients for the AG effect of M1 were highly correlated with those obtained by using the coefficients of M2. Milk production after 305 DIM can be predicted by using the RR coefficient estimates of the AG effect during the first 305 DIM.

An economic prediction of the finer resolution level wavelet coefficients in electronic structure calculations.

PubMed

Nagy, Szilvia; Pipek, János

2015-12-21

In wavelet based electronic structure calculations, introducing a new, finer resolution level is usually an expensive task, this is why often a two-level approximation is used with very fine starting resolution level. This process results in large matrices to calculate with and a large number of coefficients to be stored. In our previous work we have developed an adaptively refined solution scheme that determines the indices, where the refined basis functions are to be included, and later a method for predicting the next, finer resolution coefficients in a very economic way. In the present contribution, we would like to determine whether the method can be applied for predicting not only the first, but also the other, higher resolution level coefficients. Also the energy expectation values of the predicted wave functions are studied, as well as the scaling behaviour of the coefficients in the fine resolution limit.

A Large-scale Finite Element Model on Micromechanical Damage and Failure of Carbon Fiber/Epoxy Composites Including Thermal Residual Stress

NASA Astrophysics Data System (ADS)

Liu, P. F.; Li, X. K.

2018-06-01

The purpose of this paper is to study micromechanical progressive failure properties of carbon fiber/epoxy composites with thermal residual stress by finite element analysis (FEA). Composite microstructures with hexagonal fiber distribution are used for the representative volume element (RVE), where an initial fiber breakage is assumed. Fiber breakage with random fiber strength is predicted using Monte Carlo simulation, progressive matrix damage is predicted by proposing a continuum damage mechanics model and interface failure is simulated using Xu and Needleman's cohesive model. Temperature dependent thermal expansion coefficients for epoxy matrix are used. FEA by developing numerical codes using ANSYS finite element software is divided into two steps: 1. Thermal residual stresses due to mismatch between fiber and matrix are calculated; 2. Longitudinal tensile load is further exerted on the RVE to perform progressive failure analysis of carbon fiber/epoxy composites. Numerical convergence is solved by introducing the viscous damping effect properly. The extended Mori-Tanaka method that considers interface debonding is used to get homogenized mechanical responses of composites. Three main results by FEA are obtained: 1. the real-time matrix cracking, fiber breakage and interface debonding with increasing tensile strain is simulated. 2. the stress concentration coefficients on neighbouring fibers near the initial broken fiber and the axial fiber stress distribution along the broken fiber are predicted, compared with the results using the global and local load-sharing models based on the shear-lag theory. 3. the tensile strength of composite by FEA is compared with those by the shear-lag theory and experiments. Finally, the tensile stress-strain curve of composites by FEA is applied to the progressive failure analysis of composite pressure vessel.

A Large-scale Finite Element Model on Micromechanical Damage and Failure of Carbon Fiber/Epoxy Composites Including Thermal Residual Stress

NASA Astrophysics Data System (ADS)

Liu, P. F.; Li, X. K.

2017-09-01

The purpose of this paper is to study micromechanical progressive failure properties of carbon fiber/epoxy composites with thermal residual stress by finite element analysis (FEA). Composite microstructures with hexagonal fiber distribution are used for the representative volume element (RVE), where an initial fiber breakage is assumed. Fiber breakage with random fiber strength is predicted using Monte Carlo simulation, progressive matrix damage is predicted by proposing a continuum damage mechanics model and interface failure is simulated using Xu and Needleman's cohesive model. Temperature dependent thermal expansion coefficients for epoxy matrix are used. FEA by developing numerical codes using ANSYS finite element software is divided into two steps: 1. Thermal residual stresses due to mismatch between fiber and matrix are calculated; 2. Longitudinal tensile load is further exerted on the RVE to perform progressive failure analysis of carbon fiber/epoxy composites. Numerical convergence is solved by introducing the viscous damping effect properly. The extended Mori-Tanaka method that considers interface debonding is used to get homogenized mechanical responses of composites. Three main results by FEA are obtained: 1. the real-time matrix cracking, fiber breakage and interface debonding with increasing tensile strain is simulated. 2. the stress concentration coefficients on neighbouring fibers near the initial broken fiber and the axial fiber stress distribution along the broken fiber are predicted, compared with the results using the global and local load-sharing models based on the shear-lag theory. 3. the tensile strength of composite by FEA is compared with those by the shear-lag theory and experiments. Finally, the tensile stress-strain curve of composites by FEA is applied to the progressive failure analysis of composite pressure vessel.

Experimental and computational analysis of sound absorption behavior in needled nonwovens

NASA Astrophysics Data System (ADS)

Soltani, Parham; Azimian, Mehdi; Wiegmann, Andreas; Zarrebini, Mohammad

2018-07-01

In this paper application of X-ray micro-computed tomography (μCT) together with fluid simulation techniques to predict sound absorption characteristics of needled nonwovens is discussed. Melt-spun polypropylene fibers of different fineness were made on an industrial scale compact melt spinning line. A conventional batt forming-needling line was used to prepare the needled samples. The normal incidence sound absorption coefficients were measured using impedance tube method. Realistic 3D images of samples at micron-level spatial resolution were obtained using μCT. Morphology of fabrics was characterized in terms of porosity, fiber diameter distribution, fiber curliness and pore size distribution from high-resolution realistic 3D images using GeoDict software. In order to calculate permeability and flow resistivity of media, fluid flow was simulated by numerically solving incompressible laminar Newtonian flow through the 3D pore space of realistic structures. Based on the flow resistivity, the frequency-dependent acoustic absorption coefficient of the needled nonwovens was predicted using the empirical model of Delany and Bazley (1970) and its associated modified models. The results were compared and validated with the corresponding experimental results. Based on morphological analysis, it was concluded that for a given weight per unit area, finer fibers yield to presence of higher number of fibers in the samples. This results in formation of smaller and more tortuous pores, which in turn leads to increase in flow resistivity of media. It was established that, among the empirical models, Mechel modification to Delany and Bazley model had superior predictive ability when compared to that of the original Delany and Bazley model at frequency range of 100-5000 Hz and is well suited to polypropylene needled nonwovens.

Constructing Confidence Intervals for Reliability Coefficients Using Central and Noncentral Distributions.

ERIC Educational Resources Information Center

Weber, Deborah A.

Greater understanding and use of confidence intervals is central to changes in statistical practice (G. Cumming and S. Finch, 2001). Reliability coefficients and confidence intervals for reliability coefficients can be computed using a variety of methods. Estimating confidence intervals includes both central and noncentral distribution approaches.…

Near-infrared hyperspectral imaging and partial least squares regression for rapid and reagentless determination of Enterobacteriaceae on chicken fillets.

PubMed

Feng, Yao-Ze; Elmasry, Gamal; Sun, Da-Wen; Scannell, Amalia G M; Walsh, Des; Morcy, Noha

2013-06-01

Bacterial pathogens are the main culprits for outbreaks of food-borne illnesses. This study aimed to use the hyperspectral imaging technique as a non-destructive tool for quantitative and direct determination of Enterobacteriaceae loads on chicken fillets. Partial least squares regression (PLSR) models were established and the best model using full wavelengths was obtained in the spectral range 930-1450 nm with coefficients of determination R(2)≥ 0.82 and root mean squared errors (RMSEs) ≤ 0.47 log(10)CFUg(-1). In further development of simplified models, second derivative spectra and weighted PLS regression coefficients (BW) were utilised to select important wavelengths. However, the three wavelengths (930, 1121 and 1345 nm) selected from BW were competent and more preferred for predicting Enterobacteriaceae loads with R(2) of 0.89, 0.86 and 0.87 and RMSEs of 0.33, 0.40 and 0.45 log(10)CFUg(-1) for calibration, cross-validation and prediction, respectively. Besides, the constructed prediction map provided the distribution of Enterobacteriaceae bacteria on chicken fillets, which cannot be achieved by conventional methods. It was demonstrated that hyperspectral imaging is a potential tool for determining food sanitation and detecting bacterial pathogens on food matrix without using complicated laboratory regimes. Copyright © 2012 Elsevier Ltd. All rights reserved.

Computational design of low aspect ratio wing-winglet configurations for transonic wind-tunnel tests

NASA Technical Reports Server (NTRS)

Kuhlman, John M.; Brown, Christopher K.

1989-01-01

Computational designs were performed for three different low aspect ratio wing planforms fitted with nonplanar winglets; one of the three configurations was selected to be constructed as a wind tunnel model for testing in the NASA LaRC 8-foot transonic pressure tunnel. A design point of M = 0.8, C(sub L) is approximate or = to 0.3 was selected, for wings of aspect ratio equal to 2.2, and leading edge sweep angles of 45 deg and 50 deg. Winglet length is 15 percent of the wing semispan, with a cant angle of 15 deg, and a leading edge sweep of 50 deg. Winglet total area equals 2.25 percent of the wing reference area. The design process and the predicted transonic performance are summarized for each configuration. In addition, a companion low-speed design study was conducted, using one of the transonic design wing-winglet planforms but with different camber and thickness distributions. A low-speed wind tunnel model was constructed to match this low-speed design geometry, and force coefficient data were obtained for the model at speeds of 100 to 150 ft/sec. Measured drag coefficient reductions were of the same order of magnitude as those predicted by numerical subsonic performance predictions.

Dependencies of lepton angular distribution coefficients on the transverse momentum and rapidity of Z bosons produced in p p collisions at the LHC

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chang, Wen -Chen; McClellan, Randall Evan; Peng, Jen -Chieh

Here, high precision data of lepton angular distributions formore » $$\\gamma^*/Z$$ production in $pp$ collisions at the LHC, covering broad ranges of dilepton transverse momenta ($$q_T$$) and rapidity ($y$), were recently reported. Strong $$q_T$$ dependencies were observed for several angular distribution coefficients, $$A_i$$, including $$A_0 - A_4$$. Significant $y$ dependencies were also found for the coefficients $$A_1$$, $$A_3$$ and $$A_4$$, while $$A_0$$ and $$A_2$$ exhibit very weak rapidity dependence. Using an intuitive geometric picture we show that the $$q_T$$ and $y$ dependencies of the angular distributions coefficients can be well described.« less

Dependencies of lepton angular distribution coefficients on the transverse momentum and rapidity of Z bosons produced in p p collisions at the LHC

DOE PAGES

Chang, Wen -Chen; McClellan, Randall Evan; Peng, Jen -Chieh; ...

2017-09-21

Here, high precision data of lepton angular distributions formore » $$\\gamma^*/Z$$ production in $pp$ collisions at the LHC, covering broad ranges of dilepton transverse momenta ($$q_T$$) and rapidity ($y$), were recently reported. Strong $$q_T$$ dependencies were observed for several angular distribution coefficients, $$A_i$$, including $$A_0 - A_4$$. Significant $y$ dependencies were also found for the coefficients $$A_1$$, $$A_3$$ and $$A_4$$, while $$A_0$$ and $$A_2$$ exhibit very weak rapidity dependence. Using an intuitive geometric picture we show that the $$q_T$$ and $y$ dependencies of the angular distributions coefficients can be well described.« less

Retrieve Aerosol Concentration Based On Surface Model and Distribution of Concentration of PM2.5 ——A Case Study of Beijing

NASA Astrophysics Data System (ADS)

Cui, H.

2017-12-01

As China's economy continues to grow, urbanization continues to advance, along with growth in all areas to pollutant emissions in the air industry, air quality also continued to deteriorate. Aerosol concentrations as a measure of air quality of the most important part of are more and more people's attention. Traditional monitoring stations measuring aerosol concentration method is accurate, but time-consuming and can't be done simultaneously measure a large area, can only rely on data from several monitoring sites to predict the concentration of the panorama. Remote Sensing Technology retrieves aerosol concentrations being by virtue of their efficient, fast advantages gradually into sight. In this paper, by the method of surface model to start with the physical processes of atmospheric transport, innovative aerosol concentration coefficient proposed to replace the traditional aerosol concentrations, pushed to a set of retrieval of aerosol concentration coefficient method, enabling fast and efficient Get accurate air pollution target area. At the same paper also monitoring data for PM2.5 in Beijing were analyzed from different angles, from the perspective of the data summarized in Beijing PM2.5 concentration of time, space, geographical distribution and concentration of PM2.5 and explored the relationship between aerosol concentration coefficient and concentration of PM2.5.

Do lab-derived distribution coefficient values of pesticides match distribution coefficient values determined from column and field-scale experiments? A critical analysis of relevant literature.

PubMed

Vereecken, H; Vanderborght, J; Kasteel, R; Spiteller, M; Schäffer, A; Close, M

2011-01-01

In this study, we analyzed sorption parameters for pesticides that were derived from batch and column or batch and field experiments. The batch experiments analyzed in this study were run with the same pesticide and soil as in the column and field experiments. We analyzed the relationship between the pore water velocity of the column and field experiments, solute residence times, and sorption parameters, such as the organic carbon normalized distribution coefficient ( ) and the mass exchange coefficient in kinetic models, as well as the predictability of sorption parameters from basic soil properties. The batch/column analysis included 38 studies with a total of 139 observations. The batch/field analysis included five studies, resulting in a dataset of 24 observations. For the batch/column data, power law relationships between pore water velocity, residence time, and sorption constants were derived. The unexplained variability in these equations was reduced, taking into account the saturation status and the packing status (disturbed-undisturbed) of the soil sample. A new regression equation was derived that allows estimating the values derived from column experiments using organic matter and bulk density with an value of 0.56. Regression analysis of the batch/column data showed that the relationship between batch- and column-derived values depends on the saturation status and packing of the soil column. Analysis of the batch/field data showed that as the batch-derived value becomes larger, field-derived values tend to be lower than the corresponding batch-derived values, and vice versa. The present dataset also showed that the variability in the ratio of batch- to column-derived value increases with increasing pore water velocity, with a maximum value approaching 3.5. American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America.

An empirically derived basis for calculating the area, rate, and distribution of water-drop impingement on airfoils

NASA Technical Reports Server (NTRS)

Bergrun, Norman R

1952-01-01

An empirically derived basis for predicting the area, rate, and distribution of water-drop impingement on airfoils of arbitrary section is presented. The concepts involved represent an initial step toward the development of a calculation technique which is generally applicable to the design of thermal ice-prevention equipment for airplane wing and tail surfaces. It is shown that sufficiently accurate estimates, for the purpose of heated-wing design, can be obtained by a few numerical computations once the velocity distribution over the airfoil has been determined. The calculation technique presented is based on results of extensive water-drop trajectory computations for five airfoil cases which consisted of 15-percent-thick airfoils encompassing a moderate lift-coefficient range. The differential equations pertaining to the paths of the drops were solved by a differential analyzer.

A novel method for the investigation of liquid/liquid distribution coefficients and interface permeabilities applied to the water-octanol-drug system.

PubMed

Stein, Paul C; di Cagno, Massimiliano; Bauer-Brandl, Annette

2011-09-01

In this work a new, accurate and convenient technique for the measurement of distribution coefficients and membrane permeabilities based on nuclear magnetic resonance (NMR) is described. This method is a novel implementation of localized NMR spectroscopy and enables the simultaneous analysis of the drug content in the octanol and in the water phase without separation. For validation of the method, the distribution coefficients at pH = 7.4 of four active pharmaceutical ingredients (APIs), namely ibuprofen, ketoprofen, nadolol, and paracetamol (acetaminophen), were determined using a classical approach. These results were compared to the NMR experiments which are described in this work. For all substances, the respective distribution coefficients found with the two techniques coincided very well. Furthermore, the NMR experiments make it possible to follow the distribution of the drug between the phases as a function of position and time. Our results show that the technique, which is available on any modern NMR spectrometer, is well suited to the measurement of distribution coefficients. The experiments present also new insight into the dynamics of the water-octanol interface itself and permit measurement of the interface permeability.

Ensemble modeling of stochastic unsteady open-channel flow in terms of its time-space evolutionary probability distribution - Part 2: numerical application

NASA Astrophysics Data System (ADS)

Dib, Alain; Kavvas, M. Levent

2018-03-01

The characteristic form of the Saint-Venant equations is solved in a stochastic setting by using a newly proposed Fokker-Planck Equation (FPE) methodology. This methodology computes the ensemble behavior and variability of the unsteady flow in open channels by directly solving for the flow variables' time-space evolutionary probability distribution. The new methodology is tested on a stochastic unsteady open-channel flow problem, with an uncertainty arising from the channel's roughness coefficient. The computed statistical descriptions of the flow variables are compared to the results obtained through Monte Carlo (MC) simulations in order to evaluate the performance of the FPE methodology. The comparisons show that the proposed methodology can adequately predict the results of the considered stochastic flow problem, including the ensemble averages, variances, and probability density functions in time and space. Unlike the large number of simulations performed by the MC approach, only one simulation is required by the FPE methodology. Moreover, the total computational time of the FPE methodology is smaller than that of the MC approach, which could prove to be a particularly crucial advantage in systems with a large number of uncertain parameters. As such, the results obtained in this study indicate that the proposed FPE methodology is a powerful and time-efficient approach for predicting the ensemble average and variance behavior, in both space and time, for an open-channel flow process under an uncertain roughness coefficient.

Interstitial distribution of charged macromolecules in the dog lung: a kinetic model.

PubMed

Parker, J C; Miniati, M; Pitt, R; Taylor, A E

1987-01-01

A mathematic model was constructed to investigate conflicting physiologic data concerning the charge effect of continuous capillaries to macromolecules in the lung. We simulated the equilibration kinetics of lactate dehydrogenase (MR 4.2 nM) isozymes LDH 1 (pI = 5.0) and LDH 5 (pI = 7.9) between plasma and lymph using previously measured permeability coefficients, lung tissue distribution volumes (VA) and plasma concentrations (CP) in lung tissue. Our hypothesis is that the fixed anionic charges in interstitium, basement membrane, and cell surfaces determine equilibration rather than charged membrane effects at the capillary barrier, so the same capillary permeability coefficients were used for both isozymes. Capillary filtration rates and protein fluxes were calculated using conventional flux equations. Initial conditions at baseline and increased left atrial pressures (PLA) were those measured in animal studies. Simulated equilibration of isozymes over 30 h in the model at baseline capillary pressures accurately predicted the observed differences in lymph/plasma concentration ratios (CL/CP) between isotopes at 4 h and equilibration of these ratios at 24 h. Quantitative prediction of isozyme CL/CP ratios was also obtained at increased PLA. However, an additional cation selective compartment representing the surface glycocalyx was required to accurately simulate the initial higher transcapillary clearances of cationic LDH 5. Thus experimental data supporting the negative barrier, positive barrier, and no charge barrier hypotheses were accurately reproduced by the model using only the observed differences in interstitial partitioning of isozymes without differences in capillary selectivity.

Confidence bounds for normal and lognormal distribution coefficients of variation

Treesearch

Steve Verrill

2003-01-01

This paper compares the so-called exact approach for obtaining confidence intervals on normal distribution coefficients of variation to approximate methods. Approximate approaches were found to perform less well than the exact approach for large coefficients of variation and small sample sizes. Web-based computer programs are described for calculating confidence...

Measurements and Modelling of Sputtering Rates with Low Energy Ions

NASA Astrophysics Data System (ADS)

Ruzic, David N.; Smith, Preston C.; Turkot, Robert B., Jr.

1996-10-01

The angular-resolved sputtering yield of Be by D+, and Al by Ar+ was predicted and then measured. A 50 to 1000 eV ion beam from a Colutron was focused on to commercial grade and magnetron target grade samples. The S-65 C grade beryllium samples were supplied by Brush Wellman and the Al samples from TOSOH SMD. In our vacuum chamber the samples can be exposed to a dc D or Ar plasma to remove oxide, load the surface and more-nearly simulate steady state operating conditions in the plasma device. The angular distribution of the sputtered atoms was measured by collection on a single crystal graphite witness plate. The areal density of Be or Al (and BeO2 or Al2O3, after exposure to air) was then measured using a Scanning Auger Spectrometer. Total yield was also measured by deposition onto a quartz crystal oscillator simultaneously to deposition onto the witness plate. A three dimensional version of vectorized fractal TRIM (VFTRIM3D), a Monte-Carlo computer code which includes surface roughness characterized by fractal geometry, was used to predict the angular distribution of the sputtered particles and a global sputtering coefficient. Over a million trajectories were simulated for each incident angle to determine the azimuthal and polar angle distributions of the sputtered atoms. The experimental results match closely with the simulations for total yield, while the measured angular distributions depart somewhat from the predicted cosine curve.

Thermodynamics of Boron Removal from Silicon Using CaO-MgO-Al2O3-SiO2 Slags

NASA Astrophysics Data System (ADS)

Jakobsson, Lars Klemet; Tangstad, Merete

2018-04-01

Slag refining is one of few metallurgical methods for removal of boron from silicon. It is important to know the thermodynamic properties of boron in slags to understand the refining process. The relation of the distribution coefficient of boron to the activity of silica, partial pressure of oxygen, and capacity of slags for boron oxide was investigated. The link between these parameters explains why the distribution coefficient of boron does not change much with changing slag composition. In addition, the thermodynamic properties of dilute boron oxide in CaO-MgO-Al2O3-SiO2 slags was determined. The ratio of the activity coefficient of boron oxide and silica was found to be the most important parameter for understanding changes in the distribution coefficient of boron for different slags. Finally, the relation between the activity coefficient of boron oxide and slag structure was investigated. It was found that the structure can explain how the distribution coefficient of boron changes depending on slag composition.

Optical Quasi-Soliton Solutions for the Cubic-Quintic Nonlinear SCHRÖDINGER Equation with Variable Coefficients

NASA Astrophysics Data System (ADS)

Yang, Qin; Zhang, Jie-Fang

Optical quasi-soliton solutions for the cubic-quintic nonlinear Schrödinger equation (CQNLSE) with variable coefficients are considered. Based on the extended tanh-function method, we not only successfully obtained bright and dark quasi-soliton solutions, but also obtained the kink quasi-soliton solutions under certain parametric conditions. We conclude that the quasi-solitons induced by the combined effects of the group velocity dispersion (GVD) distribution, the nonlinearity distribution, higher-order nonlinearity distribution, and the amplification or absorption coefficient are quite different from those of the solitons induced only by the combined effects of the GVD, the nonlinearity distribution, and the amplification or absorption coefficient without considering the higher-order nonlinearity distribution (i.e. α(z)=0). Furthermore, we choose appropriate optical fiber parameters D(z) and R(z) to control the velocity of quasi-soliton and time shift, and discuss the evolution behavior of the special quasi-soliton.

Effects of Surface and Subsurface Bed Material Composition on Gravel Transport and Flow Competence Relations—Possibilities for Prediction

NASA Astrophysics Data System (ADS)

Bunte, K.; Abt, S. R.; Swingle, K. W.; Cenderelli, D. A.; Gaeuman, D. A.

2014-12-01

Bedload transport and flow competence relations are difficult to predict in coarse-bedded steep streams where widely differing sediment supply, bed stability, and complex flow hydraulics greatly affect amounts and sizes of transported gravel particles. This study explains how properties of bed material surface and subsurface size distributions are directly related to gravel transport and may be used for prediction of gravel transport and flow competence relations. Gravel transport, flow competence, and bed material size were measured in step-pool and plane-bed streams. Power functions were fitted to gravel transport QB=aQb and flow competence Dmax=cQd relations; Q is water discharge. Frequency distributions of surface FDsurf and subsurface FDsub bed material were likewise described by power functions FDsurf=hD j and FDsub=kDm fitted over six 0.5-phi size classes within 4 to 22.4 mm. Those gravel sizes are typically mobile even in moderate floods. Study results show that steeper subsurface bed material size distributions lead to steeper gravel transport and flow competence relations, whereas larger amounts of sediment contained in those 6 size bedmaterial classes (larger h and k) flatten the relations. Similarly, steeper surface size distributions decrease the coefficients of the gravel transport and flow competence relations, whereas larger amounts of sediment within the six bed material classes increase the intercepts of gravel transport and flow competence relations. Those relations are likely causative in streams where bedload stems almost entirely from the channel bed as opposed to direct (unworked) contributions from hillslopes and tributaries. The exponent of the subsurface bed material distribution m predicted the gravel transport exponent b with r2 near 0.7 and flow competence exponent d with r2 near 0.5. The intercept of bed surface distributions h increased the intercept a of gravel transport and c of the flow competence relations with r2 near 0.6.

Thermal conductivity of microporous layers: Analytical modeling and experimental validation

NASA Astrophysics Data System (ADS)

Andisheh-Tadbir, Mehdi; Kjeang, Erik; Bahrami, Majid

2015-11-01

A new compact relationship is developed for the thermal conductivity of the microporous layer (MPL) used in polymer electrolyte fuel cells as a function of pore size distribution, porosity, and compression pressure. The proposed model is successfully validated against experimental data obtained from a transient plane source thermal constants analyzer. The thermal conductivities of carbon paper samples with and without MPL were measured as a function of load (1-6 bars) and the MPL thermal conductivity was found between 0.13 and 0.17 W m-1 K-1. The proposed analytical model predicts the experimental thermal conductivities within 5%. A correlation generated from the analytical model was used in a multi objective genetic algorithm to predict the pore size distribution and porosity for an MPL with optimized thermal conductivity and mass diffusivity. The results suggest that an optimized MPL, in terms of heat and mass transfer coefficients, has an average pore size of 122 nm and 63% porosity.

Statistical properties of cross-correlation in the Korean stock market

NASA Astrophysics Data System (ADS)

Oh, G.; Eom, C.; Wang, F.; Jung, W.-S.; Stanley, H. E.; Kim, S.

2011-01-01

We investigate the statistical properties of the cross-correlation matrix between individual stocks traded in the Korean stock market using the random matrix theory (RMT) and observe how these affect the portfolio weights in the Markowitz portfolio theory. We find that the distribution of the cross-correlation matrix is positively skewed and changes over time. We find that the eigenvalue distribution of original cross-correlation matrix deviates from the eigenvalues predicted by the RMT, and the largest eigenvalue is 52 times larger than the maximum value among the eigenvalues predicted by the RMT. The β_{473} coefficient, which reflect the largest eigenvalue property, is 0.8, while one of the eigenvalues in the RMT is approximately zero. Notably, we show that the entropy function E(σ) with the portfolio risk σ for the original and filtered cross-correlation matrices are consistent with a power-law function, E( σ) σ^{-γ}, with the exponent γ 2.92 and those for Asian currency crisis decreases significantly.

Predicting commuter flows in spatial networks using a radiation model based on temporal ranges

NASA Astrophysics Data System (ADS)

Ren, Yihui; Ercsey-Ravasz, Mária; Wang, Pu; González, Marta C.; Toroczkai, Zoltán

2014-11-01

Understanding network flows such as commuter traffic in large transportation networks is an ongoing challenge due to the complex nature of the transportation infrastructure and human mobility. Here we show a first-principles based method for traffic prediction using a cost-based generalization of the radiation model for human mobility, coupled with a cost-minimizing algorithm for efficient distribution of the mobility fluxes through the network. Using US census and highway traffic data, we show that traffic can efficiently and accurately be computed from a range-limited, network betweenness type calculation. The model based on travel time costs captures the log-normal distribution of the traffic and attains a high Pearson correlation coefficient (0.75) when compared with real traffic. Because of its principled nature, this method can inform many applications related to human mobility driven flows in spatial networks, ranging from transportation, through urban planning to mitigation of the effects of catastrophic events.

Mobility of Heavy Metals (Pb, Cd, Zn) in the Pampeano and Puelche Aquifers, Argentina: Partition and Retardation Coefficients.

PubMed

Jakomin, L M; Marbán, L; Grondona, S; Glok Galli, M; Martínez, D E

2015-09-01

The prediction about metals behaviour in soil requires knowledge on their solid-liquid partitioning. Usually it is expressed with an empirical distribution coefficient or Kd, which gives the ratio of the metal concentration in the solid phase to that in the solution. Kd values have been determined for Zn, Pb and Cd from samples representing the two most exploited aquifers in Argentina, Pampeano and Puelche, at three different locations in the province of Buenos Aires. The Pampeano aquifer presented higher Kd values than the Puelche aquifer. Comparing Kd values, different relationships could be observed: (a) Pampeano aquifer: Pb > Zn > Cd, and (b) Puelche aquifer: Pb > Cd > Zn. Kd for Cd seems to be linked to cationic exchange capacity, but solid phases precipitation can be more determining for Pb and Zn.

Prediction of seebeck coefficient for compounds without restriction to fixed stoichiometry: A machine learning approach.

PubMed

Furmanchuk, Al'ona; Saal, James E; Doak, Jeff W; Olson, Gregory B; Choudhary, Alok; Agrawal, Ankit

2018-02-05

The regression model-based tool is developed for predicting the Seebeck coefficient of crystalline materials in the temperature range from 300 K to 1000 K. The tool accounts for the single crystal versus polycrystalline nature of the compound, the production method, and properties of the constituent elements in the chemical formula. We introduce new descriptive features of crystalline materials relevant for the prediction the Seebeck coefficient. To address off-stoichiometry in materials, the predictive tool is trained on a mix of stoichiometric and nonstoichiometric materials. The tool is implemented into a web application (http://info.eecs.northwestern.edu/SeebeckCoefficientPredictor) to assist field scientists in the discovery of novel thermoelectric materials. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Effect of annealing on structural changes and oxygen diffusion in amorphous HfO2 using classical molecular dynamics

NASA Astrophysics Data System (ADS)

Shen, Wenqing; Kumari, Niru; Gibson, Gary; Jeon, Yoocharn; Henze, Dick; Silverthorn, Sarah; Bash, Cullen; Kumar, Satish

2018-02-01

Non-volatile memory is a promising alternative to present memory technologies. Oxygen vacancy diffusion has been widely accepted as one of the reasons for the resistive switching mechanism of transition-metal-oxide based resistive random access memory. In this study, molecular dynamics simulation is applied to investigate the diffusion coefficient and activation energy of oxygen in amorphous hafnia. Two sets of empirical potential, Charge-Optimized Many-Body (COMB) and Morse-BKS (MBKS), were considered to investigate the structural and diffusion properties at different temperatures. COMB predicts the activation energy of 0.53 eV for the temperature range of 1000-2000 K, while MBKS predicts 2.2 eV at high temperature (1600-2000 K) and 0.36 eV at low temperature (1000-1600 K). Structural changes and appearance of nano-crystalline phases with increasing temperature might affect the activation energy of oxygen diffusion predicted by MBKS, which is evident from the change in coordination number distribution and radial distribution function. None of the potentials make predictions that are fully consistent with density functional theory simulations of both the structure and diffusion properties of HfO2. This suggests the necessity of developing a better multi-body potential that considers charge exchange.

The role of environmental variables in structuring landscape-scale species distributions in seafloor habitats.

PubMed

Kraan, Casper; Aarts, Geert; Van der Meer, Jaap; Piersma, Theunis

2010-06-01

Ongoing statistical sophistication allows a shift from describing species' spatial distributions toward statistically disentangling the possible roles of environmental variables in shaping species distributions. Based on a landscape-scale benthic survey in the Dutch Wadden Sea, we show the merits of spatially explicit generalized estimating equations (GEE). The intertidal macrozoobenthic species, Macoma balthica, Cerastoderma edule, Marenzelleria viridis, Scoloplos armiger, Corophium volutator, and Urothoe poseidonis served as test cases, with median grain-size and inundation time as typical environmental explanatory variables. GEEs outperformed spatially naive generalized linear models (GLMs), and removed much residual spatial structure, indicating the importance of median grain-size and inundation time in shaping landscape-scale species distributions in the intertidal. GEE regression coefficients were smaller than those attained with GLM, and GEE standard errors were larger. The best fitting GEE for each species was used to predict species' density in relation to median grain-size and inundation time. Although no drastic changes were noted compared to previous work that described habitat suitability for benthic fauna in the Wadden Sea, our predictions provided more detailed and unbiased estimates of the determinants of species-environment relationships. We conclude that spatial GEEs offer the necessary methodological advances to further steps toward linking pattern to process.

Explicit use of the Biot coefficient in predicting shear-wave velocity of water-saturated sediments

USGS Publications Warehouse

Lee, M.W.

2006-01-01

Predicting the shear-wave (S-wave) velocity is important in seismic modelling, amplitude analysis with offset, and other exploration and engineering applications. Under the low-frequency approximation, the classical Biot-Gassmann theory relates the Biot coefficient to the bulk modulus of water-saturated sediments. If the Biot coefficient under in situ conditions can be estimated, the shear modulus or the S-wave velocity can be calculated. The Biot coefficient derived from the compressional-wave (P-wave) velocity of water-saturated sediments often differs from and is less than that estimated from the S-wave velocity, owing to the interactions between the pore fluid and the grain contacts. By correcting the Biot coefficients derived from P-wave velocities of water-saturated sediments measured at various differential pressures, an accurate method of predicting S-wave velocities is proposed. Numerical results indicate that the predicted S-wave velocities for consolidated and unconsolidated sediments agreewell with measured velocities. ?? 2006 European Association of Geoscientists & Engineers.

An analysis of the symmetry issue in the ℓ-distribution method of gas radiation in non-uniform gaseous media

NASA Astrophysics Data System (ADS)

André, Frédéric

2017-03-01

The recently proposed ℓ-distribution/ICE (Iterative Copula Evaluation) method of gas radiation suffers from symmetry issues when applied in highly non-isothermal and non-homogeneous gaseous media. This problem is studied in a detailed theoretical way. The objective of the present paper is: 1/to provide a mathematical analysis of this problem of symmetry and, 2/to suggest a decisive factor, defined in terms of the ratio between the narrow band Planck and Rosseland mean absorption coefficients, to handle this issue. Comparisons of model predictions with reference LBL calculations show that the proposed criterion improves the accuracy of the intuitive ICE method for applications in highly non-uniform gases at high temperatures.

A view on thermodynamics of concentrated electrolytes: Modification necessity for electrostatic contribution of osmotic coefficient

NASA Astrophysics Data System (ADS)

Sahu, Jyoti; Juvekar, Vinay A.

2018-05-01

Prediction of the osmotic coefficient of concentrated electrolytes is needed in a wide variety of industrial applications. There is a need to correctly segregate the electrostatic contribution to osmotic coefficient from nonelectrostatic contribution. This is achieved in a rational way in this work. Using the Robinson-Stokes-Glueckauf hydrated ion model to predict non-electrostatic contribution to the osmotic coefficient, it is shown that hydration number should be independent of concentration so that the observed linear dependence of osmotic coefficient on electrolyte concentration in high concentration range could be predicted. The hydration number of several electrolytes (LiCl, NaCl, KCl, MgCl2, and MgSO4) has been estimated by this method. The hydration number predicted by this model shows correct dependence on temperature. It is also shown that the electrostatic contribution to osmotic coefficient is underpredicted by the Debye-Hückel theory at concentration beyond 0.1 m. The Debye-Hückel theory is modified by introducing a concentration dependent hydrated ionic size. Using the present analysis, it is possible to correctly estimate the electrostatic contribution to the osmotic coefficient, beyond the range of validation of the D-H theory. This would allow development of a more fundamental model for electrostatic interaction at high electrolyte concentrations.

Verifying the Dependence of Fractal Coefficients on Different Spatial Distributions

NASA Astrophysics Data System (ADS)

Gospodinov, Dragomir; Marekova, Elisaveta; Marinov, Alexander

2010-01-01

A fractal distribution requires that the number of objects larger than a specific size r has a power-law dependence on the size N(r) = C/rD∝r-D where D is the fractal dimension. Usually the correlation integral is calculated to estimate the correlation fractal dimension of epicentres. A `box-counting' procedure could also be applied giving the `capacity' fractal dimension. The fractal dimension can be an integer and then it is equivalent to a Euclidean dimension (it is zero of a point, one of a segment, of a square is two and of a cube is three). In general the fractal dimension is not an integer but a fractional dimension and there comes the origin of the term `fractal'. The use of a power-law to statistically describe a set of events or phenomena reveals the lack of a characteristic length scale, that is fractal objects are scale invariant. Scaling invariance and chaotic behavior constitute the base of a lot of natural hazards phenomena. Many studies of earthquakes reveal that their occurrence exhibits scale-invariant properties, so the fractal dimension can characterize them. It has first been confirmed that both aftershock rate decay in time and earthquake size distribution follow a power law. Recently many other earthquake distributions have been found to be scale-invariant. The spatial distribution of both regional seismicity and aftershocks show some fractal features. Earthquake spatial distributions are considered fractal, but indirectly. There are two possible models, which result in fractal earthquake distributions. The first model considers that a fractal distribution of faults leads to a fractal distribution of earthquakes, because each earthquake is characteristic of the fault on which it occurs. The second assumes that each fault has a fractal distribution of earthquakes. Observations strongly favour the first hypothesis. The fractal coefficients analysis provides some important advantages in examining earthquake spatial distribution, which are:—Simple way to quantify scale-invariant distributions of complex objects or phenomena by a small number of parameters.—It is becoming evident that the applicability of fractal distributions to geological problems could have a more fundamental basis. Chaotic behaviour could underlay the geotectonic processes and the applicable statistics could often be fractal. The application of fractal distribution analysis has, however, some specific aspects. It is usually difficult to present an adequate interpretation of the obtained values of fractal coefficients for earthquake epicenter or hypocenter distributions. That is why in this paper we aimed at other goals—to verify how a fractal coefficient depends on different spatial distributions. We simulated earthquake spatial data by generating randomly points first in a 3D space - cube, then in a parallelepiped, diminishing one of its sides. We then continued this procedure in 2D and 1D space. For each simulated data set we calculated the points' fractal coefficient (correlation fractal dimension of epicentres) and then checked for correlation between the coefficients values and the type of spatial distribution. In that way one can obtain a set of standard fractal coefficients' values for varying spatial distributions. These then can be used when real earthquake data is analyzed by comparing the real data coefficients values to the standard fractal coefficients. Such an approach can help in interpreting the fractal analysis results through different types of spatial distributions.

Polynomial Chaos Based Acoustic Uncertainty Predictions from Ocean Forecast Ensembles

NASA Astrophysics Data System (ADS)

Dennis, S.

2016-02-01

Most significant ocean acoustic propagation occurs at tens of kilometers, at scales small compared basin and to most fine scale ocean modeling. To address the increased emphasis on uncertainty quantification, for example transmission loss (TL) probability density functions (PDF) within some radius, a polynomial chaos (PC) based method is utilized. In order to capture uncertainty in ocean modeling, Navy Coastal Ocean Model (NCOM) now includes ensembles distributed to reflect the ocean analysis statistics. Since the ensembles are included in the data assimilation for the new forecast ensembles, the acoustic modeling uses the ensemble predictions in a similar fashion for creating sound speed distribution over an acoustically relevant domain. Within an acoustic domain, singular value decomposition over the combined time-space structure of the sound speeds can be used to create Karhunen-Loève expansions of sound speed, subject to multivariate normality testing. These sound speed expansions serve as a basis for Hermite polynomial chaos expansions of derived quantities, in particular TL. The PC expansion coefficients result from so-called non-intrusive methods, involving evaluation of TL at multi-dimensional Gauss-Hermite quadrature collocation points. Traditional TL calculation from standard acoustic propagation modeling could be prohibitively time consuming at all multi-dimensional collocation points. This method employs Smolyak order and gridding methods to allow adaptive sub-sampling of the collocation points to determine only the most significant PC expansion coefficients to within a preset tolerance. Practically, the Smolyak order and grid sizes grow only polynomially in the number of Karhunen-Loève terms, alleviating the curse of dimensionality. The resulting TL PC coefficients allow the determination of TL PDF normality and its mean and standard deviation. In the non-normal case, PC Monte Carlo methods are used to rapidly establish the PDF. This work was sponsored by the Office of Naval Research

Testing a 1-D Analytical Salt Intrusion Model and the Predictive Equation in Malaysian Estuaries

NASA Astrophysics Data System (ADS)

Gisen, Jacqueline Isabella; Savenije, Hubert H. G.

2013-04-01

Little is known about the salt intrusion behaviour in Malaysian estuaries. Study on this topic sometimes requires large amounts of data especially if a 2-D or 3-D numerical models are used for analysis. In poor data environments, 1-D analytical models are more appropriate. For this reason, a fully analytical 1-D salt intrusion model, based on the theory of Savenije in 2005, was tested in three Malaysian estuaries (Bernam, Selangor and Muar) because it is simple and requires minimal data. In order to achieve that, site surveys were conducted in these estuaries during the dry season (June-August) at spring tide by moving boat technique. Data of cross-sections, water levels and salinity were collected, and then analysed with the salt intrusion model. This paper demonstrates a good fit between the simulated and observed salinity distribution for all three estuaries. Additionally, the calibrated Van der Burgh's coefficient K, Dispersion coefficient D0, and salt intrusion length L, for the estuaries also displayed a reasonable correlations with those calculated from the predictive equations. This indicates that not only is the salt intrusion model valid for the case studies in Malaysia but also the predictive model. Furthermore, the results from this study describe the current state of the estuaries with which the Malaysian water authority in Malaysia can make decisions on limiting water abstraction or dredging. Keywords: salt intrusion, Malaysian estuaries, discharge, predictive model, dispersion

Design of novel quinazolinone derivatives as inhibitors for 5HT7 receptor.

PubMed

Chitta, Aparna; Jatavath, Mohan Babu; Fatima, Sabiha; Manga, Vijjulatha

2012-02-01

To study the pharmacophore properties of quinazolinone derivatives as 5HT(7) inhibitors, 3D QSAR methodologies, namely Comparative Molecular Field Analysis (CoMFA) and Comparative Molecular Similarity Indices Analysis (CoMSIA) were applied, partial least square (PLS) analysis was performed and QSAR models were generated. The derived model showed good statistical reliability in terms of predicting the 5HT(7) inhibitory activity of the quinazolione derivative, based on molecular property fields like steric, electrostatic, hydrophobic, hydrogen bond donor and hydrogen bond acceptor fields. This is evident from statistical parameters like q(2) (cross validated correlation coefficient) of 0.642, 0.602 and r(2) (conventional correlation coefficient) of 0.937, 0.908 for CoMFA and CoMSIA respectively. The predictive ability of the models to determine 5HT(7) antagonistic activity is validated using a test set of 26 molecules that were not included in the training set and the predictive r(2) obtained for the test set was 0.512 & 0.541. Further, the results of the derived model are illustrated by means of contour maps, which give an insight into the interaction of the drug with the receptor. The molecular fields so obtained served as the basis for the design of twenty new ligands. In addition, ADME (Adsorption, Distribution, Metabolism and Elimination) have been calculated in order to predict the relevant pharmaceutical properties, and the results are in conformity with required drug like properties.

Predictability and Quantification of Complex Groundwater Table Dynamics Driven by Irregular Surface Water Fluctuations

NASA Astrophysics Data System (ADS)

Xin, Pei; Wang, Shen S. J.; Shen, Chengji; Zhang, Zeyu; Lu, Chunhui; Li, Ling

2018-03-01

Shallow groundwater interacts strongly with surface water across a quarter of global land area, affecting significantly the terrestrial eco-hydrology and biogeochemistry. We examined groundwater behavior subjected to unimodal impulse and irregular surface water fluctuations, combining physical experiments, numerical simulations, and functional data analysis. Both the experiments and numerical simulations demonstrated a damped and delayed response of groundwater table to surface water fluctuations. To quantify this hysteretic shallow groundwater behavior, we developed a regression model with the Gamma distribution functions adopted to account for the dependence of groundwater behavior on antecedent surface water conditions. The regression model fits and predicts well the groundwater table oscillations resulting from propagation of irregular surface water fluctuations in both laboratory and large-scale aquifers. The coefficients of the Gamma distribution function vary spatially, reflecting the hysteresis effect associated with increased amplitude damping and delay as the fluctuation propagates. The regression model, in a relatively simple functional form, has demonstrated its capacity of reproducing high-order nonlinear effects that underpin the surface water and groundwater interactions. The finding has important implications for understanding and predicting shallow groundwater behavior and associated biogeochemical processes, and will contribute broadly to studies of groundwater-dependent ecology and biogeochemistry.

A statistical formulation of one-dimensional electron fluid turbulence

NASA Technical Reports Server (NTRS)

Fyfe, D.; Montgomery, D.

1977-01-01

A one-dimensional electron fluid model is investigated using the mathematical methods of modern fluid turbulence theory. Non-dissipative equilibrium canonical distributions are determined in a phase space whose co-ordinates are the real and imaginary parts of the Fourier coefficients for the field variables. Spectral densities are calculated, yielding a wavenumber electric field energy spectrum proportional to k to the negative second power for large wavenumbers. The equations of motion are numerically integrated and the resulting spectra are found to compare well with the theoretical predictions.

A DISCUSSION ON DIFFERENT APPROACHES FOR ASSESSING LIFETIME RISKS OF RADON-INDUCED LUNG CANCER.

PubMed

Chen, Jing; Murith, Christophe; Palacios, Martha; Wang, Chunhong; Liu, Senlin

2017-11-01

Lifetime risks of radon induced lung cancer were assessed based on epidemiological approaches for Canadian, Swiss and Chinese populations, using the most recent vital statistic data and radon distribution characteristics available for each country. In the risk calculation, the North America residential radon risk model was used for the Canadian population, the European residential radon risk model for the Swiss population, the Chinese residential radon risk model for the Chinese population, and the EPA/BEIR-VI radon risk model for all three populations. The results were compared with the risk calculated from the International Commission on Radiological Protection (ICRP)'s exposure-to-risk conversion coefficients. In view of the fact that the ICRP coefficients were recommended for radiation protection of all populations, it was concluded that, generally speaking, lifetime absolute risks calculated with ICRP-recommended coefficients agree reasonably well with the range of radon induced lung cancer risk predicted by risk models derived from epidemiological pooling analyses. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Solubility Measurements and Predictions of Gypsum, Anhydrite, and Calcite Over Wide Ranges of Temperature, Pressure, and Ionic Strength with Mixed Electrolytes

NASA Astrophysics Data System (ADS)

Dai, Zhaoyi; Kan, Amy T.; Shi, Wei; Zhang, Nan; Zhang, Fangfu; Yan, Fei; Bhandari, Narayan; Zhang, Zhang; Liu, Ya; Ruan, Gedeng; Tomson, Mason B.

2017-02-01

Today's oil and gas production from deep reservoirs permits exploitation of more oil and gas reserves but increases risks due to conditions of high temperature and high pressure. Predicting mineral solubility under such extreme conditions is critical for mitigating scaling risks, a common and costly problem. Solubility predictions use solubility products and activity coefficients, commonly from Pitzer theory virial coefficients. However, inaccurate activity coefficients and solubility data have limited accurate mineral solubility predictions and applications of the Pitzer theory. This study measured gypsum solubility under its stable phase conditions up to 1400 bar; it also confirmed the anhydrite solubility reported in the literature. Using a novel method, the virial coefficients for Ca2+ and {{SO}}4^{2 - } (i.e., β_{{{{CaSO}}4 }}^{(0)} ,β_{{{{CaSO}}4 }}^{(2)} ,C_{{{{CaSO}}4 }}^{φ }) were calculated over wide ranges of temperature and pressure (0-250 °C and 1-1400 bar). The determination of this set of virial coefficients widely extends the applicable temperature and pressure ranges of the Pitzer theory in Ca2+ and SO 4 2- systems. These coefficients can be applied to improve the prediction of calcite solubility in the presence of high concentrations of Ca2+ and SO 4 2- ions. These new virial coefficients can also be used to predict the solubilities of gypsum and anhydrite accurately. Moreover, based on the derived β_{{{{CaSO}}4 }}^{(2)} values in this study, the association constants of {{CaSO}}4^{( 0 )} at 1 bar and 25 °C can be estimated by K_{{assoc}} = - 2β_{{{{CaSO}}4 }}^{(2)}. These values match very well with those reported in the literature based on other methods.

Near-surface wind speed statistical distribution: comparison between ECMWF System 4 and ERA-Interim

NASA Astrophysics Data System (ADS)

Marcos, Raül; Gonzalez-Reviriego, Nube; Torralba, Verónica; Cortesi, Nicola; Young, Doo; Doblas-Reyes, Francisco J.

2017-04-01

In the framework of seasonal forecast verification, knowing whether the characteristics of the climatological wind speed distribution, simulated by the forecasting systems, are similar to the observed ones is essential to guide the subsequent process of bias adjustment. To bring some light about this topic, this work assesses the properties of the statistical distributions of 10m wind speed from both ERA-Interim reanalysis and seasonal forecasts of ECMWF system 4. The 10m wind speed distribution has been characterized in terms of the four main moments of the probability distribution (mean, standard deviation, skewness and kurtosis) together with the coefficient of variation and goodness of fit Shapiro-Wilks test, allowing the identification of regions with higher wind variability and non-Gaussian behaviour at monthly time-scales. Also, the comparison of the predicted and observed 10m wind speed distributions has been measured considering both inter-annual and intra-seasonal variability. Such a comparison is important in both climate research and climate services communities because it provides useful climate information for decision-making processes and wind industry applications.

Assessing deep and shallow learning methods for quantitative prediction of acute chemical toxicity.

PubMed

Liu, Ruifeng; Madore, Michael; Glover, Kyle P; Feasel, Michael G; Wallqvist, Anders

2018-05-02

Animal-based methods for assessing chemical toxicity are struggling to meet testing demands. In silico approaches, including machine-learning methods, are promising alternatives. Recently, deep neural networks (DNNs) were evaluated and reported to outperform other machine-learning methods for quantitative structure-activity relationship modeling of molecular properties. However, most of the reported performance evaluations relied on global performance metrics, such as the root mean squared error (RMSE) between the predicted and experimental values of all samples, without considering the impact of sample distribution across the activity spectrum. Here, we carried out an in-depth analysis of DNN performance for quantitative prediction of acute chemical toxicity using several datasets. We found that the overall performance of DNN models on datasets of up to 30,000 compounds was similar to that of random forest (RF) models, as measured by the RMSE and correlation coefficients between the predicted and experimental results. However, our detailed analyses demonstrated that global performance metrics are inappropriate for datasets with a highly uneven sample distribution, because they show a strong bias for the most populous compounds along the toxicity spectrum. For highly toxic compounds, DNN and RF models trained on all samples performed much worse than the global performance metrics indicated. Surprisingly, our variable nearest neighbor method, which utilizes only structurally similar compounds to make predictions, performed reasonably well, suggesting that information of close near neighbors in the training sets is a key determinant of acute toxicity predictions.

Prediction skill of rainstorm events over India in the TIGGE weather prediction models

NASA Astrophysics Data System (ADS)

Karuna Sagar, S.; Rajeevan, M.; Vijaya Bhaskara Rao, S.; Mitra, A. K.

2017-12-01

Extreme rainfall events pose a serious threat of leading to severe floods in many countries worldwide. Therefore, advance prediction of its occurrence and spatial distribution is very essential. In this paper, an analysis has been made to assess the skill of numerical weather prediction models in predicting rainstorms over India. Using gridded daily rainfall data set and objective criteria, 15 rainstorms were identified during the monsoon season (June to September). The analysis was made using three TIGGE (THe Observing System Research and Predictability Experiment (THORPEX) Interactive Grand Global Ensemble) models. The models considered are the European Centre for Medium-Range Weather Forecasts (ECMWF), National Centre for Environmental Prediction (NCEP) and the UK Met Office (UKMO). Verification of the TIGGE models for 43 observed rainstorm days from 15 rainstorm events has been made for the period 2007-2015. The comparison reveals that rainstorm events are predictable up to 5 days in advance, however with a bias in spatial distribution and intensity. The statistical parameters like mean error (ME) or Bias, root mean square error (RMSE) and correlation coefficient (CC) have been computed over the rainstorm region using the multi-model ensemble (MME) mean. The study reveals that the spread is large in ECMWF and UKMO followed by the NCEP model. Though the ensemble spread is quite small in NCEP, the ensemble member averages are not well predicted. The rank histograms suggest that the forecasts are under prediction. The modified Contiguous Rain Area (CRA) technique was used to verify the spatial as well as the quantitative skill of the TIGGE models. Overall, the contribution from the displacement and pattern errors to the total RMSE is found to be more in magnitude. The volume error increases from 24 hr forecast to 48 hr forecast in all the three models.

An Evaluation of Semiempirical Models for Partitioning Photosynthetically Active Radiation Into Diffuse and Direct Beam Components

NASA Astrophysics Data System (ADS)

Oliphant, Andrew J.; Stoy, Paul C.

2018-03-01

Photosynthesis is more efficient under diffuse than direct beam photosynthetically active radiation (PAR) per unit PAR, but diffuse PAR is infrequently measured at research sites. We examine four commonly used semiempirical models (Erbs et al., 1982, https://doi.org/10.1016/0038-092X(82)90302-4; Gu et al., 1999, https://doi.org/10.1029/1999JD901068; Roderick, 1999, https://doi.org/10.1016/S0168-1923(99)00028-3; Weiss & Norman, 1985, https://doi.org/10.1016/0168-1923(85)90020-6) that partition PAR into diffuse and direct beam components based on the negative relationship between atmospheric transparency and scattering of PAR. Radiation observations at 58 sites (140 site years) from the La Thuille FLUXNET data set were used for model validation and coefficient testing. All four models did a reasonable job of predicting the diffuse fraction of PAR (ϕ) at the 30 min timescale, with site median r2 values ranging between 0.85 and 0.87, model efficiency coefficients (MECs) between 0.62 and 0.69, and regression slopes within 10% of unity. Model residuals were not strongly correlated with astronomical or standard meteorological variables. We conclude that the Roderick (1999, https://doi.org/10.1016/S0168-1923(99)00028-3) and Gu et al. (1999, https://doi.org/10.1029/1999JD901068) models performed better overall than the two older models. Using the basic form of these models, the data set was used to find both individual site and universal model coefficients that optimized predictive accuracy. A new universal form of the model is presented in section 5 that increased site median MEC to 0.73. Site-specific model coefficients increased median MEC further to 0.78, indicating usefulness of local/regional training of coefficients to capture the local distributions of aerosols and cloud types.

Aqueous Binary Lanthanide(III) Nitrate Ln(NO3)3 Electrolytes Revisited: Extended Pitzer and Bromley Treatments

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chatterjee, Sayandev; Campbell, Emily L.; Neiner, Doinita

To date, only limited thermodynamic models describing activity coefficients of the aqueous solutions of lanthanide ions are available. This work expands the existing experimental osmotic coefficient data obtained by classical isopiestic technique for the aqueous binary trivalent lanthanide nitrate Ln(NO3)3 solutions using a combination of water activity and vapor pressure osmometry measurements. The combined osmotic coefficient database for each aqueous lanthanide nitrate at 25°C, consisting of literature available data as well as data obtained in this work, was used to test the validity of Pitzer and Bromley thermodynamic models for the accurate prediction of mean molal activity coefficients of themore » Ln(NO3)3 solutions in wide concentration ranges. The new and improved Pitzer and Bromley parameters were calculated. It was established that the Ln(NO3)3 activity coefficients in the solutions with ionic strength up to 12 mol kg-1 can be estimated by both Pitzer and single-parameter Bromley models, even though the latter provides for more accurate prediction, particularly in the lower ionic strength regime (up to 6 mol kg-1). On the other hand for the concentrated solutions, the extended three-parameter Bromley model can be employed to predict the Ln(NO3)3 activity coefficients with remarkable accuracy. The accuracy of the extended Bromley model in predicting the activity coefficients was greater than ~95% and ~90% for all solutions with the ionic strength up to 12 mol kg-1 and and 20 mol kg-1, respectively. This is the first time that the activity coefficients for concentrated lanthanide solutions have been predicted with such a remarkable accuracy.« less

The influence of a wall function on turbine blade heat transfer prediction

NASA Technical Reports Server (NTRS)

Whitaker, Kevin W.

1989-01-01

The second phase of a continuing investigation to improve the prediction of turbine blade heat transfer coefficients was completed. The present study specifically investigated how a numeric wall function in the turbulence model of a two-dimensional boundary layer code, STAN5, affected heat transfer prediction capabilities. Several sources of inaccuracy in the wall function were identified and then corrected or improved. Heat transfer coefficient predictions were then obtained using each one of the modifications to determine its effect. Results indicated that the modifications made to the wall function can significantly affect the prediction of heat transfer coefficients on turbine blades. The improvement in accuracy due the modifications is still inconclusive and is still being investigated.

Electric field control in DC cable test termination by nano silicone rubber composite

NASA Astrophysics Data System (ADS)

Song, Shu-Wei; Li, Zhongyuan; Zhao, Hong; Zhang, Peihong; Han, Baozhong; Fu, Mingli; Hou, Shuai

2017-07-01

The electric field distributions in high voltage direct current cable termination are investigated with silicone rubber nanocomposite being the electric stress control insulator. The nanocomposite is composed of silicone rubber, nanoscale carbon black and graphitic carbon. The experimental results show that the physical parameters of the nanocomposite, such as thermal activation energy and nonlinearity-relevant coefficient, can be manipulated by varying the proportion of the nanoscale fillers. The numerical simulation shows that safe electric field distribution calls for certain parametric region of the thermal activation energy and nonlinearity-relevant coefficient. Outside the safe parametric region, local maximum of electric field strength around the stress cone appears in the termination insulator, enhancing the breakdown of the cable termination. In the presence of the temperature gradient, thermal activation energy and nonlinearity-relevant coefficient work as complementary factors to produce a reasonable electric field distribution. The field maximum in the termination insulator show complicate variation in the transient processes. The stationary field distribution favors the increase of the nonlinearity-relevant coefficient; for the transient field distribution in the process of negative lighting impulse, however, an optimized value of the nonlinearity-relevant coefficient is necessary to equalize the electric field in the termination.

[Prediction of soil adsorption coefficients of organic compounds in a wide range of soil types by soil column liquid chromatography].

PubMed

Guo, Rongbo; Chen, Jiping; Zhang, Qing; Wu, Wenzhong; Liang, Xinmiao

2004-01-01

Using the methanol-water mixtures as mobile phases of soil column liquid chromatography (SCLC), prediction of soil adsorption coefficients (K(d)) by SCLC was validated in a wide range of soil types. The correlations between the retention factors measured by SCLC and soil adsorption coefficients measured by batch experiments were studied for five soils with different properties, i.e., Eurosoil 1#, 2#, 3#, 4# and 5#. The results show that good correlations existed between the retention factors and soil adsorption coefficients for Eurosoil 1#, 2#, 3# and 4#. For Eurosoil 5# which has a pH value of near 3, the correlation between retention factors and soil adsorption coefficients was unsatisfactory using methanol-water as mobile phase of SCLC. However, a good correlation was obtained using a methanol-buffer mixture with pH 3 as the mobile phase. This study proved that the SCLC is suitable for the prediction of soil adsorption coefficients.

Prediction of Partition Coefficients of Organic Compounds between SPME/PDMS and Aqueous Solution

PubMed Central

Chao, Keh-Ping; Lu, Yu-Ting; Yang, Hsiu-Wen

2014-01-01

Polydimethylsiloxane (PDMS) is commonly used as the coated polymer in the solid phase microextraction (SPME) technique. In this study, the partition coefficients of organic compounds between SPME/PDMS and the aqueous solution were compiled from the literature sources. The correlation analysis for partition coefficients was conducted to interpret the effect of their physicochemical properties and descriptors on the partitioning process. The PDMS-water partition coefficients were significantly correlated to the polarizability of organic compounds (r = 0.977, p < 0.05). An empirical model, consisting of the polarizability, the molecular connectivity index, and an indicator variable, was developed to appropriately predict the partition coefficients of 61 organic compounds for the training set. The predictive ability of the empirical model was demonstrated by using it on a test set of 26 chemicals not included in the training set. The empirical model, applying the straightforward calculated molecular descriptors, for estimating the PDMS-water partition coefficient will contribute to the practical applications of the SPME technique. PMID:24534804

Spatial glass transition temperature variations in polymer glass: application to a maltodextrin-water system.

PubMed

van Sleeuwen, Rutger M T; Zhang, Suying; Normand, Valéry

2012-03-12

A model was developed to predict spatial glass transition temperature (T(g)) distributions in glassy maltodextrin particles during transient moisture sorption. The simulation employed a numerical mass transfer model with a concentration dependent apparent diffusion coefficient (D(app)) measured using Dynamic Vapor Sorption. The mass average moisture content increase and the associated decrease in T(g) were successfully modeled over time. Large spatial T(g) variations were predicted in the particle, resulting in a temporary broadening of the T(g) region. Temperature modulated differential scanning calorimetry confirmed that the variation in T(g) in nonequilibrated samples was larger than in equilibrated samples. This experimental broadening was characterized by an almost doubling of the T(g) breadth compared to the start of the experiment. Upon reaching equilibrium, both the experimental and predicted T(g) breadth contracted back to their initial value.

A vortex-filament and core model for wings with edge vortex separation

NASA Technical Reports Server (NTRS)

Pao, J. L.; Lan, C. E.

1981-01-01

A method for predicting aerodynamic characteristics of slender wings with edge vortex separation was developed. Semiempirical but simple methods were used to determine the initial positions of the free sheet and vortex core. Comparison with available data indicates that: the present method is generally accurate in predicting the lift and induced drag coefficients but the predicted pitching moment is too positive; the spanwise lifting pressure distributions estimated by the one vortex core solution of the present method are significantly better than the results of Mehrotra's method relative to the pressure peak values for the flat delta; the two vortex core system applied to the double delta and strake wing produce overall aerodynamic characteristics which have good agreement with data except for the pitching moment; and the computer time for the present method is about two thirds of that of Mehrotra's method.

Modeling and predicting historical volatility in exchange rate markets

NASA Astrophysics Data System (ADS)

Lahmiri, Salim

2017-04-01

Volatility modeling and forecasting of currency exchange rate is an important task in several business risk management tasks; including treasury risk management, derivatives pricing, and portfolio risk evaluation. The purpose of this study is to present a simple and effective approach for predicting historical volatility of currency exchange rate. The approach is based on a limited set of technical indicators as inputs to the artificial neural networks (ANN). To show the effectiveness of the proposed approach, it was applied to forecast US/Canada and US/Euro exchange rates volatilities. The forecasting results show that our simple approach outperformed the conventional GARCH and EGARCH with different distribution assumptions, and also the hybrid GARCH and EGARCH with ANN in terms of mean absolute error, mean of squared errors, and Theil's inequality coefficient. Because of the simplicity and effectiveness of the approach, it is promising for US currency volatility prediction tasks.

A vortex-filament and core model for wings with edge vortex separation

NASA Technical Reports Server (NTRS)

Pao, J. L.; Lan, C. E.

1982-01-01

A vortex filament-vortex core method for predicting aerodynamic characteristics of slender wings with edge vortex separation was developed. Semi-empirical but simple methods were used to determine the initial positions of the free sheet and vortex core. Comparison with available data indicates that: (1) the present method is generally accurate in predicting the lift and induced drag coefficients but the predicted pitching moment is too positive; (2) the spanwise lifting pressure distributions estimated by the one vortex core solution of the present method are significantly better than the results of Mehrotra's method relative to the pressure peak values for the flat delta; (3) the two vortex core system applied to the double delta and strake wings produce overall aerodynamic characteristics which have good agreement with data except for the pitching moment; and (4) the computer time for the present method is about two thirds of that of Mehrotra's method.

Optimal descriptor as a translator of eclectic data into prediction of cytotoxicity for metal oxide nanoparticles under different conditions.

PubMed

Toropova, Alla P; Toropov, Andrey A; Rallo, Robert; Leszczynska, Danuta; Leszczynski, Jerzy

2015-02-01

The Monte Carlo technique has been used to build up quantitative structure-activity relationships (QSARs) for prediction of dark cytotoxicity and photo-induced cytotoxicity of metal oxide nanoparticles to bacteria Escherichia coli (minus logarithm of lethal concentration for 50% bacteria pLC50, LC50 in mol/L). The representation of nanoparticles include (i) in the case of the dark cytotoxicity a simplified molecular input-line entry system (SMILES), and (ii) in the case of photo-induced cytotoxicity a SMILES plus symbol '^'. The predictability of the approach is checked up with six random distributions of available data into the visible training and calibration sets, and invisible validation set. The statistical characteristics of these models are correlation coefficient 0.90-0.94 (training set) and 0.73-0.98 (validation set). Copyright © 2014 Elsevier Inc. All rights reserved.

Evaluation of Computational Fluid Dynamics and Coupled Fluid-Solid Modeling for a Direct Transfer Preswirl System.

PubMed

Javiya, Umesh; Chew, John; Hills, Nick; Dullenkopf, Klaus; Scanlon, Timothy

2013-05-01

The prediction of the preswirl cooling air delivery and disk metal temperature are important for the cooling system performance and the rotor disk thermal stresses and life assessment. In this paper, standalone 3D steady and unsteady computation fluid dynamics (CFD), and coupled FE-CFD calculations are presented for prediction of these temperatures. CFD results are compared with previous measurements from a direct transfer preswirl test rig. The predicted cooling air temperatures agree well with the measurement, but the nozzle discharge coefficients are under predicted. Results from the coupled FE-CFD analyses are compared directly with thermocouple temperature measurements and with heat transfer coefficients on the rotor disk previously obtained from a rotor disk heat conduction solution. Considering the modeling limitations, the coupled approach predicted the solid metal temperatures well. Heat transfer coefficients on the rotor disk from CFD show some effect of the temperature variations on the heat transfer coefficients. Reasonable agreement is obtained with values deduced from the previous heat conduction solution.

Calculated spanwise lift distributions, influence functions, and influence coefficients for unswept wings in subsonic flow

NASA Technical Reports Server (NTRS)

Diederich, Franklin W; Zlotnick, Martin

1955-01-01

Spanwise lift distributions have been calculated for nineteen unswept wings with various aspect ratios and taper ratios and with a variety of angle-of-attack or twist distributions, including flap and aileron deflections, by means of the Weissinger method with eight control points on the semispan. Also calculated were aerodynamic influence coefficients which pertain to a certain definite set of stations along the span, and several methods are presented for calculating aerodynamic influence functions and coefficients for stations other than those stipulated. The information presented in this report can be used in the analysis of untwisted wings or wings with known twist distributions, as well as in aeroelastic calculations involving initially unknown twist distributions.

New method for calculating the coupling coefficient in graded index optical fibers

NASA Astrophysics Data System (ADS)

Savović, Svetislav; Djordjevich, Alexandar

2018-05-01

A simple method is proposed for determining the mode coupling coefficient D in graded index multimode optical fibers. It only requires observation of the output modal power distribution P(m, z) for one fiber length z as the Gaussian launching modal power distribution changes, with the Gaussian input light distribution centered along the graded index optical fiber axis (θ0 = 0) without radial offset (r0 = 0). A similar method we previously proposed for calculating the coupling coefficient D in a step-index multimode optical fibers where the output angular power distributions P(θ, z) for one fiber length z with the Gaussian input light distribution launched centrally along the step-index optical fiber axis (θ0 = 0) is needed to be known.

High-Order Residual-Distribution Schemes for Discontinuous Problems on Irregular Triangular Grids

NASA Technical Reports Server (NTRS)

Mazaheri, Alireza; Nishikawa, Hiroaki

2016-01-01

In this paper, we develop second- and third-order non-oscillatory shock-capturing hyperbolic residual distribution schemes for irregular triangular grids, extending our second- and third-order schemes to discontinuous problems. We present extended first-order N- and Rusanov-scheme formulations for hyperbolic advection-diffusion system, and demonstrate that the hyperbolic diffusion term does not affect the solution of inviscid problems for vanishingly small viscous coefficient. We then propose second- and third-order blended hyperbolic residual-distribution schemes with the extended first-order Rusanov-scheme. We show that these proposed schemes are extremely accurate in predicting non-oscillatory solutions for discontinuous problems. We also propose a characteristics-based nonlinear wave sensor for accurately detecting shocks, compression, and expansion regions. Using this proposed sensor, we demonstrate that the developed hyperbolic blended schemes do not produce entropy-violating solutions (unphysical stocks). We then verify the design order of accuracy of these blended schemes on irregular triangular grids.

Algorithm of probabilistic assessment of fully-mechanized longwall downtime

NASA Astrophysics Data System (ADS)

Domrachev, A. N.; Rib, S. V.; Govorukhin, Yu M.; Krivopalov, V. G.

2017-09-01

The problem of increasing the load on a long fully-mechanized longwall has several aspects, one of which is the improvement of efficiency in using available stoping equipment due to the increase in coefficient of the machine operating time of a shearer and other mining machines that form an integral part of the longwall set of equipment. The task of predicting the reliability indicators of stoping equipment is solved by the statistical evaluation of parameters of downtime exponential distribution and failure recovery. It is more difficult to solve the problems of downtime accounting in case of accidents in the face workings and, despite the statistical data on accidents in mine workings, no solution has been found to date. The authors have proposed a variant of probability assessment of workings caving using Poisson distribution and the duration of their restoration using normal distribution. The above results confirm the possibility of implementing the approach proposed by the authors.

Incorporation of lysosomal sequestration in the mechanistic model for prediction of tissue distribution of basic drugs.

PubMed

Assmus, Frauke; Houston, J Brian; Galetin, Aleksandra

2017-11-15

The prediction of tissue-to-plasma water partition coefficients (Kpu) from in vitro and in silico data using the tissue-composition based model (Rodgers & Rowland, J Pharm Sci. 2005, 94(6):1237-48.) is well established. However, distribution of basic drugs, in particular into lysosome-rich lung tissue, tends to be under-predicted by this approach. The aim of this study was to develop an extended mechanistic model for the prediction of Kpu which accounts for lysosomal sequestration and the contribution of different cell types in the tissue of interest. The extended model is based on compound-specific physicochemical properties and tissue composition data to describe drug ionization, distribution into tissue water and drug binding to neutral lipids, neutral phospholipids and acidic phospholipids in tissues, including lysosomes. Physiological data on the types of cells contributing to lung, kidney and liver, their lysosomal content and lysosomal pH were collated from the literature. The predictive power of the extended mechanistic model was evaluated using a dataset of 28 basic drugs (pK a ≥7.8, 17 β-blockers, 11 structurally diverse drugs) for which experimentally determined Kpu data in rat tissue have been reported. Accounting for the lysosomal sequestration in the extended mechanistic model improved the accuracy of Kpu predictions in lung compared to the original Rodgers model (56% drugs within 2-fold or 88% within 3-fold of observed values). Reduction in the extent of Kpu under-prediction was also evident in liver and kidney. However, consideration of lysosomal sequestration increased the occurrence of over-predictions, yielding overall comparable model performances for kidney and liver, with 68% and 54% of Kpu values within 2-fold error, respectively. High lysosomal concentration ratios relative to cytosol (>1000-fold) were predicted for the drugs investigated; the extent differed depending on the lysosomal pH and concentration of acidic phospholipids among cell types. Despite this extensive lysosomal sequestration in the individual cells types, the maximal change in the overall predicted tissue Kpu was <3-fold for lysosome-rich tissues investigated here. Accounting for the variability in cellular physiological model input parameters, in particular lysosomal pH and fraction of the cellular volume occupied by the lysosomes, only partially explained discrepancies between observed and predicted Kpu data in the lung. Improved understanding of the system properties, e.g., cell/organelle composition is required to support further development of mechanistic equations for the prediction of drug tissue distribution. Application of this revised mechanistic model is recommended for prediction of Kpu in lysosome-rich tissue to facilitate the advancement of physiologically-based prediction of volume of distribution and drug exposure in the tissues. Copyright © 2017 Elsevier B.V. All rights reserved.

Volatilization of benzene and eight alkyl-substituted benzene compounds from water

USGS Publications Warehouse

Rathbun, R.E.; Tai, D.Y.

1988-01-01

Predicting the fate of organic compounds in streams and rivers often requires knowledge of the volatilization characteristics of the compounds. The reference-substance concept, involving laboratory-determined ratios of the liquid-film coefficients for volatilization of the organic compounds to the liquid-film coefficient for oxygen absorption, is used to predict liquid-film coefficients for streams and rivers. In the absence of experimental data, two procedures have been used for estimating these liquid-film coefficient ratios. These procedures, based on the molecular-diffusion coefficient and on the molecular weight, have been widely used but never extensively evaluated. Liquid-film coefficients for the volatilization of benzene and eight alkyl-substituted benzene compounds (toluene through n-octylbenzene) from water were measured in a constant-temperature, stirred water bath. Liquid-film coefficients for oxygen absorption were measured simultaneously. A range of water mixing conditions was used with a water temperature of 298.2 K. The ratios of the liquid-film coefficients for volatilization to the liquid-film coefficient for oxygen absorption for all of the organic compounds were independent of mixing conditions in the water. Experimental ratios ranged from 0.606 for benzene to 0.357 for n-octylbenzene. The molecular-diffusion-coefficient procedure accurately predicted the ratios for ethylbenzene through n-pentylbenzene with a power dependence of 0.566 on the molecular-diffusion coefficient, in agreement with published values. Predicted ratios for benzene and toluene were slightly larger than the experimental ratios. These differences were attributed to possible interactions between the molecules of these compounds and the water molecules and to benzene-benzene interactions that form dimers. Because these interactions also are likely to occur in natural waters, it was concluded that the experimental ratios are more correct than the predicted ratios for application purposes in the reference-substance concept. Predicted ratios for n-hexylbenzene, n-heptylbenzene, and n-octylbenzene were larger than the experimental ratios. These differences were attributed to a sorption-desorption process between these compounds and the surfaces of the constant-temperature water bath. Other experimental problems associated with preparing water solutions of these slightly soluble compounds also may have contributed to the differences. Because these processes are not part of the true volatilization process, it was concluded that the predicted ratios for these three compounds are probably more correct than the experimental ratios for application purposes in the reference-substance concept. Any model of the fate of these compounds in streams and rivers would have to include terms accounting for sorption processes, however. The molecular-weight procedure accurately predicted the ratios for ethylbenzene through n-pentylbenzene, but only if the power dependence on the molecular weight was decreased from the commonly used -0.500 to -0.427. Deviations for the low- and high-molecular-weight compounds were similar to those observed for the molecular-diffusion-coefficient procedure.

Fuselage and nozzle pressure distributions on a 1/12-scale F-15 propulsion model at transonic speeds. [conducted in langley 16 foot transonic tunnel

NASA Technical Reports Server (NTRS)

Pendergraft, O. C., Jr.

1979-01-01

Static pressure coefficient distributions on the forebody, afterbody, and nozzles of a 1/12 scale F-15 propulsion model were determined. The effects of nozzle power setting and horizontal tail deflection angle on the pressure coefficient distributions were investigated.

AN EMPIRICAL INVESTIGATION OF THE EFFECTS OF NONNORMALITY UPON THE SAMPLING DISTRIBUTION OF THE PROJECT MOMENT CORRELATION COEFFICIENT.

ERIC Educational Resources Information Center

HJELM, HOWARD; NORRIS, RAYMOND C.

THE STUDY EMPIRICALLY DETERMINED THE EFFECTS OF NONNORMALITY UPON SOME SAMPLING DISTRIBUTIONS OF THE PRODUCT MOMENT CORRELATION COEFFICIENT (PMCC). SAMPLING DISTRIBUTIONS OF THE PMCC WERE OBTAINED BY DRAWING NUMEROUS SAMPLES FROM CONTROL AND EXPERIMENTAL POPULATIONS HAVING VARIOUS DEGREES OF NONNORMALITY AND BY CALCULATING CORRELATION COEFFICIENTS…

Empirical Sampling Distributions of Equating Coefficients for Graded and Nominal Response Instruments.

ERIC Educational Resources Information Center

Baker, Frank B.

1997-01-01

Examined the sampling distributions of equating coefficients produced by the characteristic curve method for tests using graded and nominal response scoring using simulated data. For both models and across all three equating situations, the sampling distributions were generally bell-shaped and peaked, and occasionally had a small degree of…

Measurements of Pressure Distributions and Force Coefficients in a Squeeze Film Damper. Part 1: Fully Open Ended Configuration

NASA Technical Reports Server (NTRS)

Jung, S. Y.; Sanandres, Luis A.; Vance, J. M.

1991-01-01

Measurements of pressure distributions and force coefficients were carried out in two types of squeeze film dampers, executing a circular centered orbit, an open-ended configuration, and a partially sealed one, in order to investigate the effect of fluid inertia and cavitation on pressure distributions and force coefficients. Dynamic pressure measurements were carried out for two orbit radii, epsilon 0.5 and 0.8. It was found that the partially sealed configuration was less influenced by fluid inertia than the open ended configuration.

Application of Visible and Near-Infrared Hyperspectral Imaging to Determine Soluble Protein Content in Oilseed Rape Leaves

PubMed Central

Zhang, Chu; Liu, Fei; Kong, Wenwen; He, Yong

2015-01-01

Visible and near-infrared hyperspectral imaging covering spectral range of 380–1030 nm as a rapid and non-destructive method was applied to estimate the soluble protein content of oilseed rape leaves. Average spectrum (500–900 nm) of the region of interest (ROI) of each sample was extracted, and four samples out of 128 samples were defined as outliers by Monte Carlo-partial least squares (MCPLS). Partial least squares (PLS) model using full spectra obtained dependable performance with the correlation coefficient (rp) of 0.9441, root mean square error of prediction (RMSEP) of 0.1658 mg/g and residual prediction deviation (RPD) of 2.98. The weighted regression coefficient (Bw), successive projections algorithm (SPA) and genetic algorithm-partial least squares (GAPLS) selected 18, 15, and 16 sensitive wavelengths, respectively. SPA-PLS model obtained the best performance with rp of 0.9554, RMSEP of 0.1538 mg/g and RPD of 3.25. Distribution of protein content within the rape leaves were visualized and mapped on the basis of the SPA-PLS model. The overall results indicated that hyperspectral imaging could be used to determine and visualize the soluble protein content of rape leaves. PMID:26184198

[From clinical judgment to linear regression model.

PubMed

Palacios-Cruz, Lino; Pérez, Marcela; Rivas-Ruiz, Rodolfo; Talavera, Juan O

2013-01-01

When we think about mathematical models, such as linear regression model, we think that these terms are only used by those engaged in research, a notion that is far from the truth. Legendre described the first mathematical model in 1805, and Galton introduced the formal term in 1886. Linear regression is one of the most commonly used regression models in clinical practice. It is useful to predict or show the relationship between two or more variables as long as the dependent variable is quantitative and has normal distribution. Stated in another way, the regression is used to predict a measure based on the knowledge of at least one other variable. Linear regression has as it's first objective to determine the slope or inclination of the regression line: Y = a + bx, where "a" is the intercept or regression constant and it is equivalent to "Y" value when "X" equals 0 and "b" (also called slope) indicates the increase or decrease that occurs when the variable "x" increases or decreases in one unit. In the regression line, "b" is called regression coefficient. The coefficient of determination (R 2 ) indicates the importance of independent variables in the outcome.

FUN3D Analyses in Support of the First Aeroelastic Prediction Workshop

NASA Technical Reports Server (NTRS)

Chwalowski, Pawel; Heeg, Jennifer; Wieseman, Carol D.; Florance, Jennifer P.

2013-01-01

This paper presents the computational aeroelastic results generated in support of the first Aeroelastic Prediction Workshop for the Benchmark Supercritical Wing (BSCW) and the HIgh REynolds Number AeroStructural Dynamics (HIRENASD) configurations and compares them to the experimental data. The computational results are obtained using FUN3D, an unstructured grid Reynolds-averaged Navier-Stokes solver developed at NASA Langley Research Center. The analysis results for both configurations include aerodynamic coefficients and surface pressures obtained for steady-state or static aeroelastic equilibrium (BSCW and HIRENASD, respectively) and for unsteady flow due to a pitching wing (BSCW) or modally-excited wing (HIRENASD). Frequency response functions of the pressure coefficients with respect to displacement are computed and compared with the experimental data. For the BSCW, the shock location is computed aft of the experimentally-located shock position. The pressure distribution upstream of this shock is in excellent agreement with the experimental data, but the pressure downstream of the shock in the separated flow region does not match as well. For HIRENASD, very good agreement between the numerical results and the experimental data is observed at the mid-span wing locations.

Investigation of the Laminar Aerodynamic Heat-transfer Characteristics of a Hemisphere-cylinder in the Langley 11-inch Hypersonic Tunnel at a Mach Number of 6.8

NASA Technical Reports Server (NTRS)

Crawford, Davis H; Mccauley, William D

1957-01-01

A program to investigate the aerodynamic heat transfer of a nonisothermal hemisphere-cylinder has been conducted in the Langley 11-inch hypersonic tunnel at a Mach number of 6.8 and a Reynolds number from approximately 0.14 x 10(6) to 1.06 x 10(6) based on diameter and free-stream conditions. The experimental heat-transfer coefficients were slightly less over the whole body than those predicted by the theory of Stine and Wanlass (NACA technical note 3344) for an isothermal surface. For stations within 45 degrees of the stagnation point the heat-transfer coefficients could be correlated by a single relation between local Stanton number and local Reynolds number. Pitot pressure profiles taken at a Mach number of 6.8 on a hemisphere-cylinder have verified that the local Mach number or velocity outside the boundary layer required in the theories may be computed from the surface pressures by using isentropic flow relations and conditions immediately behind a normal shock. The experimental pressure distribution at Mach number of 6.8 is closely predicted by the modified Newtonian theory.

Conformational Spread in the Flagellar Motor Switch: A Model Study

PubMed Central

Maini, Philip K.; Berry, Richard M.; Bai, Fan

2012-01-01

The reliable response to weak biological signals requires that they be amplified with fidelity. In E. coli, the flagellar motors that control swimming can switch direction in response to very small changes in the concentration of the signaling protein CheY-P, but how this works is not well understood. A recently proposed allosteric model based on cooperative conformational spread in a ring of identical protomers seems promising as it is able to qualitatively reproduce switching, locked state behavior and Hill coefficient values measured for the rotary motor. In this paper we undertook a comprehensive simulation study to analyze the behavior of this model in detail and made predictions on three experimentally observable quantities: switch time distribution, locked state interval distribution, Hill coefficient of the switch response. We parameterized the model using experimental measurements, finding excellent agreement with published data on motor behavior. Analysis of the simulated switching dynamics revealed a mechanism for chemotactic ultrasensitivity, in which cooperativity is indispensable for realizing both coherent switching and effective amplification. These results showed how cells can combine elements of analog and digital control to produce switches that are simultaneously sensitive and reliable. PMID:22654654

Random matrix theory analysis of cross-correlations in the US stock market: Evidence from Pearson’s correlation coefficient and detrended cross-correlation coefficient

NASA Astrophysics Data System (ADS)

Wang, Gang-Jin; Xie, Chi; Chen, Shou; Yang, Jiao-Jiao; Yang, Ming-Yan

2013-09-01

In this study, we first build two empirical cross-correlation matrices in the US stock market by two different methods, namely the Pearson’s correlation coefficient and the detrended cross-correlation coefficient (DCCA coefficient). Then, combining the two matrices with the method of random matrix theory (RMT), we mainly investigate the statistical properties of cross-correlations in the US stock market. We choose the daily closing prices of 462 constituent stocks of S&P 500 index as the research objects and select the sample data from January 3, 2005 to August 31, 2012. In the empirical analysis, we examine the statistical properties of cross-correlation coefficients, the distribution of eigenvalues, the distribution of eigenvector components, and the inverse participation ratio. From the two methods, we find some new results of the cross-correlations in the US stock market in our study, which are different from the conclusions reached by previous studies. The empirical cross-correlation matrices constructed by the DCCA coefficient show several interesting properties at different time scales in the US stock market, which are useful to the risk management and optimal portfolio selection, especially to the diversity of the asset portfolio. It will be an interesting and meaningful work to find the theoretical eigenvalue distribution of a completely random matrix R for the DCCA coefficient because it does not obey the Marčenko-Pastur distribution.

Predicting bioconcentration of chemicals into vegetation from soil or air using the molecular connectivity index

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dowdy, D.L.; McKone, T.E.; Hsieh, D.P.H.

1995-12-31

Bioconcentration factors (BCFs) are the ratio of chemical concentration found in an exposed organism (in this case a plant) to the concentration in an air or soil exposure medium. The authors examine here the use of molecular connectivity indices (MCIs) as quantitative structure-activity relationships (QSARS) for predicting BCFs for organic chemicals between plants and air or soil. The authors compare the reliability of the octanol-air partition coefficient (K{sub oa}) to the MC based prediction method for predicting plant/air partition coefficients. The authors also compare the reliability of the octanol/water partition coefficient (K{sub ow}) to the MC based prediction method formore » predicting plant/soil partition coefficients. The results here indicate that, relative to the use of K{sub ow} or K{sub oa} as predictors of BCFs the MC can substantially increase the reliability with which BCFs can be estimated. The authors find that the MC provides a relatively precise and accurate method for predicting the potential biotransfer of a chemical from environmental media into plants. In addition, the MC is much faster and more cost effective than direct measurements.« less

Impact of different satellite soil moisture products on the predictions of a continuous distributed hydrological model

NASA Astrophysics Data System (ADS)

Laiolo, P.; Gabellani, S.; Campo, L.; Silvestro, F.; Delogu, F.; Rudari, R.; Pulvirenti, L.; Boni, G.; Fascetti, F.; Pierdicca, N.; Crapolicchio, R.; Hasenauer, S.; Puca, S.

2016-06-01

The reliable estimation of hydrological variables in space and time is of fundamental importance in operational hydrology to improve the flood predictions and hydrological cycle description. Nowadays remotely sensed data can offer a chance to improve hydrological models especially in environments with scarce ground based data. The aim of this work is to update the state variables of a physically based, distributed and continuous hydrological model using four different satellite-derived data (three soil moisture products and a land surface temperature measurement) and one soil moisture analysis to evaluate, even with a non optimal technique, the impact on the hydrological cycle. The experiments were carried out for a small catchment, in the northern part of Italy, for the period July 2012-June 2013. The products were pre-processed according to their own characteristics and then they were assimilated into the model using a simple nudging technique. The benefits on the model predictions of discharge were tested against observations. The analysis showed a general improvement of the model discharge predictions, even with a simple assimilation technique, for all the assimilation experiments; the Nash-Sutcliffe model efficiency coefficient was increased from 0.6 (relative to the model without assimilation) to 0.7, moreover, errors on discharge were reduced up to the 10%. An added value to the model was found in the rainfall season (autumn): all the assimilation experiments reduced the errors up to the 20%. This demonstrated that discharge prediction of a distributed hydrological model, which works at fine scale resolution in a small basin, can be improved with the assimilation of coarse-scale satellite-derived data.

Feedback brake distribution control for minimum pitch

NASA Astrophysics Data System (ADS)

Tavernini, Davide; Velenis, Efstathios; Longo, Stefano

2017-06-01

The distribution of brake forces between front and rear axles of a vehicle is typically specified such that the same level of brake force coefficient is imposed at both front and rear wheels. This condition is known as 'ideal' distribution and it is required to deliver the maximum vehicle deceleration and minimum braking distance. For subcritical braking conditions, the deceleration demand may be delivered by different distributions between front and rear braking forces. In this research we show how to obtain the optimal distribution which minimises the pitch angle of a vehicle and hence enhances driver subjective feel during braking. A vehicle model including suspension geometry features is adopted. The problem of the minimum pitch brake distribution for a varying deceleration level demand is solved by means of a model predictive control (MPC) technique. To address the problem of the undesirable pitch rebound caused by a full-stop of the vehicle, a second controller is designed and implemented independently from the braking distribution in use. An extended Kalman filter is designed for state estimation and implemented in a high fidelity environment together with the MPC strategy. The proposed solution is compared with the reference 'ideal' distribution as well as another previous feed-forward solution.

Structure-activity relationships to estimate the effective Henry's law coefficients of organics of atmospheric interest

NASA Astrophysics Data System (ADS)

Raventos-Duran, Teresa; Valorso, Richard; Aumont, Bernard; Camredon, Marie

2010-05-01

The oxidation of volatile organic compounds emitted in the atmosphere involves complex reaction mechanisms which leads to the formation of oxygenated organic intermediates, usually denoted as secondary organics. The fate of these secondary organics remains poorly quantified due to a lack of information about their speciation, distribution and evolution in the gas and condensed phases. A significant fraction of secondary organics may dissolve into the tropospheric aqueous phase owing to the presence of polar moieties generated during the oxidation processes. The partitioning of organics between the gas and the aqueous atmospheric phases is usually described in the basis of Henry's law. Atmospheric models require a knowledge of the Henry's law coefficient (H) for every water soluble organic species described in the chemical mechanism. Methods that can predict reliable H values for the vast number of organic compounds are therefore required. We have compiled a data set of experimental Henry's law constants for compounds bearing functional groups of atmospheric relevance. This data set was then used to develop GROMHE, a structure activity relationship to predict H values based on a group contribution approach. We assessed its performance with two other available estimation methods. The results show that for all these methods the reliability of the estimates decreases with increasing solubility. We discuss differences between methods and found that GROMHE had greater prediction ability.

Unified model of brain tissue microstructure dynamically binds diffusion and osmosis with extracellular space geometry

NASA Astrophysics Data System (ADS)

Yousefnezhad, Mohsen; Fotouhi, Morteza; Vejdani, Kaveh; Kamali-Zare, Padideh

2016-09-01

We present a universal model of brain tissue microstructure that dynamically links osmosis and diffusion with geometrical parameters of brain extracellular space (ECS). Our model robustly describes and predicts the nonlinear time dependency of tortuosity (λ =√{D /D* } ) changes with very high precision in various media with uniform and nonuniform osmolarity distribution, as demonstrated by previously published experimental data (D = free diffusion coefficient, D* = effective diffusion coefficient). To construct this model, we first developed a multiscale technique for computationally effective modeling of osmolarity in the brain tissue. Osmolarity differences across cell membranes lead to changes in the ECS dynamics. The evolution of the underlying dynamics is then captured by a level set method. Subsequently, using a homogenization technique, we derived a coarse-grained model with parameters that are explicitly related to the geometry of cells and their associated ECS. Our modeling results in very accurate analytical approximation of tortuosity based on time, space, osmolarity differences across cell membranes, and water permeability of cell membranes. Our model provides a unique platform for studying ECS dynamics not only in physiologic conditions such as sleep-wake cycles and aging but also in pathologic conditions such as stroke, seizure, and neoplasia, as well as in predictive pharmacokinetic modeling such as predicting medication biodistribution and efficacy and novel biomolecule development and testing.

QSAR models for thiophene and imidazopyridine derivatives inhibitors of the Polo-Like Kinase 1.

PubMed

Comelli, Nieves C; Duchowicz, Pablo R; Castro, Eduardo A

2014-10-01

The inhibitory activity of 103 thiophene and 33 imidazopyridine derivatives against Polo-Like Kinase 1 (PLK1) expressed as pIC50 (-logIC50) was predicted by QSAR modeling. Multivariate linear regression (MLR) was employed to model the relationship between 0D and 3D molecular descriptors and biological activities of molecules using the replacement method (MR) as variable selection tool. The 136 compounds were separated into several training and test sets. Two splitting approaches, distribution of biological data and structural diversity, and the statistical experimental design procedure D-optimal distance were applied to the dataset. The significance of the training set models was confirmed by statistically higher values of the internal leave one out cross-validated coefficient of determination (Q2) and external predictive coefficient of determination for the test set (Rtest2). The model developed from a training set, obtained with the D-optimal distance protocol and using 3D descriptor space along with activity values, separated chemical features that allowed to distinguish high and low pIC50 values reasonably well. Then, we verified that such model was sufficient to reliably and accurately predict the activity of external diverse structures. The model robustness was properly characterized by means of standard procedures and their applicability domain (AD) was analyzed by leverage method. Copyright © 2014 Elsevier B.V. All rights reserved.

Optimization and Modeling of Extreme Freshwater Discharge from Japanese First-Class River Basins to Coastal Oceans

NASA Astrophysics Data System (ADS)

Kuroki, R.; Yamashiki, Y. A.; Varlamov, S.; Miyazawa, Y.; Gupta, H. V.; Racault, M.; Troselj, J.

2017-12-01

We estimated the effects of extreme fluvial outflow events from river mouths on the salinity distribution in the Japanese coastal zones. Targeted extreme event was a typhoon from 06/09/2015 to 12/09/2015, and we generated a set of hourly simulated river outflow data of all Japanese first-class rivers from these basins to the Pacific Ocean and the Sea of Japan during the period by using our model "Cell Distributed Runoff Model Version 3.1.1 (CDRMV3.1.1)". The model simulated fresh water discharges for the case of the typhoon passage over Japan. We used these data with a coupled hydrological-oceanographic model JCOPE-T, developed by Japan Agency for Marine-earth Science and Technology (JAMSTEC), for estimation of the circulation and salinity distribution in Japanese coastal zones. By using the model, the coastal oceanic circulation was reproduced adequately, which was verified by satellite remote sensing. In addition to this, we have successfully optimized 5 parameters, soil roughness coefficient, river roughness coefficient, effective porosity, saturated hydraulic conductivity, and effective rainfall by using Shuffled Complex Evolution method developed by University of Arizona (SCE-UA method), that is one of the optimization method for hydrological model. Increasing accuracy of peak discharge prediction of extreme typhoon events on river mouths is essential for continental-oceanic mutual interaction.

High Pressure/Temperature Metal Silicate Partitioning of Tungsten

NASA Technical Reports Server (NTRS)

Shofner, G. A.; Danielson, L.; Righter, K.; Campbell, A. J.

2010-01-01

The behavior of chemical elements during metal/silicate segregation and their resulting distribution in Earth's mantle and core provide insight into core formation processes. Experimental determination of partition coefficients allows calculations of element distributions that can be compared to accepted values of element abundances in the silicate (mantle) and metallic (core) portions of the Earth. Tungsten (W) is a moderately siderophile element and thus preferentially partitions into metal versus silicate under many planetary conditions. The partitioning behavior has been shown to vary with temperature, silicate composition, oxygen fugacity, and pressure. Most of the previous work on W partitioning has been conducted at 1-bar conditions or at relatively low pressures, i.e. <10 GPa, and in two cases at or near 20 GPa. According to those data, the stronger influences on the distribution coefficient of W are temperature, composition, and oxygen fugacity with a relatively slight influence in pressure. Predictions based on extrapolation of existing data and parameterizations suggest an increased pressured dependence on metal/ silicate partitioning of W at higher pressures 5. However, the dependence on pressure is not as well constrained as T, fO2, and silicate composition. This poses a problem because proposed equilibration pressures for core formation range from 27 to 50 GPa, falling well outside the experimental range, therefore requiring exptrapolation of a parametereized model. Higher pressure data are needed to improve our understanding of W partitioning at these more extreme conditions.

Analytical transport network theory to guide the design of 3-D microstructural networks in energy materials: Part 1. Flow without reactions

NASA Astrophysics Data System (ADS)

Cocco, Alex P.; Nakajo, Arata; Chiu, Wilson K. S.

2017-12-01

We present a fully analytical, heuristic model - the "Analytical Transport Network Model" - for steady-state, diffusive, potential flow through a 3-D network. Employing a combination of graph theory, linear algebra, and geometry, the model explicitly relates a microstructural network's topology and the morphology of its channels to an effective material transport coefficient (a general term meant to encompass, e.g., conductivity or diffusion coefficient). The model's transport coefficient predictions agree well with those from electrochemical fin (ECF) theory and finite element analysis (FEA), but are computed 0.5-1.5 and 5-6 orders of magnitude faster, respectively. In addition, the theory explicitly relates a number of morphological and topological parameters directly to the transport coefficient, whereby the distributions that characterize the structure are readily available for further analysis. Furthermore, ATN's explicit development provides insight into the nature of the tortuosity factor and offers the potential to apply theory from network science and to consider the optimization of a network's effective resistance in a mathematically rigorous manner. The ATN model's speed and relative ease-of-use offer the potential to aid in accelerating the design (with respect to transport), and thus reducing the cost, of energy materials.

Revealing how network structure affects accuracy of link prediction

NASA Astrophysics Data System (ADS)

Yang, Jin-Xuan; Zhang, Xiao-Dong

2017-08-01

Link prediction plays an important role in network reconstruction and network evolution. The network structure affects the accuracy of link prediction, which is an interesting problem. In this paper we use common neighbors and the Gini coefficient to reveal the relation between them, which can provide a good reference for the choice of a suitable link prediction algorithm according to the network structure. Moreover, the statistical analysis reveals correlation between the common neighbors index, Gini coefficient index and other indices to describe the network structure, such as Laplacian eigenvalues, clustering coefficient, degree heterogeneity, and assortativity of network. Furthermore, a new method to predict missing links is proposed. The experimental results show that the proposed algorithm yields better prediction accuracy and robustness to the network structure than existing currently used methods for a variety of real-world networks.

Investigating Whistler Mode Wave Diffusion Coefficients at Mars

NASA Astrophysics Data System (ADS)

Shane, A. D.; Liemohn, M. W.; Xu, S.; Florie, C.

2017-12-01

Observations of electron pitch angle distributions have suggested collisions are not the only pitch angle scattering process occurring in the Martian ionosphere. This unknown scattering process is causing high energy electrons (>100 eV) to become isotropized. Whistler mode waves are one pitch angle scattering mechanism known to preferentially scatter high energy electrons in certain plasma regimes. The distribution of whistler mode wave diffusion coefficients are dependent on the background magnetic field strength and thermal electron density, as well as the frequency and wave normal angle of the wave. We have solved for the whistler mode wave diffusion coefficients using the quasi-linear diffusion equations and have integrated them into a superthermal electron transport (STET) model. Preliminary runs have produced results that qualitatively match the observed electron pitch angle distributions at Mars. We performed parametric sweeps over magnetic field, thermal electron density, wave frequency, and wave normal angle to understand the relationship between the plasma parameters and the diffusion coefficient distributions, but also to investigate what regimes whistler mode waves scatter only high energy electrons. Increasing the magnetic field strength and lowering the thermal electron density shifts the distribution of diffusion coefficients toward higher energies and lower pitch angles. We have created an algorithm to identify Mars Atmosphere Volatile and EvolutioN (MAVEN) observations of high energy isotropic pitch angle distributions in the Martian ionosphere. We are able to map these distributions at Mars, and compare the conditions under which these are observed at Mars with the results of our parametric sweeps. Lastly, we will also look at each term in the kinetic diffusion equation to determine if the energy and mixed diffusion coefficients are important enough to incorporate into STET as well.

Wind-Tunnel Investigation of a Balloon as a Towed Decelerator at Mach Numbers from 1.47 to 2.50

NASA Technical Reports Server (NTRS)

McShera, John T.; Keyes, J. Wayne

1961-01-01

A wind-tunnel investigation has been conducted to study the characteristics of a towed spherical balloon as a drag device at Mach numbers from 1.47 to 2.50, Reynolds numbers from 0.36 x 10(exp 6) to 1.0 x 10(exp 6) , and angles of attack from -15 to 15 deg. Towed spherical balloons were found to be stable at supersonic speeds. The drag coefficient of the balloon is reduced by the presence of a tow cable and a further reduction occurs with the addition of a payload. The balloon inflation pressure required to maintain an almost spherical shape is about equal to the free-stream dynamic pressure. Measured pressure and temperature distribution around the balloon alone were in fair agreement with predicted values. There was a pronounced decrease in the pressure coefficients on the balloon when attached to a tow cable behind a payload.

Modeling Analysis for NASA GRC Vacuum Facility 5 Upgrade

NASA Technical Reports Server (NTRS)

Yim, J. T.; Herman, D. A.; Burt, J. M.

2013-01-01

A model of the VF5 test facility at NASA Glenn Research Center was developed using the direct simulation Monte Carlo Hypersonic Aerothermodynamics Particle (HAP) code. The model results were compared to several cold flow and thruster hot fire cases. The main uncertainty in the model is the determination of the effective sticking coefficient -- which sets the pumping effectiveness of the cryopanels and oil diffusion pumps including baffle transmission. An effective sticking coefficient of 0.25 was found to provide generally good agreement with the experimental chamber pressure data. The model, which assumes a cold diffuse inflow, also fared satisfactorily in predicting the pressure distribution during thruster operation. The model was used to assess other chamber configurations to improve the local effective pumping speed near the thruster. A new configuration of the existing cryopumps is found to show more than 2x improvement over the current baseline configuration.

A hybrid PSO-SVM-based method for predicting the friction coefficient between aircraft tire and coating

NASA Astrophysics Data System (ADS)

Zhan, Liwei; Li, Chengwei

2017-02-01

A hybrid PSO-SVM-based model is proposed to predict the friction coefficient between aircraft tire and coating. The presented hybrid model combines a support vector machine (SVM) with particle swarm optimization (PSO) technique. SVM has been adopted to solve regression problems successfully. Its regression accuracy is greatly related to optimizing parameters such as the regularization constant C , the parameter gamma γ corresponding to RBF kernel and the epsilon parameter \\varepsilon in the SVM training procedure. However, the friction coefficient which is predicted based on SVM has yet to be explored between aircraft tire and coating. The experiment reveals that drop height and tire rotational speed are the factors affecting friction coefficient. Bearing in mind, the friction coefficient can been predicted using the hybrid PSO-SVM-based model by the measured friction coefficient between aircraft tire and coating. To compare regression accuracy, a grid search (GS) method and a genetic algorithm (GA) are used to optimize the relevant parameters (C , γ and \\varepsilon ), respectively. The regression accuracy could be reflected by the coefficient of determination ({{R}2} ). The result shows that the hybrid PSO-RBF-SVM-based model has better accuracy compared with the GS-RBF-SVM- and GA-RBF-SVM-based models. The agreement of this model (PSO-RBF-SVM) with experiment data confirms its good performance.

Viscothermal Coupling Effects on Sound Attenuation in Concentrated Colloidal Dispersions.

NASA Astrophysics Data System (ADS)

Han, Wei

1995-11-01

This thesis describes a Unified Coupled Phase Continuum (UCPC) model to analyze sound propagation through aerosols, emulsions and suspensions in terms of frequency dependent attenuation coefficient and sound speed. Expressions for the viscous and thermal coupling coefficients explicitly account for the effects of particle size, shape factor, orientation as well as concentration and the sound frequency. The UCPC model also takes into account the intrinsic acoustic absorption within the fluid medium due to its viscosity and heat conductivity. The effective complex wave number as a function of frequency is derived. A frequency- and concentration-dependent complex Nusselt number for the interfacial thermal coupling coefficient is derived using an approximate similarity between the 'viscous skin drag' and 'heat conduction flux' associated with the discontinuous suspended phase, on the basis of a cell model. The theoretical predictions of attenuation spectra provide satisfactory agreement with reported experimental data on two concentrated suspensions (polystyrene latex and kaolin pigment), two concentrated emulsions (toluene -in-water, n-hexadecane-in-water), and two aerosols (oleic acid droplets-in-nitrogen, alumina-in-air), covering a wide range of relative magnitudes (from 10^ {-3} to 10^{3}) of thermal versus viscous contributions, for dispersed phase volume fractions as high as 50%. The relative differences between the additive result of separate viscous and thermal loss estimates and combined viscothermal absorption results are also presented. Effects of particle shape on viscous attenuation of sound in concentrated suspensions of non-spherical clay particles are studied. Attenuation spectra for 18 frequencies from 3 to 100 MHz are measured and analyzed for eleven kaolin clay slurries with solid concentrations ranging from 0.6% to 35% (w/w). A modified viscous drag coefficient that considers frequency, concentration, particle size, shape and orientation of spheroids, is developed and applied to estimate the viscous attenuation coefficients. With incorporation of particle size and shape distributions (PSSD), predictions agree quantitatively with observed attenuation coefficients. The effects of particle aspect ratio and orientation become more evident as particle concentrations and frequencies are increased. The UCPC model combined with the ultrasonic spectroscopy techniques can provide for theoretical and experimental frameworks in characterization of concentrated colloidal dispersions.

Consistent Large-Eddy Simulation of a Temporal Mixing Layer Laden with Evaporating Drops. Part 2; A Posteriori Modelling

NASA Technical Reports Server (NTRS)

Leboissertier, Anthony; Okong'O, Nora; Bellan, Josette

2005-01-01

Large-eddy simulation (LES) is conducted of a three-dimensional temporal mixing layer whose lower stream is initially laden with liquid drops which may evaporate during the simulation. The gas-phase equations are written in an Eulerian frame for two perfect gas species (carrier gas and vapour emanating from the drops), while the liquid-phase equations are written in a Lagrangian frame. The effect of drop evaporation on the gas phase is considered through mass, species, momentum and energy source terms. The drop evolution is modelled using physical drops, or using computational drops to represent the physical drops. Simulations are performed using various LES models previously assessed on a database obtained from direct numerical simulations (DNS). These LES models are for: (i) the subgrid-scale (SGS) fluxes and (ii) the filtered source terms (FSTs) based on computational drops. The LES, which are compared to filtered-and-coarsened (FC) DNS results at the coarser LES grid, are conducted with 64 times fewer grid points than the DNS, and up to 64 times fewer computational than physical drops. It is found that both constant-coefficient and dynamic Smagorinsky SGS-flux models, though numerically stable, are overly dissipative and damp generated small-resolved-scale (SRS) turbulent structures. Although the global growth and mixing predictions of LES using Smagorinsky models are in good agreement with the FC-DNS, the spatial distributions of the drops differ significantly. In contrast, the constant-coefficient scale-similarity model and the dynamic gradient model perform well in predicting most flow features, with the latter model having the advantage of not requiring a priori calibration of the model coefficient. The ability of the dynamic models to determine the model coefficient during LES is found to be essential since the constant-coefficient gradient model, although more accurate than the Smagorinsky model, is not consistently numerically stable despite using DNS-calibrated coefficients. With accurate SGS-flux models, namely scale-similarity and dynamic gradient, the FST model allows up to a 32-fold reduction in computational drops compared to the number of physical drops, without degradation of accuracy; a 64-fold reduction leads to a slight decrease in accuracy.

A new spatial snow distribution in hydrological models parameterized from observed spatial variability of precipitation.

NASA Astrophysics Data System (ADS)

Skaugen, Thomas; Weltzien, Ingunn

2016-04-01

The traditional catchment hydrological model with its many free calibration parameters is not a well suited tool for prediction under conditions for which is has not been calibrated. Important tasks for hydrological modelling such as prediction in ungauged basins and assessing hydrological effects of climate change are hence not solved satisfactory. In order to reduce the number of calibration parameters in hydrological models we have introduced a new model which uses a dynamic gamma distribution as the spatial frequency distribution of snow water equivalent (SWE). The parameters are estimated from observed spatial variability of precipitation and the magnitude of accumulation and melting events and are hence not subject to calibration. The relationship between spatial mean and variance of precipitation is found to follow a pattern where decreasing temporal correlation with increasing accumulation or duration of the event leads to a levelling off or even a decrease of the spatial variance. The new model for snow distribution is implemented in the, already parameter parsimonious, DDD (Distance Distribution Dynamics) hydrological model and was tested for 71 Norwegian catchments. We compared the new snow distribution model with the current operational snow distribution model where a fixed, calibrated coefficient of variation parameterizes a log-normal model for snow distribution. Results show that the precision of runoff simulations is equal, but that the new snow distribution model better simulates snow covered area (SCA) when compared with MODIS satellite derived snow cover. In addition, SWE is simulated more realistically in that seasonal snow is melted out and the building up of "snow towers" is prevented and hence spurious trends in SWE.

Computational prediction of ionic liquid 1-octanol/water partition coefficients.

PubMed

Kamath, Ganesh; Bhatnagar, Navendu; Baker, Gary A; Baker, Sheila N; Potoff, Jeffrey J

2012-04-07

Wet 1-octanol/water partition coefficients (log K(ow)) predicted for imidazolium-based ionic liquids using adaptive bias force-molecular dynamics (ABF-MD) simulations lie in excellent agreement with experimental values. These encouraging results suggest prospects for this computational tool in the a priori prediction of log K(ow) values of ionic liquids broadly with possible screening implications as well (e.g., prediction of CO(2)-philic ionic liquids).

Prediction of temperature and HAZ in thermal-based processes with Gaussian heat source by a hybrid GA-ANN model

NASA Astrophysics Data System (ADS)

Fazli Shahri, Hamid Reza; Mahdavinejad, Ramezanali

2018-02-01

Thermal-based processes with Gaussian heat source often produce excessive temperature which can impose thermally-affected layers in specimens. Therefore, the temperature distribution and Heat Affected Zone (HAZ) of materials are two critical factors which are influenced by different process parameters. Measurement of the HAZ thickness and temperature distribution within the processes are not only difficult but also expensive. This research aims at finding a valuable knowledge on these factors by prediction of the process through a novel combinatory model. In this study, an integrated Artificial Neural Network (ANN) and genetic algorithm (GA) was used to predict the HAZ and temperature distribution of the specimens. To end this, a series of full factorial design of experiments were conducted by applying a Gaussian heat flux on Ti-6Al-4 V at first, then the temperature of the specimen was measured by Infrared thermography. The HAZ width of each sample was investigated through measuring the microhardness. Secondly, the experimental data was used to create a GA-ANN model. The efficiency of GA in design and optimization of the architecture of ANN was investigated. The GA was used to determine the optimal number of neurons in hidden layer, learning rate and momentum coefficient of both output and hidden layers of ANN. Finally, the reliability of models was assessed according to the experimental results and statistical indicators. The results demonstrated that the combinatory model predicted the HAZ and temperature more effective than a trial-and-error ANN model.

Calculation of Distribution Coefficients of Cobalt and Copper in Matte and Slag Phases in Reduction-Vulcanization Process of Copper Converter Slag

NASA Astrophysics Data System (ADS)

Du, Ke; Li, Hongxu; Zhang, Mingming

2017-11-01

Copper and cobalt are two of the most valuable metals that can be recovered from copper converter slag. In the reduction-vulcanization process, copper is reduced before cobalt, while FeS vulcanizes Cu2O into Cu2S and forms the matte phase. The matte phase can dissolve the reduced metals as solvent. In this study, the distribution coefficient of cobalt between metallic cobalt in matte and CoO in slag, namely L Co, was calculated to be 5000-8500 at the reaction temperature of 1600-1700 K, while the distribution coefficient between CoS and CoO, namely L_{Co}^{{^' } }}, was calculated to be between 6 and 8. The distribution coefficient of copper between metallic copper in matte and Cu2O in slag, namely L Cu, was calculated to be in the range of 7500-8500, while the coefficient between Cu2S and Cu2O, namely L_{Cu}^{{^' } }}, was calculated to be in the range of 60,000-75,000.

Measurements and Modeling of Soot Formation and Radiation in Microgravity Jet Diffusion Flames. Volume 4

NASA Technical Reports Server (NTRS)

Ku, Jerry C.; Tong, Li; Greenberg, Paul S.

1996-01-01

This is a computational and experimental study for soot formation and radiative heat transfer in jet diffusion flames under normal gravity (1-g) and microgravity (0-g) conditions. Instantaneous soot volume fraction maps are measured using a full-field imaging absorption technique developed by the authors. A compact, self-contained drop rig is used for microgravity experiments in the 2.2-second drop tower facility at NASA Lewis Research Center. On modeling, we have coupled flame structure and soot formation models with detailed radiation transfer calculations. Favre-averaged boundary layer equations with a k-e-g turbulence model are used to predict the flow field, and a conserved scalar approach with an assumed Beta-pdf are used to predict gaseous species mole fraction. Scalar transport equations are used to describe soot volume fraction and number density distributions, with formation and oxidation terms modeled by one-step rate equations and thermophoretic effects included. An energy equation is included to couple flame structure and radiation analyses through iterations, neglecting turbulence-radiation interactions. The YIX solution for a finite cylindrical enclosure is used for radiative heat transfer calculations. The spectral absorption coefficient for soot aggregates is calculated from the Rayleigh solution using complex refractive index data from a Drude- Lorentz model. The exponential-wide-band model is used to calculate the spectral absorption coefficient for H20 and C02. It is shown that when compared to results from true spectral integration, the Rosseland mean absorption coefficient can provide reasonably accurate predictions for the type of flames studied. The soot formation model proposed by Moss, Syed, and Stewart seems to produce better fits to experimental data and more physically sound than the simpler model by Khan et al. Predicted soot volume fraction and temperature results agree well with published data for a normal gravity co-flow laminar flames and turbulent jet flames. Predicted soot volume fraction results also agree with our data for 1-g and 0-g laminar jet names as well as 1-g turbulent jet flames.

Bayesian Poisson hierarchical models for crash data analysis: Investigating the impact of model choice on site-specific predictions.

PubMed

Khazraee, S Hadi; Johnson, Valen; Lord, Dominique

2018-08-01

The Poisson-gamma (PG) and Poisson-lognormal (PLN) regression models are among the most popular means for motor vehicle crash data analysis. Both models belong to the Poisson-hierarchical family of models. While numerous studies have compared the overall performance of alternative Bayesian Poisson-hierarchical models, little research has addressed the impact of model choice on the expected crash frequency prediction at individual sites. This paper sought to examine whether there are any trends among candidate models predictions e.g., that an alternative model's prediction for sites with certain conditions tends to be higher (or lower) than that from another model. In addition to the PG and PLN models, this research formulated a new member of the Poisson-hierarchical family of models: the Poisson-inverse gamma (PIGam). Three field datasets (from Texas, Michigan and Indiana) covering a wide range of over-dispersion characteristics were selected for analysis. This study demonstrated that the model choice can be critical when the calibrated models are used for prediction at new sites, especially when the data are highly over-dispersed. For all three datasets, the PIGam model would predict higher expected crash frequencies than would the PLN and PG models, in order, indicating a clear link between the models predictions and the shape of their mixing distributions (i.e., gamma, lognormal, and inverse gamma, respectively). The thicker tail of the PIGam and PLN models (in order) may provide an advantage when the data are highly over-dispersed. The analysis results also illustrated a major deficiency of the Deviance Information Criterion (DIC) in comparing the goodness-of-fit of hierarchical models; models with drastically different set of coefficients (and thus predictions for new sites) may yield similar DIC values, because the DIC only accounts for the parameters in the lowest (observation) level of the hierarchy and ignores the higher levels (regression coefficients). Copyright © 2018. Published by Elsevier Ltd.

Theory versus experiment for the rotordynamic coefficients of labyrinth gas seals. II - A comparison to experiment

NASA Technical Reports Server (NTRS)

Childs, D. W.; Scharrer, J. K.

1987-01-01

An experimental test facility is used to measure the leakage and rotordynamic coefficients of teeth-on-rotor and teeth-on-stator labyrinth gas seals. The test results are presented along with the theoretically predicted values for the two seal configurations at three different radial clearances and shaft speeds to 16,000 cpm. The test results show that the theory accurately predicts the cross-coupled stiffness for both seal configurations and shows improvement in the prediction of the direct damping for the teeth-on-rotor seal. The theory fails to predict a decrease in the direct damping coefficient for an increase in the radial clearance for the teeth-on-stator seal.

Sensitivity Analysis of the Bone Fracture Risk Model

NASA Technical Reports Server (NTRS)

Lewandowski, Beth; Myers, Jerry; Sibonga, Jean Diane

2017-01-01

Introduction: The probability of bone fracture during and after spaceflight is quantified to aid in mission planning, to determine required astronaut fitness standards and training requirements and to inform countermeasure research and design. Probability is quantified with a probabilistic modeling approach where distributions of model parameter values, instead of single deterministic values, capture the parameter variability within the astronaut population and fracture predictions are probability distributions with a mean value and an associated uncertainty. Because of this uncertainty, the model in its current state cannot discern an effect of countermeasures on fracture probability, for example between use and non-use of bisphosphonates or between spaceflight exercise performed with the Advanced Resistive Exercise Device (ARED) or on devices prior to installation of ARED on the International Space Station. This is thought to be due to the inability to measure key contributors to bone strength, for example, geometry and volumetric distributions of bone mass, with areal bone mineral density (BMD) measurement techniques. To further the applicability of model, we performed a parameter sensitivity study aimed at identifying those parameter uncertainties that most effect the model forecasts in order to determine what areas of the model needed enhancements for reducing uncertainty. Methods: The bone fracture risk model (BFxRM), originally published in (Nelson et al) is a probabilistic model that can assess the risk of astronaut bone fracture. This is accomplished by utilizing biomechanical models to assess the applied loads; utilizing models of spaceflight BMD loss in at-risk skeletal locations; quantifying bone strength through a relationship between areal BMD and bone failure load; and relating fracture risk index (FRI), the ratio of applied load to bone strength, to fracture probability. There are many factors associated with these calculations including environmental factors, factors associated with the fall event, mass and anthropometric values of the astronaut, BMD characteristics, characteristics of the relationship between BMD and bone strength and bone fracture characteristics. The uncertainty in these factors is captured through the use of parameter distributions and the fracture predictions are probability distributions with a mean value and an associated uncertainty. To determine parameter sensitivity, a correlation coefficient is found between the sample set of each model parameter and the calculated fracture probabilities. Each parameters contribution to the variance is found by squaring the correlation coefficients, dividing by the sum of the squared correlation coefficients, and multiplying by 100. Results: Sensitivity analyses of BFxRM simulations of preflight, 0 days post-flight and 365 days post-flight falls onto the hip revealed a subset of the twelve factors within the model which cause the most variation in the fracture predictions. These factors include the spring constant used in the hip biomechanical model, the midpoint FRI parameter within the equation used to convert FRI to fracture probability and preflight BMD values. Future work: Plans are underway to update the BFxRM by incorporating bone strength information from finite element models (FEM) into the bone strength portion of the BFxRM. Also, FEM bone strength information along with fracture outcome data will be incorporated into the FRI to fracture probability.

Molecular dynamics studies of transport properties and equation of state of supercritical fluids

NASA Astrophysics Data System (ADS)

Nwobi, Obika C.

Many chemical propulsion systems operate with one or more of the reactants above the critical point in order to enhance their performance. Most of the computational fluid dynamics (CFD) methods used to predict these flows require accurate information on the transport properties and equation of state at these supercritical conditions. This work involves the determination of transport coefficients and equation of state of supercritical fluids by equilibrium molecular dynamics (MD) simulations on parallel computers using the Green-Kubo formulae and the virial equation of state, respectively. MD involves the solution of equations of motion of a system of molecules that interact with each other through an intermolecular potential. Provided that an accurate potential can be found for the system of interest, MD can be used regardless of the phase and thermodynamic conditions of the substances involved. The MD program uses the effective Lennard-Jones potential, with system sizes of 1000-1200 molecules and, simulations of 2,000,000 time-steps for computing transport coefficients and 200,000 time-steps for pressures. The computer code also uses linked cell lists for efficient sorting of molecules, periodic boundary conditions, and a modified velocity Verlet algorithm for particle displacement. Particle decomposition is used for distributing the molecules to different processors of a parallel computer. Simulations have been carried out on pure argon, nitrogen, oxygen and ethylene at various supercritical conditions, with self-diffusion coefficients, shear viscosity coefficients, thermal conductivity coefficients and pressures computed for most of the conditions. Results compare well with experimental and the National Institute of Standards and Technology (NIST) values. The results show that the number of molecules and the potential cut-off radius have no significant effect on the computed coefficients, while long-time integration is necessary for accurate determination of the coefficients.

Discrete Element Method Simulations of the Inter-Particle Contact Parameters for the Mono-Sized Iron Ore Particles.

PubMed

Li, Tongqing; Peng, Yuxing; Zhu, Zhencai; Zou, Shengyong; Yin, Zixin

2017-05-11

Aiming at predicting what happens in reality inside mills, the contact parameters of iron ore particles for discrete element method (DEM) simulations should be determined accurately. To allow the irregular shape to be accurately determined, the sphere clump method was employed in modelling the particle shape. The inter-particle contact parameters were systematically altered whilst the contact parameters between the particle and wall were arbitrarily assumed, in order to purely assess its impact on the angle of repose for the mono-sized iron ore particles. Results show that varying the restitution coefficient over the range considered does not lead to any obvious difference in the angle of repose, but the angle of repose has strong sensitivity to the rolling/static friction coefficient. The impacts of the rolling/static friction coefficient on the angle of repose are interrelated, and increasing the inter-particle rolling/static friction coefficient can evidently increase the angle of repose. However, the impact of the static friction coefficient is more profound than that of the rolling friction coefficient. Finally, a predictive equation is established and a very close agreement between the predicted and simulated angle of repose is attained. This predictive equation can enormously shorten the inter-particle contact parameters calibration time that can help in the implementation of DEM simulations.

The stochastic distribution of available coefficient of friction for human locomotion of five different floor surfaces.

PubMed

Chang, Wen-Ruey; Matz, Simon; Chang, Chien-Chi

2014-05-01

The maximum coefficient of friction that can be supported at the shoe and floor interface without a slip is usually called the available coefficient of friction (ACOF) for human locomotion. The probability of a slip could be estimated using a statistical model by comparing the ACOF with the required coefficient of friction (RCOF), assuming that both coefficients have stochastic distributions. An investigation of the stochastic distributions of the ACOF of five different floor surfaces under dry, water and glycerol conditions is presented in this paper. One hundred friction measurements were performed on each floor surface under each surface condition. The Kolmogorov-Smirnov goodness-of-fit test was used to determine if the distribution of the ACOF was a good fit with the normal, log-normal and Weibull distributions. The results indicated that the ACOF distributions had a slightly better match with the normal and log-normal distributions than with the Weibull in only three out of 15 cases with a statistical significance. The results are far more complex than what had heretofore been published and different scenarios could emerge. Since the ACOF is compared with the RCOF for the estimate of slip probability, the distribution of the ACOF in seven cases could be considered a constant for this purpose when the ACOF is much lower or higher than the RCOF. A few cases could be represented by a normal distribution for practical reasons based on their skewness and kurtosis values without a statistical significance. No representation could be found in three cases out of 15. Copyright © 2013 Elsevier Ltd and The Ergonomics Society. All rights reserved.

Optical pathlengths in dental caries lesions

NASA Astrophysics Data System (ADS)

Mujat, Claudia; ten Bosch, Jaap J.; Dogariu, Aristide C.

2001-04-01

The average pathlength of light inside dental enamel and incipient lesions is measured and compared, in order to quantitatively confirm the prediction that incipient lesions have higher scattering coefficients that sound enamel. The technique used, called optical pathlength spectroscopy provides experimental access to the pathlength distribution of light inside highly scattering samples. This is desirable for complex biological materials, where current theoretical models are very difficult to apply. To minimize the effects of surface reflections the average pathlength is measured in wet sound enamel and white spots. We obtain values of 367 micrometers and 272 micrometers average pathlength for sound enamel and white spots respectively. We also investigate the differences between open and subsurface lesions, by measuring the change in the pathlength distribution of light as they go from dry to wet.

CFD Prediction on the Pressure Distribution and Streamlines around an Isolated Single-Storey House Considering the Effect of Topographic Characteristics

NASA Astrophysics Data System (ADS)

Abdullah, J.; Zaini, S. S.; Aziz, M. S. A.; Majid, T. A.; Deraman, S. N. C.; Yahya, W. N. W.

2018-04-01

Single-storey houses are classified as low rise building and vulnerable to damages under windstorm event. This study was carried out with the aim to investigate the pressure distribution and streamlines around an isolated house by considering the effect of terrain characteristics. The topographic features such as flat, depression, ridge, and valley, are considered in this study. This simulation were analysed with Ansys FLUENT 14.0 software package. The result showed the topography characteristics influence the value of pressure coefficient and streamlines especially when the house was located at ridge terrain. The findings strongly suggested that wind analysis should include all topographic features in the analysis in order to establish the true wind force exerted on any structure.

Correlation of tissue-plasma partition coefficients between normal tissues and subcutaneous xenografts of human tumor cell lines in mouse as a prediction tool of drug penetration in tumors.

PubMed

Poulin, Patrick; Hop, Cornelis Eca; Salphati, Laurent; Liederer, Bianca M

2013-04-01

Understanding drug distribution and accumulation in tumors would be informative in the assessment of efficacy in targeted therapy; however, existing methods for predicting tissue drug distribution focus on normal tissues and do not incorporate tumors. The main objective of this study was to describe the relationships between tissue-plasma concentration ratios (Kp ) of normal tissues and those of subcutaneous xenograft tumors under nonsteady-state conditions, and establish regression equations that could potentially be used for the prediction of drug levels in several human tumor xenografts in mouse, based solely on a Kp value determined in a normal tissue (e.g., muscle). A dataset of 17 compounds was collected from the literature and from Genentech. Tissue and plasma concentration data in mouse were obtained following oral gavage or intraperitoneal administration. Linear regression analyses were performed between Kp values in several normal tissues (muscle, lung, liver, or brain) and those in human tumor xenografts (CL6, EBC-1, HT-29, PC3, U-87, MCF-7-neo-Her2, or BT474M1.1). The tissue-plasma ratios in normal tissues reasonably correlated with the tumor-plasma ratios in CL6, EBC-1, HT-29, U-87, BT474M1.1, and MCF-7-neo-Her2 xenografts (r(2) in the range 0.62-1) but not with the PC3 xenograft. In general, muscle and lung exhibited the strongest correlation with tumor xenografts, followed by liver. Regression coefficients from brain were low, except between brain and the glioblastoma U-87 xenograft (r(2) in the range 0.62-0.94). Furthermore, reasonably strong correlations were observed between muscle and lung and between muscle and liver (r(2) in the range 0.67-0.96). The slopes of the regressions differed depending on the class of drug (strong vs. weak base) and type of tissue (brain vs. other tissues and tumors). Overall, this study will contribute to our understanding of tissue-plasma partition coefficients for tumors and facilitate the use of physiologically based pharmacokinetics (PBPK) modeling for chemotherapy in oncology studies. © 2013 Wiley Periodicals, Inc. and the American Pharmacists Association J Pharm Sci 102:1355-1369, 2013. Copyright © 2013 Wiley Periodicals, Inc.

Diffusion coefficients of organic molecules in sucrose-water solutions and comparison with Stokes-Einstein predictions

NASA Astrophysics Data System (ADS)

Chenyakin, Yuri; Ullmann, Dagny A.; Evoy, Erin; Renbaum-Wolff, Lindsay; Kamal, Saeid; Bertram, Allan K.

2017-02-01

The diffusion coefficients of organic species in secondary organic aerosol (SOA) particles are needed to predict the growth and reactivity of these particles in the atmosphere. Previously, viscosity measurements, along with the Stokes-Einstein relation, have been used to estimate the diffusion rates of organics within SOA particles or proxies of SOA particles. To test the Stokes-Einstein relation, we have measured the diffusion coefficients of three fluorescent organic dyes (fluorescein, rhodamine 6G and calcein) within sucrose-water solutions with varying water activity. Sucrose-water solutions were used as a proxy for SOA material found in the atmosphere. Diffusion coefficients were measured using fluorescence recovery after photobleaching. For the three dyes studied, the diffusion coefficients vary by 4-5 orders of magnitude as the water activity varied from 0.38 to 0.80, illustrating the sensitivity of the diffusion coefficients to the water content in the matrix. At the lowest water activity studied (0.38), the average diffusion coefficients were 1.9 × 10-13, 1.5 × 10-14 and 7.7 × 10-14 cm2 s-1 for fluorescein, rhodamine 6G and calcein, respectively. The measured diffusion coefficients were compared with predictions made using literature viscosities and the Stokes-Einstein relation. We found that at water activity ≥ 0.6 (which corresponds to a viscosity of ≤ 360 Pa s and Tg/T ≤ 0.81), predicted diffusion rates agreed with measured diffusion rates within the experimental uncertainty (Tg represents the glass transition temperature and T is the temperature of the measurements). When the water activity was 0.38 (which corresponds to a viscosity of 3.3 × 106 Pa s and a Tg/T of 0.94), the Stokes-Einstein relation underpredicted the diffusion coefficients of fluorescein, rhodamine 6G and calcein by a factor of 118 (minimum of 10 and maximum of 977), a factor of 17 (minimum of 3 and maximum of 104) and a factor of 70 (minimum of 8 and maximum of 494), respectively. This disagreement is significantly smaller than the disagreement observed when comparing measured and predicted diffusion coefficients of water in sucrose-water mixtures.

Solid harmonic wavelet scattering for predictions of molecule properties

NASA Astrophysics Data System (ADS)

Eickenberg, Michael; Exarchakis, Georgios; Hirn, Matthew; Mallat, Stéphane; Thiry, Louis

2018-06-01

We present a machine learning algorithm for the prediction of molecule properties inspired by ideas from density functional theory (DFT). Using Gaussian-type orbital functions, we create surrogate electronic densities of the molecule from which we compute invariant "solid harmonic scattering coefficients" that account for different types of interactions at different scales. Multilinear regressions of various physical properties of molecules are computed from these invariant coefficients. Numerical experiments show that these regressions have near state-of-the-art performance, even with relatively few training examples. Predictions over small sets of scattering coefficients can reach a DFT precision while being interpretable.

Stagnation point properties for non-continuum gaseous jet impinging at a flat plate surface from a planar exit

NASA Astrophysics Data System (ADS)

Cai, Chunpei

2013-10-01

In this paper, we investigate highly rarefied gaseous jet flows out of a planar exit and impinging at a normally set flat plate. Especially, we concentrate on the plate center stagnation point pressure and heat flux coefficients. For a specular reflective plate, the stagnation point pressure coefficient can be represented using two non-dimensional factors: the characteristic gas exit speed ratio S0 and the geometry ratio of H/L, where H is the planar exit semi-height and L is the center-to-center distance from the exit to the plate. For a diffuse reflective plate, the stagnation point pressure and heat flux coefficients involve an extra factor of T0/Tw, i.e., the ratio of exit gas temperature to the plate wall temperature. These results allow us to develop four diagrams, from which we can conveniently obtain the pressure and heat flux coefficients for the stagnation impingement point, at the collisionless flow limit. After normalization with these maximum coefficients, the pressure and heat flux coefficient distributions along the surface essentially degenerate to almost identical curves. As a result, with known plate surface pressure coefficient distributions and these diagrams, we can conveniently construct the heat flux coefficient distributions along the plate surface, and vice versa.

Modelling transient temperature distribution for injecting hot water through a well to an aquifer thermal energy storage system

NASA Astrophysics Data System (ADS)

Yang, Shaw-Yang; Yeh, Hund-Der; Li, Kuang-Yi

2010-10-01

Heat storage systems are usually used to store waste heat and solar energy. In this study, a mathematical model is developed to predict both the steady-state and transient temperature distributions of an aquifer thermal energy storage (ATES) system after hot water is injected through a well into a confined aquifer. The ATES has a confined aquifer bounded by aquicludes with different thermomechanical properties and geothermal gradients along the depth. Consider that the heat is transferred by conduction and forced convection within the aquifer and by conduction within the aquicludes. The dimensionless semi-analytical solutions of temperature distributions of the ATES system are developed using Laplace and Fourier transforms and their corresponding time-domain results are evaluated numerically by the modified Crump method. The steady-state solution is obtained from the transient solution through the final-value theorem. The effect of the heat transfer coefficient on aquiclude temperature distribution is appreciable only near the outer boundaries of the aquicludes. The present solutions are useful for estimating the temperature distribution of heat injection and the aquifer thermal capacity of ATES systems.

Initial-phase investigation of multi-dimensional streamflow simulations in the Colorado River, Moab Valley, Grand County, Utah, 2004

USGS Publications Warehouse

Kenney, Terry A.

2005-01-01

A multi-dimensional hydrodynamic model was applied to aid in the assessment of the potential hazard posed to the uranium mill tailings near Moab, Utah, by flooding in the Colorado River as it flows through Moab Valley. Discharge estimates for the 100- and 500-year recurrence interval and for the Probable Maximum Flood (PMF) were evaluated with the model for the existing channel geometry. These discharges also were modeled for three other channel-deepening configurations representing hypothetical scour of the channel at the downstream portal of Moab Valley. Water-surface elevation, velocity distribution, and shear-stress distribution were predicted for each simulation.The hydrodynamic model was developed from measured channel topography and over-bank topographic data acquired from several sources. A limited calibration of the hydrodynamic model was conducted. The extensive presence of tamarisk or salt cedar in the over-bank regions of the study reach presented challenges for determining roughness coefficients.Predicted water-surface elevations for the current channel geometry indicated that the toe of the tailings pile would be inundated by about 4 feet by the 100-year discharge and 25 feet by the PMF discharge. A small area at the toe of the tailings pile was characterized by velocities of about 1 to 2 feet per second for the 100-year discharge. Predicted velocities near the toe for the PMF discharge increased to between 2 and 4 feet per second over a somewhat larger area. The manner to which velocities progress from the 100-year discharge to the PMF discharge in the area of the tailings pile indicates that the tailings pile obstructs the over-bank flow of flood discharges. The predicted path of flow for all simulations along the existing Colorado River channel indicates that the current distribution of tamarisk in the over-bank region affects how flood-flow velocities are spatially distributed. Shear-stress distributions were predicted throughout the study reach for each discharge and channel geometry examined. Material transport was evaluated by applying these shear-stress values to empirically determined critical shear-stress values for grain sizes ranging from very fine sands to very coarse gravels.

A Whole-Body Physiologically Based Pharmacokinetic Model for Colistin and Colistin methanesulfonate (CMS) in Rat.

PubMed

Bouchene, Salim; Marchand, Sandrine; Couet, William; Friberg, Lena E; Gobin, Patrice; Lamarche, Isabelle; Grégoire, Nicolas; Björkman, Sven; Karlsson, Mats O

2018-04-17

Colistin is a polymyxin antibiotic used to treat patients infected with multidrug-resistant Gram negative bacteria (MDR-GNB). The objective of this work was to develop a whole-body physiologically based pharmacokinetic (WB-PBPK) model to predict tissue distribution of colistin in rat. The distribution of a drug in a tissue is commonly characterized by its tissue-to-plasma partition coefficient, K p . Colistin and its prodrug, colistin methanesulfonate (CMS) K p priors were measured experimentally from rat tissue homogenates or predicted in silico. The PK parameters of both compounds were estimated fitting in vivo their plasma concentration-time profiles from six rats receiving an i.v. bolus of CMS. The variability in the data was quantified by applying a non-linear mixed effect (NLME) modelling approach. A WB-PBPK model was developed assuming a well-stirred and perfusion-limited distribution in tissue compartments. Prior information on tissue distribution of colistin and CMS was investigated following three scenarios: K p were estimated using in silico K p priors (I) or K p were estimated using experimental K p priors (II) or K p were fixed to the experimental values (III). The WB-PBPK model best described colistun and CMS plasma concentration-time profiles in scenario II. Colistin predicted concentrations in kidneys in scenario II were higher than in other tissues, which was consistent with its large experimental K p prior. This might be explained by a high affinity of colistin for renal parenchyma and active reabsorption into the proximal tubular cells. In contrast, renal accumulation of colistin was not predicted in scenario I. Colistin and CMS clearance estimates were in agreement with published values. The developed model suggests using experimental priors over in silico K p priors for kidneys to provide a better prediction of colistin renal distribution. Such models might serve in drug development for interspecies scaling and investigating the impact of disease state on colistin disposition. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

Shear forces in the contact patch of a braked-racing tyre

NASA Astrophysics Data System (ADS)

Gruber, Patrick; Sharp, Robin S.

2012-12-01

This article identifies tyre modelling features that are fundamental to the accurate simulation of the shear forces in the contact patch of a steady-rolling, slipping and cambered racing tyre. The features investigated include contact patch shape, contact pressure distribution, carcass flexibility, rolling radius (RR) variations and friction coefficient. Using a previously described physical tyre model of modular nature, validated for static conditions, the influence of each feature on the shear forces generated is examined under different running conditions, including normal loads of 1500, 3000 and 4500 N, camber angles of 0° and-3°, and longitudinal slip ratios from 0 to-20%. Special attention is paid to heavy braking, in which context the aligning moment is of great interest in terms of its connection with the limit-handling feel. The results of the simulations reveal that true representations of the contact patch shape, carcass flexibility and lateral RR variation are essential for an accurate prediction of the distribution and the magnitude of the shear forces generated at the tread-road interface of the cambered tyre. Independent of the camber angle, the contact pressure distribution primarily influences the shear force distribution and the slip characteristics around the peak longitudinal force. At low brake-slip ratios, the friction coefficient affects the shear forces in terms of their distribution, while, at medium to high-slip ratios, the force magnitude is significantly affected. On the one hand, these findings help in the creation of efficient yet accurate tyre models. On the other hand, the research results allow improved understanding of how individual tyre components affect the generation of shear forces in the contact patch of a rolling and slipping tyre.

A proof for Rhiel's range estimator of the coefficient of variation for skewed distributions.

PubMed

Rhiel, G Steven

2007-02-01

In this research study is proof that the coefficient of variation (CV(high-low)) calculated from the highest and lowest values in a set of data is applicable to specific skewed distributions with varying means and standard deviations. Earlier Rhiel provided values for d(n), the standardized mean range, and a(n), an adjustment for bias in the range estimator of micro. These values are used in estimating the coefficient of variation from the range for skewed distributions. The d(n) and an values were specified for specific skewed distributions with a fixed mean and standard deviation. In this proof it is shown that the d(n) and an values are applicable for the specific skewed distributions when the mean and standard deviation can take on differing values. This will give the researcher confidence in using this statistic for skewed distributions regardless of the mean and standard deviation.

TU-F-18C-05: Evaluation of a Method to Calculate Patient-Oriented MGD Coefficients Using Estimates of Glandular Tissue Distribution

DOE Office of Scientific and Technical Information (OSTI.GOV)

Porras-Chaverri, M; University of Costa Rica, San Jose; Galavis, P

Purpose: Evaluate mammographic mean glandular dose (MGD) coefficients for particular known tissue distributions using a novel formalism that incorporates the effect of the heterogeneous glandular tissue distribution, by comparing them with MGD coefficients derived from the corresponding anthropomorphic computer breast phantom. Methods: MGD coefficients were obtained using MCNP5 simulations with the currently used homogeneous assumption and the heterogeneously-layered breast (HLB) geometry and compared against those from the computer phantom (ground truth). The tissue distribution for the HLB geometry was estimated using glandularity map image pairs corrected for the presence of non-glandular fibrous tissue. Heterogeneity of tissue distribution was quantified usingmore » the glandular tissue distribution index, Idist. The phantom had 5 cm compressed breast thickness (MLO and CC views) and 29% whole breast glandular percentage. Results: Differences as high as 116% were found between the MGD coefficients with the homogeneous breast core assumption and those from the corresponding ground truth. Higher differences were found for cases with more heterogeneous distribution of glandular tissue. The Idist for all cases was in the [−0.8{sup −}+0.3] range. The use of the methods presented in this work results in better agreement with ground truth with an improvement as high as 105 pp. The decrease in difference across all phantom cases was in the [9{sup −}105] pp range, dependent on the distribution of glandular tissue and was larger for the cases with the highest Idist values. Conclusion: Our results suggest that the use of corrected glandularity image pairs, as well as the HLB geometry, improves the estimates of MGD conversion coefficients by accounting for the distribution of glandular tissue within the breast. The accuracy of this approach with respect to ground truth is highly dependent on the particular glandular tissue distribution studied. Predrag Bakic discloses current funding from NIH, NSF, and DoD, former funding from Real Time Tomography, LLC and a current research collaboration with Barco and Hologic.« less

[Prediction of soil nutrients spatial distribution based on neural network model combined with goestatistics].

PubMed

Li, Qi-Quan; Wang, Chang-Quan; Zhang, Wen-Jiang; Yu, Yong; Li, Bing; Yang, Juan; Bai, Gen-Chuan; Cai, Yan

2013-02-01

In this study, a radial basis function neural network model combined with ordinary kriging (RBFNN_OK) was adopted to predict the spatial distribution of soil nutrients (organic matter and total N) in a typical hilly region of Sichuan Basin, Southwest China, and the performance of this method was compared with that of ordinary kriging (OK) and regression kriging (RK). All the three methods produced the similar soil nutrient maps. However, as compared with those obtained by multiple linear regression model, the correlation coefficients between the measured values and the predicted values of soil organic matter and total N obtained by neural network model increased by 12. 3% and 16. 5% , respectively, suggesting that neural network model could more accurately capture the complicated relationships between soil nutrients and quantitative environmental factors. The error analyses of the prediction values of 469 validation points indicated that the mean absolute error (MAE) , mean relative error (MRE), and root mean squared error (RMSE) of RBFNN_OK were 6.9%, 7.4%, and 5. 1% (for soil organic matter), and 4.9%, 6.1% , and 4.6% (for soil total N) smaller than those of OK (P<0.01), and 2.4%, 2.6% , and 1.8% (for soil organic matter), and 2.1%, 2.8%, and 2.2% (for soil total N) smaller than those of RK, respectively (P<0.05).

Modeling the growth kinetics of Bacillus cereus as a function of temperature, pH, sodium lactate and sodium chloride concentrations.

PubMed

Olmez, Hülya Kaptan; Aran, Necla

2005-02-01

Mathematical models describing the growth kinetic parameters (lag phase duration and growth rate) of Bacillus cereus as a function of temperature, pH, sodium lactate and sodium chloride concentrations were obtained in this study. In order to get a residual distribution closer to a normal distribution, the natural logarithm of the growth kinetic parameters were used in modeling. For reasons of parsimony, the polynomial models were reduced to contain only the coefficients significant at a level of p

Prediction of passive blood-brain partitioning: straightforward and effective classification models based on in silico derived physicochemical descriptors

PubMed Central

Vilar, Santiago; Chakrabarti, Mayukh; Costanzi, Stefano

2010-01-01

The distribution of compounds between blood and brain is a very important consideration for new candidate drug molecules. In this paper, we describe the derivation of two linear discriminant analysis (LDA) models for the prediction of passive blood-brain partitioning, expressed in terms of log BB values. The models are based on computationally derived physicochemical descriptors, namely the octanol/water partition coefficient (log P), the topological polar surface area (TPSA) and the total number of acidic and basic atoms, and were obtained using a homogeneous training set of 307 compounds, for all of which the published experimental log BB data had been determined in vivo. In particular, since molecules with log BB > 0.3 cross the blood-brain barrier (BBB) readily while molecules with log BB < −1 are poorly distributed to the brain, on the basis of these thresholds we derived two distinct models, both of which show a percentage of good classification of about 80%. Notably, the predictive power of our models was confirmed by the analysis of a large external dataset of compounds with reported activity on the central nervous system (CNS) or lack thereof. The calculation of straightforward physicochemical descriptors is the only requirement for the prediction of the log BB of novel compounds through our models, which can be conveniently applied in conjunction with drug design and virtual screenings. PMID:20427217

Prediction of passive blood-brain partitioning: straightforward and effective classification models based on in silico derived physicochemical descriptors.

PubMed

Vilar, Santiago; Chakrabarti, Mayukh; Costanzi, Stefano

2010-06-01

The distribution of compounds between blood and brain is a very important consideration for new candidate drug molecules. In this paper, we describe the derivation of two linear discriminant analysis (LDA) models for the prediction of passive blood-brain partitioning, expressed in terms of logBB values. The models are based on computationally derived physicochemical descriptors, namely the octanol/water partition coefficient (logP), the topological polar surface area (TPSA) and the total number of acidic and basic atoms, and were obtained using a homogeneous training set of 307 compounds, for all of which the published experimental logBB data had been determined in vivo. In particular, since molecules with logBB>0.3 cross the blood-brain barrier (BBB) readily while molecules with logBB<-1 are poorly distributed to the brain, on the basis of these thresholds we derived two distinct models, both of which show a percentage of good classification of about 80%. Notably, the predictive power of our models was confirmed by the analysis of a large external dataset of compounds with reported activity on the central nervous system (CNS) or lack thereof. The calculation of straightforward physicochemical descriptors is the only requirement for the prediction of the logBB of novel compounds through our models, which can be conveniently applied in conjunction with drug design and virtual screenings. Published by Elsevier Inc.

Red blood cell distribution width and haemoglobin are associated with hospital admission in patients with acute allergic reactions.

PubMed

Lippi, Giuseppe; Buonocore, Ruggero; Picanza, Alessandra; Schirosa, Fabio; Cervellin, Gianfranco

2016-01-01

Red blood cell distribution width (RDW) is significantly associated with a variety of human disorders. This study aimed to investigate whether RDW value at admission may predict the need of hospitalisation in patients presenting to the emergency department (ED) with acute allergic reactions. The study population consisted of adult patients (aged > 17) admitted to the ED for acute allergic reactions. One hundred and thirty-two subjects were included, 12 of whom (9%) required hospital admission for severity of symptoms. Patients who needed hospital admission displayed significantly lower values of haemoglobin and significantly higher values of RDW-coefficient of variation (RDW-CV). In multivariate analysis, haemoglobin and RDW-CV were found to be independent predictors of hospital admission. The area under the curve (AUC), sensitivity and specificity for predicting hospital admission were 0.72, 0.88 and 0.42 for haemoglobin and 0.73, 0.88 and 0.50 for RDW-CV, respectively. The combination of these tests (both positive) was characterised by 0.76 AUC, 0.83 sensitivity, 0.67 specificity, 0.96 negative predictive value and 0.30 positive predictive. The results of this study suggest that two common and inexpensive parameters such as haemoglobin and RDW are independent predictors of hospital admission in patients presenting to the ED with acute allergic reactions.

Particle tracking by using single coefficient of Wigner-Ville distribution

NASA Astrophysics Data System (ADS)

Widjaja, J.; Dawprateep, S.; Chuamchaitrakool, P.; Meemon, P.

2016-11-01

A new method for extracting information from particle holograms by using a single coefficient of Wigner-Ville distribution (WVD) is proposed to obviate drawbacks of conventional numerical reconstructions. Our previous study found that analysis of the holograms by using the WVD gives output coefficients which are mainly confined along a diagonal direction intercepted at the origin of the WVD plane. The slope of this diagonal direction is inversely proportional to the particle position. One of these coefficients always has minimum amplitude, regardless of the particle position. By detecting position of the coefficient with minimum amplitude in the WVD plane, the particle position can be accurately measured. The proposed method is verified through computer simulations.

Efficient and robust method for simultaneous reconstruction of the temperature distribution and radiative properties in absorbing, emitting, and scattering media

NASA Astrophysics Data System (ADS)

Niu, Chun-Yang; Qi, Hong; Huang, Xing; Ruan, Li-Ming; Tan, He-Ping

2016-11-01

A rapid computational method called generalized sourced multi-flux method (GSMFM) was developed to simulate outgoing radiative intensities in arbitrary directions at the boundary surfaces of absorbing, emitting, and scattering media which were served as input for the inverse analysis. A hybrid least-square QR decomposition-stochastic particle swarm optimization (LSQR-SPSO) algorithm based on the forward GSMFM solution was developed to simultaneously reconstruct multi-dimensional temperature distribution and absorption and scattering coefficients of the cylindrical participating media. The retrieval results for axisymmetric temperature distribution and non-axisymmetric temperature distribution indicated that the temperature distribution and scattering and absorption coefficients could be retrieved accurately using the LSQR-SPSO algorithm even with noisy data. Moreover, the influences of extinction coefficient and scattering albedo on the accuracy of the estimation were investigated, and the results suggested that the reconstruction accuracy decreased with the increase of extinction coefficient and the scattering albedo. Finally, a non-contact measurement platform of flame temperature field based on the light field imaging was set up to validate the reconstruction model experimentally.

Integrating Environmental and Mosquito Data to Model Disease: Evaluating Alternative Modeling Approaches for Forecasting West Nile Virus in South Dakota, USA

NASA Astrophysics Data System (ADS)

Davis, J. K.; Vincent, G. P.; Hildreth, M.; Kightlinger, L.; Carlson, C.; Wimberly, M. C.

2017-12-01

South Dakota has the highest annual incidence of human cases of West Nile virus (WNV) in all US states, and human cases can vary wildly among years; predicting WNV risk in advance is a necessary exercise if public health officials are to respond efficiently and effectively to risk. Case counts are associated with environmental factors that affect mosquitoes, avian hosts, and the virus itself. They are also correlated with entomological risk indices obtained by trapping and testing mosquitoes. However, neither weather nor insect data alone provide a sufficient basis to make timely and accurate predictions, and combining them into models of human disease is not necessarily straightforward. Here we present lessons learned in three years of making real-time forecasts of this threat to public health. Various methods of integrating data from NASA's North American Land Data Assimilation System (NLDAS) with mosquito surveillance data were explored in a model comparison framework. We found that a model of human disease summarizing weather data (by polynomial distributed lags with seasonally-varying coefficients) and mosquito data (by a mixed-effects model that smooths out these sparse and highly-variable data) made accurate predictions of risk, and was generalizable enough to be recommended in similar applications. A model based on lagged effects of temperature and humidity provided the most accurate predictions. We also found that model accuracy was improved by allowing coefficients to vary smoothly throughout the season, giving different weights to different predictor variables during different parts of the season.

Predictive ecotoxicity of MoA 1 of organic chemicals using in silico approaches.

PubMed

de Morais E Silva, Luana; Alves, Mateus Feitosa; Scotti, Luciana; Lopes, Wilton Silva; Scotti, Marcus Tullius

2018-05-30

Persistent organic products are compounds used for various purposes, such as personal care products, surfactants, colorants, industrial additives, food, pesticides and pharmaceuticals. These substances are constantly introduced into the environment and many of these pollutants are difficult to degrade. Toxic compounds classified as MoA 1 (Mode of Action 1) are low toxicity compounds that comprise nonreactive chemicals. In silico methods such as Quantitative Structure-Activity Relationships (QSARs) have been used to develop important models for prediction in several areas of science, as well as aquatic toxicity studies. The aim of the present study was to build a QSAR model-based set of theoretical Volsurf molecular descriptors using the fish acute toxicity values of compounds defined as MoA 1 to identify the molecular properties related to this mechanism. The selected Partial Least Squares (PLS) results based on the values of cross-validation coefficients of determination (Q cv 2 ) show the following values: Q cv 2 = 0.793, coefficient of determination (R 2 ) = 0.823, explained variance in external prediction (Q ext 2 ) = 0.87. From the selected descriptors, not only the hydrophobicity is related to the toxicity as already mentioned in previously published studies but other physicochemical properties combined contribute to the activity of these compounds. The symmetric distribution of the hydrophobic moieties in the structure of the compounds as well as the shape, as branched chains, are important features that are related to the toxicity. This information from the model can be useful in predicting so as to minimize the toxicity of organic compounds. Copyright © 2018. Published by Elsevier Inc.

Use of a W-band polarimeter to measure microphysical characteristics of clouds

NASA Astrophysics Data System (ADS)

Galloway, John Charles

1997-08-01

This dissertation presents W-Band measurements of the copolar correlation co-efficient and Doppler spectrum taken from the University of Wyoming King Air research airplane. These measurements demonstrate the utility of making W-Band polarimetric and Doppler spectrum measurements from an airborne platform in investigations of cloud microphysical properties. Comparison of copolar correlation coefficient measurements with aircraft in situ probe measurements verifies that polarimetric measurements indicate phase transitions, and hydrometeor alignment in ice clouds. Melting layers in clouds were measured by the W-Band system on board the King Air during 1992 and 1994. Both measurements established the use of the linear depolarization ratio, LDR, to locate the melting layer using an airborne W-Band system. The measurement during 1994 allowed direct comparison of the magnitude of the copolar correlation coefficient with the values of LDR. The relation between the measurements corresponds with a predicted relationship between the two parameters for observation of particles exhibiting isotropy in the plane of polarization. Measurements of needle crystals at horizontal and vertical incidence provided further evidence that the copolar correlation coefficient values agreed with the expected response from hydrometeors possessing a preferred alignment for the side looking case, and hydrometeors without a preferred alignment for the vertical incidence case. Observation of significant specific differential phase at vertical incidence, the first reported at W-Band, corresponded to a significant increase in differential reflectivity overhead, which was most likely produced by hydrometeor alignment driven by cloud electrification. Comparison of the drop size distributions estimated using the Doppler spectra with those measured by the wingtip probes on the King Air reveals that the radar system is better suited under some liquid cloud conditions to provide microphysical measurements of the cloud or precipitation than the probes. The radiometric calibration of the radar system determines the accuracy of the drop size distribution estimate. The results presented here indicate that the procedure used to absolutely calibrate the W-Band radar system successfully characterized the reflectivity measurements to the extent required to obtain close correspondence between the radar and probe measurements of the drop size distribution.

Measurements of top quark spin observables in $$ t\\overline{t} $$ events using dilepton final states in $$ \\sqrt{s}=8 $$ TeV pp collisions with the ATLAS detector

DOE PAGES

Aaboud, M.; Aad, G.; Abbott, B.; ...

2017-03-22

Measurements of top quark spin observables in tt¯ events are presented based on 20.2 fb –1 of √s = 8 TeV proton-proton collisions recorded with the ATLAS detector at the LHC. The analysis is performed in the dilepton final state, characterised by the presence of two isolated leptons (electrons or muons). There are 15 observables, each sensitive to a different coefficient of the spin density matrix of tt¯ production, which are measured independently. Ten of these observables are measured for the first time. All of them are corrected for detector resolution and acceptance effects back to the parton and stable-particlemore » levels. The measured values of the observables at parton level are compared to Standard Model predictions at next-to-leading order in QCD. The corrected distributions at stable-particle level are presented and the means of the distributions are compared to Monte Carlo predictions. No significant deviation from the Standard Model is observed for any observable.« less

Measurements of top quark spin observables in $$ t\\overline{t} $$ events using dilepton final states in $$ \\sqrt{s}=8 $$ TeV pp collisions with the ATLAS detector

DOE Office of Scientific and Technical Information (OSTI.GOV)

Aaboud, M.; Aad, G.; Abbott, B.

Measurements of top quark spin observables in tt¯ events are presented based on 20.2 fb –1 of √s = 8 TeV proton-proton collisions recorded with the ATLAS detector at the LHC. The analysis is performed in the dilepton final state, characterised by the presence of two isolated leptons (electrons or muons). There are 15 observables, each sensitive to a different coefficient of the spin density matrix of tt¯ production, which are measured independently. Ten of these observables are measured for the first time. All of them are corrected for detector resolution and acceptance effects back to the parton and stable-particlemore » levels. The measured values of the observables at parton level are compared to Standard Model predictions at next-to-leading order in QCD. The corrected distributions at stable-particle level are presented and the means of the distributions are compared to Monte Carlo predictions. No significant deviation from the Standard Model is observed for any observable.« less

Design charts for predicting downwash angles and wake characteristics behind plain and flapped wings

NASA Technical Reports Server (NTRS)

Silverstein, Abe; Katzoff, S

1939-01-01

Equations and design charts are given for predicting the downwash angles and the wake characteristics for power-off conditions behind plain and flapped wings of the types used in modern design practice. The downwash charts cover the cases of elliptical wings and wings of taper ratios 1, 2, 3, and 5, with aspect ratios of 6, 9, and 12, having flaps covering 0, 40, 70, and 100 percent of the span. Curves of the span load distributions for all these cases are included. Data on the lift and the drag of flapped airfoil sections and curves for finding the contribution of the flap to the total wing lift for different types of flap and for the entire range of flap spans are also included. The wake width and the distribution of dynamic pressure across the wake are given in terms of the profile-drag coefficient and the distance behind the wing. A method of estimating the wake position is also given. The equations and charts are based on theory that has been shown in a previous report to be in agreement with experiment.

A first generation dynamic ingress, redistribution and transport model of soil track-in: DIRT.

PubMed

Johnson, D L

2008-12-01

This work introduces a spatially resolved quantitative model, based on conservation of mass and first order transfer kinetics, for following the transport and redistribution of outdoor soil to, and within, the indoor environment by track-in on footwear. Implementations of the DIRT model examined the influence of room size, rug area and location, shoe size, and mass transfer coefficients for smooth and carpeted floor surfaces using the ratio of mass loading on carpeted to smooth floor surfaces as a performance metric. Results showed that in the limit for large numbers of random steps the dual aspects of deposition to and track-off from the carpets govern this ratio. Using recently obtained experimental measurements, historic transport and distribution parameters, cleaning efficiencies for the different floor surfaces, and indoor dust deposition rates to provide model boundary conditions, DIRT predicts realistic floor surface loadings. The spatio-temporal variability in model predictions agrees with field observations and suggests that floor surface dust loadings are constantly in flux; steady state distributions are hardly, if ever, achieved.

Assessment of langatate material constants and temperature coefficients using SAW delay line measurements.

PubMed

Sturtevant, Blake T; Pereira da Cunha, Mauricio

2010-03-01

This paper reports on the assessment of langatate (LGT) acoustic material constants and temperature coefficients by surface acoustic wave (SAW) delay line measurements up to 130 degrees C. Based upon a full set of material constants recently reported by the authors, 7 orientations in the LGT plane with Euler angles (90 degrees, 23 degrees, Psi) were identified for testing. Each of the 7 selected orientations exhibited calculated coupling coefficients (K(2)) between 0.2% and 0.75% and also showed a large range of predicted temperature coefficient of delay (TCD) values around room temperature. Additionally, methods for estimating the uncertainty in predicted SAW propagation properties were developed and applied to SAW phase velocity and temperature coefficient of delay calculations. Starting from a purchased LGT boule, the SAW wafers used in this work were aligned, cut, ground, and polished at University of Maine facilities, followed by device fabrication and testing. Using repeated measurements of 2 devices on separate wafers for each of the 7 orientations, the room temperature SAW phase velocities were extracted with a precision of 0.1% and found to be in agreement with the predicted values. The normalized frequency change and the temperature coefficient of delay for all 7 orientations agreed with predictions within the uncertainty of the measurement and the predictions over the entire 120 degrees C temperature range measured. Two orientations, with Euler angles (90 degrees, 23 degrees, 123 degrees) and (90 degrees, 23 degrees, 119 degrees), were found to have high predicted coupling for LGT (K(2) > 0.5%) and were shown experimentally to exhibit temperature compensation in the vicinity of room temperature, with turnover temperatures at 50 and 60 degrees C, respectively.

Pattern placement errors: application of in-situ interferometer-determined Zernike coefficients in determining printed image deviations

NASA Astrophysics Data System (ADS)

Roberts, William R.; Gould, Christopher J.; Smith, Adlai H.; Rebitz, Ken

2000-08-01

Several ideas have recently been presented which attempt to measure and predict lens aberrations for new low k1 imaging systems. Abbreviated sets of Zernike coefficients have been produced and used to predict Across Chip Linewidth Variation. Empirical use of the wavefront aberrations can now be used in commercially available lithography simulators to predict pattern distortion and placement errors. Measurement and Determination of Zernike coefficients has been a significant effort of many. However the use of this data has generally been limited to matching lenses or picking best fit lense pairs. We will use wavefront aberration data collected using the Litel InspecStep in-situ Interferometer as input data for Prolith/3D to model and predict pattern placement errors and intrafield overlay variation. Experiment data will be collected and compared to the simulated predictions.

Anomalous behavior of poly(ethylene glycol) p-tert-octylphenyl ether (Triton X-100) in the water-cyclohexane system

NASA Astrophysics Data System (ADS)

Chernysheva, M. G.; Tyasto, Z. A.; Badun, G. A.

2009-02-01

The distribution of Triton X-100 nonionic surfactant in the water-cyclohexane system was investigated by the scintillating phase method. It was shown that an increase in the distribution coefficient as the volume ratio between the aqueous and organic phases grew was explained by the presence in Triton X-100 of homologues with different numbers of ethoxyethyl groups and with the distribution coefficients between the phases different by many times. For the real composition of Triton X-100, distribution coefficients of components of the surfactant were estimated, and the behavior of the surfactant in the system under consideration was simulated; the results were in close agreement with the experimental data.

Using the range to calculate the coefficient of variation.

PubMed

Rhiel, G Steven

2004-12-01

In this research a coefficient of variation (CVhigh-low) is calculated from the highest and lowest values in a set of data. Use of CVhigh-low when the population is normal, leptokurtic, and skewed is discussed. The statistic is the most effective when sampling from the normal distribution. With the leptokurtic distributions, CVhigh-low works well for comparing the relative variability between two or more distributions but does not provide a very "good" point estimate of the population coefficient of variation. With skewed distributions CVhigh-low works well in identifying which data set has the more relative variation but does not specify how much difference there is in the variation. It also does not provide a "good" point estimate.

Content Based Image Retrieval based on Wavelet Transform coefficients distribution

PubMed Central

Lamard, Mathieu; Cazuguel, Guy; Quellec, Gwénolé; Bekri, Lynda; Roux, Christian; Cochener, Béatrice

2007-01-01

In this paper we propose a content based image retrieval method for diagnosis aid in medical fields. We characterize images without extracting significant features by using distribution of coefficients obtained by building signatures from the distribution of wavelet transform. The research is carried out by computing signature distances between the query and database images. Several signatures are proposed; they use a model of wavelet coefficient distribution. To enhance results, a weighted distance between signatures is used and an adapted wavelet base is proposed. Retrieval efficiency is given for different databases including a diabetic retinopathy, a mammography and a face database. Results are promising: the retrieval efficiency is higher than 95% for some cases using an optimization process. PMID:18003013

Prediction of Aerodynamic Coefficients using Neural Networks for Sparse Data

NASA Technical Reports Server (NTRS)

Rajkumar, T.; Bardina, Jorge; Clancy, Daniel (Technical Monitor)

2002-01-01

Basic aerodynamic coefficients are modeled as functions of angles of attack and sideslip with vehicle lateral symmetry and compressibility effects. Most of the aerodynamic parameters can be well-fitted using polynomial functions. In this paper a fast, reliable way of predicting aerodynamic coefficients is produced using a neural network. The training data for the neural network is derived from wind tunnel test and numerical simulations. The coefficients of lift, drag, pitching moment are expressed as a function of alpha (angle of attack) and Mach number. The results produced from preliminary neural network analysis are very good.

Impact Assessment of Mikania Micrantha on Land Cover and Maxent Modeling to Predict its Potential Invasion Sites

NASA Astrophysics Data System (ADS)

Baidar, T.; Shrestha, A. B.; Ranjit, R.; Adhikari, R.; Ghimire, S.; Shrestha, N.

2017-05-01

Mikania micrantha is one of the major invasive alien plant species in tropical moist forest regions of Asia including Nepal. Recently, this weed is spreading at an alarming rate in Chitwan National Park (CNP) and threatening biodiversity. This paper aims to assess the impacts of Mikania micrantha on different land cover and to predict potential invasion sites in CNP using Maxent model. Primary data for this were presence point coordinates and perceived Mikania micrantha cover collected through systematic random sampling technique. Rapideye image, Shuttle Radar Topographic Mission data and bioclimatic variables were acquired as secondary data. Mikania micrantha distribution maps were prepared by overlaying the presence points on image classified by object based image analysis. The overall accuracy of classification was 90 % with Kappa coefficient 0.848. A table depicting the number of sample points in each land cover with respective Mikania micrantha coverage was extracted from the distribution maps to show the impact. The riverine forest was found to be the most affected land cover with 85.98 % presence points and sal forest was found to be very less affected with only 17.02 % presence points. Maxent modeling predicted the areas near the river valley as the potential invasion sites with statistically significant Area Under the Receiver Operating Curve (AUC) value of 0.969. Maximum temperature of warmest month and annual precipitation were identified as the predictor variables that contribute the most to Mikania micrantha's potential distribution.

Intravoxel water diffusion heterogeneity MR imaging of nasopharyngeal carcinoma using stretched exponential diffusion model.

PubMed

Lai, Vincent; Lee, Victor Ho Fun; Lam, Ka On; Sze, Henry Chun Kin; Chan, Queenie; Khong, Pek Lan

2015-06-01

To determine the utility of stretched exponential diffusion model in characterisation of the water diffusion heterogeneity in different tumour stages of nasopharyngeal carcinoma (NPC). Fifty patients with newly diagnosed NPC were prospectively recruited. Diffusion-weighted MR imaging was performed using five b values (0-2,500 s/mm(2)). Respective stretched exponential parameters (DDC, distributed diffusion coefficient; and alpha (α), water heterogeneity) were calculated. Patients were stratified into low and high tumour stage groups based on the American Joint Committee on Cancer (AJCC) staging for determination of the predictive powers of DDC and α using t test and ROC curve analyses. The mean ± standard deviation values were DDC = 0.692 ± 0.199 (×10(-3) mm(2)/s) for low stage group vs 0.794 ± 0.253 (×10(-3) mm(2)/s) for high stage group; α = 0.792 ± 0.145 for low stage group vs 0.698 ± 0.155 for high stage group. α was significantly lower in the high stage group while DDC was negatively correlated. DDC and α were both reliable independent predictors (p < 0.001), with α being more powerful. Optimal cut-off values were (sensitivity, specificity, positive likelihood ratio, negative likelihood ratio) DDC = 0.692 × 10(-3) mm(2)/s (94.4 %, 64.3 %, 2.64, 0.09), α = 0.720 (72.2 %, 100 %, -, 0.28). The heterogeneity index α is robust and can potentially help in staging and grading prediction in NPC. • Stretched exponential diffusion models can help in tissue characterisation in nasopharyngeal carcinoma • α and distributed diffusion coefficient (DDC) are negatively correlated • α is a robust heterogeneity index marker • α can potentially help in staging and grading prediction.

Simultaneous inversion of intrinsic and scattering attenuation parameters incorporating multiple scattering effect

NASA Astrophysics Data System (ADS)

Ogiso, M.

2017-12-01

Heterogeneous attenuation structure is important for not only understanding the earth structure and seismotectonics, but also ground motion prediction. Attenuation of ground motion in high frequency range is often characterized by the distribution of intrinsic and scattering attenuation parameters (intrinsic Q and scattering coefficient). From the viewpoint of ground motion prediction, both intrinsic and scattering attenuation affect the maximum amplitude of ground motion while scattering attenuation also affect the duration time of ground motion. Hence, estimation of both attenuation parameters will lead to sophisticate the ground motion prediction. In this study, we try to estimate both parameters in southwestern Japan in a tomographic manner. We will conduct envelope fitting of seismic coda since coda has sensitivity to both intrinsic attenuation and scattering coefficients. Recently, Takeuchi (2016) successfully calculated differential envelope when these parameters have fluctuations. We adopted his equations to calculate partial derivatives of these parameters since we did not need to assume homogeneous velocity structure. Matrix for inversion of structural parameters would become too huge to solve in a straightforward manner. Hence, we adopted ART-type Bayesian Reconstruction Method (Hirahara, 1998) to project the difference of envelopes to structural parameters iteratively. We conducted checkerboard reconstruction test. We assumed checkerboard pattern of 0.4 degree interval in horizontal direction and 20 km in depth direction. Reconstructed structures well reproduced the assumed pattern in shallower part while not in deeper part. Since the inversion kernel has large sensitivity around source and stations, resolution in deeper part would be limited due to the sparse distribution of earthquakes. To apply the inversion method which described above to actual waveforms, we have to correct the effects of source and site amplification term. We consider these issues to estimate the actual intrinsic and scattering structures of the target region.Acknowledgment We used the waveforms of Hi-net, NIED. This study was supported by the Earthquake Research Institute of the University of Tokyo cooperative research program.

Seismic AVO response character of coal bed methane content in the Zhaozhuang coalmine of Qinshui Basin,China

NASA Astrophysics Data System (ADS)

Zou, G.

2016-12-01

Coal bed methane content (CBMC) is a measure of the quantity of methane stored in coals, and is important for many applications, including the quantitative assessment of methane resources and methane extraction and control. The coal bed methane content (CBMC) in the Zhaozhuang coalmine of Jincheng coalfield, northwestern Qinshui Basin, is studied based on seismic data and well-logs together with laboratory measurements. The amplitude versus offset (AVO) response from the log characteristics was analyzed and the seismic amplitude, after relative preserved amplitude processing, was corrected to maintain the relative amplitude characteristics. The AVO attributes were calculated based on AVO theory and the statistical relationship between AVO attributes and CBMC was established and used to predict the CBMC. The results show that the Shuey approximation has better adaptability according to the Zoeppritz equation result; the designed fold number for an ordinary seismic data is insufficient for pre-stack data regarding the signal to noise ratio (SNR). Therefore a larger grid analysis was created in order to improve the SNR. The velocity field created by logging is better than that created by stack velocity in both accuracy and effectiveness. A reasonable distribution of the amplitude versus offset (AVO) attributes can be facilitated by taking the AVO response from logging as a standard for calibrating the amplitude distribution. Some AVO attributes have a close relationship with CBMC. The worst attribute is weighted polarization product, for which the correlation coefficient is 0.23; and the best attribute is the intercept, of which the correlation coefficient is -0.79. CBMC predicted by AVO attributes is better overall than that predicted by direct interpolation of CBMC; the validation error of the former is 12.5%, which is lower than that of the latter. CBMC of this area ranges from 7.1 m3/t to 21.4 m3/t.

SU-E-I-07: An Improved Technique for Scatter Correction in PET

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lin, S; Wang, Y; Lue, K

2014-06-01

Purpose: In positron emission tomography (PET), the single scatter simulation (SSS) algorithm is widely used for scatter estimation in clinical scans. However, bias usually occurs at the essential steps of scaling the computed SSS distribution to real scatter amounts by employing the scatter-only projection tail. The bias can be amplified when the scatter-only projection tail is too small, resulting in incorrect scatter correction. To this end, we propose a novel scatter calibration technique to accurately estimate the amount of scatter using pre-determined scatter fraction (SF) function instead of the employment of scatter-only tail information. Methods: As the SF depends onmore » the radioactivity distribution and the attenuating material of the patient, an accurate theoretical relation cannot be devised. Instead, we constructed an empirical transformation function between SFs and average attenuation coefficients based on a serious of phantom studies with different sizes and materials. From the average attenuation coefficient, the predicted SFs were calculated using empirical transformation function. Hence, real scatter amount can be obtained by scaling the SSS distribution with the predicted SFs. The simulation was conducted using the SimSET. The Siemens Biograph™ 6 PET scanner was modeled in this study. The Software for Tomographic Image Reconstruction (STIR) was employed to estimate the scatter and reconstruct images. The EEC phantom was adopted to evaluate the performance of our proposed technique. Results: The scatter-corrected image of our method demonstrated improved image contrast over that of SSS. For our technique and SSS of the reconstructed images, the normalized standard deviation were 0.053 and 0.182, respectively; the root mean squared errors were 11.852 and 13.767, respectively. Conclusion: We have proposed an alternative method to calibrate SSS (C-SSS) to the absolute scatter amounts using SF. This method can avoid the bias caused by the insufficient tail information and therefore improve the accuracy of scatter estimation.« less

ToxiM: A Toxicity Prediction Tool for Small Molecules Developed Using Machine Learning and Chemoinformatics Approaches.

PubMed

Sharma, Ashok K; Srivastava, Gopal N; Roy, Ankita; Sharma, Vineet K

2017-01-01

The experimental methods for the prediction of molecular toxicity are tedious and time-consuming tasks. Thus, the computational approaches could be used to develop alternative methods for toxicity prediction. We have developed a tool for the prediction of molecular toxicity along with the aqueous solubility and permeability of any molecule/metabolite. Using a comprehensive and curated set of toxin molecules as a training set, the different chemical and structural based features such as descriptors and fingerprints were exploited for feature selection, optimization and development of machine learning based classification and regression models. The compositional differences in the distribution of atoms were apparent between toxins and non-toxins, and hence, the molecular features were used for the classification and regression. On 10-fold cross-validation, the descriptor-based, fingerprint-based and hybrid-based classification models showed similar accuracy (93%) and Matthews's correlation coefficient (0.84). The performances of all the three models were comparable (Matthews's correlation coefficient = 0.84-0.87) on the blind dataset. In addition, the regression-based models using descriptors as input features were also compared and evaluated on the blind dataset. Random forest based regression model for the prediction of solubility performed better ( R 2 = 0.84) than the multi-linear regression (MLR) and partial least square regression (PLSR) models, whereas, the partial least squares based regression model for the prediction of permeability (caco-2) performed better ( R 2 = 0.68) in comparison to the random forest and MLR based regression models. The performance of final classification and regression models was evaluated using the two validation datasets including the known toxins and commonly used constituents of health products, which attests to its accuracy. The ToxiM web server would be a highly useful and reliable tool for the prediction of toxicity, solubility, and permeability of small molecules.

ToxiM: A Toxicity Prediction Tool for Small Molecules Developed Using Machine Learning and Chemoinformatics Approaches

PubMed Central

Sharma, Ashok K.; Srivastava, Gopal N.; Roy, Ankita; Sharma, Vineet K.

2017-01-01

The experimental methods for the prediction of molecular toxicity are tedious and time-consuming tasks. Thus, the computational approaches could be used to develop alternative methods for toxicity prediction. We have developed a tool for the prediction of molecular toxicity along with the aqueous solubility and permeability of any molecule/metabolite. Using a comprehensive and curated set of toxin molecules as a training set, the different chemical and structural based features such as descriptors and fingerprints were exploited for feature selection, optimization and development of machine learning based classification and regression models. The compositional differences in the distribution of atoms were apparent between toxins and non-toxins, and hence, the molecular features were used for the classification and regression. On 10-fold cross-validation, the descriptor-based, fingerprint-based and hybrid-based classification models showed similar accuracy (93%) and Matthews's correlation coefficient (0.84). The performances of all the three models were comparable (Matthews's correlation coefficient = 0.84–0.87) on the blind dataset. In addition, the regression-based models using descriptors as input features were also compared and evaluated on the blind dataset. Random forest based regression model for the prediction of solubility performed better (R2 = 0.84) than the multi-linear regression (MLR) and partial least square regression (PLSR) models, whereas, the partial least squares based regression model for the prediction of permeability (caco-2) performed better (R2 = 0.68) in comparison to the random forest and MLR based regression models. The performance of final classification and regression models was evaluated using the two validation datasets including the known toxins and commonly used constituents of health products, which attests to its accuracy. The ToxiM web server would be a highly useful and reliable tool for the prediction of toxicity, solubility, and permeability of small molecules. PMID:29249969

Applying geographic profiling used in the field of criminology for predicting the nest locations of bumble bees.

PubMed

Suzuki-Ohno, Yukari; Inoue, Maki N; Ohno, Kazunori

2010-07-21

We tested whether geographic profiling (GP) can predict multiple nest locations of bumble bees. GP was originally developed in the field of criminology for predicting the area where an offender most likely resides on the basis of the actual crime sites and the predefined probability of crime interaction. The predefined probability of crime interaction in the GP model depends on the distance of a site from an offender's residence. We applied GP for predicting nest locations, assuming that foraging and nest sites were the crime sites and the offenders' residences, respectively. We identified the foraging and nest sites of the invasive species Bombus terrestris in 2004, 2005, and 2006. We fitted GP model coefficients to the field data of the foraging and nest sites, and used GP with the fitting coefficients. GP succeeded in predicting about 10-30% of actual nests. Sensitivity analysis showed that the predictability of the GP model mainly depended on the coefficient value of buffer zone, the distance at the mode of the foraging probability. GP will be able to predict the nest locations of bumble bees in other area by using the fitting coefficient values measured in this study. It will be possible to further improve the predictability of the GP model by considering food site preference and nest density. (c) 2010 Elsevier Ltd. All rights reserved.

Characteristics of heat exchange in the region of injection into a supersonic high-temperature flow

NASA Technical Reports Server (NTRS)

Bakirov, F. G.; Shaykhutdinov, Z. G.

1985-01-01

An experimental investigation of the local heat transfer coefficient distribution during gas injection into the supersonic-flow portion of a Laval nozzle is discussed. The controlling dimensionless parameters of the investigated process are presented in terms of a generalized relation for the maximum value of the heat transfer coefficient in the nozzle cross section behind the injection hole. Data on the heat transfer coefficient variation along the nozzle length as a function of gas injection rate are also presented, along with the heat transfer coefficient distribution over a cross section of the nozzle.

Distribution of health care resources in Mongolia using the Gini coefficient.

PubMed

Erdenee, Oyunchimeg; Paramita, Sekar Ayu; Yamazaki, Chiho; Koyama, Hiroshi

2017-08-29

Attaining the perfect balance of health care resources is probably impracticable; however, it is possible to achieve improvements in the distribution of these resources. In terms of the distribution of health resources, equal access to these resources would make health services available to all people. The aim of this study was to compare the distributions of health care resources in urban, suburban, and rural areas of Mongolia. We compared urban and rural areas using the Mann-Whitney U test and further investigated the distribution equality of physicians, nurses, and hospital beds throughout Mongolia using the Gini coefficient-a common measure of distribution derived from the Lorenz curve. Two indicators were calculated: the distribution per 10 000 population and the distribution per 1000 km 2 area. Urban and rural areas were significantly different only in the distribution of physicians per population. However, in terms of the distribution per area, there were statistical differences in physicians, nurses, and hospital beds. We also found that distributions per population unit were equal, with Gini coefficients for physicians, nurses, and hospital beds of 0.18, 0.07, and 0.06, respectively. Distributions per area unit were highly unequal, with Gini coefficients for physicians, nurses, and hospital beds of 0.74, 0.67, and 0.69, respectively. Although the distributions of health care resources per population were adequate for the population size, a striking difference was found in terms of the distributions per geographical area. Because of the nomadic lifestyle of rural and remote populations in Mongolia, geographical imbalances need to be taken into consideration when formulating policy, rather than simply increasing the number of health care resources.

A comparison of adaptive sampling designs and binary spatial models: A simulation study using a census of Bromus inermis

USGS Publications Warehouse

Irvine, Kathryn M.; Thornton, Jamie; Backus, Vickie M.; Hohmann, Matthew G.; Lehnhoff, Erik A.; Maxwell, Bruce D.; Michels, Kurt; Rew, Lisa

2013-01-01

Commonly in environmental and ecological studies, species distribution data are recorded as presence or absence throughout a spatial domain of interest. Field based studies typically collect observations by sampling a subset of the spatial domain. We consider the effects of six different adaptive and two non-adaptive sampling designs and choice of three binary models on both predictions to unsampled locations and parameter estimation of the regression coefficients (species–environment relationships). Our simulation study is unique compared to others to date in that we virtually sample a true known spatial distribution of a nonindigenous plant species, Bromus inermis. The census of B. inermis provides a good example of a species distribution that is both sparsely (1.9 % prevalence) and patchily distributed. We find that modeling the spatial correlation using a random effect with an intrinsic Gaussian conditionally autoregressive prior distribution was equivalent or superior to Bayesian autologistic regression in terms of predicting to un-sampled areas when strip adaptive cluster sampling was used to survey B. inermis. However, inferences about the relationships between B. inermis presence and environmental predictors differed between the two spatial binary models. The strip adaptive cluster designs we investigate provided a significant advantage in terms of Markov chain Monte Carlo chain convergence when trying to model a sparsely distributed species across a large area. In general, there was little difference in the choice of neighborhood, although the adaptive king was preferred when transects were randomly placed throughout the spatial domain.

Structural and optical behavior due to thermal effects in end-pumped Yb:YAG disk lasers.

PubMed

Sazegari, Vahid; Milani, Mohammad Reza Jafari; Jafari, Ahmad Khayat

2010-12-20

We employ a Monte Carlo ray-tracing code along with the ANSYS package to predict the optical and structural behavior in end-pumped CW Yb:YAG disk lasers. The presence of inhomogeneous temperature, stress, and strain distributions is responsible for many deleterious effects for laser action through disk fracture, strain-induced birefringence, and thermal lensing. The thermal lensing, in turn, results in the optical phase distortion in solid-state lasers. Furthermore, the dependence of optical phase distortion on variables such as the heat transfer coefficient, the cooling fluid temperature, and crystal thickness is discussed.

Improved Gas Metal Arc Welding Multi-Physics Process Model and Its Application to MIL A46100 Armor-Grade Steel Butt-welds

DTIC Science & Technology

2014-01-01

expansion a 1/K 11e–6-12e–6 Specific heat C p J/kg K 440-520 Thermal conductivity k W/m K 35-50 Heat transfer coefficient h W/m2 K 45 Sink temperature...filler-metal consumable electrode to the weld; third, prediction of the temporal evolution and the spatial distribution of thermal and mechanical...the thermal The current issue and full text archive of this journal is available at www.emeraldinsight.com/1573-6105.htm Received 20 May 2013 Revised 13

The Study of Rain Specific Attenuation for the Prediction of Satellite Propagation in Malaysia

NASA Astrophysics Data System (ADS)

Mandeep, J. S.; Ng, Y. Y.; Abdullah, H.; Abdullah, M.

2010-06-01

Specific attenuation is the fundamental quantity in the calculation of rain attenuation for terrestrial path and slant paths representing as rain attenuation per unit distance (dB/km). Specific attenuation is an important element in developing the predicted rain attenuation model. This paper deals with the empirical determination of the power law coefficients which allow calculating the specific attenuation in dB/km from the knowledge of the rain rate in mm/h. The main purpose of the paper is to obtain the coefficients of k and α of power law relationship between specific attenuation. Three years (from 1st January 2006 until 31st December 2008) rain gauge and beacon data taken from USM, Nibong Tebal have been used to do the empirical procedure analysis of rain specific attenuation. The data presented are semi-empirical in nature. A year-to-year variation of the coefficients has been indicated and the empirical measured data was compared with ITU-R provided regression coefficient. The result indicated that the USM empirical measured data was significantly vary from ITU-R predicted value. Hence, ITU-R recommendation for regression coefficients of rain specific attenuation is not suitable for predicting rain attenuation at Malaysia.

On-line consolidation of thermoplastic composites

NASA Astrophysics Data System (ADS)

Shih, Po-Jen

An on-line consolidation system, which includes a computer-controlled filament winding machine and a consolidation head assembly, has been designed and constructed to fabricate composite parts from thermoplastic towpregs. A statistical approach was used to determine the significant processing parameters and their effect on the mechanical and physical properties of composite cylinders fabricated by on-line consolidation. A central composite experimental design was used to select the processing conditions for manufacturing the composite cylinders. The thickness, density, void content, degree of crystallinity and interlaminar shear strength (ILSS) were measured for each composite cylinder. Micrographs showed that complete intimate contact and uniform fiber-matrix distribution were achieved. The degree of crystallinity of the cylinders was found to be in the range of 25-30%. Under optimum processing conditions, an ILSS of 58 MPa and a void content of <1% were achieved for APC-2 (PEEK/Carbon fiber) composite cylinders. An in-situ measurement system which uses a slip ring assembly and a computer data acquisition system was developed to obtain temperature data during winding. Composite cylinders were manufactured with eight K-type thermocouples installed in various locations inside the cylinder. The temperature distribution inside the composite cylinder during winding was measured for different processing conditions. ABAQUS finite element models of the different processes that occur during on-line consolidation were constructed. The first model was used to determine the convective heat transfer coefficient for the hot-air heat source. A convective heat transfer coefficient of 260 w/msp{2°}K was obtained by matching the calculated temperature history to the in-situ measurement data. To predict temperature distribution during winding an ABAQUS winding simulation model was developed. The winding speed was modeled by incrementally moving the convective boundary conditions around the outer surface of the composite cylinder. A towpreg heating model was constructed to predict the temperature distribution on the cross section of the incoming towpreg. For the process-induced thermal stresses analysis, a thermoelastic finite element model was constructed. Using the temperature history obtained from thermal analysis as the initial conditions, the thermal stresses during winding and cooling were investigated.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chen, Hang, E-mail: hangchen@mit.edu; Thill, Peter; Cao, Jianshu

In biochemical systems, intrinsic noise may drive the system switch from one stable state to another. We investigate how kinetic switching between stable states in a bistable network is influenced by dynamic disorder, i.e., fluctuations in the rate coefficients. Using the geometric minimum action method, we first investigate the optimal transition paths and the corresponding minimum actions based on a genetic toggle switch model in which reaction coefficients draw from a discrete probability distribution. For the continuous probability distribution of the rate coefficient, we then consider two models of dynamic disorder in which reaction coefficients undergo different stochastic processes withmore » the same stationary distribution. In one, the kinetic parameters follow a discrete Markov process and in the other they follow continuous Langevin dynamics. We find that regulation of the parameters modulating the dynamic disorder, as has been demonstrated to occur through allosteric control in bistable networks in the immune system, can be crucial in shaping the statistics of optimal transition paths, transition probabilities, and the stationary probability distribution of the network.« less

Analytical equation for outflow along the flow in a perforated fluid distribution pipe

PubMed Central

Liu, Huanfang; Lv, Hongxing; Jin, Jin

2017-01-01

Perforated fluid distribution pipes have been widely used in agriculture, water supply and drainage, ventilation, the chemical industry, and other sectors. The momentum equation for variable mass flow with a variable exchange coefficient and variable friction coefficient was developed by using the momentum conservation method under the condition of a certain slope. The change laws of the variable momentum exchange coefficient and the variable resistance coefficient along the flow were analyzed, and the function of the momentum exchange coefficient was given. According to the velocity distribution of the power function, the momentum equation of variable mass flow was solved for different Reynolds numbers. The analytical solution contains components of pressure, gravity, friction and momentum and reflects the influence of various factors on the pressure distribution along the perforated pipe. The calculated results of the analytical solution were compared with the experimental values of the study by Jin et al. 1984 and Wang et al. 2001 with the mean errors 8.2%, 3.8% and 2.7%, and showed that the analytical solution of the variable mass momentum equation was qualitatively and quantitatively consistent with the experimental results. PMID:29065112

Distributional behavior of diffusion coefficients obtained by single trajectories in annealed transit time model

NASA Astrophysics Data System (ADS)

Akimoto, Takuma; Yamamoto, Eiji

2016-12-01

Local diffusion coefficients in disordered systems such as spin glass systems and living cells are highly heterogeneous and may change over time. Such a time-dependent and spatially heterogeneous environment results in irreproducibility of single-particle-tracking measurements. Irreproducibility of time-averaged observables has been theoretically studied in the context of weak ergodicity breaking in stochastic processes. Here, we provide rigorous descriptions of equilibrium and non-equilibrium diffusion processes for the annealed transit time model, which is a heterogeneous diffusion model in living cells. We give analytical solutions for the mean square displacement (MSD) and the relative standard deviation of the time-averaged MSD for equilibrium and non-equilibrium situations. We find that the time-averaged MSD grows linearly with time and that the time-averaged diffusion coefficients are intrinsically random (irreproducible) even in the long-time measurements in non-equilibrium situations. Furthermore, the distribution of the time-averaged diffusion coefficients converges to a universal distribution in the sense that it does not depend on initial conditions. Our findings pave the way for a theoretical understanding of distributional behavior of the time-averaged diffusion coefficients in disordered systems.

Modelling population distribution using remote sensing imagery and location-based data

NASA Astrophysics Data System (ADS)

Song, J.; Prishchepov, A. V.

2017-12-01

Detailed spatial distribution of population density is essential for city studies such as urban planning, environmental pollution and city emergency, even estimate pressure on the environment and human exposure and risks to health. However, most of the researches used census data as the detailed dynamic population distribution are difficult to acquire, especially in microscale research. This research describes a method using remote sensing imagery and location-based data to model population distribution at the function zone level. Firstly, urban functional zones within a city were mapped by high-resolution remote sensing images and POIs. The workflow of functional zones extraction includes five parts: (1) Urban land use classification. (2) Segmenting images in built-up area. (3) Identification of functional segments by POIs. (4) Identification of functional blocks by functional segmentation and weight coefficients. (5) Assessing accuracy by validation points. The result showed as Fig.1. Secondly, we applied ordinary least square and geographically weighted regression to assess spatial nonstationary relationship between light digital number (DN) and population density of sampling points. The two methods were employed to predict the population distribution over the research area. The R²of GWR model were in the order of 0.7 and typically showed significant variations over the region than traditional OLS model. The result showed as Fig.2.Validation with sampling points of population density demonstrated that the result predicted by the GWR model correlated well with light value. The result showed as Fig.3. Results showed: (1) Population density is not linear correlated with light brightness using global model. (2) VIIRS night-time light data could estimate population density integrating functional zones at city level. (3) GWR is a robust model to map population distribution, the adjusted R2 of corresponding GWR models were higher than the optimal OLS models, confirming that GWR models demonstrate better prediction accuracy. So this method provide detailed population density information for microscale citizen studies.

Woody plants and the prediction of climate-change impacts on bird diversity.

PubMed

Kissling, W D; Field, R; Korntheuer, H; Heyder, U; Böhning-Gaese, K

2010-07-12

Current methods of assessing climate-induced shifts of species distributions rarely account for species interactions and usually ignore potential differences in response times of interacting taxa to climate change. Here, we used species-richness data from 1005 breeding bird and 1417 woody plant species in Kenya and employed model-averaged coefficients from regression models and median climatic forecasts assembled across 15 climate-change scenarios to predict bird species richness under climate change. Forecasts assuming an instantaneous response of woody plants and birds to climate change suggested increases in future bird species richness across most of Kenya whereas forecasts assuming strongly lagged woody plant responses to climate change indicated a reversed trend, i.e. reduced bird species richness. Uncertainties in predictions of future bird species richness were geographically structured, mainly owing to uncertainties in projected precipitation changes. We conclude that assessments of future species responses to climate change are very sensitive to current uncertainties in regional climate-change projections, and to the inclusion or not of time-lagged interacting taxa. We expect even stronger effects for more specialized plant-animal associations. Given the slow response time of woody plant distributions to climate change, current estimates of future biodiversity of many animal taxa may be both biased and too optimistic.

Determination of fluence rate and temperature distributions in the rat brain; implications for photodynamic therapy.

PubMed

Angell-Petersen, Even; Hirschberg, Henry; Madsen, Steen J

2007-01-01

Light and heat distributions are measured in a rat glioma model used in photodynamic therapy. A fiber delivering 632-nm light is fixed in the brain of anesthetized BDIX rats. Fluence rates are measured using calibrated isotropic probes that are positioned stereotactically. Mathematical models are then used to derive tissue optical properties, enabling calculation of fluence rate distributions for general tumor and light application geometries. The fluence rates in tumor-free brains agree well with the models based on diffusion theory and Monte Carlo simulation. In both cases, the best fit is found for absorption and reduced scattering coefficients of 0.57 and 28 cm(-1), respectively. In brains with implanted BT(4)C tumors, a discrepancy between diffusion and Monte Carlo-derived two-layer models is noted. Both models suggest that tumor tissue has higher absorption and less scattering than normal brain. Temperatures are measured by inserting thermocouples directly into tumor-free brains. A model based on diffusion theory and the bioheat equation is found to be in good agreement with the experimental data and predict a thermal penetration depth of 0.60 cm in normal rat brain. The predicted parameters can be used to estimate the fluences, fluence rates, and temperatures achieved during photodynamic therapy.

Impedance computed tomography using an adaptive smoothing coefficient algorithm.

PubMed

Suzuki, A; Uchiyama, A

2001-01-01

In impedance computed tomography, a fixed coefficient regularization algorithm has been frequently used to improve the ill-conditioning problem of the Newton-Raphson algorithm. However, a lot of experimental data and a long period of computation time are needed to determine a good smoothing coefficient because a good smoothing coefficient has to be manually chosen from a number of coefficients and is a constant for each iteration calculation. Thus, sometimes the fixed coefficient regularization algorithm distorts the information or fails to obtain any effect. In this paper, a new adaptive smoothing coefficient algorithm is proposed. This algorithm automatically calculates the smoothing coefficient from the eigenvalue of the ill-conditioned matrix. Therefore, the effective images can be obtained within a short computation time. Also the smoothing coefficient is automatically adjusted by the information related to the real resistivity distribution and the data collection method. In our impedance system, we have reconstructed the resistivity distributions of two phantoms using this algorithm. As a result, this algorithm only needs one-fifth the computation time compared to the fixed coefficient regularization algorithm. When compared to the fixed coefficient regularization algorithm, it shows that the image is obtained more rapidly and applicable in real-time monitoring of the blood vessel.

A quantitative property-property relationship for the internal diffusion coefficients of organic compounds in solid materials.

PubMed

Huang, L; Fantke, P; Ernstoff, A; Jolliet, O

2017-11-01

Indoor releases of organic chemicals encapsulated in solid materials are major contributors to human exposures and are directly related to the internal diffusion coefficient in solid materials. Existing correlations to estimate the diffusion coefficient are only valid for a limited number of chemical-material combinations. This paper develops and evaluates a quantitative property-property relationship (QPPR) to predict diffusion coefficients for a wide range of organic chemicals and materials. We first compiled a training dataset of 1103 measured diffusion coefficients for 158 chemicals in 32 consolidated material types. Following a detailed analysis of the temperature influence, we developed a multiple linear regression model to predict diffusion coefficients as a function of chemical molecular weight (MW), temperature, and material type (adjusted R 2 of .93). The internal validations showed the model to be robust, stable and not a result of chance correlation. The external validation against two separate prediction datasets demonstrated the model has good predicting ability within its applicability domain (Rext2>.8), namely MW between 30 and 1178 g/mol and temperature between 4 and 180°C. By covering a much wider range of organic chemicals and materials, this QPPR facilitates high-throughput estimates of human exposures for chemicals encapsulated in solid materials. © 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Discrete Element Method Simulations of the Inter-Particle Contact Parameters for the Mono-Sized Iron Ore Particles

PubMed Central

Li, Tongqing; Peng, Yuxing; Zhu, Zhencai; Zou, Shengyong; Yin, Zixin

2017-01-01

Aiming at predicting what happens in reality inside mills, the contact parameters of iron ore particles for discrete element method (DEM) simulations should be determined accurately. To allow the irregular shape to be accurately determined, the sphere clump method was employed in modelling the particle shape. The inter-particle contact parameters were systematically altered whilst the contact parameters between the particle and wall were arbitrarily assumed, in order to purely assess its impact on the angle of repose for the mono-sized iron ore particles. Results show that varying the restitution coefficient over the range considered does not lead to any obvious difference in the angle of repose, but the angle of repose has strong sensitivity to the rolling/static friction coefficient. The impacts of the rolling/static friction coefficient on the angle of repose are interrelated, and increasing the inter-particle rolling/static friction coefficient can evidently increase the angle of repose. However, the impact of the static friction coefficient is more profound than that of the rolling friction coefficient. Finally, a predictive equation is established and a very close agreement between the predicted and simulated angle of repose is attained. This predictive equation can enormously shorten the inter-particle contact parameters calibration time that can help in the implementation of DEM simulations. PMID:28772880

Analytical performance specifications for changes in assay bias (Δbias) for data with logarithmic distributions as assessed by effects on reference change values.

PubMed

Petersen, Per H; Lund, Flemming; Fraser, Callum G; Sölétormos, György

2016-11-01

Background The distributions of within-subject biological variation are usually described as coefficients of variation, as are analytical performance specifications for bias, imprecision and other characteristics. Estimation of specifications required for reference change values is traditionally done using relationship between the batch-related changes during routine performance, described as Δbias, and the coefficients of variation for analytical imprecision (CV A ): the original theory is based on standard deviations or coefficients of variation calculated as if distributions were Gaussian. Methods The distribution of between-subject biological variation can generally be described as log-Gaussian. Moreover, recent analyses of within-subject biological variation suggest that many measurands have log-Gaussian distributions. In consequence, we generated a model for the estimation of analytical performance specifications for reference change value, with combination of Δbias and CV A based on log-Gaussian distributions of CV I as natural logarithms. The model was tested using plasma prolactin and glucose as examples. Results Analytical performance specifications for reference change value generated using the new model based on log-Gaussian distributions were practically identical with the traditional model based on Gaussian distributions. Conclusion The traditional and simple to apply model used to generate analytical performance specifications for reference change value, based on the use of coefficients of variation and assuming Gaussian distributions for both CV I and CV A , is generally useful.

Pharmaceuticals' sorptions relative to properties of thirteen different soils.

PubMed

Kodešová, Radka; Grabic, Roman; Kočárek, Martin; Klement, Aleš; Golovko, Oksana; Fér, Miroslav; Nikodem, Antonín; Jakšík, Ondřej

2015-04-01

Transport of human and veterinary pharmaceuticals in soils and consequent ground-water contamination are influenced by many factors, including compound sorption on soil particles. Here we evaluate the sorption isotherms for 7 pharmaceuticals on 13 soils, described by Freundlich equations, and assess the impact of soil properties on various pharmaceuticals' sorption on soils. Sorption of ionizable pharmaceuticals was, in many cases, highly affected by soil pH. The sorption coefficient of sulfamethoxazole was negatively correlated to soil pH, and thus positively related to hydrolytic acidity and exchangeable acidity. Sorption coefficients for clindamycin and clarithromycin were positively related to soil pH and thus negatively related to hydrolytic acidity and exchangeable acidity, and positively related to base cation saturation. The sorption coefficients for the remaining pharmaceuticals (trimethoprim, metoprolol, atenolol, and carbamazepine) were also positively correlated with the base cation saturation and cation exchange capacity. Positive correlations between sorption coefficients and clay content were found for clindamycin, clarithromycin, atenolol, and metoprolol. Positive correlations between sorption coefficients and organic carbon content were obtained for trimethoprim and carbamazepine. Pedotransfer rules for predicting sorption coefficients of various pharmaceuticals included hydrolytic acidity (sulfamethoxazole), organic carbon content (trimethoprimand carbamazepine), base cation saturation (atenolol and metoprolol), exchangeable acidity and clay content (clindamycin), and soil active pH and clay content (clarithromycin). Pedotransfer rules, predicting the Freundlich sorption coefficients, could be applied for prediction of pharmaceutical mobility in soils with similar soil properties. Predicted sorption coefficients together with pharmaceutical half-lives and other imputes (e.g., soil-hydraulic, geological, hydro-geological, climatic) may be used for assessing potential ground-water contamination. Copyright © 2014 Elsevier B.V. All rights reserved.

Absolute backscatter coefficient estimates of tissue-mimicking phantoms in the 5–50 MHz frequency range

PubMed Central

McCormick, Matthew M.; Madsen, Ernest L.; Deaner, Meagan E.; Varghese, Tomy

2011-01-01

Absolute backscatter coefficients in tissue-mimicking phantoms were experimentally determined in the 5–50 MHz frequency range using a broadband technique. A focused broadband transducer from a commercial research system, the VisualSonics Vevo 770, was used with two tissue-mimicking phantoms. The phantoms differed regarding the thin layers covering their surfaces to prevent desiccation and regarding glass bead concentrations and diameter distributions. Ultrasound scanning of these phantoms was performed through the thin layer. To avoid signal saturation, the power spectra obtained from the backscattered radio frequency signals were calibrated by using the signal from a liquid planar reflector, a water-brominated hydrocarbon interface with acoustic impedance close to that of water. Experimental values of absolute backscatter coefficients were compared with those predicted by the Faran scattering model over the frequency range 5–50 MHz. The mean percent difference and standard deviation was 54% ± 45% for the phantom with a mean glass bead diameter of 5.40 μm and was 47% ± 28% for the phantom with 5.16 μm mean diameter beads. PMID:21877789

Influence of soil pH on the sorption of ionizable chemicals: modeling advances.

PubMed

Franco, Antonio; Fu, Wenjing; Trapp, Stefan

2009-03-01

The soil-water distribution coefficient of ionizable chemicals (K(d)) depends on the soil acidity, mainly because the pH governs speciation. Using pH-specific K(d) values normalized to organic carbon (K(OC)) from the literature, a method was developed to estimate the K(OC) of monovalent organic acids and bases. The regression considers pH-dependent speciation and species-specific partition coefficients, calculated from the dissociation constant (pK(a)) and the octanol-water partition coefficient of the neutral molecule (log P(n)). Probably because of the lower pH near the organic colloid-water interface, the optimal pH to model dissociation was lower than the bulk soil pH. The knowledge of the soil pH allows calculation of the fractions of neutral and ionic molecules in the system, thus improving the existing regression for acids. The same approach was not successful with bases, for which the impact of pH on the total sorption is contrasting. In fact, the shortcomings of the model assumptions affect the predictive power for acids and for bases differently. We evaluated accuracy and limitations of the regressions for their use in the environmental fate assessment of ionizable chemicals.

Strong copper(II) species in estuarine and sea waters investigated by a method with high detection window.

PubMed

Alberti, Giancarla; Biesuz, Raffaela; D'Agostino, Girolamo; Scarponi, Giuseppe; Pesavento, Maria

2007-02-15

The distribution of copper(II) in species of different stability in some estuarine and sea water samples (Adriatic Sea) was investigated by a method based on the sorption of the metal ion on a strongly sorbing resin, Chelex 100, whose sorbing properties have been previously characterized. From them, it is possible to predict very high values of detection windows at the considered conditions, for example side reaction coefficient as high as 10(10) at pH 7.5. Strong copper(II) species in equilibrium with Chelex 100 were detected, at concentration 2-20nM, with a reaction coefficient approximately 10(10.6) at pH 7.45 in sea water, strictly depending on the acidity. They represent 50-70% of the total metal ion and are the strongest copper(II) complexes found in sea water. Weak complexes too were detected in all the samples, with reaction coefficient lower than ca. 10(9) at the same pH. The method applied, named resin titration (RT), was described in a previous investigation, and is here modified in order to be carried out on oceanographic boat during a cruise in the Adriatic Sea.

Optical measurement of transverse molecular diffusion in a microchannel.

PubMed Central

Kamholz, A E; Schilling, E A; Yager, P

2001-01-01

Quantitative analysis of molecular diffusion is a necessity for the efficient design of most microfluidic devices as well as an important biophysical method in its own right. This study demonstrates the rapid measurement of diffusion coefficients of large and small molecules in a microfluidic device, the T-sensor, by means of conventional epifluorescence microscopy. Data were collected by monitoring the transverse flux of analyte from a sample stream into a second stream flowing alongside it. As indicated by the low Reynolds numbers of the system (< 1), flow is laminar, and molecular transport between streams occurs only by diffusion. Quantitative determinations were made by fitting data with predictions of a one-dimensional model. Analysis was made of the flow development and its effect on the distribution of diffusing analyte using a three-dimensional modeling software package. Diffusion coefficients were measured for four fluorescently labeled molecules: fluorescein-biotin, insulin, ovalbumin, and streptavidin. The resulting values differed from accepted results by an average of 2.4%. Microfluidic system parameters can be selected to achieve accurate diffusion coefficient measurements and to optimize other microfluidic devices that rely on precise transverse transport of molecules. PMID:11259309

Measurement of the azimuthal angle distribution of leptons from W boson decays as a function of the W transverse momentum in pp collisions at {radical}(s)=1.8 TeV

DOE Office of Scientific and Technical Information (OSTI.GOV)

Acosta, D.; Field, R.D.; Klimenko, S.

We present the first measurement of the A{sub 2} and A{sub 3} angular coefficients of the W boson produced in proton-antiproton collisions. We study W{yields}e{nu}{sub e} and W{yields}{mu}{nu}{sub {mu}} candidate events produced in association with at least one jet at CDF, during Run Ia and Run Ib of the Tevatron at {radical}(s)=1.8 TeV. The corresponding integrated luminosity was 110 pb{sup -1}. The jet balances the transverse momentum of the W and introduces QCD effects in W boson production. The extraction of the angular coefficients is achieved through the direct measurement of the azimuthal angle of the charged lepton in themore » Collins-Soper rest-frame of the W boson. The angular coefficients are measured as a function of the transverse momentum of the W boson. The electron, muon, and combined results are in good agreement with the standard model prediction, up to order {alpha}{sub s}{sup 2} in QCD.« less

Separation of nitrogen heterocyclic compounds from model coal tar fraction by solvent extraction

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kim, S.J.; Chun, Y.J.

2005-07-01

The separation of four kinds of nitrogen heterocyclic compounds (NHCs) from a model mixture comprising NHCs (indole (In), quinoline (Q), iso-quinoline (iQ), quinaldine (Qu)), three kinds of bicyclic aromatic compounds (BACs; 1-methyl-naphthalene (IMN), 2-methyl naphthalene (2MN), dimethylnaphthalene (DMN)), biphenyl (Bp) and phenyl ether (Pe) was examined by a solvent extraction. The model mixture used as a raw material of this work was prepared according to the components and compositions contained in coal tar fraction (the temperature ranges of fraction: 240-265{sup o}C). An aqueous solution of methanol, ethanol, iso-propyl alcohol, N,N-dimethyl acetamide, DMF, formamide, N-methylformamide/methanol, and formamide/methanol were used as solvents.more » An aqueous solution of formamide was found suitable for separating NHCs contained in coal tar fraction based on distribution coefficient and selectivity. The effect of operation factors on separating NHCs was investigated by the distribution equilibrium using an aqueous solution of formamide. Increasing the operation temperature and the volume ratio of solvent to feed at initial (S/F)(o) resulted in improving the distribution coefficients of each NHC, but increasing the volume fraction of water in the solvent at initial (y(w,O)) resulted in deteriorating the distribution coefficients of each NHC. With increasing y(w,O) and (S/F)(o), the selectivities of each NHC in reference to DMN increased. Increase in operation temperature resulted in decrease in selectivities of each NHC in reference to DMN. At an experimental condition fixed, the sequence of the distribution coefficient and selectivity in reference to DMN for each NHC was In {gt} iQ {gt} Q {gt} Qu, and also the sequence of the distribution coefficient for each BAC was IMN {gt} 2MN {gt} DMN. The sequence of the distribution coefficient for entire compounds analyzed by this work was In {gt} iQ {gt} Q {gt} Qu {gt} BP {gt} 1MN {gt} 2MN {gt} Pe {gt} DMN.« less

Prediction of Aerodynamic Coefficient using Genetic Algorithm Optimized Neural Network for Sparse Data

NASA Technical Reports Server (NTRS)

Rajkumar, T.; Bardina, Jorge; Clancy, Daniel (Technical Monitor)

2002-01-01

Wind tunnels use scale models to characterize aerodynamic coefficients, Wind tunnel testing can be slow and costly due to high personnel overhead and intensive power utilization. Although manual curve fitting can be done, it is highly efficient to use a neural network to define the complex relationship between variables. Numerical simulation of complex vehicles on the wide range of conditions required for flight simulation requires static and dynamic data. Static data at low Mach numbers and angles of attack may be obtained with simpler Euler codes. Static data of stalled vehicles where zones of flow separation are usually present at higher angles of attack require Navier-Stokes simulations which are costly due to the large processing time required to attain convergence. Preliminary dynamic data may be obtained with simpler methods based on correlations and vortex methods; however, accurate prediction of the dynamic coefficients requires complex and costly numerical simulations. A reliable and fast method of predicting complex aerodynamic coefficients for flight simulation I'S presented using a neural network. The training data for the neural network are derived from numerical simulations and wind-tunnel experiments. The aerodynamic coefficients are modeled as functions of the flow characteristics and the control surfaces of the vehicle. The basic coefficients of lift, drag and pitching moment are expressed as functions of angles of attack and Mach number. The modeled and training aerodynamic coefficients show good agreement. This method shows excellent potential for rapid development of aerodynamic models for flight simulation. Genetic Algorithms (GA) are used to optimize a previously built Artificial Neural Network (ANN) that reliably predicts aerodynamic coefficients. Results indicate that the GA provided an efficient method of optimizing the ANN model to predict aerodynamic coefficients. The reliability of the ANN using the GA includes prediction of aerodynamic coefficients to an accuracy of 110% . In our problem, we would like to get an optimized neural network architecture and minimum data set. This has been accomplished within 500 training cycles of a neural network. After removing training pairs (outliers), the GA has produced much better results. The neural network constructed is a feed forward neural network with a back propagation learning mechanism. The main goal has been to free the network design process from constraints of human biases, and to discover better forms of neural network architectures. The automation of the network architecture search by genetic algorithms seems to have been the best way to achieve this goal.

SPATIAL DISTRIBUTIONS OF ABSORPTION, LOCAL SUPPRESSION, AND EMISSIVITY REDUCTION OF SOLAR ACOUSTIC WAVES IN MAGNETIC REGIONS

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chou, D.-Y.; Yang, M.-H.; Zhao Hui

Observed acoustic power in magnetic regions is lower than the quiet Sun because of absorption, emissivity reduction, and local suppression of solar acoustic waves in magnetic regions. In the previous studies, we have developed a method to measure the coefficients of absorption, emissivity reduction, and local suppression of sunspots. In this study, we go one step further to measure the spatial distributions of three coefficients in two active regions, NOAA 9055 and 9057. The maps of absorption, emissivity reduction, and local suppression coefficients correlate with the magnetic map, including plage regions, except the emissivity reduction coefficient of NOAA 9055 wheremore » the emissivity reduction coefficient is too weak and lost among the noise.« less

A 2-D numerical simulation study on longitudinal solute transport and longitudinal dispersion coefficient

NASA Astrophysics Data System (ADS)

Zhang, Wei

2011-07-01

The longitudinal dispersion coefficient, DL, is a fundamental parameter of longitudinal solute transport models: the advection-dispersion (AD) model and various deadzone models. Since DL cannot be measured directly, and since its calibration using tracer test data is quite expensive and not always available, researchers have developed various methods, theoretical or empirical, for estimating DL by easier available cross-sectional hydraulic measurements (i.e., the transverse velocity profile, etc.). However, for known and unknown reasons, DL cannot be satisfactorily predicted using these theoretical/empirical formulae. Either there is very large prediction error for theoretical methods, or there is a lack of generality for the empirical formulae. Here, numerical experiments using Mike21, a software package that implements one of the most rigorous two-dimensional hydrodynamic and solute transport equations, for longitudinal solute transport in hypothetical streams, are presented. An analysis of the evolution of simulated solute clouds indicates that the two fundamental assumptions in Fischer's longitudinal transport analysis may be not reasonable. The transverse solute concentration distribution, and hence the longitudinal transport appears to be controlled by a dimensionless number ?, where Q is the average volumetric flowrate, Dt is a cross-sectional average transverse dispersion coefficient, and W is channel flow width. A simple empirical ? relationship may be established. Analysis and a revision of Fischer's theoretical formula suggest that ɛ influences the efficiency of transverse mixing and hence has restraining effect on longitudinal spreading. The findings presented here would improve and expand our understanding of longitudinal solute transport in open channel flow.

Pesticide adsorption in relation to soil properties and soil type distribution in regional scale.

PubMed

Kodešová, Radka; Kočárek, Martin; Kodeš, Vít; Drábek, Ondřej; Kozák, Josef; Hejtmánková, Kateřina

2011-02-15

Study was focused on the evaluation of pesticide adsorption in soils, as one of the parameters, which are necessary to know when assessing possible groundwater contamination caused by pesticides commonly used in agriculture. Batch sorption tests were performed for 11 selected pesticides and 13 representative soils. The Freundlich equations were used to describe adsorption isotherms. Multiple-linear regressions were used to predict the Freundlich adsorption coefficients from measured soil properties. Resulting functions and a soil map of the Czech Republic were used to generate maps of the coefficient distribution. The multiple linear regressions showed that the K(F) coefficient depended on: (a) combination of OM (organic matter content), pH(KCl) and CEC (cation exchange capacity), or OM, SCS (sorption complex saturation) and salinity (terbuthylazine), (b) combination of OM and pH(KCl), or OM, SCS and salinity (prometryne), (c) combination of OM and pH(KCl), or OM and ρ(z) (metribuzin), (d) combination of OM, CEC and clay content, or clay content, CEC and salinity (hexazinone), (e) combination of OM and pH(KCl), or OM and SCS (metolachlor), (f) OM or combination of OM and CaCO(3) (chlorotoluron), (g) OM (azoxystrobin), (h) combination of OM and pH(KCl) (trifluralin), (i) combination of OM and clay content (fipronil), (j) combination of OM and pH(KCl), or OM, pH(KCl) and CaCO(3) (thiacloprid), (k) combination of OM, pH(KCl) and CEC, or sand content, pH(KCl) and salinity (chlormequat chloride). Copyright © 2010 Elsevier B.V. All rights reserved.

Geary autocorrelation and DCCA coefficient: Application to predict apoptosis protein subcellular localization via PSSM

NASA Astrophysics Data System (ADS)

Liang, Yunyun; Liu, Sanyang; Zhang, Shengli

2017-02-01

Apoptosis is a fundamental process controlling normal tissue homeostasis by regulating a balance between cell proliferation and death. Predicting subcellular location of apoptosis proteins is very helpful for understanding its mechanism of programmed cell death. Prediction of apoptosis protein subcellular location is still a challenging and complicated task, and existing methods mainly based on protein primary sequences. In this paper, we propose a new position-specific scoring matrix (PSSM)-based model by using Geary autocorrelation function and detrended cross-correlation coefficient (DCCA coefficient). Then a 270-dimensional (270D) feature vector is constructed on three widely used datasets: ZD98, ZW225 and CL317, and support vector machine is adopted as classifier. The overall prediction accuracies are significantly improved by rigorous jackknife test. The results show that our model offers a reliable and effective PSSM-based tool for prediction of apoptosis protein subcellular localization.

Synchronization of distributed power grids with the external loading system

NASA Astrophysics Data System (ADS)

Wei, Duqu; Mei, Chuncao

2018-06-01

In this paper, the synchronization between spatially distributed power plants and their supported consumers is studied, where the case of Kuramoto-like model power grids connected to an external permanent magnet synchronous motor (PMSM) is taken as an example. We focus on the dependence of the synchronization on the coupling coefficient. To quantitatively study the synchronization degree, we introduce the order parameter and the frequency deviation to measure the synchronization of the coupled system. It is found that as the external coupling coefficient is increased, the distributed power grids and the loading system become more and more synchronized in space, and the complete synchronization appears at a particular value of external coupling coefficient. Our results may provide a useful tip for analyzing the synchronous ability of distributed power grids.

Forecasting of the selected features of Poaceae (R. Br.) Barnh., Artemisia L. and Ambrosia L. pollen season in Szczecin, north-western Poland, using Gumbel's distribution.

PubMed

Puc, Małgorzata; Wolski, Tomasz

2013-01-01

The allergenic pollen content of the atmosphere varies according to climate, biogeography and vegetation. Minimisation of the pollen allergy symptoms is related to the possibility of avoidance of large doses of the allergen. Measurements performed in Szczecin over a period of 13 years (2000-2012 inclusive) permitted prediction of theoretical maximum concentrations of pollen grains and their probability for the pollen season of Poaceae, Artemisia and Ambrosia. Moreover, the probabilities were determined of a given date as the beginning of the pollen season, the date of the maximum pollen count, Seasonal Pollen Index value and the number of days with pollen count above threshold values. Aerobiological monitoring was conducted using a Hirst volumetric trap (Lanzoni VPPS). Linear trend with determination coefficient (R(2)) was calculated. Model for long-term forecasting was performed by the method based on Gumbel's distribution. A statistically significant negative correlation was determined between the duration of pollen season of Poaceae and Artemisia and the Seasonal Pollen Index value. Seasonal, total pollen counts of Artemisia and Ambrosia showed a strong and statistically significant decreasing tendency. On the basis of Gumbel's distribution, a model was proposed for Szczecin, allowing prediction of the probabilities of the maximum pollen count values that can appear once in e.g. 5, 10 or 100 years. Short pollen seasons are characterised by a higher intensity of pollination than long ones. Prediction of the maximum pollen count values, dates of the pollen season beginning, and the number of days with pollen count above the threshold, on the basis of Gumbel's distribution, is expected to lead to improvement in the prophylaxis and therapy of persons allergic to pollen.

Analysis of porosity distribution of large-scale porous media and their reconstruction by Langevin equation.

PubMed

Jafari, G Reza; Sahimi, Muhammad; Rasaei, M Reza; Tabar, M Reza Rahimi

2011-02-01

Several methods have been developed in the past for analyzing the porosity and other types of well logs for large-scale porous media, such as oil reservoirs, as well as their permeability distributions. We developed a method for analyzing the porosity logs ϕ(h) (where h is the depth) and similar data that are often nonstationary stochastic series. In this method one first generates a new stationary series based on the original data, and then analyzes the resulting series. It is shown that the series based on the successive increments of the log y(h)=ϕ(h+δh)-ϕ(h) is a stationary and Markov process, characterized by a Markov length scale h(M). The coefficients of the Kramers-Moyal expansion for the conditional probability density function (PDF) P(y,h|y(0),h(0)) are then computed. The resulting PDFs satisfy a Fokker-Planck (FP) equation, which is equivalent to a Langevin equation for y(h) that provides probabilistic predictions for the porosity logs. We also show that the Hurst exponent H of the self-affine distributions, which have been used in the past to describe the porosity logs, is directly linked to the drift and diffusion coefficients that we compute for the FP equation. Also computed are the level-crossing probabilities that provide insight into identifying the high or low values of the porosity beyond the depth interval in which the data have been measured. ©2011 American Physical Society

Modeling the drug transport in the anterior segment of the eye.

PubMed

Avtar, Ram; Tandon, Deepti

2008-10-02

The aim of the present work is the development of a simple mathematical model for the time course concentration profile of topically administered drugs in the anterior chamber aqueous humor and investigation of the effects of various model parameters on the aqueous humor concentration of lipophilic and hydrophilic drugs. A simple pharmacokinetic model for the transient drug transport in the anterior segment has been developed by using the conservation of mass in the precorneal tear film, Fick's law of diffusion and Michaelis-Menten kinetics of drug metabolism in cornea, and the conservation of mass in the anterior chamber. An analytical solution describing the drug concentration in the anterior chamber has been obtained. The model predicts that an increase in the drug metabolic (consumption) rate in the corneal epithelium reduces the drug concentration in the anterior chamber for both lipophilic and hydrophilic molecules. A decrease in the clearance rate and distribution volume of the drug in the anterior chamber raises the aqueous humor concentration significantly. It is also observed that decay rate of drug concentration in the anterior chamber is higher for lipophilic molecules than that for hydrophilic molecules. The bioavailability of drugs applied topically to the eye may be improved by a rise in the precorneal tear volume, diffusion coefficient in corneal epithelium and distribution coefficient across the endothelium anterior chamber interface, and by reducing the drug metabolism, drug clearance rate and distribution volume in anterior chamber.

PREDICTION OF THE SOLUBILITY, ACTIVITY COEFFICIENT AND LIQUID/LIQUID PARTITION COEFFICIENT OF ORGANIC COMPOUNDS

EPA Science Inventory

Solvation models, based on fundamental chemical structure theory, were developed in the SPARC mechanistic tool box to predict a large array of physical properties of organic compounds in water and in non-aqueous solvents strictly from molecular structure. The SPARC self-interact...

Comparison of equilibrium and non-equilibrium distribution coefficients for the human drug carbamazepine

USDA-ARS?s Scientific Manuscript database

The distribution coefficient (KD) for the human drug carbamazepine was measured using a non-equilibrium technique. Repacked soil columns were prepared using an Airport silt loam (Typic Natrustalf) with an average organic matter content of 2.45%. Carbamazepine solutions were then leached through th...

Estimates of the Sampling Distribution of Scalability Coefficient H

ERIC Educational Resources Information Center

Van Onna, Marieke J. H.

2004-01-01

Coefficient "H" is used as an index of scalability in nonparametric item response theory (NIRT). It indicates the degree to which a set of items rank orders examinees. Theoretical sampling distributions, however, have only been derived asymptotically and only under restrictive conditions. Bootstrap methods offer an alternative possibility to…

Prediction of soil organic carbon partition coefficients by soil column liquid chromatography.

PubMed

Guo, Rongbo; Liang, Xinmiao; Chen, Jiping; Wu, Wenzhong; Zhang, Qing; Martens, Dieter; Kettrup, Antonius

2004-04-30

To avoid the limitation of the widely used prediction methods of soil organic carbon partition coefficients (KOC) from hydrophobic parameters, e.g., the n-octanol/water partition coefficients (KOW) and the reversed phase high performance liquid chromatographic (RP-HPLC) retention factors, the soil column liquid chromatographic (SCLC) method was developed for KOC prediction. The real soils were used as the packing materials of RP-HPLC columns, and the correlations between the retention factors of organic compounds on soil columns (ksoil) and KOC measured by batch equilibrium method were studied. Good correlations were achieved between ksoil and KOC for three types of soils with different properties. All the square of the correlation coefficients (R2) of the linear regression between log ksoil and log KOC were higher than 0.89 with standard deviations of less than 0.21. In addition, the prediction of KOC from KOW and the RP-HPLC retention factors on cyanopropyl (CN) stationary phase (kCN) was comparatively evaluated for the three types of soils. The results show that the prediction of KOC from kCN and KOW is only applicable to some specific types of soils. The results obtained in the present study proved that the SCLC method is appropriate for the KOC prediction for different types of soils, however the applicability of using hydrophobic parameters to predict KOC largely depends on the properties of soil concerned.