Maximum Simulated Likelihood and Expectation-Maximization Methods to Estimate Random Coefficients Logit with Panel Data

DEFF Research Database (Denmark)

Cherchi, Elisabetta; Guevara, Cristian

2012-01-01

with cross-sectional or with panel data, and (d) EM systematically attained more efficient estimators than the MSL method. The results imply that if the purpose of the estimation is only to determine the ratios of the model parameters (e.g., the value of time), the EM method should be preferred. For all......The random coefficients logit model allows a more realistic representation of agents' behavior. However, the estimation of that model may involve simulation, which may become impractical with many random coefficients because of the curse of dimensionality. In this paper, the traditional maximum...... simulated likelihood (MSL) method is compared with the alternative expectation- maximization (EM) method, which does not require simulation. Previous literature had shown that for cross-sectional data, MSL outperforms the EM method in the ability to recover the true parameters and estimation time...

Drag coefficient Variability and Thermospheric models

Science.gov (United States)

Moe, Kenneth

Satellite drag coefficients depend upon a variety of factors: The shape of the satellite, its altitude, the eccentricity of its orbit, the temperature and mean molecular mass of the ambient atmosphere, and the time in the sunspot cycle. At altitudes where the mean free path of the atmospheric molecules is large compared to the dimensions of the satellite, the drag coefficients can be determined from the theory of free-molecule flow. The dependence on altitude is caused by the concentration of atomic oxygen which plays an important role by its ability to adsorb on the satellite surface and thereby affect the energy loss of molecules striking the surface. The eccentricity of the orbit determines the satellite velocity at perigee, and therefore the energy of the incident molecules relative to the energy of adsorption of atomic oxygen atoms on the surface. The temperature of the ambient atmosphere determines the extent to which the random thermal motion of the molecules influences the momentum transfer to the satellite. The time in the sunspot cycle affects the ambient temperature as well as the concentration of atomic oxygen at a particular altitude. Tables and graphs will be used to illustrate the variability of drag coefficients. Before there were any measurements of gas-surface interactions in orbit, Izakov and Cook independently made an excellent estimate that the drag coefficient of satellites of compact shape would be 2.2. That numerical value, independent of altitude, was used by Jacchia to construct his model from the early measurements of satellite drag. Consequently, there is an altitude dependent bias in the model. From the sparce orbital experiments that have been done, we know that the molecules which strike satellite surfaces rebound in a diffuse angular distribution with an energy loss given by the energy accommodation coefficient. As more evidence accumulates on the energy loss, more realistic drag coefficients are being calculated. These improved drag

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

Science.gov (United States)

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.

Determination of Nonlinear Stiffness Coefficients for Finite Element Models with Application to the Random Vibration Problem

Science.gov (United States)

Muravyov, Alexander A.

1999-01-01

In this paper, a method for obtaining nonlinear stiffness coefficients in modal coordinates for geometrically nonlinear finite-element models is developed. The method requires application of a finite-element program with a geometrically non- linear static capability. The MSC/NASTRAN code is employed for this purpose. The equations of motion of a MDOF system are formulated in modal coordinates. A set of linear eigenvectors is used to approximate the solution of the nonlinear problem. The random vibration problem of the MDOF nonlinear system is then considered. The solutions obtained by application of two different versions of a stochastic linearization technique are compared with linear and exact (analytical) solutions in terms of root-mean-square (RMS) displacements and strains for a beam structure.

Diffusion coefficients for multi-step persistent random walks on lattices

International Nuclear Information System (INIS)

Gilbert, Thomas; Sanders, David P

2010-01-01

We calculate the diffusion coefficients of persistent random walks on lattices, where the direction of a walker at a given step depends on the memory of a certain number of previous steps. In particular, we describe a simple method which enables us to obtain explicit expressions for the diffusion coefficients of walks with a two-step memory on different classes of one-, two- and higher dimensional lattices.

Entropy Characterization of Random Network Models

Directory of Open Access Journals (Sweden)

Pedro J. Zufiria

2017-06-01

Full Text Available This paper elaborates on the Random Network Model (RNM as a mathematical framework for modelling and analyzing the generation of complex networks. Such framework allows the analysis of the relationship between several network characterizing features (link density, clustering coefficient, degree distribution, connectivity, etc. and entropy-based complexity measures, providing new insight on the generation and characterization of random networks. Some theoretical and computational results illustrate the utility of the proposed framework.

A Two-Stage Estimation Method for Random Coefficient Differential Equation Models with Application to Longitudinal HIV Dynamic Data.

Science.gov (United States)

Fang, Yun; Wu, Hulin; Zhu, Li-Xing

2011-07-01

We propose a two-stage estimation method for random coefficient ordinary differential equation (ODE) models. A maximum pseudo-likelihood estimator (MPLE) is derived based on a mixed-effects modeling approach and its asymptotic properties for population parameters are established. The proposed method does not require repeatedly solving ODEs, and is computationally efficient although it does pay a price with the loss of some estimation efficiency. However, the method does offer an alternative approach when the exact likelihood approach fails due to model complexity and high-dimensional parameter space, and it can also serve as a method to obtain the starting estimates for more accurate estimation methods. In addition, the proposed method does not need to specify the initial values of state variables and preserves all the advantages of the mixed-effects modeling approach. The finite sample properties of the proposed estimator are studied via Monte Carlo simulations and the methodology is also illustrated with application to an AIDS clinical data set.

The relationship between multilevel models and non-parametric multilevel mixture models: Discrete approximation of intraclass correlation, random coefficient distributions, and residual heteroscedasticity.

Science.gov (United States)

Rights, Jason D; Sterba, Sonya K

2016-11-01

Multilevel data structures are common in the social sciences. Often, such nested data are analysed with multilevel models (MLMs) in which heterogeneity between clusters is modelled by continuously distributed random intercepts and/or slopes. Alternatively, the non-parametric multilevel regression mixture model (NPMM) can accommodate the same nested data structures through discrete latent class variation. The purpose of this article is to delineate analytic relationships between NPMM and MLM parameters that are useful for understanding the indirect interpretation of the NPMM as a non-parametric approximation of the MLM, with relaxed distributional assumptions. We define how seven standard and non-standard MLM specifications can be indirectly approximated by particular NPMM specifications. We provide formulas showing how the NPMM can serve as an approximation of the MLM in terms of intraclass correlation, random coefficient means and (co)variances, heteroscedasticity of residuals at level 1, and heteroscedasticity of residuals at level 2. Further, we discuss how these relationships can be useful in practice. The specific relationships are illustrated with simulated graphical demonstrations, and direct and indirect interpretations of NPMM classes are contrasted. We provide an R function to aid in implementing and visualizing an indirect interpretation of NPMM classes. An empirical example is presented and future directions are discussed. © 2016 The British Psychological Society.

Estimation of the Coefficient of Restitution of Rocking Systems by the Random Decrement Technique

DEFF Research Database (Denmark)

Brincker, Rune; Demosthenous, Milton; Manos, George C.

1994-01-01

The aim of this paper is to investigate the possibility of estimating an average damping parameter for a rocking system due to impact, the so-called coefficient of restitution, from the random response, i.e. when the loads are random and unknown, and the response is measured. The objective...... is to obtain an estimate of the free rocking response from the measured random response using the Random Decrement (RDD) Technique, and then estimate the coefficient of restitution from this free response estimate. In the paper this approach is investigated by simulating the response of a single degree...

Estimation of the Coefficient of Restitution of Rocking Systems by the Random Decrement Technique

DEFF Research Database (Denmark)

Brincker, Rune; Demosthenous, M.; Manos, G. C.

The aim of this paper is to investigate the possibility of estimating an average damping parameter for a rocking system due to impact, the so-called coefficient of restitution, from the random response, i.e. when the loads are random and unknown, and the response is measured. The objective is to ...... of freedom system loaded by white noise, estimating the coefficient of restitution as explained, and comparing the estimates with the value used in the simulations. Several estimates for the coefficient of restitution are considered, and reasonable results are achieved....

A Monte Carlo experiment to analyze the curse of dimensionality in estimating random coefficients models with a full variance–covariance matrix

DEFF Research Database (Denmark)

Cherchi, Elisabetta; Guevara, Cristian Angelo

2012-01-01

of parameters increases is usually known as the “curse of dimensionality” in the simulation methods. We investigate this problem in the case of the random coefficients Logit model. We compare the traditional Maximum Simulated Likelihood (MSL) method with two alternative estimation methods: the Expectation......–Maximization (EM) and the Laplace Approximation (HH) methods that do not require simulation. We use Monte Carlo experimentation to investigate systematically the performance of the methods under different circumstances, including different numbers of variables, sample sizes and structures of the variance...

Formulae of differentiation for solving differential equations with complex-valued random coefficients

International Nuclear Information System (INIS)

Kim, Ki Hong; Lee, Dong Hun

1999-01-01

Generalizing the work of Shapiro and Loginov, we derive new formulae of differentiation useful for solving differential equations with complex-valued random coefficients. We apply the formulae to the quantum-mechanical problem of noninteracting electrons moving in a correlated random potential in one dimension

Analysis and computation of the elastic wave equation with random coefficients

KAUST Repository

Motamed, Mohammad; Nobile, Fabio; Tempone, Raul

2015-01-01

We consider the stochastic initial-boundary value problem for the elastic wave equation with random coefficients and deterministic data. We propose a stochastic collocation method for computing statistical moments of the solution or statistics

Application of QMC methods to PDEs with random coefficients : a survey of analysis and implementation

KAUST Repository

Kuo, Frances

2016-01-05

In this talk I will provide a survey of recent research efforts on the application of quasi-Monte Carlo (QMC) methods to PDEs with random coefficients. Such PDE problems occur in the area of uncertainty quantification. In recent years many papers have been written on this topic using a variety of methods. QMC methods are relatively new to this application area. I will consider different models for the randomness (uniform versus lognormal) and contrast different QMC algorithms (single-level versus multilevel, first order versus higher order, deterministic versus randomized). I will give a summary of the QMC error analysis and proof techniques in a unified view, and provide a practical guide to the software for constructing QMC points tailored to the PDE problems.

EXISTENCE AND UNIQUENESS OF SOLUTIONS TO STOCHASTIC DIFFERENTIAL EQUATION WITH RANDOM COEFFICIENTS

Institute of Scientific and Technical Information of China (English)

无

2010-01-01

This paper mainly deals with a stochastic differential equation (SDE) with random coefficients. Sufficient conditions which guarantee the existence and uniqueness of solutions to the equation are given.

Semi-analytical Model for Estimating Absorption Coefficients of Optically Active Constituents in Coastal Waters

Science.gov (United States)

Wang, D.; Cui, Y.

2015-12-01

The objectives of this paper are to validate the applicability of a multi-band quasi-analytical algorithm (QAA) in retrieval absorption coefficients of optically active constituents in turbid coastal waters, and to further improve the model using a proposed semi-analytical model (SAA). The ap(531) and ag(531) semi-analytically derived using SAA model are quite different from the retrievals procedures of QAA model that ap(531) and ag(531) are semi-analytically derived from the empirical retrievals results of a(531) and a(551). The two models are calibrated and evaluated against datasets taken from 19 independent cruises in West Florida Shelf in 1999-2003, provided by SeaBASS. The results indicate that the SAA model produces a superior performance to QAA model in absorption retrieval. Using of the SAA model in retrieving absorption coefficients of optically active constituents from West Florida Shelf decreases the random uncertainty of estimation by >23.05% from the QAA model. This study demonstrates the potential of the SAA model in absorption coefficients of optically active constituents estimating even in turbid coastal waters. Keywords: Remote sensing; Coastal Water; Absorption Coefficient; Semi-analytical Model

Analysis and implementation issues for the numerical approximation of parabolic equations with random coefficients

KAUST Repository

Nobile, Fabio; Tempone, Raul

2009-01-01

We consider the problem of numerically approximating statistical moments of the solution of a time- dependent linear parabolic partial differential equation (PDE), whose coefficients and/or forcing terms are spatially correlated random fields. The stochastic coefficients of the PDE are approximated by truncated Karhunen-Loève expansions driven by a finite number of uncorrelated random variables. After approxi- mating the stochastic coefficients, the original stochastic PDE turns into a new deterministic parametric PDE of the same type, the dimension of the parameter set being equal to the number of random variables introduced. After proving that the solution of the parametric PDE problem is analytic with respect to the parameters, we consider global polynomial approximations based on tensor product, total degree or sparse polynomial spaces and constructed by either a Stochastic Galerkin or a Stochastic Collocation approach. We derive convergence rates for the different cases and present numerical results that show how these approaches are a valid alternative to the more traditional Monte Carlo Method for this class of problems. © 2009 John Wiley & Sons, Ltd.

Analysis and implementation issues for the numerical approximation of parabolic equations with random coefficients

KAUST Repository

Nobile, Fabio

2009-11-05

We consider the problem of numerically approximating statistical moments of the solution of a time- dependent linear parabolic partial differential equation (PDE), whose coefficients and/or forcing terms are spatially correlated random fields. The stochastic coefficients of the PDE are approximated by truncated Karhunen-Loève expansions driven by a finite number of uncorrelated random variables. After approxi- mating the stochastic coefficients, the original stochastic PDE turns into a new deterministic parametric PDE of the same type, the dimension of the parameter set being equal to the number of random variables introduced. After proving that the solution of the parametric PDE problem is analytic with respect to the parameters, we consider global polynomial approximations based on tensor product, total degree or sparse polynomial spaces and constructed by either a Stochastic Galerkin or a Stochastic Collocation approach. We derive convergence rates for the different cases and present numerical results that show how these approaches are a valid alternative to the more traditional Monte Carlo Method for this class of problems. © 2009 John Wiley & Sons, Ltd.

Adaptive Algebraic Multigrid for Finite Element Elliptic Equations with Random Coefficients

Energy Technology Data Exchange (ETDEWEB)

Kalchev, D

2012-04-02

This thesis presents a two-grid algorithm based on Smoothed Aggregation Spectral Element Agglomeration Algebraic Multigrid (SA-{rho}AMGe) combined with adaptation. The aim is to build an efficient solver for the linear systems arising from discretization of second-order elliptic partial differential equations (PDEs) with stochastic coefficients. Examples include PDEs that model subsurface flow with random permeability field. During a Markov Chain Monte Carlo (MCMC) simulation process, that draws PDE coefficient samples from a certain distribution, the PDE coefficients change, hence the resulting linear systems to be solved change. At every such step the system (discretized PDE) needs to be solved and the computed solution used to evaluate some functional(s) of interest that then determine if the coefficient sample is acceptable or not. The MCMC process is hence computationally intensive and requires the solvers used to be efficient and fast. This fact that at every step of MCMC the resulting linear system changes, makes an already existing solver built for the old problem perhaps not as efficient for the problem corresponding to the new sampled coefficient. This motivates the main goal of our study, namely, to adapt an already existing solver to handle the problem (with changed coefficient) with the objective to achieve this goal to be faster and more efficient than building a completely new solver from scratch. Our approach utilizes the local element matrices (for the problem with changed coefficients) to build local problems associated with constructed by the method agglomerated elements (a set of subdomains that cover the given computational domain). We solve a generalized eigenproblem for each set in a subspace spanned by the previous local coarse space (used for the old solver) and a vector, component of the error, that the old solver cannot handle. A portion of the spectrum of these local eigen-problems (corresponding to eigenvalues close to zero) form the

Application of random regression models to the genetic evaluation ...

African Journals Online (AJOL)

The model included fixed regression on AM (range from 30 to 138 mo) and the effect of herd-measurement date concatenation. Random parts of the model were RRM coefficients for additive and permanent environmental effects, while residual effects were modelled to account for heterogeneity of variance by AY. Estimates ...

Random matrix theory analysis of cross-correlations in the US stock market: Evidence from Pearson’s correlation coefficient and detrended cross-correlation coefficient

Science.gov (United States)

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.

Comparing linear probability model coefficients across groups

DEFF Research Database (Denmark)

Holm, Anders; Ejrnæs, Mette; Karlson, Kristian Bernt

2015-01-01

of the following three components: outcome truncation, scale parameters and distributional shape of the predictor variable. These results point to limitations in using linear probability model coefficients for group comparisons. We also provide Monte Carlo simulations and real examples to illustrate......This article offers a formal identification analysis of the problem in comparing coefficients from linear probability models between groups. We show that differences in coefficients from these models can result not only from genuine differences in effects, but also from differences in one or more...... these limitations, and we suggest a restricted approach to using linear probability model coefficients in group comparisons....

Using Multisite Experiments to Study Cross-Site Variation in Treatment Effects: A Hybrid Approach with Fixed Intercepts and A Random Treatment Coefficient

Science.gov (United States)

Bloom, Howard S.; Raudenbush, Stephen W.; Weiss, Michael J.; Porter, Kristin

2017-01-01

The present article considers a fundamental question in evaluation research: "By how much do program effects vary across sites?" The article first presents a theoretical model of cross-site impact variation and a related estimation model with a random treatment coefficient and fixed site-specific intercepts. This approach eliminates…

Random-growth urban model with geographical fitness

Science.gov (United States)

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.

Random Modeling of Daily Rainfall and Runoff Using a Seasonal Model and Wavelet Denoising

Directory of Open Access Journals (Sweden)

Chien-ming Chou

2014-01-01

Full Text Available Instead of Fourier smoothing, this study applied wavelet denoising to acquire the smooth seasonal mean and corresponding perturbation term from daily rainfall and runoff data in traditional seasonal models, which use seasonal means for hydrological time series forecasting. The denoised rainfall and runoff time series data were regarded as the smooth seasonal mean. The probability distribution of the percentage coefficients can be obtained from calibrated daily rainfall and runoff data. For validated daily rainfall and runoff data, percentage coefficients were randomly generated according to the probability distribution and the law of linear proportion. Multiplying the generated percentage coefficient by the smooth seasonal mean resulted in the corresponding perturbation term. Random modeling of daily rainfall and runoff can be obtained by adding the perturbation term to the smooth seasonal mean. To verify the accuracy of the proposed method, daily rainfall and runoff data for the Wu-Tu watershed were analyzed. The analytical results demonstrate that wavelet denoising enhances the precision of daily rainfall and runoff modeling of the seasonal model. In addition, the wavelet denoising technique proposed in this study can obtain the smooth seasonal mean of rainfall and runoff processes and is suitable for modeling actual daily rainfall and runoff processes.

Vertical random variability of the distribution coefficient in the soil and its effect on the migration of fallout radionuclides

International Nuclear Information System (INIS)

Bunzl, K.

2002-01-01

In the field, the distribution coefficient, K d , for the sorption of a radionuclide by the soil cannot be expected to be constant. Even in a well defined soil horizon, K d will vary stochastically in horizontal as well as in vertical direction around a mean value. The horizontal random variability of K d produce a pronounced tailing effect in the concentration depth profile of a fallout radionuclide, much less is known on the corresponding effect of the vertical random variability. To analyze this effect theoretically, the classical convection-dispersion model in combination with the random-walk particle method was applied. The concentration depth profile of a radionuclide was calculated one year after deposition assuming constant values of the pore water velocity, the diffusion/dispersion coefficient, and the distribution coefficient (K d = 100 cm 3 x g -1 ) and exhibiting a vertical variability for K d according to a log-normal distribution with a geometric mean of 100 cm 3 x g -1 and a coefficient of variation of CV 0.53. The results show that these two concentration depth profiles are only slightly different, the location of the peak is shifted somewhat upwards, and the dispersion of the concentration depth profile is slightly larger. A substantial tailing effect of the concentration depth profile is not perceivable. Especially with respect to the location of the peak, a very good approximation of the concentration depth profile is obtained if the arithmetic mean of the K d -values (K d = 113 cm 3 x g -1 ) and a slightly increased dispersion coefficient are used in the analytical solution of the classical convection-dispersion equation with constant K d . The evaluation of the observed concentration depth profile with the analytical solution of the classical convection-dispersion equation with constant parameters will, within the usual experimental limits, hardly reveal the presence of a log-normal random distribution of K d in the vertical direction in

Full Random Coefficients Multilevel Modeling of the Relationship between Land Use and Trip Time on Weekdays and Weekends

Directory of Open Access Journals (Sweden)

Tae-Hyoung Tommy Gim

2017-10-01

Full Text Available Interests in weekend trips are increasing, but few have studied how they are affected by land use. In this study, we analyze the relationship between compact land use characteristics and trip time in Seoul, Korea by comparing two research models, each of which uses the weekday and weekend data of the same travelers. To secure sufficient numbers of subjects and groups, full random coefficients multilevel models define the trip as level one and the neighborhood as level two, and find that level-two land use characteristics account for less variation in trip time than level-one individual characteristics. At level one, weekday trip time is found to be reduced by the choice of the automobile as a travel mode, but not by its ownership per se. In addition, it becomes reduced if made by high income travelers and extended to travel to quality jobs. Among four land use characteristics at level two, population density, road connectivity, and subway availability are shown to be significant in the weekday model. Only subway availability has a positive relationship with trip time and this finding is consistent with the level-one result that the choice of automobile alternatives increases trip time. The other land use characteristic, land use balance, turns out to be a single significant land use variable in the weekend model, implying that it is concerned mainly with non-work, non-mandatory travel.

Diffusion coefficient adaptive correction in Lagrangian puff model

International Nuclear Information System (INIS)

Tan Wenji; Wang Dezhong; Ma Yuanwei; Ji Zhilong

2014-01-01

Lagrangian puff model is widely used in the decision support system for nuclear emergency management. The diffusion coefficient is one of the key parameters impacting puff model. An adaptive method was proposed in this paper, which could correct the diffusion coefficient in Lagrangian puff model, and it aimed to improve the accuracy of calculating the nuclide concentration distribution. This method used detected concentration data, meteorological data and source release data to estimate the actual diffusion coefficient with least square method. The diffusion coefficient adaptive correction method was evaluated by Kincaid data in MVK, and was compared with traditional Pasquill-Gifford (P-G) diffusion scheme method. The results indicate that this diffusion coefficient adaptive correction method can improve the accuracy of Lagrangian puff model. (authors)

Modified Regression Correlation Coefficient for Poisson Regression Model

Science.gov (United States)

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).

Comparison of activity coefficient models for electrolyte systems

DEFF Research Database (Denmark)

Lin, Yi; ten Kate, Antoon; Mooijer, Miranda

2010-01-01

Three activity coefficient models for electrolyte solutions were evaluated and compared. The activity coefficient models are: The electrolyte NRTL model (ElecNRTL) by Aspentech, the mixed solvent electrolyte model (MSE) by OLI Systems Inc., and the Extended UNIQUAC model from the Technical Univer...

Transmission coefficient and heat conduction of a harmonic chain with random masses

International Nuclear Information System (INIS)

Verheggen, T.

1979-01-01

We find upper and lower bounds for the transmission coefficient of a chain of random masses. Using these bounds we show that the heat conduction in such a chain does not obey Fourier's law: For different temperatures at the ends of a chain containing N particles the energy flux falls off like Nsup(-1/2) rather than N -1 . (orig.)

Evolution of the concentration PDF in random environments modeled by global random walk

Science.gov (United States)

Suciu, Nicolae; Vamos, Calin; Attinger, Sabine; Knabner, Peter

2013-04-01

The evolution of the probability density function (PDF) of concentrations of chemical species transported in random environments is often modeled by ensembles of notional particles. The particles move in physical space along stochastic-Lagrangian trajectories governed by Ito equations, with drift coefficients given by the local values of the resolved velocity field and diffusion coefficients obtained by stochastic or space-filtering upscaling procedures. A general model for the sub-grid mixing also can be formulated as a system of Ito equations solving for trajectories in the composition space. The PDF is finally estimated by the number of particles in space-concentration control volumes. In spite of their efficiency, Lagrangian approaches suffer from two severe limitations. Since the particle trajectories are constructed sequentially, the demanded computing resources increase linearly with the number of particles. Moreover, the need to gather particles at the center of computational cells to perform the mixing step and to estimate statistical parameters, as well as the interpolation of various terms to particle positions, inevitably produce numerical diffusion in either particle-mesh or grid-free particle methods. To overcome these limitations, we introduce a global random walk method to solve the system of Ito equations in physical and composition spaces, which models the evolution of the random concentration's PDF. The algorithm consists of a superposition on a regular lattice of many weak Euler schemes for the set of Ito equations. Since all particles starting from a site of the space-concentration lattice are spread in a single numerical procedure, one obtains PDF estimates at the lattice sites at computational costs comparable with those for solving the system of Ito equations associated to a single particle. The new method avoids the limitations concerning the number of particles in Lagrangian approaches, completely removes the numerical diffusion, and

Estimating varying coefficients for partial differential equation models.

Science.gov (United States)

Zhang, Xinyu; Cao, Jiguo; Carroll, Raymond J

2017-09-01

Partial differential equations (PDEs) are used to model complex dynamical systems in multiple dimensions, and their parameters often have important scientific interpretations. In some applications, PDE parameters are not constant but can change depending on the values of covariates, a feature that we call varying coefficients. We propose a parameter cascading method to estimate varying coefficients in PDE models from noisy data. Our estimates of the varying coefficients are shown to be consistent and asymptotically normally distributed. The performance of our method is evaluated by a simulation study and by an empirical study estimating three varying coefficients in a PDE model arising from LIDAR data. © 2017, The International Biometric Society.

Monte Carlo Finite Volume Element Methods for the Convection-Diffusion Equation with a Random Diffusion Coefficient

Directory of Open Access Journals (Sweden)

Qian Zhang

2014-01-01

Full Text Available The paper presents a framework for the construction of Monte Carlo finite volume element method (MCFVEM for the convection-diffusion equation with a random diffusion coefficient, which is described as a random field. We first approximate the continuous stochastic field by a finite number of random variables via the Karhunen-Loève expansion and transform the initial stochastic problem into a deterministic one with a parameter in high dimensions. Then we generate independent identically distributed approximations of the solution by sampling the coefficient of the equation and employing finite volume element variational formulation. Finally the Monte Carlo (MC method is used to compute corresponding sample averages. Statistic error is estimated analytically and experimentally. A quasi-Monte Carlo (QMC technique with Sobol sequences is also used to accelerate convergence, and experiments indicate that it can improve the efficiency of the Monte Carlo method.

Varying coefficients model with measurement error.

Science.gov (United States)

Li, Liang; Greene, Tom

2008-06-01

We propose a semiparametric partially varying coefficient model to study the relationship between serum creatinine concentration and the glomerular filtration rate (GFR) among kidney donors and patients with chronic kidney disease. A regression model is used to relate serum creatinine to GFR and demographic factors in which coefficient of GFR is expressed as a function of age to allow its effect to be age dependent. GFR measurements obtained from the clearance of a radioactively labeled isotope are assumed to be a surrogate for the true GFR, with the relationship between measured and true GFR expressed using an additive error model. We use locally corrected score equations to estimate parameters and coefficient functions, and propose an expected generalized cross-validation (EGCV) method to select the kernel bandwidth. The performance of the proposed methods, which avoid distributional assumptions on the true GFR and residuals, is investigated by simulation. Accounting for measurement error using the proposed model reduced apparent inconsistencies in the relationship between serum creatinine and GFR among different clinical data sets derived from kidney donor and chronic kidney disease source populations.

Reactor kinetics revisited: a coefficient based model (CBM)

International Nuclear Information System (INIS)

Ratemi, W.M.

2011-01-01

In this paper, a nuclear reactor kinetics model based on Guelph expansion coefficients calculation ( Coefficients Based Model, CBM), for n groups of delayed neutrons is developed. The accompanying characteristic equation is a polynomial form of the Inhour equation with the same coefficients of the CBM- kinetics model. Those coefficients depend on Universal abc- values which are dependent on the type of the fuel fueling a nuclear reactor. Furthermore, such coefficients are linearly dependent on the inserted reactivity. In this paper, the Universal abc- values have been presented symbolically, for the first time, as well as with their numerical values for U-235 fueled reactors for one, two, three, and six groups of delayed neutrons. Simulation studies for constant and variable reactivity insertions are made for the CBM kinetics model, and a comparison of results, with numerical solutions of classical kinetics models for one, two, three, and six groups of delayed neutrons are presented. The results show good agreements, especially for single step insertion of reactivity, with the advantage of the CBM- solution of not encountering the stiffness problem accompanying the numerical solutions of the classical kinetics model. (author)

Dynamics analysis of SIR epidemic model with correlation coefficients and clustering coefficient in networks.

Science.gov (United States)

Zhang, Juping; Yang, Chan; Jin, Zhen; Li, Jia

2018-07-14

In this paper, the correlation coefficients between nodes in states are used as dynamic variables, and we construct SIR epidemic dynamic models with correlation coefficients by using the pair approximation method in static networks and dynamic networks, respectively. Considering the clustering coefficient of the network, we analytically investigate the existence and the local asymptotic stability of each equilibrium of these models and derive threshold values for the prevalence of diseases. Additionally, we obtain two equivalent epidemic thresholds in dynamic networks, which are compared with the results of the mean field equations. Copyright © 2018 Elsevier Ltd. All rights reserved.

Absorption and scattering coefficient dependence of laser-Doppler flowmetry models for large tissue volumes

International Nuclear Information System (INIS)

Binzoni, T; Leung, T S; Ruefenacht, D; Delpy, D T

2006-01-01

Based on quasi-elastic scattering theory (and random walk on a lattice approach), a model of laser-Doppler flowmetry (LDF) has been derived which can be applied to measurements in large tissue volumes (e.g. when the interoptode distance is >30 mm). The model holds for a semi-infinite medium and takes into account the transport-corrected scattering coefficient and the absorption coefficient of the tissue, and the scattering coefficient of the red blood cells. The model holds for anisotropic scattering and for multiple scattering of the photons by the moving scatterers of finite size. In particular, it has also been possible to take into account the simultaneous presence of both Brownian and pure translational movements. An analytical and simplified version of the model has also been derived and its validity investigated, for the case of measurements in human skeletal muscle tissue. It is shown that at large optode spacing it is possible to use the simplified model, taking into account only a 'mean' light pathlength, to predict the blood flow related parameters. It is also demonstrated that the 'classical' blood volume parameter, derived from LDF instruments, may not represent the actual blood volume variations when the investigated tissue volume is large. The simplified model does not need knowledge of the tissue optical parameters and thus should allow the development of very simple and cost-effective LDF hardware

A stochastic model for density-dependent microwave Snow- and Graupel scattering coefficients of the NOAA JCSDA community radiative transfer model

Science.gov (United States)

Stegmann, Patrick G.; Tang, Guanglin; Yang, Ping; Johnson, Benjamin T.

2018-05-01

A structural model is developed for the single-scattering properties of snow and graupel particles with a strongly heterogeneous morphology and an arbitrary variable mass density. This effort is aimed to provide a mechanism to consider particle mass density variation in the microwave scattering coefficients implemented in the Community Radiative Transfer Model (CRTM). The stochastic model applies a bicontinuous random medium algorithm to a simple base shape and uses the Finite-Difference-Time-Domain (FDTD) method to compute the single-scattering properties of the resulting complex morphology.

Stochastic Modelling of the Diffusion Coefficient for Concrete

DEFF Research Database (Denmark)

Thoft-Christensen, Palle

In the paper, a new stochastic modelling of the diffusion coefficient D is presented. The modelling is based on physical understanding of the diffusion process and on some recent experimental results. The diffusion coefficients D is strongly dependent on the w/c ratio and the temperature....

Method of model reduction and multifidelity models for solute transport in random layered porous media

Energy Technology Data Exchange (ETDEWEB)

Xu, Zhijie; Tartakovsky, Alexandre M.

2017-09-01

This work presents a hierarchical model for solute transport in bounded layered porous media with random permeability. The model generalizes the Taylor-Aris dispersion theory to stochastic transport in random layered porous media with a known velocity covariance function. In the hierarchical model, we represent (random) concentration in terms of its cross-sectional average and a variation function. We derive a one-dimensional stochastic advection-dispersion-type equation for the average concentration and a stochastic Poisson equation for the variation function, as well as expressions for the effective velocity and dispersion coefficient. We observe that velocity fluctuations enhance dispersion in a non-monotonic fashion: the dispersion initially increases with correlation length λ, reaches a maximum, and decreases to zero at infinity. Maximum enhancement can be obtained at the correlation length about 0.25 the size of the porous media perpendicular to flow.

Coefficient of restitution of model repaired car body parts

OpenAIRE

D. Hadryś; M. Miros

2008-01-01

Purpose: The qualification of influence of model repaired car body parts on the value of coefficient of restitution and evaluation of impact energy absorption of model repaired car body parts.Design/methodology/approach: Investigation of plastic strain and coefficient of restitution of new and repaired model car body parts with using impact test machine for different impact energy.Findings: The results of investigations show that the value of coefficient of restitution changes with speed (ene...

A new neural network model for solving random interval linear programming problems.

Science.gov (United States)

Arjmandzadeh, Ziba; Safi, Mohammadreza; Nazemi, Alireza

2017-05-01

This paper presents a neural network model for solving random interval linear programming problems. The original problem involving random interval variable coefficients is first transformed into an equivalent convex second order cone programming problem. A neural network model is then constructed for solving the obtained convex second order cone problem. Employing Lyapunov function approach, it is also shown that the proposed neural network model is stable in the sense of Lyapunov and it is globally convergent to an exact satisfactory solution of the original problem. Several illustrative examples are solved in support of this technique. Copyright © 2017 Elsevier Ltd. All rights reserved.

Permeability of model porous medium formed by random discs

Science.gov (United States)

Gubaidullin, A. A.; Gubkin, A. S.; Igoshin, D. E.; Ignatev, P. A.

2018-03-01

Two-dimension model of the porous medium with skeleton of randomly located overlapping discs is proposed. The geometry and computational grid are built in open package Salome. Flow of Newtonian liquid in longitudinal and transverse directions is calculated and its flow rate is defined. The numerical solution of the Navier-Stokes equations for a given pressure drop at the boundaries of the area is realized in the open package OpenFOAM. Calculated value of flow rate is used for defining of permeability coefficient on the base of Darcy law. For evaluating of representativeness of computational domain the permeability coefficients in longitudinal and transverse directions are compered.

Guideline for Adopting the Local Reaction Assumption for Porous Absorbers in Terms of Random Incidence Absorption Coefficients

DEFF Research Database (Denmark)

Jeong, Cheol-Ho

2011-01-01

resistivity and the absorber thickness on the difference between the two surface reaction models are examined and discussed. For a porous absorber backed by a rigid surface, the assumption of local reaction always underestimates the random incidence absorption coefficient and the local reaction models give...... incidence acoustical characteristics of typical building elements made of porous materials assuming extended and local reaction. For each surface reaction, five well-established wave propagation models, the Delany-Bazley, Miki, Beranek, Allard-Champoux, and Biot model, are employed. Effects of the flow...... errors of less than 10% if the thickness exceeds 120 mm for a flow resistivity of 5000 Nm-4s. As the flow resistivity doubles, a decrease in the required thickness by 25 mm is observed to achieve the same amount of error. For an absorber backed by an air gap, the thickness ratio between the material...

Genetic Analysis of Daily Maximum Milking Speed by a Random Walk Model in Dairy Cows

DEFF Research Database (Denmark)

Karacaören, Burak; Janss, Luc; Kadarmideen, Haja

Data were obtained from dairy cows stationed at research farm ETH Zurich for maximum milking speed. The main aims of this paper are a) to evaluate if the Wood curve is suitable to model mean lactation curve b) to predict longitudinal breeding values by random regression and random walk models of ...... filter applications: random walk model could give online prediction of breeding values. Hence without waiting for whole lactation records, genetic evaluation could be made when the daily or monthly data is available......Data were obtained from dairy cows stationed at research farm ETH Zurich for maximum milking speed. The main aims of this paper are a) to evaluate if the Wood curve is suitable to model mean lactation curve b) to predict longitudinal breeding values by random regression and random walk models...... of maximum milking speed. Wood curve did not provide a good fit to the data set. Quadratic random regressions gave better predictions compared with the random walk model. However random walk model does not need to be evaluated for different orders of regression coefficients. In addition with the Kalman...

Overview of models allowing calculation of activity coefficients

Energy Technology Data Exchange (ETDEWEB)

Jaussaud, C.; Sorel, C

2004-07-01

Activity coefficients must be estimated to accurately quantify the extraction equilibrium involved in spent fuel reprocessing. For these calculations, binary data are required for each electrolyte over a concentration range sometimes exceeding the maximum solubility. The activity coefficients must be extrapolated to model the behavior of binary supersaturated aqueous solution. According to the bibliography, the most suitable models are based on the local composition concept. (authors)

Van der Waals coefficients beyond the classical shell model

Energy Technology Data Exchange (ETDEWEB)

Tao, Jianmin, E-mail: jianmint@sas.upenn.edu [Department of Chemistry, University of Pennsylvania, Philadelphia, Pennsylvania 19104-6323 (United States); Fang, Yuan; Hao, Pan [Department of Physics and Engineering Physics, Tulane University, New Orleans, Louisiana 70118 (United States); Scuseria, G. E. [Department of Chemistry and Department of Physics and Astronomy, Rice University, Houston, Texas 77251-1892, USA and Department of Chemistry, Faculty of Science, King Abdulaziz University, Jeddah 21589 (Saudi Arabia); Ruzsinszky, Adrienn; Perdew, John P. [Department of Physics, Temple University, Philadelphia, Pennsylvania 19122 (United States)

2015-01-14

Van der Waals (vdW) coefficients can be accurately generated and understood by modelling the dynamic multipole polarizability of each interacting object. Accurate static polarizabilities are the key to accurate dynamic polarizabilities and vdW coefficients. In this work, we present and study in detail a hollow-sphere model for the dynamic multipole polarizability proposed recently by two of the present authors (JT and JPP) to simulate the vdW coefficients for inhomogeneous systems that allow for a cavity. The inputs to this model are the accurate static multipole polarizabilities and the electron density. A simplification of the full hollow-sphere model, the single-frequency approximation (SFA), circumvents the need for a detailed electron density and for a double numerical integration over space. We find that the hollow-sphere model in SFA is not only accurate for nanoclusters and cage molecules (e.g., fullerenes) but also yields vdW coefficients among atoms, fullerenes, and small clusters in good agreement with expensive time-dependent density functional calculations. However, the classical shell model (CSM), which inputs the static dipole polarizabilities and estimates the static higher-order multipole polarizabilities therefrom, is accurate for the higher-order vdW coefficients only when the interacting objects are large. For the lowest-order vdW coefficient C{sub 6}, SFA and CSM are exactly the same. The higher-order (C{sub 8} and C{sub 10}) terms of the vdW expansion can be almost as important as the C{sub 6} term in molecular crystals. Application to a variety of clusters shows that there is strong non-additivity of the long-range vdW interactions between nanoclusters.

Modification of van La ar activity coefficient model

International Nuclear Information System (INIS)

Vakili-Nezhaad, G. R.; Modarress, H.; Mansoori, G. A.

2001-01-01

Based on statistical and mechanical arguments, the original van La ar activity coefficient model has been improved by reasonable assumptions. This modifications has been done by replacing the van der Waals equation of state with the Redlich-K wong equation of state in the formulation of van La ar with consistent mixing rules for the energy and volume parameters of this equation of state (a mix , b mix ). Other equations of state, such as the Soave modification of the Redlich-K wong equation of state, P eng-Robinson and Mohsen-Nia, Modarress and Mansoori equations of state, have been introduced in the formulation of van La ar for the activity coefficients of the components present in the binary liquid mixtures, and their effects on the accuracy of the resultant activity coefficient models have been examined. The results of these revised models have been compared with the experimental data and it was found that the Redlich-K wong equation of state with the van der Waals mixing rules for the volume and energy parameters of this equation, is the best choice among these equations of state. In addition, it can improve the original van La ar activity coefficient model and, therefore a better agreement with the experimental data is obtained

Partially linear varying coefficient models stratified by a functional covariate

KAUST Repository

Maity, Arnab; Huang, Jianhua Z.

2012-01-01

We consider the problem of estimation in semiparametric varying coefficient models where the covariate modifying the varying coefficients is functional and is modeled nonparametrically. We develop a kernel-based estimator of the nonparametric

New limb-darkening coefficients for modeling binary star light curves

Science.gov (United States)

Van Hamme, W.

1993-01-01

We present monochromatic, passband-specific, and bolometric limb-darkening coefficients for a linear as well as nonlinear logarithmic and square root limb-darkening laws. These coefficients, including the bolometric ones, are needed when modeling binary star light curves with the latest version of the Wilson-Devinney light curve progam. We base our calculations on the most recent ATLAS stellar atmosphere models for solar chemical composition stars with a wide range of effective temperatures and surface gravitites. We examine how well various limb-darkening approximations represent the variation of the emerging specific intensity across a stellar surface as computed according to the model. For binary star light curve modeling purposes, we propose the use of a logarithmic or a square root law. We design our tables in such a manner that the relative quality of either law with respect to another can be easily compared. Since the computation of bolometric limb-darkening coefficients first requires monochromatic coefficients, we also offer tables of these coefficients (at 1221 wavelength values between 9.09 nm and 160 micrometer) and tables of passband-specific coefficients for commonly used photometric filters.

Non-linear Bayesian update of PCE coefficients

KAUST Repository

Litvinenko, Alexander

2014-01-06

Given: a physical system modeled by a PDE or ODE with uncertain coefficient q(?), a measurement operator Y (u(q), q), where u(q, ?) uncertain solution. Aim: to identify q(?). The mapping from parameters to observations is usually not invertible, hence this inverse identification problem is generally ill-posed. To identify q(!) we derived non-linear Bayesian update from the variational problem associated with conditional expectation. To reduce cost of the Bayesian update we offer a unctional approximation, e.g. polynomial chaos expansion (PCE). New: We apply Bayesian update to the PCE coefficients of the random coefficient q(?) (not to the probability density function of q).

Non-linear Bayesian update of PCE coefficients

KAUST Repository

Litvinenko, Alexander; Matthies, Hermann G.; Pojonk, Oliver; Rosic, Bojana V.; Zander, Elmar

2014-01-01

Given: a physical system modeled by a PDE or ODE with uncertain coefficient q(?), a measurement operator Y (u(q), q), where u(q, ?) uncertain solution. Aim: to identify q(?). The mapping from parameters to observations is usually not invertible, hence this inverse identification problem is generally ill-posed. To identify q(!) we derived non-linear Bayesian update from the variational problem associated with conditional expectation. To reduce cost of the Bayesian update we offer a unctional approximation, e.g. polynomial chaos expansion (PCE). New: We apply Bayesian update to the PCE coefficients of the random coefficient q(?) (not to the probability density function of q).

Random diffusion and leverage effect in financial markets.

Science.gov (United States)

Perelló, Josep; Masoliver, Jaume

2003-03-01

We prove that Brownian market models with random diffusion coefficients provide an exact measure of the leverage effect [J-P. Bouchaud et al., Phys. Rev. Lett. 87, 228701 (2001)]. This empirical fact asserts that past returns are anticorrelated with future diffusion coefficient. Several models with random diffusion have been suggested but without a quantitative study of the leverage effect. Our analysis lets us to fully estimate all parameters involved and allows a deeper study of correlated random diffusion models that may have practical implications for many aspects of financial markets.

Rock shape, restitution coefficients and rockfall trajectory modelling

Science.gov (United States)

Glover, James; Christen, Marc; Bühler, Yves; Bartelt, Perry

2014-05-01

Restitution coefficients are used in rockfall trajectory modelling to describe the ratio between incident and rebound velocities during ground impact. They are central to the problem of rockfall hazard analysis as they link rock mass characteristics to terrain properties. Using laboratory experiments as a guide, we first show that restitution coefficients exhibit a wide range of scatter, although the material properties of the rock and ground are constant. This leads us to the conclusion that restitution coefficients are poor descriptors of rock-ground interaction. The primary problem is that "apparent" restitution coefficients are applied at the rock's centre-of-mass and do not account for rock shape. An accurate description of the rock-ground interaction requires the contact forces to be applied at the rock surface with consideration of the momentary rock position and spin. This leads to a variety of rock motions including bouncing, sliding, skipping and rolling. Depending on the impact configuration a wide range of motions is possible. This explains the large scatter of apparent restitution coefficients. We present a rockfall model based on newly developed hard-contact algorithms which includes the effects of rock shape and therefore is able to reproduce the results of different impact configurations. We simulate the laboratory experiments to show that it is possible to reproduce run-out and dispersion of different rock shapes using parameters obtained from independent tests. Although this is a step forward in rockfall trajectory modelling, the problem of parametersing real terrain remains.

Statistical properties of random clique networks

Science.gov (United States)

Ding, Yi-Min; Meng, Jun; Fan, Jing-Fang; Ye, Fang-Fu; Chen, Xiao-Song

2017-10-01

In this paper, a random clique network model to mimic the large clustering coefficient and the modular structure that exist in many real complex networks, such as social networks, artificial networks, and protein interaction networks, is introduced by combining the random selection rule of the Erdös and Rényi (ER) model and the concept of cliques. We find that random clique networks having a small average degree differ from the ER network in that they have a large clustering coefficient and a power law clustering spectrum, while networks having a high average degree have similar properties as the ER model. In addition, we find that the relation between the clustering coefficient and the average degree shows a non-monotonic behavior and that the degree distributions can be fit by multiple Poisson curves; we explain the origin of such novel behaviors and degree distributions.

A comparison of confidence interval methods for the intraclass correlation coefficient in community-based cluster randomization trials with a binary outcome.

Science.gov (United States)

Braschel, Melissa C; Svec, Ivana; Darlington, Gerarda A; Donner, Allan

2016-04-01

Many investigators rely on previously published point estimates of the intraclass correlation coefficient rather than on their associated confidence intervals to determine the required size of a newly planned cluster randomized trial. Although confidence interval methods for the intraclass correlation coefficient that can be applied to community-based trials have been developed for a continuous outcome variable, fewer methods exist for a binary outcome variable. The aim of this study is to evaluate confidence interval methods for the intraclass correlation coefficient applied to binary outcomes in community intervention trials enrolling a small number of large clusters. Existing methods for confidence interval construction are examined and compared to a new ad hoc approach based on dividing clusters into a large number of smaller sub-clusters and subsequently applying existing methods to the resulting data. Monte Carlo simulation is used to assess the width and coverage of confidence intervals for the intraclass correlation coefficient based on Smith's large sample approximation of the standard error of the one-way analysis of variance estimator, an inverted modified Wald test for the Fleiss-Cuzick estimator, and intervals constructed using a bootstrap-t applied to a variance-stabilizing transformation of the intraclass correlation coefficient estimate. In addition, a new approach is applied in which clusters are randomly divided into a large number of smaller sub-clusters with the same methods applied to these data (with the exception of the bootstrap-t interval, which assumes large cluster sizes). These methods are also applied to a cluster randomized trial on adolescent tobacco use for illustration. When applied to a binary outcome variable in a small number of large clusters, existing confidence interval methods for the intraclass correlation coefficient provide poor coverage. However, confidence intervals constructed using the new approach combined with Smith

Influence of inhomogeneous surface heat capacity on the estimation of radiative response coefficients in a two-zone energy balance model

Science.gov (United States)

Park, Jungmin; Choi, Yong-Sang

2018-04-01

Observationally constrained values of the global radiative response coefficient are pivotal to assess the reliability of modeled climate feedbacks. A widely used approach is to measure transient global radiative imbalance related to surface temperature changes. However, in this approach, a potential error in the estimate of radiative response coefficients may arise from surface inhomogeneity in the climate system. We examined this issue theoretically using a simple two-zone energy balance model. Here, we dealt with the potential error by subtracting the prescribed radiative response coefficient from those calculated within the two-zone framework. Each zone was characterized by the different magnitude of the radiative response coefficient and the surface heat capacity, and the dynamical heat transport in the atmosphere between the zones was parameterized as a linear function of the temperature difference between the zones. Then, the model system was forced by randomly generated monthly varying forcing mimicking time-varying forcing like an observation. The repeated simulations showed that inhomogeneous surface heat capacity causes considerable miscalculation (down to -1.4 W m-2 K-1 equivalent to 31.3% of the prescribed value) in the global radiative response coefficient. Also, the dynamical heat transport reduced this miscalculation driven by inhomogeneity of surface heat capacity. Therefore, the estimation of radiative response coefficients using the surface temperature-radiation relation is appropriate for homogeneous surface areas least affected by the exterior.

Exploring the Influence of Neighborhood Characteristics on Burglary Risks: A Bayesian Random Effects Modeling Approach

Directory of Open Access Journals (Sweden)

Hongqiang Liu

2016-06-01

Full Text Available A Bayesian random effects modeling approach was used to examine the influence of neighborhood characteristics on burglary risks in Jianghan District, Wuhan, China. This random effects model is essentially spatial; a spatially structured random effects term and an unstructured random effects term are added to the traditional non-spatial Poisson regression model. Based on social disorganization and routine activity theories, five covariates extracted from the available data at the neighborhood level were used in the modeling. Three regression models were fitted and compared by the deviance information criterion to identify which model best fit our data. A comparison of the results from the three models indicates that the Bayesian random effects model is superior to the non-spatial models in fitting the data and estimating regression coefficients. Our results also show that neighborhoods with above average bar density and department store density have higher burglary risks. Neighborhood-specific burglary risks and posterior probabilities of neighborhoods having a burglary risk greater than 1.0 were mapped, indicating the neighborhoods that should warrant more attention and be prioritized for crime intervention and reduction. Implications and limitations of the study are discussed in our concluding section.

Convergence of quasi-optimal Stochastic Galerkin methods for a class of PDES with random coefficients

KAUST Repository

Beck, Joakim; Nobile, Fabio; Tamellini, Lorenzo; Tempone, Raul

2014-01-01

In this work we consider quasi-optimal versions of the Stochastic Galerkin method for solving linear elliptic PDEs with stochastic coefficients. In particular, we consider the case of a finite number N of random inputs and an analytic dependence of the solution of the PDE with respect to the parameters in a polydisc of the complex plane CN. We show that a quasi-optimal approximation is given by a Galerkin projection on a weighted (anisotropic) total degree space and prove a (sub)exponential convergence rate. As a specific application we consider a thermal conduction problem with non-overlapping inclusions of random conductivity. Numerical results show the sharpness of our estimates. © 2013 Elsevier Ltd. All rights reserved.

Convergence of quasi-optimal Stochastic Galerkin methods for a class of PDES with random coefficients

KAUST Repository

Beck, Joakim

2014-03-01

In this work we consider quasi-optimal versions of the Stochastic Galerkin method for solving linear elliptic PDEs with stochastic coefficients. In particular, we consider the case of a finite number N of random inputs and an analytic dependence of the solution of the PDE with respect to the parameters in a polydisc of the complex plane CN. We show that a quasi-optimal approximation is given by a Galerkin projection on a weighted (anisotropic) total degree space and prove a (sub)exponential convergence rate. As a specific application we consider a thermal conduction problem with non-overlapping inclusions of random conductivity. Numerical results show the sharpness of our estimates. © 2013 Elsevier Ltd. All rights reserved.

Basis adaptation and domain decomposition for steady-state partial differential equations with random coefficients

Energy Technology Data Exchange (ETDEWEB)

Tipireddy, R.; Stinis, P.; Tartakovsky, A. M.

2017-12-01

We present a novel approach for solving steady-state stochastic partial differential equations (PDEs) with high-dimensional random parameter space. The proposed approach combines spatial domain decomposition with basis adaptation for each subdomain. The basis adaptation is used to address the curse of dimensionality by constructing an accurate low-dimensional representation of the stochastic PDE solution (probability density function and/or its leading statistical moments) in each subdomain. Restricting the basis adaptation to a specific subdomain affords finding a locally accurate solution. Then, the solutions from all of the subdomains are stitched together to provide a global solution. We support our construction with numerical experiments for a steady-state diffusion equation with a random spatially dependent coefficient. Our results show that highly accurate global solutions can be obtained with significantly reduced computational costs.

Backward Stochastic Riccati Equations and Infinite Horizon L-Q Optimal Control with Infinite Dimensional State Space and Random Coefficients

International Nuclear Information System (INIS)

Guatteri, Giuseppina; Tessitore, Gianmario

2008-01-01

We study the Riccati equation arising in a class of quadratic optimal control problems with infinite dimensional stochastic differential state equation and infinite horizon cost functional. We allow the coefficients, both in the state equation and in the cost, to be random.In such a context backward stochastic Riccati equations are backward stochastic differential equations in the whole positive real axis that involve quadratic non-linearities and take values in a non-Hilbertian space. We prove existence of a minimal non-negative solution and, under additional assumptions, its uniqueness. We show that such a solution allows to perform the synthesis of the optimal control and investigate its attractivity properties. Finally the case where the coefficients are stationary is addressed and an example concerning a controlled wave equation in random media is proposed

Modeling and optimizing of the random atomic spin gyroscope drift based on the atomic spin gyroscope

Energy Technology Data Exchange (ETDEWEB)

Quan, Wei; Lv, Lin, E-mail: lvlinlch1990@163.com; Liu, Baiqi [School of Instrument Science and Opto-Electronics Engineering, Beihang University, Beijing 100191 (China)

2014-11-15

In order to improve the atom spin gyroscope's operational accuracy and compensate the random error caused by the nonlinear and weak-stability characteristic of the random atomic spin gyroscope (ASG) drift, the hybrid random drift error model based on autoregressive (AR) and genetic programming (GP) + genetic algorithm (GA) technique is established. The time series of random ASG drift is taken as the study object. The time series of random ASG drift is acquired by analyzing and preprocessing the measured data of ASG. The linear section model is established based on AR technique. After that, the nonlinear section model is built based on GP technique and GA is used to optimize the coefficients of the mathematic expression acquired by GP in order to obtain a more accurate model. The simulation result indicates that this hybrid model can effectively reflect the characteristics of the ASG's random drift. The square error of the ASG's random drift is reduced by 92.40%. Comparing with the AR technique and the GP + GA technique, the random drift is reduced by 9.34% and 5.06%, respectively. The hybrid modeling method can effectively compensate the ASG's random drift and improve the stability of the system.

Regression Models for Predicting Force Coefficients of Aerofoils

Directory of Open Access Journals (Sweden)

Mohammed ABDUL AKBAR

2015-09-01

Full Text Available Renewable sources of energy are attractive and advantageous in a lot of different ways. Among the renewable energy sources, wind energy is the fastest growing type. Among wind energy converters, Vertical axis wind turbines (VAWTs have received renewed interest in the past decade due to some of the advantages they possess over their horizontal axis counterparts. VAWTs have evolved into complex 3-D shapes. A key component in predicting the output of VAWTs through analytical studies is obtaining the values of lift and drag coefficients which is a function of shape of the aerofoil, ‘angle of attack’ of wind and Reynolds’s number of flow. Sandia National Laboratories have carried out extensive experiments on aerofoils for the Reynolds number in the range of those experienced by VAWTs. The volume of experimental data thus obtained is huge. The current paper discusses three Regression analysis models developed wherein lift and drag coefficients can be found out using simple formula without having to deal with the bulk of the data. Drag coefficients and Lift coefficients were being successfully estimated by regression models with R2 values as high as 0.98.

Uncertainty Quantification of Turbulence Model Closure Coefficients for Transonic Wall-Bounded Flows

Science.gov (United States)

Schaefer, John; West, Thomas; Hosder, Serhat; Rumsey, Christopher; Carlson, Jan-Renee; Kleb, William

2015-01-01

The goal of this work was to quantify the uncertainty and sensitivity of commonly used turbulence models in Reynolds-Averaged Navier-Stokes codes due to uncertainty in the values of closure coefficients for transonic, wall-bounded flows and to rank the contribution of each coefficient to uncertainty in various output flow quantities of interest. Specifically, uncertainty quantification of turbulence model closure coefficients was performed for transonic flow over an axisymmetric bump at zero degrees angle of attack and the RAE 2822 transonic airfoil at a lift coefficient of 0.744. Three turbulence models were considered: the Spalart-Allmaras Model, Wilcox (2006) k-w Model, and the Menter Shear-Stress Trans- port Model. The FUN3D code developed by NASA Langley Research Center was used as the flow solver. The uncertainty quantification analysis employed stochastic expansions based on non-intrusive polynomial chaos as an efficient means of uncertainty propagation. Several integrated and point-quantities are considered as uncertain outputs for both CFD problems. All closure coefficients were treated as epistemic uncertain variables represented with intervals. Sobol indices were used to rank the relative contributions of each closure coefficient to the total uncertainty in the output quantities of interest. This study identified a number of closure coefficients for each turbulence model for which more information will reduce the amount of uncertainty in the output significantly for transonic, wall-bounded flows.

Simulating intrafraction prostate motion with a random walk model.

Science.gov (United States)

Pommer, Tobias; Oh, Jung Hun; Munck Af Rosenschöld, Per; Deasy, Joseph O

2017-01-01

Prostate motion during radiation therapy (ie, intrafraction motion) can cause unwanted loss of radiation dose to the prostate and increased dose to the surrounding organs at risk. A compact but general statistical description of this motion could be useful for simulation of radiation therapy delivery or margin calculations. We investigated whether prostate motion could be modeled with a random walk model. Prostate motion recorded during 548 radiation therapy fractions in 17 patients was analyzed and used for input in a random walk prostate motion model. The recorded motion was categorized on the basis of whether any transient excursions (ie, rapid prostate motion in the anterior and superior direction followed by a return) occurred in the trace and transient motion. This was separately modeled as a large step in the anterior/superior direction followed by a returning large step. Random walk simulations were conducted with and without added artificial transient motion using either motion data from all observed traces or only traces without transient excursions as model input, respectively. A general estimate of motion was derived with reasonable agreement between simulated and observed traces, especially during the first 5 minutes of the excursion-free simulations. Simulated and observed diffusion coefficients agreed within 0.03, 0.2 and 0.3 mm 2 /min in the left/right, superior/inferior, and anterior/posterior directions, respectively. A rapid increase in variance at the start of observed traces was difficult to reproduce and seemed to represent the patient's need to adjust before treatment. This could be estimated somewhat using artificial transient motion. Random walk modeling is feasible and recreated the characteristics of the observed prostate motion. Introducing artificial transient motion did not improve the overall agreement, although the first 30 seconds of the traces were better reproduced. The model provides a simple estimate of prostate motion during

The influence of numerical models on determining the drag coefficient

Directory of Open Access Journals (Sweden)

Dobeš Josef

2014-03-01

Full Text Available The paper deals with numerical modelling of body aerodynamic drag coefficient in the transition from laminar to turbulent flow regimes, where the selection of a suitable numerical model is problematic. On the basic problem of flow around a simple body – sphere selected computational models are tested. The values obtained by numerical simulations of drag coefficients of each model are compared with the graph of dependency of the drag coefficient vs. Reynolds number for a sphere. Next the dependency of Strouhal number vs. Reynolds number is evaluated, where the vortex shedding frequency values for given speed are obtained numerically and experimentally and then the values are compared for each numerical model and experiment. The aim is to specify trends for the selection of appropriate numerical model for flow around bodies problem in which the precise description of the flow field around the obstacle is used to define the acoustic noise source. Numerical modelling is performed by finite volume method using CFD code.

Modelling of power-reactivity coefficient measurement

International Nuclear Information System (INIS)

Strmensky, C.; Petenyi, V.; Jagrik, J.; Minarcin, M.; Hascik, R.; Toth, L.

2005-01-01

Report describes results of modeling of power-reactivity coefficient analysis on power-level. In paper we calculate values of discrepancies arisen during transient process. These discrepancies can be arisen as result of experiment evaluation and can be caused by disregard of 3D effects on neutron distribution. The results are critically discussed (Authors)

Monte Carlo tests of the Rasch model based on scalability coefficients

DEFF Research Database (Denmark)

Christensen, Karl Bang; Kreiner, Svend

2010-01-01

that summarizes the number of Guttman errors in the data matrix. These coefficients are shown to yield efficient tests of the Rasch model using p-values computed using Markov chain Monte Carlo methods. The power of the tests of unequal item discrimination, and their ability to distinguish between local dependence......For item responses fitting the Rasch model, the assumptions underlying the Mokken model of double monotonicity are met. This makes non-parametric item response theory a natural starting-point for Rasch item analysis. This paper studies scalability coefficients based on Loevinger's H coefficient...

Modeling Ballasted Tracks for Runoff Coefficient C

Science.gov (United States)

2012-08-01

In this study, the Regional Transportation District (RTD)s light rail tracks were modeled to determine the Rational Method : runoff coefficient, C, values corresponding to ballasted tracks. To accomplish this, a laboratory study utilizing a : rain...

Estimating overall exposure effects for the clustered and censored outcome using random effect Tobit regression models.

Science.gov (United States)

Wang, Wei; Griswold, Michael E

2016-11-30

The random effect Tobit model is a regression model that accommodates both left- and/or right-censoring and within-cluster dependence of the outcome variable. Regression coefficients of random effect Tobit models have conditional interpretations on a constructed latent dependent variable and do not provide inference of overall exposure effects on the original outcome scale. Marginalized random effects model (MREM) permits likelihood-based estimation of marginal mean parameters for the clustered data. For random effect Tobit models, we extend the MREM to marginalize over both the random effects and the normal space and boundary components of the censored response to estimate overall exposure effects at population level. We also extend the 'Average Predicted Value' method to estimate the model-predicted marginal means for each person under different exposure status in a designated reference group by integrating over the random effects and then use the calculated difference to assess the overall exposure effect. The maximum likelihood estimation is proposed utilizing a quasi-Newton optimization algorithm with Gauss-Hermite quadrature to approximate the integration of the random effects. We use these methods to carefully analyze two real datasets. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Comparison of Experimental Methods for Estimating Matrix Diffusion Coefficients for Contaminant Transport Modeling

Energy Technology Data Exchange (ETDEWEB)

Telfeyan, Katherine Christina [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Ware, Stuart Douglas [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Reimus, Paul William [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Birdsell, Kay Hanson [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

2017-11-06

Diffusion cell and diffusion wafer experiments were conducted to compare methods for estimating matrix diffusion coefficients in rock core samples from Pahute Mesa at the Nevada Nuclear Security Site (NNSS). A diffusion wafer method, in which a solute diffuses out of a rock matrix that is pre-saturated with water containing the solute, is presented as a simpler alternative to the traditional through-diffusion (diffusion cell) method. Both methods yielded estimates of matrix diffusion coefficients that were within the range of values previously reported for NNSS volcanic rocks. The difference between the estimates of the two methods ranged from 14 to 30%, and there was no systematic high or low bias of one method relative to the other. From a transport modeling perspective, these differences are relatively minor when one considers that other variables (e.g., fracture apertures, fracture spacings) influence matrix diffusion to a greater degree and tend to have greater uncertainty than diffusion coefficients. For the same relative random errors in concentration measurements, the diffusion cell method yields diffusion coefficient estimates that have less uncertainty than the wafer method. However, the wafer method is easier and less costly to implement and yields estimates more quickly, thus allowing a greater number of samples to be analyzed for the same cost and time. Given the relatively good agreement between the methods, and the lack of any apparent bias between the methods, the diffusion wafer method appears to offer advantages over the diffusion cell method if better statistical representation of a given set of rock samples is desired.

Comparison of experimental methods for estimating matrix diffusion coefficients for contaminant transport modeling

Science.gov (United States)

Telfeyan, Katherine; Ware, S. Doug; Reimus, Paul W.; Birdsell, Kay H.

2018-02-01

Diffusion cell and diffusion wafer experiments were conducted to compare methods for estimating effective matrix diffusion coefficients in rock core samples from Pahute Mesa at the Nevada Nuclear Security Site (NNSS). A diffusion wafer method, in which a solute diffuses out of a rock matrix that is pre-saturated with water containing the solute, is presented as a simpler alternative to the traditional through-diffusion (diffusion cell) method. Both methods yielded estimates of effective matrix diffusion coefficients that were within the range of values previously reported for NNSS volcanic rocks. The difference between the estimates of the two methods ranged from 14 to 30%, and there was no systematic high or low bias of one method relative to the other. From a transport modeling perspective, these differences are relatively minor when one considers that other variables (e.g., fracture apertures, fracture spacings) influence matrix diffusion to a greater degree and tend to have greater uncertainty than effective matrix diffusion coefficients. For the same relative random errors in concentration measurements, the diffusion cell method yields effective matrix diffusion coefficient estimates that have less uncertainty than the wafer method. However, the wafer method is easier and less costly to implement and yields estimates more quickly, thus allowing a greater number of samples to be analyzed for the same cost and time. Given the relatively good agreement between the methods, and the lack of any apparent bias between the methods, the diffusion wafer method appears to offer advantages over the diffusion cell method if better statistical representation of a given set of rock samples is desired.

A Solution Method for Linear and Geometrically Nonlinear MDOF Systems with Random Properties subject to Random Excitation

DEFF Research Database (Denmark)

Micaletti, R. C.; Cakmak, A. S.; Nielsen, Søren R. K.

structural properties. The resulting state-space formulation is a system of ordinary stochastic differential equations with random coefficient and deterministic initial conditions which are subsequently transformed into ordinary stochastic differential equations with deterministic coefficients and random......A method for computing the lower-order moments of randomly-excited multi-degree-of-freedom (MDOF) systems with random structural properties is proposed. The method is grounded in the techniques of stochastic calculus, utilizing a Markov diffusion process to model the structural system with random...... initial conditions. This transformation facilitates the derivation of differential equations which govern the evolution of the unconditional statistical moments of response. Primary consideration is given to linear systems and systems with odd polynomial nonlinearities, for in these cases...

Friction coefficient and limiter load test analysis by flexibility coefficient model of Hold-Down Spring of nuclear reactor vessel internals

Energy Technology Data Exchange (ETDEWEB)

Xie, Linjun [Zhejiang Univ. of Technology, Hangzhou (China). College of Mechanical Engineering; Xue, Guohong; Zhang, Ming [Shanghai Nuclear Engineering Research and Design Institute, Shanghai (China)

2017-11-15

The friction force between the contact surfaces of a reactor internal hold-down spring (HDS) and core barrel flanges can directly influence the axial stiffness of an HDS. However, friction coefficient cannot be obtained through theoretical analysis. This study performs a mathematical deduction of the physical model of an HDS. Moreover, a mathematical model of axial load P, displacement δ, and flexibility coefficient is established, and a set of test apparatuses is designed to simulate the preloading process of the HDS. According to the experimental research and theoretical analysis, P-δ curves and the flexibility coefficient λ are obtained in the loading processes of the HDS. The friction coefficient f of the M1000 HDS is further calculated as 0.224. The displacement limit load value (4,638 kN) can be obtained through a displacement limit experiment. With the friction coefficient considered, the theoretical load is 4,271 kN, which is relatively close to the experimental result. Thus, the friction coefficient exerts an influence on the displacement limit load P. The friction coefficient should be considered in the design analysis for HDS.

Friction coefficient and limiter load test analysis by flexibility coefficient model of Hold-Down Spring of nuclear reactor vessel internals

International Nuclear Information System (INIS)

Xie, Linjun

2017-01-01

The friction force between the contact surfaces of a reactor internal hold-down spring (HDS) and core barrel flanges can directly influence the axial stiffness of an HDS. However, friction coefficient cannot be obtained through theoretical analysis. This study performs a mathematical deduction of the physical model of an HDS. Moreover, a mathematical model of axial load P, displacement δ, and flexibility coefficient is established, and a set of test apparatuses is designed to simulate the preloading process of the HDS. According to the experimental research and theoretical analysis, P-δ curves and the flexibility coefficient λ are obtained in the loading processes of the HDS. The friction coefficient f of the M1000 HDS is further calculated as 0.224. The displacement limit load value (4,638 kN) can be obtained through a displacement limit experiment. With the friction coefficient considered, the theoretical load is 4,271 kN, which is relatively close to the experimental result. Thus, the friction coefficient exerts an influence on the displacement limit load P. The friction coefficient should be considered in the design analysis for HDS.

Variable-coefficient higher-order nonlinear Schroedinger model in optical fibers: Variable-coefficient bilinear form, Baecklund transformation, brightons and symbolic computation

International Nuclear Information System (INIS)

Tian Bo; Gao Yitian; Zhu Hongwu

2007-01-01

Symbolically investigated in this Letter is a variable-coefficient higher-order nonlinear Schroedinger (vcHNLS) model for ultrafast signal-routing, fiber laser systems and optical communication systems with distributed dispersion and nonlinearity management. Of physical and optical interests, with bilinear method extend, the vcHNLS model is transformed into a variable-coefficient bilinear form, and then an auto-Baecklund transformation is constructed. Constraints on coefficient functions are analyzed. Potentially observable with future optical-fiber experiments, variable-coefficient brightons are illustrated. Relevant properties and features are discussed as well. Baecklund transformation and other results of this Letter will be of certain value to the studies on inhomogeneous fiber media, core of dispersion-managed brightons, fiber amplifiers, laser systems and optical communication links with distributed dispersion and nonlinearity management

Solution Methods for Structures with Random Properties Subject to Random Excitation

DEFF Research Database (Denmark)

Köylüoglu, H. U.; Nielsen, Søren R. K.; Cakmak, A. S.

This paper deals with the lower order statistical moments of the response of structures with random stiffness and random damping properties subject to random excitation. The arising stochastic differential equations (SDE) with random coefficients are solved by two methods, a second order...... the SDE with random coefficients with deterministic initial conditions to an equivalent nonlinear SDE with deterministic coefficient and random initial conditions. In both methods, the statistical moment equations are used. Hierarchy of statistical moments in the markovian approach is closed...... by the cumulant neglect closure method applied at the fourth order level....

Partially linear varying coefficient models stratified by a functional covariate

KAUST Repository

Maity, Arnab

2012-10-01

We consider the problem of estimation in semiparametric varying coefficient models where the covariate modifying the varying coefficients is functional and is modeled nonparametrically. We develop a kernel-based estimator of the nonparametric component and a profiling estimator of the parametric component of the model and derive their asymptotic properties. Specifically, we show the consistency of the nonparametric functional estimates and derive the asymptotic expansion of the estimates of the parametric component. We illustrate the performance of our methodology using a simulation study and a real data application.

Modeling and experiments for the time-dependent diffusion coefficient during methane desorption from coal

Science.gov (United States)

Cheng-Wu, Li; Hong-Lai, Xue; Cheng, Guan; Wen-biao, Liu

2018-04-01

Statistical analysis shows that in the coal matrix, the diffusion coefficient for methane is time-varying, and its integral satisfies the formula μt κ /(1 + β κ ). Therefore, a so-called dynamic diffusion coefficient model (DDC model) is developed. To verify the suitability and accuracy of the DDC model, a series of gas diffusion experiments were conducted using coal particles of different sizes. The results show that the experimental data can be accurately described by the DDC and bidisperse models, but the fit to the DDC model is slightly better. For all coal samples, as time increases, the effective diffusion coefficient first shows a sudden drop, followed by a gradual decrease before stabilizing at longer times. The effective diffusion coefficient has a negative relationship with the size of the coal particle. Finally, the relationship between the constants of the DDC model and the effective diffusion coefficient is discussed. The constant α (μ/R 2 ) denotes the effective coefficient at the initial time, and the constants κ and β control the attenuation characteristic of the effective diffusion coefficient.

Surplus thermal energy model of greenhouses and coefficient analysis for effective utilization

Directory of Open Access Journals (Sweden)

Seung-Hwan Yang

2016-03-01

Full Text Available If a greenhouse in the temperate and subtropical regions is maintained in a closed condition, the indoor temperature commonly exceeds that required for optimal plant growth, even in the cold season. This study considered this excess energy as surplus thermal energy (STE, which can be recovered, stored and used when heating is necessary. To use the STE economically and effectively, the amount of STE must be estimated before designing a utilization system. Therefore, this study proposed an STE model using energy balance equations for the three steps of the STE generation process. The coefficients in the model were determined by the results of previous research and experiments using the test greenhouse. The proposed STE model produced monthly errors of 17.9%, 10.4% and 7.4% for December, January and February, respectively. Furthermore, the effects of the coefficients on the model accuracy were revealed by the estimation error assessment and linear regression analysis through fixing dynamic coefficients. A sensitivity analysis of the model coefficients indicated that the coefficients have to be determined carefully. This study also provides effective ways to increase the amount of STE.

Surplus thermal energy model of greenhouses and coefficient analysis for effective utilization

Energy Technology Data Exchange (ETDEWEB)

Yang, S.H.; Son, J.E.; Lee, S.D.; Cho, S.I.; Ashtiani-Araghi, A.; Rhee, J.Y.

2016-11-01

If a greenhouse in the temperate and subtropical regions is maintained in a closed condition, the indoor temperature commonly exceeds that required for optimal plant growth, even in the cold season. This study considered this excess energy as surplus thermal energy (STE), which can be recovered, stored and used when heating is necessary. To use the STE economically and effectively, the amount of STE must be estimated before designing a utilization system. Therefore, this study proposed an STE model using energy balance equations for the three steps of the STE generation process. The coefficients in the model were determined by the results of previous research and experiments using the test greenhouse. The proposed STE model produced monthly errors of 17.9%, 10.4% and 7.4% for December, January and February, respectively. Furthermore, the effects of the coefficients on the model accuracy were revealed by the estimation error assessment and linear regression analysis through fixing dynamic coefficients. A sensitivity analysis of the model coefficients indicated that the coefficients have to be determined carefully. This study also provides effective ways to increase the amount of STE. (Author)

A varying-coefficient method for analyzing longitudinal clinical trials data with nonignorable dropout

Science.gov (United States)

Forster, Jeri E.; MaWhinney, Samantha; Ball, Erika L.; Fairclough, Diane

2011-01-01

Dropout is common in longitudinal clinical trials and when the probability of dropout depends on unobserved outcomes even after conditioning on available data, it is considered missing not at random and therefore nonignorable. To address this problem, mixture models can be used to account for the relationship between a longitudinal outcome and dropout. We propose a Natural Spline Varying-coefficient mixture model (NSV), which is a straightforward extension of the parametric Conditional Linear Model (CLM). We assume that the outcome follows a varying-coefficient model conditional on a continuous dropout distribution. Natural cubic B-splines are used to allow the regression coefficients to semiparametrically depend on dropout and inference is therefore more robust. Additionally, this method is computationally stable and relatively simple to implement. We conduct simulation studies to evaluate performance and compare methodologies in settings where the longitudinal trajectories are linear and dropout time is observed for all individuals. Performance is assessed under conditions where model assumptions are both met and violated. In addition, we compare the NSV to the CLM and a standard random-effects model using an HIV/AIDS clinical trial with probable nonignorable dropout. The simulation studies suggest that the NSV is an improvement over the CLM when dropout has a nonlinear dependence on the outcome. PMID:22101223

Pedestrian Walking Behavior Revealed through a Random Walk Model

Directory of Open Access Journals (Sweden)

Hui Xiong

2012-01-01

Full Text Available This paper applies method of continuous-time random walks for pedestrian flow simulation. In the model, pedestrians can walk forward or backward and turn left or right if there is no block. Velocities of pedestrian flow moving forward or diffusing are dominated by coefficients. The waiting time preceding each jump is assumed to follow an exponential distribution. To solve the model, a second-order two-dimensional partial differential equation, a high-order compact scheme with the alternating direction implicit method, is employed. In the numerical experiments, the walking domain of the first one is two-dimensional with two entrances and one exit, and that of the second one is two-dimensional with one entrance and one exit. The flows in both scenarios are one way. Numerical results show that the model can be used for pedestrian flow simulation.

Measurement and modeling of interface heat transfer coefficients

International Nuclear Information System (INIS)

Rollett, A.D.; Lewis, H.D.; Dunn, P.S.

1985-01-01

The results of preliminary work on the modeling and measurement of the heat transfer coefficients of metal/mold interfaces is reported. The system investigated is the casting of uranium in graphite molds. The motivation for the work is primarily to improve the accuracy of process modeling of prototype mold designs at the Los Alamos Foundry. The evolution in design of a suitable mold for unidirectional solidification is described, illustrating the value of simulating mold designs prior to use. Experiment indicated a heat transfer coefficient of 2 kW/m 2 /K both with and without superheat. It was possible to distinguish between solidification due to the mold and that due to radiative heat loss. This permitted an experimental estimate of the emissivity, epsilon = 0.2, of the solidified metal

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

Science.gov (United States)

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.

Modelling the light absorption coefficients of oceanic waters: Implications for underwater optical applications

Science.gov (United States)

Prabhakaran, Sai Shri; Sahu, Sanjay Kumar; Dev, Pravin Jeba; Shanmugam, Palanisamy

2018-05-01

Spectral absorption coefficients of particulate (algal and non-algal components) and dissolved substances are modelled and combined with the pure seawater component to determine the total light absorption coefficients of seawater in the Bay of Bengal. Two parameters namely chlorophyll-a (Chl) concentration and turbidity were measured using commercially available instruments with high sampling rates. For modelling the light absorption coefficients of oceanic waters, the measured data are classified into two broad groups - algal dominant and non-algal particle (NAP) dominant. With these criteria the individual absorption coefficients of phytoplankton and NAP were established based on their concentrations using an iterative method. To account for the spectral dependence of absorption by phytoplankton, the wavelength-dependent coefficients were introduced into the model. The CDOM absorption was determined by subtracting the individual absorption coefficients of phytoplankton and NAP from the measured total absorption data and then related to the Chl concentration. Validity of the model is assessed based on independent in-situ data from certain discrete locations in the Bay of Bengal. The total absorption coefficients estimated using the new model by considering the contributions of algal, non-algal and CDOM have good agreement with the measured total absorption data with the error range of 6.9 to 28.3%. Results obtained by the present model are important for predicting the propagation of the radiant energy within the ocean and interpreting remote sensing observation data.

Modeling diffusion coefficients in binary mixtures of polar and non-polar compounds

DEFF Research Database (Denmark)

Medvedev, Oleg; Shapiro, Alexander

2005-01-01

The theory of transport coefficients in liquids, developed previously, is tested on a description of the diffusion coefficients in binary polar/non-polar mixtures, by applying advanced thermodynamic models. Comparison to a large set of experimental data shows good performance of the model. Only f...

Search for Directed Networks by Different Random Walk Strategies

Science.gov (United States)

Zhu, Zi-Qi; Jin, Xiao-Ling; Huang, Zhi-Long

2012-03-01

A comparative study is carried out on the efficiency of five different random walk strategies searching on directed networks constructed based on several typical complex networks. Due to the difference in search efficiency of the strategies rooted in network clustering, the clustering coefficient in a random walker's eye on directed networks is defined and computed to be half of the corresponding undirected networks. The search processes are performed on the directed networks based on Erdös—Rényi model, Watts—Strogatz model, Barabási—Albert model and clustered scale-free network model. It is found that self-avoiding random walk strategy is the best search strategy for such directed networks. Compared to unrestricted random walk strategy, path-iteration-avoiding random walks can also make the search process much more efficient. However, no-triangle-loop and no-quadrangle-loop random walks do not improve the search efficiency as expected, which is different from those on undirected networks since the clustering coefficient of directed networks are smaller than that of undirected networks.

Hybrid Modeling of Intra-DCT Coefficients for Real-Time Video Encoding

Directory of Open Access Journals (Sweden)

Li Jin

2008-01-01

Full Text Available Abstract The two-dimensional discrete cosine transform (2-D DCT and its subsequent quantization are widely used in standard video encoders. However, since most DCT coefficients become zeros after quantization, a number of redundant computations are performed. This paper proposes a hybrid statistical model used to predict the zeroquantized DCT (ZQDCT coefficients for intratransform and to achieve better real-time performance. First, each pixel block at the input of DCT is decomposed into a series of mean values and a residual block. Subsequently, a statistical model based on Gaussian distribution is used to predict the ZQDCT coefficients of the residual block. Then, a sufficient condition under which each quantized coefficient becomes zero is derived from the mean values. Finally, a hybrid model to speed up the DCT and quantization calculations is proposed. Experimental results show that the proposed model can reduce more redundant computations and achieve better real-time performance than the reference in the literature at the cost of negligible video quality degradation. Experiments also show that the proposed model significantly reduces multiplications for DCT and quantization. This is particularly suitable for processors in portable devices where multiplications consume more power than additions. Computational reduction implies longer battery lifetime and energy economy.

Random Intercept and Random Slope 2-Level Multilevel Models

Directory of Open Access Journals (Sweden)

Rehan Ahmad Khan

2012-11-01

Full Text Available Random intercept model and random intercept & random slope model carrying two-levels of hierarchy in the population are presented and compared with the traditional regression approach. The impact of students’ satisfaction on their grade point average (GPA was explored with and without controlling teachers influence. The variation at level-1 can be controlled by introducing the higher levels of hierarchy in the model. The fanny movement of the fitted lines proves variation of student grades around teachers.

Block Empirical Likelihood for Longitudinal Single-Index Varying-Coefficient Model

Directory of Open Access Journals (Sweden)

Yunquan Song

2013-01-01

Full Text Available In this paper, we consider a single-index varying-coefficient model with application to longitudinal data. In order to accommodate the within-group correlation, we apply the block empirical likelihood procedure to longitudinal single-index varying-coefficient model, and prove a nonparametric version of Wilks’ theorem which can be used to construct the block empirical likelihood confidence region with asymptotically correct coverage probability for the parametric component. In comparison with normal approximations, the proposed method does not require a consistent estimator for the asymptotic covariance matrix, making it easier to conduct inference for the model's parametric component. Simulations demonstrate how the proposed method works.

A dynamic global-coefficient mixed subgrid-scale model for large-eddy simulation of turbulent flows

International Nuclear Information System (INIS)

Singh, Satbir; You, Donghyun

2013-01-01

Highlights: ► A new SGS model is developed for LES of turbulent flows in complex geometries. ► A dynamic global-coefficient SGS model is coupled with a scale-similarity model. ► Overcome some of difficulties associated with eddy-viscosity closures. ► Does not require averaging or clipping of the model coefficient for stabilization. ► The predictive capability is demonstrated in a number of turbulent flow simulations. -- Abstract: A dynamic global-coefficient mixed subgrid-scale eddy-viscosity model for large-eddy simulation of turbulent flows in complex geometries is developed. In the present model, the subgrid-scale stress is decomposed into the modified Leonard stress, cross stress, and subgrid-scale Reynolds stress. The modified Leonard stress is explicitly computed assuming a scale similarity, while the cross stress and the subgrid-scale Reynolds stress are modeled using the global-coefficient eddy-viscosity model. The model coefficient is determined by a dynamic procedure based on the global-equilibrium between the subgrid-scale dissipation and the viscous dissipation. The new model relieves some of the difficulties associated with an eddy-viscosity closure, such as the nonalignment of the principal axes of the subgrid-scale stress tensor and the strain rate tensor and the anisotropy of turbulent flow fields, while, like other dynamic global-coefficient models, it does not require averaging or clipping of the model coefficient for numerical stabilization. The combination of the global-coefficient eddy-viscosity model and a scale-similarity model is demonstrated to produce improved predictions in a number of turbulent flow simulations

A Correction of Random Incidence Absorption Coefficients for the Angular Distribution of Acoustic Energy under Measurement Conditions

DEFF Research Database (Denmark)

Jeong, Cheol-Ho

2009-01-01

Most acoustic measurements are based on an assumption of ideal conditions. One such ideal condition is a diffuse and reverberant field. In practice, a perfectly diffuse sound field cannot be achieved in a reverberation chamber. Uneven incident energy density under measurement conditions can cause...... discrepancies between the measured value and the theoretical random incidence absorption coefficient. Therefore the angular distribution of the incident acoustic energy onto an absorber sample should be taken into account. The angular distribution of the incident energy density was simulated using the beam...... tracing method for various room shapes and source positions. The averaged angular distribution is found to be similar to a Gaussian distribution. As a result, an angle-weighted absorption coefficient was proposed by considering the angular energy distribution to improve the agreement between...

Global industrial impact coefficient based on random walk process and inter-country input-output table

Science.gov (United States)

Xing, Lizhi; Dong, Xianlei; Guan, Jun

2017-04-01

Input-output table is very comprehensive and detailed in describing the national economic system with lots of economic relationships, which contains supply and demand information among industrial sectors. The complex network, a theory and method for measuring the structure of complex system, can describe the structural characteristics of the internal structure of the research object by measuring the structural indicators of the social and economic system, revealing the complex relationship between the inner hierarchy and the external economic function. This paper builds up GIVCN-WIOT models based on World Input-Output Database in order to depict the topological structure of Global Value Chain (GVC), and assumes the competitive advantage of nations is equal to the overall performance of its domestic sectors' impact on the GVC. Under the perspective of econophysics, Global Industrial Impact Coefficient (GIIC) is proposed to measure the national competitiveness in gaining information superiority and intermediate interests. Analysis of GIVCN-WIOT models yields several insights including the following: (1) sectors with higher Random Walk Centrality contribute more to transmitting value streams within the global economic system; (2) Half-Value Ratio can be used to measure robustness of open-economy macroeconomics in the process of globalization; (3) the positive correlation between GIIC and GDP indicates that one country's global industrial impact could reveal its international competitive advantage.

The coefficient of restitution of pressurized balls: a mechanistic model

Science.gov (United States)

Georgallas, Alex; Landry, Gaëtan

2016-01-01

Pressurized, inflated balls used in professional sports are regulated so that their behaviour upon impact can be anticipated and allow the game to have its distinctive character. However, the dynamics governing the impacts of such balls, even on stationary hard surfaces, can be extremely complex. The energy transformations, which arise from the compression of the gas within the ball and from the shear forces associated with the deformation of the wall, are examined in this paper. We develop a simple mechanistic model of the dependence of the coefficient of restitution, e, upon both the gauge pressure, P_G, of the gas and the shear modulus, G, of the wall. The model is validated using the results from a simple series of experiments using three different sports balls. The fits to the data are extremely good for P_G > 25 kPa and consistent values are obtained for the value of G for the wall material. As far as the authors can tell, this simple, mechanistic model of the pressure dependence of the coefficient of restitution is the first in the literature. *%K Coefficient of Restitution, Dynamics, Inflated Balls, Pressure, Impact Model

New Inference Procedures for Semiparametric Varying-Coefficient Partially Linear Cox Models

Directory of Open Access Journals (Sweden)

Yunbei Ma

2014-01-01

Full Text Available In biomedical research, one major objective is to identify risk factors and study their risk impacts, as this identification can help clinicians to both properly make a decision and increase efficiency of treatments and resource allocation. A two-step penalized-based procedure is proposed to select linear regression coefficients for linear components and to identify significant nonparametric varying-coefficient functions for semiparametric varying-coefficient partially linear Cox models. It is shown that the penalized-based resulting estimators of the linear regression coefficients are asymptotically normal and have oracle properties, and the resulting estimators of the varying-coefficient functions have optimal convergence rates. A simulation study and an empirical example are presented for illustration.

Influence on dose coefficients for workers of the new metabolic models

International Nuclear Information System (INIS)

Gomez Parada, I.M.; Rojo, A.M.

1998-01-01

The International Commission on Radiological Protection (ICRP) has recently reviewed the biokinetic models used in the internal contamination dose assessment. ICRP has adopted a new model for the human respiratory tract and has updated, in ICRP Publications 56, 67 and 69, some of the biokinetic models of ICRP Publication 30. In this paper, the dose coefficients for some selected radionuclides issued in ICRP Publication 68 are compared with those obtained using the software LUPED (LUng Dose Evaluation Program). The former were calculated using the new systemic models, while the latter are based on the old metabolic models. The aim is to know to what extent the new models for systematic retention influence the dose coefficients for workers. (author) [es

Polynomial Chaos Expansion of Random Coefficients and the Solution of Stochastic Partial Differential Equations in the Tensor Train Format

KAUST Repository

Dolgov, Sergey

2015-11-03

We apply the tensor train (TT) decomposition to construct the tensor product polynomial chaos expansion (PCE) of a random field, to solve the stochastic elliptic diffusion PDE with the stochastic Galerkin discretization, and to compute some quantities of interest (mean, variance, and exceedance probabilities). We assume that the random diffusion coefficient is given as a smooth transformation of a Gaussian random field. In this case, the PCE is delivered by a complicated formula, which lacks an analytic TT representation. To construct its TT approximation numerically, we develop the new block TT cross algorithm, a method that computes the whole TT decomposition from a few evaluations of the PCE formula. The new method is conceptually similar to the adaptive cross approximation in the TT format but is more efficient when several tensors must be stored in the same TT representation, which is the case for the PCE. In addition, we demonstrate how to assemble the stochastic Galerkin matrix and to compute the solution of the elliptic equation and its postprocessing, staying in the TT format. We compare our technique with the traditional sparse polynomial chaos and the Monte Carlo approaches. In the tensor product polynomial chaos, the polynomial degree is bounded for each random variable independently. This provides higher accuracy than the sparse polynomial set or the Monte Carlo method, but the cardinality of the tensor product set grows exponentially with the number of random variables. However, when the PCE coefficients are implicitly approximated in the TT format, the computations with the full tensor product polynomial set become possible. In the numerical experiments, we confirm that the new methodology is competitive in a wide range of parameters, especially where high accuracy and high polynomial degrees are required.

Zero Distribution of System with Unknown Random Variables Case Study: Avoiding Collision Path

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Parman Setyamartana

2014-07-01

Full Text Available This paper presents the stochastic analysis of finding the feasible trajectories of robotics arm motion at obstacle surrounding. Unknown variables are coefficients of polynomials joint angle so that the collision-free motion is achieved. ãk is matrix consisting of these unknown feasible polynomial coefficients. The pattern of feasible polynomial in the obstacle environment shows as random. This paper proposes to model the pattern of this randomness values using random polynomial with unknown variables as coefficients. The behavior of the system will be obtained from zero distribution as the characteristic of such random polynomial. Results show that the pattern of random polynomial of avoiding collision can be constructed from zero distribution. Zero distribution is like building block of the system with obstacles as uncertainty factor. By scale factor k, which has range, the random coefficient pattern can be predicted.

Tensor models, Kronecker coefficients and permutation centralizer algebras

Science.gov (United States)

Geloun, Joseph Ben; Ramgoolam, Sanjaye

2017-11-01

We show that the counting of observables and correlators for a 3-index tensor model are organized by the structure of a family of permutation centralizer algebras. These algebras are shown to be semi-simple and their Wedderburn-Artin decompositions into matrix blocks are given in terms of Clebsch-Gordan coefficients of symmetric groups. The matrix basis for the algebras also gives an orthogonal basis for the tensor observables which diagonalizes the Gaussian two-point functions. The centres of the algebras are associated with correlators which are expressible in terms of Kronecker coefficients (Clebsch-Gordan multiplicities of symmetric groups). The color-exchange symmetry present in the Gaussian model, as well as a large class of interacting models, is used to refine the description of the permutation centralizer algebras. This discussion is extended to a general number of colors d: it is used to prove the integrality of an infinite family of number sequences related to color-symmetrizations of colored graphs, and expressible in terms of symmetric group representation theory data. Generalizing a connection between matrix models and Belyi maps, correlators in Gaussian tensor models are interpreted in terms of covers of singular 2-complexes. There is an intriguing difference, between matrix and higher rank tensor models, in the computational complexity of superficially comparable correlators of observables parametrized by Young diagrams.

On the Construction of Bivariate Exponential Distributions with an Arbitrary Correlation Coefficient

DEFF Research Database (Denmark)

Bladt, Mogens; Nielsen, Bo Friis

2010-01-01

coefficient (also negative). Secondly, the class satisfies that any linear combination (projection) of the marginal random variables is a phase-type distribution. The latter property is partially important for the development of hypothesis testing in linear models. Finally, it is easy to simulate...

Mechanistic model for dispersion coefficients in bubble column

CSIR Research Space (South Africa)

Skosana, PJ

2015-05-01

Full Text Available predicts axial and radial dispersion coefficients that are of the same order of magnitude as the reported data. Whereas the model is based on a description of the underlying physical phenomena, its validity and extrapolation is expected to be more reliable...

Analysis and computation of the elastic wave equation with random coefficients

KAUST Repository

Motamed, Mohammad

2015-10-21

We consider the stochastic initial-boundary value problem for the elastic wave equation with random coefficients and deterministic data. We propose a stochastic collocation method for computing statistical moments of the solution or statistics of some given quantities of interest. We study the convergence rate of the error in the stochastic collocation method. In particular, we show that, the rate of convergence depends on the regularity of the solution or the quantity of interest in the stochastic space, which is in turn related to the regularity of the deterministic data in the physical space and the type of the quantity of interest. We demonstrate that a fast rate of convergence is possible in two cases: for the elastic wave solutions with high regular data; and for some high regular quantities of interest even in the presence of low regular data. We perform numerical examples, including a simplified earthquake, which confirm the analysis and show that the collocation method is a valid alternative to the more traditional Monte Carlo sampling method for approximating quantities with high stochastic regularity.

Determination of coefficient matrices for ARMA model

International Nuclear Information System (INIS)

Tran Dinh Tri.

1990-10-01

A new recursive algorithm for determining coefficient matrices of ARMA model from measured data is presented. The Yule-Walker equations for the case of ARMA model are derived from the ARMA innovation equation. The recursive algorithm is based on choosing appropriate form of the operator functions and suitable representation of the (n+1)-th order operator functions according to ones with the lower order. Two cases, when the order of the AR part is equal to one of the MA part, and the optimal case, were considered. (author) 5 refs

Shear viscosity coefficient from microscopic models

International Nuclear Information System (INIS)

Muronga, Azwinndini

2004-01-01

The transport coefficient of shear viscosity is studied for a hadron matter through microscopic transport model, the ultrarelativistic quantum molecular dynamics (UrQMD), using the Green-Kubo formulas. Molecular-dynamical simulations are performed for a system of light mesons in a box with periodic boundary conditions. Starting from an initial state composed of π,η,ω,ρ,φ with a uniform phase-space distribution, the evolution takes place through elastic collisions, production, and annihilation. The system approaches a stationary state of mesons and their resonances, which is characterized by common temperature. After equilibration, thermodynamic quantities such as the energy density, particle density, and pressure are calculated. From such an equilibrated state the shear viscosity coefficient is calculated from the fluctuations of stress tensor around equilibrium using Green-Kubo relations. We do our simulations here at zero net baryon density so that the equilibration times depend on the energy density. We do not include hadron strings as degrees of freedom so as to maintain detailed balance. Hence we do not get the saturation of temperature but this leads to longer equilibration times

Dilemma Produced by Infinity of a Random Walk

International Nuclear Information System (INIS)

Li Jing-Hui

2015-01-01

We report a dilemma produced by the infinity of a random walk moving along a two-dimensional space sidestep. For this random walk, our investigation shows that using a different model can lead to a different diffusion coefficient of the random walk, which is produced by the infinity of the random walk. The result obtained by us in the present work can serve as a warning to us when we build the models to investigate the corresponding scientific problems. (paper)

Modeling the Design Flow Coefficient of a Centrifugal Compressor Impeller

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A. A. Drozdov

2017-01-01

Full Text Available In calculating gas-dynamic characteristics by the universal modeling method it is necessary to determine a non-incidence flow rate through the blades of an impeller because of its relationship with the magnitude of incidence losses. The flow area decreased by the blades of finite thickness and the blades load have impact on the critical streamline direction. The universal modeling method in primary designing uses for this a scheme of replacing the influence of the blade load by the vortex effect with identical circulation. Finally, calculating the inviscid flow around the blades allows selecting a value of the inlet blade angle. For impellers with small design flow coefficients, the condition of the non-incidence inlet for the primary design and for the calculation of the inviscid flow is significantly different. The calculating correctness of the non-incidence regime for the non-viscous flow was checked earlier by measurements of the flow in the impellers. The paper presents CFD calculations of twenty impellers in a tenfold range of design flow coefficients. To provide correct comparison, it takes into account the differences in the value of the loading factor calculated by the programs of inviscid quasi-three-dimensional calculation and CFD programs. Shows the identity of inlet conditions for both methods. To increase primary design accuracy, the calculation model was refined. The formula for calculating vortex-induced velocity involves an empirical coefficient. The analysis of data for 32 impellers with different blade profiling allowed working out formulas for calculating empirical coefficient, depending on the type of an impeller, the blade load and the width of the throat at an impeller inlet. The new scheme-based calculation with the empirical coefficient is accurate enough for the primary design.

Recent developments in biokinetic models and the calculation of internal dose coefficients

International Nuclear Information System (INIS)

Fell, T.P.; Phipps, A.W.; Kendall, G.M.; Stradling, G.N.

1997-01-01

In most cases the measurement of radioactivity in an environmental or biological sample will be followed by some estimation of dose and possibly risk, either to a population or an individual. This will normally involve the use of a dose coefficient (dose per unit intake value) taken from a compendium. In recent years the calculation of dose coefficients has seen many developments in both biokinetic modelling and computational capabilities. ICRP has recommended new models for the respiratory tract and for the systemic behavior of many of the more important elements. As well as this, a general age-dependent calculation method has been developed which involves an effectively continuous variation of both biokinetic and dosimetric parameters, facilitating more realistic estimation of doses to young people. These new developments were used in work for recent ICRP, IAEA and CEC compendia of dose coefficients for both members of the public (including children) and workers. This paper presents a general overview of the method of calculation of internal doses with particular reference to the actinides. Some of the implications for dose coefficients of the new models are discussed. For example it is shown that compared with data in ICRP Publications 30 and 54: the new respiratory tract model generally predicts lower deposition in systemic tissues per unit intake; the new biokinetic models for actinides allow for burial of material deposited on bone surfaces; age-dependent models generally feature faster turnover of material in young people. All of these factors can lead to substantially different estimates of dose and examples of the new dose coefficients are given to illustrate these differences. During the development of the new models for actinides, human bioassay data were used to validate the model. Thus, one would expect the new models to give reasonable predictions of bioassay quantities. Some examples of the bioassay applications, e.g., excretion data for the

Prediction of octanol-air partition coefficients for polychlorinated biphenyls (PCBs) using 3D-QSAR models.

Science.gov (United States)

Chen, Ying; Cai, Xiaoyu; Jiang, Long; Li, Yu

2016-02-01

Based on the experimental data of octanol-air partition coefficients (KOA) for 19 polychlorinated biphenyl (PCB) congeners, two types of QSAR methods, comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA), are used to establish 3D-QSAR models using the structural parameters as independent variables and using logKOA values as the dependent variable with the Sybyl software to predict the KOA values of the remaining 190 PCB congeners. The whole data set (19 compounds) was divided into a training set (15 compounds) for model generation and a test set (4 compounds) for model validation. As a result, the cross-validation correlation coefficient (q(2)) obtained by the CoMFA and CoMSIA models (shuffled 12 times) was in the range of 0.825-0.969 (>0.5), the correlation coefficient (r(2)) obtained was in the range of 0.957-1.000 (>0.9), and the SEP (standard error of prediction) of test set was within the range of 0.070-0.617, indicating that the models were robust and predictive. Randomly selected from a set of models, CoMFA analysis revealed that the corresponding percentages of the variance explained by steric and electrostatic fields were 23.9% and 76.1%, respectively, while CoMSIA analysis by steric, electrostatic and hydrophobic fields were 0.6%, 92.6%, and 6.8%, respectively. The electrostatic field was determined as a primary factor governing the logKOA. The correlation analysis of the relationship between the number of Cl atoms and the average logKOA values of PCBs indicated that logKOA values gradually increased as the number of Cl atoms increased. Simultaneously, related studies on PCB detection in the Arctic and Antarctic areas revealed that higher logKOA values indicate a stronger PCB migration ability. From CoMFA and CoMSIA contour maps, logKOA decreased when substituents possessed electropositive groups at the 2-, 3-, 3'-, 5- and 6- positions, which could reduce the PCB migration ability. These results are

Generalization of Random Intercept Multilevel Models

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Rehan Ahmad Khan

2013-10-01

Full Text Available The concept of random intercept models in a multilevel model developed by Goldstein (1986 has been extended for k-levels. The random variation in intercepts at individual level is marginally split into components by incorporating higher levels of hierarchy in the single level model. So, one can control the random variation in intercepts by incorporating the higher levels in the model.

Modeling individual differences in randomized experiments using growth models: Recommendations for design, statistical analysis and reporting of results of internet interventions

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Hugo Hesser

2015-05-01

Full Text Available Growth models (also known as linear mixed effects models, multilevel models, and random coefficients models have the capability of studying change at the group as well as the individual level. In addition, these methods have documented advantages over traditional data analytic approaches in the analysis of repeated-measures data. These advantages include, but are not limited to, the ability to incorporate time-varying predictors, handle dependence among repeated observations in a very flexible manner, and to provide accurate estimates with missing data under fairly unrestrictive missing data assumptions. The flexibility of the growth curve modeling approach to the analysis of change makes it the preferred choice in the evaluation of direct, indirect and moderated intervention effects. Although offering many benefits, growth models present challenges in terms of design, analysis and reporting of results. This paper provides a nontechnical overview of growth models in the analysis of change in randomized experiments and advocates for their use in the field of internet interventions. Practical recommendations for design, analysis and reporting of results from growth models are provided.

Predictive QSPR Modelling for the Second Virial Coefficient of the Pure Organic Compounds.

Science.gov (United States)

Mokshyna, E; Polishchuk, P G; Nedostup, V I; Kuzmin, V E

2015-01-01

In this article we developed a system of the predictive models for the second virial coefficients of the pure compounds. Second virial coefficient is the property derived from the virial equation of state, and is of particular interest as it describes pair intermolecular interactions. The two-layer QSPR models were developed, which exploited the well-known physical equations and allowed us to include this information into traditional QSPR methodology. This shows some new perspectives for work with temperature-dependent properties. It was shown that 2D descriptors can be successfully used for modeling of complex thermodynamic properties like virial coefficients. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Influence of Boussinesq coefficient on depth-averaged modelling of rapid flows

Science.gov (United States)

Yang, Fan; Liang, Dongfang; Xiao, Yang

2018-04-01

The traditional Alternating Direction Implicit (ADI) scheme has been proven to be incapable of modelling trans-critical flows. Its inherent lack of shock-capturing capability often results in spurious oscillations and computational instabilities. However, the ADI scheme is still widely adopted in flood modelling software, and various special treatments have been designed to stabilise the computation. Modification of the Boussinesq coefficient to adjust the amount of fluid inertia is a numerical treatment that allows the ADI scheme to be applicable to rapid flows. This study comprehensively examines the impact of this numerical treatment over a range of flow conditions. A shock-capturing TVD-MacCormack model is used to provide reference results. For unsteady flows over a frictionless bed, such as idealised dam-break floods, the results suggest that an increase in the value of the Boussinesq coefficient reduces the amplitude of the spurious oscillations. The opposite is observed for steady rapid flows over a frictional bed. Finally, a two-dimensional urban flooding phenomenon is presented, involving unsteady flow over a frictional bed. The results show that increasing the value of the Boussinesq coefficient can significantly reduce the numerical oscillations and reduce the predicted area of inundation. In order to stabilise the ADI computations, the Boussinesq coefficient could be judiciously raised or lowered depending on whether the rapid flow is steady or unsteady and whether the bed is frictional or frictionless. An increase in the Boussinesq coefficient generally leads to overprediction of the propagating speed of the flood wave over a frictionless bed, but the opposite is true when bed friction is significant.

Bounds and Estimates for Transport Coefficients of Random and Porous Media with High Contrasts

International Nuclear Information System (INIS)

Berryman, J G

2004-01-01

Bounds on transport coefficients of random polycrystals of laminates are presented, including the well-known Hashin-Shtrikman bounds and some newly formulated bounds involving two formation factors for a two-component porous medium. Some new types of self-consistent estimates are then formulated based on the observed analytical structure both of these bounds and also of earlier self-consistent estimates (of the CPA or coherent potential approximation type). A numerical study is made, assuming first that the internal structure (i.e., the laminated grain structure) is not known, and then that it is known. The purpose of this aspect of the study is to attempt to quantify the differences in the predictions of properties of a system being modeled when such organized internal structure is present in the medium but detailed spatial correlation information may or (more commonly) may not be available. Some methods of estimating formation factors from data are also presented and then applied to a high-contrast fluid-permeability data set. Hashin-Shtrikman bounds are found to be very accurate estimates for low contrast heterogeneous media. But formation factor lower bounds are superior estimates for high contrast situations. The new self-consistent estimators also tend to agree better with data than either the bounds or the CPA estimates, which themselves tend to overestimate values for high contrast conducting composites

Mixed models for data from thorough QT studies: part 2. One-step assessment of conditional QT prolongation.

Science.gov (United States)

Schall, Robert

2011-01-01

We investigate mixed analysis of covariance models for the 'one-step' assessment of conditional QT prolongation. Initially, we consider three different covariance structures for the data, where between-treatment covariance of repeated measures is modelled respectively through random effects, random coefficients, and through a combination of random effects and random coefficients. In all three of those models, an unstructured covariance pattern is used to model within-treatment covariance. In a fourth model, proposed earlier in the literature, between-treatment covariance is modelled through random coefficients but the residuals are assumed to be independent identically distributed (i.i.d.). Finally, we consider a mixed model with saturated covariance structure. We investigate the precision and robustness of those models by fitting them to a large group of real data sets from thorough QT studies. Our findings suggest: (i) Point estimates of treatment contrasts from all five models are similar. (ii) The random coefficients model with i.i.d. residuals is not robust; the model potentially leads to both under- and overestimation of standard errors of treatment contrasts and therefore cannot be recommended for the analysis of conditional QT prolongation. (iii) The combined random effects/random coefficients model does not always converge; in the cases where it converges, its precision is generally inferior to the other models considered. (iv) Both the random effects and the random coefficients model are robust. (v) The random effects, the random coefficients, and the saturated model have similar precision and all three models are suitable for the one-step assessment of conditional QT prolongation. Copyright © 2010 John Wiley & Sons, Ltd.

Comparing Regression Coefficients between Nested Linear Models for Clustered Data with Generalized Estimating Equations

Science.gov (United States)

Yan, Jun; Aseltine, Robert H., Jr.; Harel, Ofer

2013-01-01

Comparing regression coefficients between models when one model is nested within another is of great practical interest when two explanations of a given phenomenon are specified as linear models. The statistical problem is whether the coefficients associated with a given set of covariates change significantly when other covariates are added into…

Modelling research on determining shape coefficients for subdivision interpretation in γ-ray spectral logging

International Nuclear Information System (INIS)

Yin Wangming; She Guanjun; Tang Bin

2011-01-01

This paper first describes the physical meaning of the shape coefficients in the subdivision interpretation of γ-ray logging; then discusses the theory, method to determine the practical shape coefficients with logging model and defines the formula to approximately calculate the coefficients. A great deal of experimental work has been preformed with a HPGe γ-ray spectrometer and reached satisfied result which has validated the effeciency of the modelling method. (authors)

Robust Control for the Segway with Unknown Control Coefficient and Model Uncertainties

Directory of Open Access Journals (Sweden)

Byung Woo Kim

2016-06-01

Full Text Available The Segway, which is a popular vehicle nowadays, is an uncertain nonlinear system and has an unknown time-varying control coefficient. Thus, we should consider the unknown time-varying control coefficient and model uncertainties to design the controller. Motivated by this observation, we propose a robust control for the Segway with unknown control coefficient and model uncertainties. To deal with the time-varying unknown control coefficient, we employ the Nussbaum gain technique. We introduce an auxiliary variable to solve the underactuated problem. Due to the prescribed performance control technique, the proposed controller does not require the adaptive technique, neural network, and fuzzy logic to compensate the uncertainties. Therefore, it can be simple. From the Lyapunov stability theory, we prove that all signals in the closed-loop system are bounded. Finally, we provide the simulation results to demonstrate the effectiveness of the proposed control scheme.

Simple, efficient estimators of treatment effects in randomized trials using generalized linear models to leverage baseline variables.

Science.gov (United States)

Rosenblum, Michael; van der Laan, Mark J

2010-04-01

Models, such as logistic regression and Poisson regression models, are often used to estimate treatment effects in randomized trials. These models leverage information in variables collected before randomization, in order to obtain more precise estimates of treatment effects. However, there is the danger that model misspecification will lead to bias. We show that certain easy to compute, model-based estimators are asymptotically unbiased even when the working model used is arbitrarily misspecified. Furthermore, these estimators are locally efficient. As a special case of our main result, we consider a simple Poisson working model containing only main terms; in this case, we prove the maximum likelihood estimate of the coefficient corresponding to the treatment variable is an asymptotically unbiased estimator of the marginal log rate ratio, even when the working model is arbitrarily misspecified. This is the log-linear analog of ANCOVA for linear models. Our results demonstrate one application of targeted maximum likelihood estimation.

Simple, Efficient Estimators of Treatment Effects in Randomized Trials Using Generalized Linear Models to Leverage Baseline Variables

Science.gov (United States)

Rosenblum, Michael; van der Laan, Mark J.

2010-01-01

Models, such as logistic regression and Poisson regression models, are often used to estimate treatment effects in randomized trials. These models leverage information in variables collected before randomization, in order to obtain more precise estimates of treatment effects. However, there is the danger that model misspecification will lead to bias. We show that certain easy to compute, model-based estimators are asymptotically unbiased even when the working model used is arbitrarily misspecified. Furthermore, these estimators are locally efficient. As a special case of our main result, we consider a simple Poisson working model containing only main terms; in this case, we prove the maximum likelihood estimate of the coefficient corresponding to the treatment variable is an asymptotically unbiased estimator of the marginal log rate ratio, even when the working model is arbitrarily misspecified. This is the log-linear analog of ANCOVA for linear models. Our results demonstrate one application of targeted maximum likelihood estimation. PMID:20628636

The Effect of Nonzero Autocorrelation Coefficients on the Distributions of Durbin-Watson Test Estimator: Three Autoregressive Models

Directory of Open Access Journals (Sweden)

Mei-Yu LEE

2014-11-01

Full Text Available This paper investigates the effect of the nonzero autocorrelation coefficients on the sampling distributions of the Durbin-Watson test estimator in three time-series models that have different variance-covariance matrix assumption, separately. We show that the expected values and variances of the Durbin-Watson test estimator are slightly different, but the skewed and kurtosis coefficients are considerably different among three models. The shapes of four coefficients are similar between the Durbin-Watson model and our benchmark model, but are not the same with the autoregressive model cut by one-lagged period. Second, the large sample case shows that the three models have the same expected values, however, the autoregressive model cut by one-lagged period explores different shapes of variance, skewed and kurtosis coefficients from the other two models. This implies that the large samples lead to the same expected values, 2(1 – ρ0, whatever the variance-covariance matrix of the errors is assumed. Finally, comparing with the two sample cases, the shape of each coefficient is almost the same, moreover, the autocorrelation coefficients are negatively related with expected values, are inverted-U related with variances, are cubic related with skewed coefficients, and are U related with kurtosis coefficients.

Numerical modelling of random walk one-dimensional diffusion

International Nuclear Information System (INIS)

Vamos, C.; Suciu, N.; Peculea, M.

1996-01-01

The evolution of a particle which moves on a discrete one-dimensional lattice, according to a random walk low, approximates better the diffusion process smaller the steps of the spatial lattice and time are. For a sufficiently large assembly of particles one can assume that their relative frequency at lattice knots approximates the distribution function of the diffusion process. This assumption has been tested by simulating on computer two analytical solutions of the diffusion equation: the Brownian motion and the steady state linear distribution. To evaluate quantitatively the similarity between the numerical and analytical solutions we have used a norm given by the absolute value of the difference of the two solutions. Also, a diffusion coefficient at any lattice knots and moment of time has been calculated, by using the numerical solution both from the diffusion equation and the particle flux given by Fick's low. The difference between diffusion coefficient of analytical solution and the spatial lattice mean coefficient of numerical solution constitutes another quantitative indication of the similarity of the two solutions. The results obtained show that the approximation depends first on the number of particles at each knot of the spatial lattice. In conclusion, the random walk is a microscopic process of the molecular dynamics type which permits simulations precision of the diffusion processes with given precision. The numerical method presented in this work may be useful both in the analysis of real experiments and for theoretical studies

Distributing Correlation Coefficients of Linear Structure-Activity/Property Models

Directory of Open Access Journals (Sweden)

Sorana D. BOLBOACA

2011-12-01

Full Text Available Quantitative structure-activity/property relationships are mathematical relationships linking chemical structure and activity/property in a quantitative manner. These in silico approaches are frequently used to reduce animal testing and risk-assessment, as well as to increase time- and cost-effectiveness in characterization and identification of active compounds. The aim of our study was to investigate the pattern of correlation coefficients distribution associated to simple linear relationships linking the compounds structure with their activities. A set of the most common ordnance compounds found at naval facilities with a limited data set with a range of toxicities on aquatic ecosystem and a set of seven properties was studied. Statistically significant models were selected and investigated. The probability density function of the correlation coefficients was investigated using a series of possible continuous distribution laws. Almost 48% of the correlation coefficients proved fit Beta distribution, 40% fit Generalized Pareto distribution, and 12% fit Pert distribution.

Simultaneous determination of reference free-stream temperature and convective heat transfer coefficients

International Nuclear Information System (INIS)

Jeong, Gi Ho; Song, Ki Bum; Kim, Kui Soon

2001-01-01

This paper deals with the development of a new method that can obtain heat transfer coefficient and reference free stream temperature simultaneously. The method is based on transient heat transfer experiments using two narrow-band TLCs. The method is validated through error analysis in terms of the random uncertainties in the measured temperatures. It is shown how the uncertainties in heat transfer coefficient and free stream temperature can be reduced. The general method described in this paper is applicable to many heat transfer models with unknown free stream temperature

Effective elasticity coefficients of native rocks and consolidated granular matter

International Nuclear Information System (INIS)

Schulz, Beatrix M.; Schulz, Michael

2008-01-01

The elastic coefficients of binary heterogeneous materials, such as several native rock materials or consolidated granular matter will be determined in terms of a perturbation expansion. Furthermore, in order to check the validity of the obtained results, these are compared with numerical investigations using Boole's model of randomly distributed spheres. Finally, we apply the results on several classes of native rocks and consolidated granular materials

Transfer coefficients to terrestrial food products in equilibrium assessment models for nuclear installations

International Nuclear Information System (INIS)

Zach, R.

1980-09-01

Transfer coefficients have become virtually indispensible in the study of the fate of radioisotopes released from nuclear installations. These coefficients are used in equilibrium assessment models where they specify the degree of transfer in food chains of individual radioisotopes from soil to plant products and from feed or forage and drinking water to animal products and ultimately to man. Information on transfer coefficients for terrestrial food chain models is very piecemeal and occurs in a wide variety of journals and reports. To enable us to choose or determine suitable values for assessments, we have addressed the following aspects of transfer coefficients on a very broad scale: (1) definitions, (2) equilibrium assumption, which stipulates that transfer coefficients be restricted to equilibrium or steady rate conditions, (3) assumption of linearity, that is the idea that radioisotope concentrations in food products increase linearly with contamination levels in the soil or animal feed, (4) methods of determination, (5) variability, (6) generic versus site-specific values, (7) statistical aspects, (8) use, (9) sources of currently used values, (10) criteria for revising values, (11) establishment and maintenance of files on transfer coefficients, and (12) future developments. (auth)

A Parameterized Inversion Model for Soil Moisture and Biomass from Polarimetric Backscattering Coefficients

Science.gov (United States)

Truong-Loi, My-Linh; Saatchi, Sassan; Jaruwatanadilok, Sermsak

2012-01-01

A semi-empirical algorithm for the retrieval of soil moisture, root mean square (RMS) height and biomass from polarimetric SAR data is explained and analyzed in this paper. The algorithm is a simplification of the distorted Born model. It takes into account the physical scattering phenomenon and has three major components: volume, double-bounce and surface. This simplified model uses the three backscattering coefficients ( sigma HH, sigma HV and sigma vv) at low-frequency (P-band). The inversion process uses the Levenberg-Marquardt non-linear least-squares method to estimate the structural parameters. The estimation process is entirely explained in this paper, from initialization of the unknowns to retrievals. A sensitivity analysis is also done where the initial values in the inversion process are varying randomly. The results show that the inversion process is not really sensitive to initial values and a major part of the retrievals has a root-mean-square error lower than 5% for soil moisture, 24 Mg/ha for biomass and 0.49 cm for roughness, considering a soil moisture of 40%, roughness equal to 3cm and biomass varying from 0 to 500 Mg/ha with a mean of 161 Mg/ha

Extracting surface diffusion coefficients from batch adsorption measurement data: application of the classic Langmuir kinetics model.

Science.gov (United States)

Chu, Khim Hoong

2017-11-09

Surface diffusion coefficients may be estimated by fitting solutions of a diffusion model to batch kinetic data. For non-linear systems, a numerical solution of the diffusion model's governing equations is generally required. We report here the application of the classic Langmuir kinetics model to extract surface diffusion coefficients from batch kinetic data. The use of the Langmuir kinetics model in lieu of the conventional surface diffusion model allows derivation of an analytical expression. The parameter estimation procedure requires determining the Langmuir rate coefficient from which the pertinent surface diffusion coefficient is calculated. Surface diffusion coefficients within the 10 -9 to 10 -6  cm 2 /s range obtained by fitting the Langmuir kinetics model to experimental kinetic data taken from the literature are found to be consistent with the corresponding values obtained from the traditional surface diffusion model. The virtue of this simplified parameter estimation method is that it reduces the computational complexity as the analytical expression involves only an algebraic equation in closed form which is easily evaluated by spreadsheet computation.

On the construction of bivariate exponential distributions with an arbitrary correlation coefficient

DEFF Research Database (Denmark)

Bladt, Mogens; Nielsen, Bo Friis

In this paper we use a concept of multivariate phase-type distributions to define a class of bivariate exponential distributions. This class has the following three appealing properties. Firstly, we may construct a pair of exponentially distributed random variables with any feasible correlation...... coefficient (also negative). Secondly, the class satisfies that any linear combination (projection) of the marginal random variables is a phase {type distributions, The latter property is potentially important for the development hypothesis testing in linear models. Thirdly, it is very easy to simulate...

Determination and importance of temperature dependence of retention coefficient (RPHPLC) in QSAR model of nitrazepams' partition coefficient in bile acid micelles.

Science.gov (United States)

Posa, Mihalj; Pilipović, Ana; Lalić, Mladena; Popović, Jovan

2011-02-15

Linear dependence between temperature (t) and retention coefficient (k, reversed phase HPLC) of bile acids is obtained. Parameters (a, intercept and b, slope) of the linear function k=f(t) highly correlate with bile acids' structures. Investigated bile acids form linear congeneric groups on a principal component (calculated from k=f(t)) score plot that are in accordance with conformations of the hydroxyl and oxo groups in a bile acid steroid skeleton. Partition coefficient (K(p)) of nitrazepam in bile acids' micelles is investigated. Nitrazepam molecules incorporated in micelles show modified bioavailability (depo effect, higher permeability, etc.). Using multiple linear regression method QSAR models of nitrazepams' partition coefficient, K(p) are derived on the temperatures of 25°C and 37°C. For deriving linear regression models on both temperatures experimentally obtained lipophilicity parameters are included (PC1 from data k=f(t)) and in silico descriptors of the shape of a molecule while on the higher temperature molecular polarisation is introduced. This indicates the fact that the incorporation mechanism of nitrazepam in BA micelles changes on the higher temperatures. QSAR models are derived using partial least squares method as well. Experimental parameters k=f(t) are shown to be significant predictive variables. Both QSAR models are validated using cross validation and internal validation method. PLS models have slightly higher predictive capability than MLR models. Copyright © 2010 Elsevier B.V. All rights reserved.

Dynamic modeling of the horizontal eddy viscosity coefficient for quasigeostrophic ocean circulation problems

Directory of Open Access Journals (Sweden)

Romit Maulik

2016-12-01

Full Text Available This paper puts forth a simplified dynamic modeling strategy for the eddy viscosity coefficient parameterized in space and time. The eddy viscosity coefficient is dynamically adjusted to the local structure of the flow using two different nonlinear eddy viscosity functional forms to capture anisotropic dissipation mechanism, namely, (i the Smagorinsky model using the local strain rate field, and (ii the Leith model using the gradient of the vorticity field. The proposed models are applied to the one-layer and two-layer wind-driven quasigeostrophic ocean circulation problems, which are standard prototypes of more realistic ocean dynamics. Results show that both models capture the quasi-stationary ocean dynamics and provide the physical level of eddy viscosity distribution without using any a priori estimation. However, it is found that slightly less dissipative results can be obtained by using the dynamic Leith model. Two-layer numerical experiments also reveal that the proposed dynamic models automatically parameterize the subgrid-scale stress terms in each active layer. Furthermore, the proposed scale-aware models dynamically provide higher values of the eddy viscosity for smaller resolutions taking into account the local resolved flow information, and addressing the intimate relationship between the eddy viscosity coefficients and the numerical resolution employed by the quasigeostrophic models.

Oracle Efficient Variable Selection in Random and Fixed Effects Panel Data Models

DEFF Research Database (Denmark)

Kock, Anders Bredahl

This paper generalizes the results for the Bridge estimator of Huang et al. (2008) to linear random and fixed effects panel data models which are allowed to grow in both dimensions. In particular we show that the Bridge estimator is oracle efficient. It can correctly distinguish between relevant...... and irrelevant variables and the asymptotic distribution of the estimators of the coefficients of the relevant variables is the same as if only these had been included in the model, i.e. as if an oracle had revealed the true model prior to estimation. In the case of more explanatory variables than observations......, we prove that the Marginal Bridge estimator can asymptotically correctly distinguish between relevant and irrelevant explanatory variables. We do this without restricting the dependence between covariates and without assuming sub Gaussianity of the error terms thereby generalizing the results...

Proportional hazards model with varying coefficients for length-biased data.

Science.gov (United States)

Zhang, Feipeng; Chen, Xuerong; Zhou, Yong

2014-01-01

Length-biased data arise in many important applications including epidemiological cohort studies, cancer prevention trials and studies of labor economics. Such data are also often subject to right censoring due to loss of follow-up or the end of study. In this paper, we consider a proportional hazards model with varying coefficients for right-censored and length-biased data, which is used to study the interact effect nonlinearly of covariates with an exposure variable. A local estimating equation method is proposed for the unknown coefficients and the intercept function in the model. The asymptotic properties of the proposed estimators are established by using the martingale theory and kernel smoothing techniques. Our simulation studies demonstrate that the proposed estimators have an excellent finite-sample performance. The Channing House data is analyzed to demonstrate the applications of the proposed method.

Choosing the best index for the average score intraclass correlation coefficient.

Science.gov (United States)

Shieh, Gwowen

2016-09-01

The intraclass correlation coefficient (ICC)(2) index from a one-way random effects model is widely used to describe the reliability of mean ratings in behavioral, educational, and psychological research. Despite its apparent utility, the essential property of ICC(2) as a point estimator of the average score intraclass correlation coefficient is seldom mentioned. This article considers several potential measures and compares their performance with ICC(2). Analytical derivations and numerical examinations are presented to assess the bias and mean square error of the alternative estimators. The results suggest that more advantageous indices can be recommended over ICC(2) for their theoretical implication and computational ease.

Discharge Coefficient of Rectangular Short-Crested Weir with Varying Slope Coefficients

Directory of Open Access Journals (Sweden)

Yuejun Chen

2018-02-01

Full Text Available Rectangular short-crested weirs are widely used for simple structure and high discharge capacity. As one of the most important and influential factors of discharge capacity, side slope can improve the hydraulic characteristics of weirs at special conditions. In order to systemically study the effects of upstream and downstream slope coefficients S1 and S2 on overflow discharge coefficient in a rectangular short-crested weir the Volume of Fluid (VOF method and the Renormalization Group (RNG κ-ε turbulence model are used. In this study, the slope coefficient ranges from V to 3H:1V and each model corresponds to five total energy heads of H0 ranging from 8.0 to 24.0 cm. Comparisons of discharge coefficients and free surface profiles between simulated and laboratory results display a good agreement. The simulated results show that the difference of discharge coefficients will decrease with upstream slopes and increase with downstream slopes as H0 increases. For a given H0, the discharge coefficient has a convex parabolic relation with S1 and a piecewise linearity relation with S2. The maximum discharge coefficient is always obtained at S2 = 0.8. There exists a difference between upstream and downstream slope coefficients in the influence range of free surface curvatures. Furthermore, a proposed discharge coefficient equation by nonlinear regression is a function of upstream and downstream slope coefficients.

Application of noise analysis technique for monitoring the moderator temperature coefficient of reactivity in pressurized water reactors

International Nuclear Information System (INIS)

Shieh, D.J.; Upadhyaya, B.R.; Sweeney, F.J.

1987-01-01

A new technique, based on the noise analysis of neutron detector and core-exit coolant temperature signals, is developed for monitoring the moderator temperature coefficient of reactivity in pressurized water reactors (PWRs). A detailed multinodal model is developed and evaluated for the reactor core subsystem of the loss-of-fluid test (LOFT) reactor. This model is used to study the effect of changing the sign of the moderator temperature coefficient of reactivity on the low-frequency phase angle relationship between the neutron detector and the core-exit temperature noise signals. Results show that the phase angle near zero frequency approaches - 180 deg for negative coefficients and 0 deg for positive coefficients when the perturbation source for the noise signals is core coolant flow, inlet coolant temperature, or random heat transfer

Measurement of model coefficients of skin sympathetic vasoconstriction

International Nuclear Information System (INIS)

Severens, Natascha M W; Van Marken Lichtenbelt, Wouter D; Frijns, Arjan J H; Kingma, Boris R M; De Mol, Bas A J M; Van Steenhoven, Anton A

2010-01-01

Many researchers have already attempted to model vasoconstriction responses, commonly using the mathematical representation proposed by Stolwijk (1971 NASA Contractor Report CR-1855 (Washington, DC: NASA)). Model makers based the parameter values in this formulation either on estimations or by attributing the difference between their passive models and measurement data fully to thermoregulation. These methods are very sensitive to errors. This study aims to present a reliable method for determining physiological values in the vasoconstriction formulation. An experimental protocol was developed that enabled us to derive the local proportional amplification coefficients of the toe, leg and arm and the transient vasoconstrictor tone. Ten subjects participated in a cooling experiment. During the experiment, core temperature, skin temperature, skin perfusion, forearm blood flow and heart rate variability were measured. The contributions to the normalized amplification coefficient for vasoconstriction of the toe, leg and arm were 84%, 11% and 5%, respectively. Comparison with relative values in the literature showed that the estimated values of Stolwijk and the values mentioned by Tanabe et al (2002 Energy Build. 34 637–46) were comparable with our measured values, but the values of Gordon (1974 The response of a human temperature regulatory system model in the cold PhD Thesis University of California, Santa Barbara) and Fiala et al (2001 Int. J. Biometeorol. 45 143159) differed significantly. With the help of regression analysis a relation was formulated between the error signal of the standardized core temperature and the vasoconstrictor tone. This relation was formulated in a general applicable way, which means that it can be used for situations where vasoconstriction thresholds are shifted, like under anesthesia or during motion sickness

Hardware architecture for projective model calculation and false match refining using random sample consensus algorithm

Science.gov (United States)

Azimi, Ehsan; Behrad, Alireza; Ghaznavi-Ghoushchi, Mohammad Bagher; Shanbehzadeh, Jamshid

2016-11-01

The projective model is an important mapping function for the calculation of global transformation between two images. However, its hardware implementation is challenging because of a large number of coefficients with different required precisions for fixed point representation. A VLSI hardware architecture is proposed for the calculation of a global projective model between input and reference images and refining false matches using random sample consensus (RANSAC) algorithm. To make the hardware implementation feasible, it is proved that the calculation of the projective model can be divided into four submodels comprising two translations, an affine model and a simpler projective mapping. This approach makes the hardware implementation feasible and considerably reduces the required number of bits for fixed point representation of model coefficients and intermediate variables. The proposed hardware architecture for the calculation of a global projective model using the RANSAC algorithm was implemented using Verilog hardware description language and the functionality of the design was validated through several experiments. The proposed architecture was synthesized by using an application-specific integrated circuit digital design flow utilizing 180-nm CMOS technology as well as a Virtex-6 field programmable gate array. Experimental results confirm the efficiency of the proposed hardware architecture in comparison with software implementation.

Correlation and prediction of osmotic coefficient and water activity of aqueous electrolyte solutions by a two-ionic parameter model

International Nuclear Information System (INIS)

Pazuki, G.R.

2005-01-01

In this study, osmotic coefficients and water activities in aqueous solutions have been modeled using a new approach based on the Pitzer model. This model contains two physically significant ionic parameters regarding ionic solvation and the closest distance of approach between ions in a solution. The proposed model was evaluated by estimating the osmotic coefficients of nine electrolytes in aqueous solutions. The obtained results showed that the model is suitable for predicting the osmotic coefficients in aqueous electrolyte solutions. Using adjustable parameters, which have been calculated from regression between the experimental osmotic coefficient and the results of this model, the water activity coefficients of aqueous solutions were calculated. The average absolute relative deviations of the osmotic coefficients between the experimental data and the calculated results were in agreement

Research on friction coefficient of nuclear Reactor Vessel Internals Hold Down Spring: Stress coefficient test analysis method

International Nuclear Information System (INIS)

Linjun, Xie; Guohong, Xue; Ming, Zhang

2016-01-01

Graphical abstract: HDS stress coefficient test apparatus. - Highlights: • This paper performs mathematic deduction to the physical model of Hold Down Spring (HDS), establishes a mathematic model of axial load P and stress, stress coefficient and friction coefficient and designs a set of test apparatuses for simulating the pretightening process of the HDS for the first time according to a model similarity criterion. • The mathematical relation between the load and the strain is obtained about the HDS, and the mathematical model of the stress coefficient and the friction coefficient is established. So, a set of test apparatuses for obtaining the stress coefficient is designed according to the model scaling criterion and the friction coefficient of the K1000 HDS is calculated to be 0.336 through the obtained stress coefficient. • The relation curve between the theoretical load and the friction coefficient is obtained through analysis and indicates that the change of the friction coefficient f would influence the pretightening load under the condition of designed stress. The necessary pretightening load in the design process is calculated to be 5469 kN according to the obtained friction coefficient. Therefore, the friction coefficient and the pretightening load under the design conditions can provide accurate pretightening data for the analysis and design of the reactor HDS according to the operations. - Abstract: This paper performs mathematic deduction to the physical model of Hold Down Spring (HDS), establishes a mathematic model of axial load P and stress, stress coefficient and friction coefficient and designs a set of test apparatuses for simulating the pretightening process of the HDS for the first time according to a model similarity criterion. By carrying out tests and researches through a stress testing technique, P–σ curves in loading and unloading processes of the HDS are obtained and the stress coefficient k f of the HDS is obtained. So, the

Research on friction coefficient of nuclear Reactor Vessel Internals Hold Down Spring: Stress coefficient test analysis method

Energy Technology Data Exchange (ETDEWEB)

Linjun, Xie, E-mail: linjunx@zjut.edu.cn [College of Mechanical Engineering, Zhejiang University of Technology, Hangzhou 310014 (China); Guohong, Xue; Ming, Zhang [Shanghai Nuclear Engineering Research & Design Institute, Shanghai 200233 (China)

2016-08-01

Graphical abstract: HDS stress coefficient test apparatus. - Highlights: • This paper performs mathematic deduction to the physical model of Hold Down Spring (HDS), establishes a mathematic model of axial load P and stress, stress coefficient and friction coefficient and designs a set of test apparatuses for simulating the pretightening process of the HDS for the first time according to a model similarity criterion. • The mathematical relation between the load and the strain is obtained about the HDS, and the mathematical model of the stress coefficient and the friction coefficient is established. So, a set of test apparatuses for obtaining the stress coefficient is designed according to the model scaling criterion and the friction coefficient of the K1000 HDS is calculated to be 0.336 through the obtained stress coefficient. • The relation curve between the theoretical load and the friction coefficient is obtained through analysis and indicates that the change of the friction coefficient f would influence the pretightening load under the condition of designed stress. The necessary pretightening load in the design process is calculated to be 5469 kN according to the obtained friction coefficient. Therefore, the friction coefficient and the pretightening load under the design conditions can provide accurate pretightening data for the analysis and design of the reactor HDS according to the operations. - Abstract: This paper performs mathematic deduction to the physical model of Hold Down Spring (HDS), establishes a mathematic model of axial load P and stress, stress coefficient and friction coefficient and designs a set of test apparatuses for simulating the pretightening process of the HDS for the first time according to a model similarity criterion. By carrying out tests and researches through a stress testing technique, P–σ curves in loading and unloading processes of the HDS are obtained and the stress coefficient k{sub f} of the HDS is obtained. So, the

Data assimilation within the Advanced Circulation (ADCIRC) modeling framework for the estimation of Manning's friction coefficient

KAUST Repository

Mayo, Talea; Butler, Troy; Dawson, Clint N.; Hoteit, Ibrahim

2014-01-01

Coastal ocean models play a major role in forecasting coastal inundation due to extreme events such as hurricanes and tsunamis. Additionally, they are used to model tides and currents under more moderate conditions. The models numerically solve the shallow water equations, which describe conservation of mass and momentum for processes with large horizontal length scales relative to the vertical length scales. The bottom stress terms that arise in the momentum equations can be defined through the Manning's n formulation, utilizing the Manning's n coefficient. The Manning's n coefficient is an empirically derived, spatially varying parameter, and depends on many factors such as the bottom surface roughness. It is critical to the accuracy of coastal ocean models, however, the coefficient is often unknown or highly uncertain. In this work we reformulate a statistical data assimilation method generally used in the estimation of model state variables to estimate this model parameter. We show that low-dimensional representations of Manning's n coefficients can be recovered by assimilating water elevation data. This is a promising approach to parameter estimation in coastal ocean modeling. © 2014 Elsevier Ltd.

A numerical model for boiling heat transfer coefficient of zeotropic mixtures

Science.gov (United States)

Barraza Vicencio, Rodrigo; Caviedes Aedo, Eduardo

2017-12-01

Zeotropic mixtures never have the same liquid and vapor composition in the liquid-vapor equilibrium. Also, the bubble and the dew point are separated; this gap is called glide temperature (Tglide). Those characteristics have made these mixtures suitable for cryogenics Joule-Thomson (JT) refrigeration cycles. Zeotropic mixtures as working fluid in JT cycles improve their performance in an order of magnitude. Optimization of JT cycles have earned substantial importance for cryogenics applications (e.g, gas liquefaction, cryosurgery probes, cooling of infrared sensors, cryopreservation, and biomedical samples). Heat exchangers design on those cycles is a critical point; consequently, heat transfer coefficient and pressure drop of two-phase zeotropic mixtures are relevant. In this work, it will be applied a methodology in order to calculate the local convective heat transfer coefficients based on the law of the wall approach for turbulent flows. The flow and heat transfer characteristics of zeotropic mixtures in a heated horizontal tube are investigated numerically. The temperature profile and heat transfer coefficient for zeotropic mixtures of different bulk compositions are analysed. The numerical model has been developed and locally applied in a fully developed, constant temperature wall, and two-phase annular flow in a duct. Numerical results have been obtained using this model taking into account continuity, momentum, and energy equations. Local heat transfer coefficient results are compared with available experimental data published by Barraza et al. (2016), and they have shown good agreement.

[Correlation coefficient-based classification method of hydrological dependence variability: With auto-regression model as example].

Science.gov (United States)

Zhao, Yu Xi; Xie, Ping; Sang, Yan Fang; Wu, Zi Yi

2018-04-01

Hydrological process evaluation is temporal dependent. Hydrological time series including dependence components do not meet the data consistency assumption for hydrological computation. Both of those factors cause great difficulty for water researches. Given the existence of hydrological dependence variability, we proposed a correlationcoefficient-based method for significance evaluation of hydrological dependence based on auto-regression model. By calculating the correlation coefficient between the original series and its dependence component and selecting reasonable thresholds of correlation coefficient, this method divided significance degree of dependence into no variability, weak variability, mid variability, strong variability, and drastic variability. By deducing the relationship between correlation coefficient and auto-correlation coefficient in each order of series, we found that the correlation coefficient was mainly determined by the magnitude of auto-correlation coefficient from the 1 order to p order, which clarified the theoretical basis of this method. With the first-order and second-order auto-regression models as examples, the reasonability of the deduced formula was verified through Monte-Carlo experiments to classify the relationship between correlation coefficient and auto-correlation coefficient. This method was used to analyze three observed hydrological time series. The results indicated the coexistence of stochastic and dependence characteristics in hydrological process.

Coefficient Alpha: A Reliability Coefficient for the 21st Century?

Science.gov (United States)

Yang, Yanyun; Green, Samuel B.

2011-01-01

Coefficient alpha is almost universally applied to assess reliability of scales in psychology. We argue that researchers should consider alternatives to coefficient alpha. Our preference is for structural equation modeling (SEM) estimates of reliability because they are informative and allow for an empirical evaluation of the assumptions…

An empirically-based model for the lift coefficients of twisted airfoils with leading-edge tubercles

Science.gov (United States)

Ni, Zao; Su, Tsung-chow; Dhanak, Manhar

2018-04-01

Experimental data for untwisted airfoils are utilized to propose a model for predicting the lift coefficients of twisted airfoils with leading-edge tubercles. The effectiveness of the empirical model is verified through comparison with results of a corresponding computational fluid-dynamic (CFD) study. The CFD study is carried out for both twisted and untwisted airfoils with tubercles, the latter shown to compare well with available experimental data. Lift coefficients of twisted airfoils predicted from the proposed empirically-based model match well with the corresponding coefficients determined using the verified CFD study. Flow details obtained from the latter provide better insight into the underlying mechanism and behavior at stall of twisted airfoils with leading edge tubercles.

Understanding deterministic diffusion by correlated random walks

International Nuclear Information System (INIS)

Klages, R.; Korabel, N.

2002-01-01

Low-dimensional periodic arrays of scatterers with a moving point particle are ideal models for studying deterministic diffusion. For such systems the diffusion coefficient is typically an irregular function under variation of a control parameter. Here we propose a systematic scheme of how to approximate deterministic diffusion coefficients of this kind in terms of correlated random walks. We apply this approach to two simple examples which are a one-dimensional map on the line and the periodic Lorentz gas. Starting from suitable Green-Kubo formulae we evaluate hierarchies of approximations for their parameter-dependent diffusion coefficients. These approximations converge exactly yielding a straightforward interpretation of the structure of these irregular diffusion coefficients in terms of dynamical correlations. (author)

Modelling the change in the oxidation coefficient during the aerobic ...

African Journals Online (AJOL)

In this work the aerobic degradation of phenol by acclimated activated sludge was studied. Results demonstrate that while the phenol removal rate by acclimated activated sludge follows the Monod model, the oxygen uptake rate obeys a Haldane-type equation. The phenol oxidation coefficient obtained at different intial ...

QSPR modeling of octanol/water partition coefficient of antineoplastic agents by balance of correlations.

Science.gov (United States)

Toropov, Andrey A; Toropova, Alla P; Raska, Ivan; Benfenati, Emilio

2010-04-01

Three different splits into the subtraining set (n = 22), the set of calibration (n = 21), and the test set (n = 12) of 55 antineoplastic agents have been examined. By the correlation balance of SMILES-based optimal descriptors quite satisfactory models for the octanol/water partition coefficient have been obtained on all three splits. The correlation balance is the optimization of a one-variable model with a target function that provides both the maximal values of the correlation coefficient for the subtraining and calibration set and the minimum of the difference between the above-mentioned correlation coefficients. Thus, the calibration set is a preliminary test set. Copyright (c) 2009 Elsevier Masson SAS. All rights reserved.

Conditional Monte Carlo randomization tests for regression models.

Science.gov (United States)

Parhat, Parwen; Rosenberger, William F; Diao, Guoqing

2014-08-15

We discuss the computation of randomization tests for clinical trials of two treatments when the primary outcome is based on a regression model. We begin by revisiting the seminal paper of Gail, Tan, and Piantadosi (1988), and then describe a method based on Monte Carlo generation of randomization sequences. The tests based on this Monte Carlo procedure are design based, in that they incorporate the particular randomization procedure used. We discuss permuted block designs, complete randomization, and biased coin designs. We also use a new technique by Plamadeala and Rosenberger (2012) for simple computation of conditional randomization tests. Like Gail, Tan, and Piantadosi, we focus on residuals from generalized linear models and martingale residuals from survival models. Such techniques do not apply to longitudinal data analysis, and we introduce a method for computation of randomization tests based on the predicted rate of change from a generalized linear mixed model when outcomes are longitudinal. We show, by simulation, that these randomization tests preserve the size and power well under model misspecification. Copyright © 2014 John Wiley & Sons, Ltd.

Infinite Random Graphs as Statistical Mechanical Models

DEFF Research Database (Denmark)

Durhuus, Bergfinnur Jøgvan; Napolitano, George Maria

2011-01-01

We discuss two examples of infinite random graphs obtained as limits of finite statistical mechanical systems: a model of two-dimensional dis-cretized quantum gravity defined in terms of causal triangulated surfaces, and the Ising model on generic random trees. For the former model we describe a ...

RMBNToolbox: random models for biochemical networks

Directory of Open Access Journals (Sweden)

Niemi Jari

2007-05-01

Full Text Available Abstract Background There is an increasing interest to model biochemical and cell biological networks, as well as to the computational analysis of these models. The development of analysis methodologies and related software is rapid in the field. However, the number of available models is still relatively small and the model sizes remain limited. The lack of kinetic information is usually the limiting factor for the construction of detailed simulation models. Results We present a computational toolbox for generating random biochemical network models which mimic real biochemical networks. The toolbox is called Random Models for Biochemical Networks. The toolbox works in the Matlab environment, and it makes it possible to generate various network structures, stoichiometries, kinetic laws for reactions, and parameters therein. The generation can be based on statistical rules and distributions, and more detailed information of real biochemical networks can be used in situations where it is known. The toolbox can be easily extended. The resulting network models can be exported in the format of Systems Biology Markup Language. Conclusion While more information is accumulating on biochemical networks, random networks can be used as an intermediate step towards their better understanding. Random networks make it possible to study the effects of various network characteristics to the overall behavior of the network. Moreover, the construction of artificial network models provides the ground truth data needed in the validation of various computational methods in the fields of parameter estimation and data analysis.

Estimation of the drag coefficient from the upper ocean response to a hurricane: A variational data assimilation approach

KAUST Repository

Zedler, Sarah

2013-08-01

We seek to determine whether a small number of measurements of upper ocean temperature and currents can be used to make estimates of the drag coefficient that have a smaller range of uncertainty than previously found. We adopt a numerical approach in an inverse problem setup using an ocean model and its adjoint, to assimilate data and to adjust the drag coefficient parameterization (here the free parameter) with wind speed that corresponds to the minimum of a model minus data misfit or cost function. Pseudo data are generated from a reference forward simulation, and are perturbed with different levels of Gaussian distributed noise. It is found that it is necessary to assimilate both surface current speed and temperature data to obtain improvement over previous estimates of the drag coefficient. When data is assimilated without any smoothing or constraints on the solution, the drag coefficient is overestimated at low wind speeds and there are unrealistic, high frequency oscillations in the adjusted drag coefficient curve. When second derivatives of the drag coefficient curve are penalized and the solution is constrained to experimental values at low wind speeds, the adjusted drag coefficient is within 10% of its target value. This result is robust to the addition of realistic random noise meant to represent turbulence due to the presence of mesoscale background features in the assimilated data, or to the wind speed time series to model its unsteady and gusty character. When an eddy is added to the background flow field in both the initial condition and the assimilated data time series, the target and adjusted drag coefficient are within 10% of one another, regardless of whether random noise is added to the assimilated data. However, when the eddy is present in the assimilated data but is not in the initial conditions, the drag coefficient is overestimated by as much as 30%. This carries the implication that when real data is assimilated, care needs to be taken in

Data assimilation within the Advanced Circulation (ADCIRC) modeling framework for the estimation of Manning's friction coefficient

KAUST Repository

Mayo, Talea

2014-04-01

Coastal ocean models play a major role in forecasting coastal inundation due to extreme events such as hurricanes and tsunamis. Additionally, they are used to model tides and currents under more moderate conditions. The models numerically solve the shallow water equations, which describe conservation of mass and momentum for processes with large horizontal length scales relative to the vertical length scales. The bottom stress terms that arise in the momentum equations can be defined through the Manning\\'s n formulation, utilizing the Manning\\'s n coefficient. The Manning\\'s n coefficient is an empirically derived, spatially varying parameter, and depends on many factors such as the bottom surface roughness. It is critical to the accuracy of coastal ocean models, however, the coefficient is often unknown or highly uncertain. In this work we reformulate a statistical data assimilation method generally used in the estimation of model state variables to estimate this model parameter. We show that low-dimensional representations of Manning\\'s n coefficients can be recovered by assimilating water elevation data. This is a promising approach to parameter estimation in coastal ocean modeling. © 2014 Elsevier Ltd.

Note on the coefficient of variations of neuronal spike trains.

Science.gov (United States)

Lengler, Johannes; Steger, Angelika

2017-08-01

It is known that many neurons in the brain show spike trains with a coefficient of variation (CV) of the interspike times of approximately 1, thus resembling the properties of Poisson spike trains. Computational studies have been able to reproduce this phenomenon. However, the underlying models were too complex to be examined analytically. In this paper, we offer a simple model that shows the same effect but is accessible to an analytic treatment. The model is a random walk model with a reflecting barrier; we give explicit formulas for the CV in the regime of excess inhibition. We also analyze the effect of probabilistic synapses in our model and show that it resembles previous findings that were obtained by simulation.

Pendulum mass affects the measurement of articular friction coefficient.

Science.gov (United States)

Akelman, Matthew R; Teeple, Erin; Machan, Jason T; Crisco, Joseph J; Jay, Gregory D; Fleming, Braden C

2013-02-01

Friction measurements of articular cartilage are important to determine the relative tribologic contributions made by synovial fluid or cartilage, and to assess the efficacy of therapies for preventing the development of post-traumatic osteoarthritis. Stanton's equation is the most frequently used formula for estimating the whole joint friction coefficient (μ) of an articular pendulum, and assumes pendulum energy loss through a mass-independent mechanism. This study examines if articular pendulum energy loss is indeed mass independent, and compares Stanton's model to an alternative model, which incorporates viscous damping, for calculating μ. Ten loads (25-100% body weight) were applied in a random order to an articular pendulum using the knees of adult male Hartley guinea pigs (n=4) as the fulcrum. Motion of the decaying pendulum was recorded and μ was estimated using two models: Stanton's equation, and an exponential decay function incorporating a viscous damping coefficient. μ estimates decreased as mass increased for both models. Exponential decay model fit error values were 82% less than the Stanton model. These results indicate that μ decreases with increasing mass, and that an exponential decay model provides a better fit for articular pendulum data at all mass values. In conclusion, inter-study comparisons of articular pendulum μ values should not be made without recognizing the loads used, as μ values are mass dependent. Copyright © 2012 Elsevier Ltd. All rights reserved.

Vapour pressures and osmotic coefficients of binary mixtures containing alcohol and pyrrolidinium-based ionic liquids

International Nuclear Information System (INIS)

Calvar, N.; Domínguez, Á.; Macedo, E.A.

2013-01-01

Highlights: • Osmotic coefficients of alcohols with pyrrolidinium ILs are determined. • Experimental data were correlated with extended Pitzer model of Archer and MNRTL. • Mean molal activity coefficients and excess Gibbs free energies were calculated. • The results have been interpreted in terms of interactions. -- Abstract: The osmotic and activity coefficients and vapour pressures of mixtures containing primary (1-propanol, 1-butanol and 1-pentanol) and secondary (2-propanol and 2-butanol) alcohols with pyrrolidinium-based ionic liquids (1-butyl-1-methyl pyrrolidinium bis(trifluoromethylsulfonyl)imide, C 4 MpyrNTf 2 , and 1-butyl-1-methyl pyrrolidinium trifluoromethanesulfonate, C 4 MpyrTFO) have been experimentally determined at T = 323.15 K. For the experimental measurements, the vapour pressure osmometry technique has been used. The results on the influence of the structure of the alcohol and of the anion of the ionic liquid on the determined properties have been discussed and compared with literature data. For the correlation of the osmotic coefficients obtained, the Extended Pitzer model of Archer and the Modified Non-Random Two Liquids model were applied. The mean molal activity coefficients and the excess Gibbs energy for the studied mixtures were calculated from the parameters obtained in the correlation

Time-varying coefficient estimation in SURE models. Application to portfolio management

DEFF Research Database (Denmark)

Casas, Isabel; Ferreira, Eva; Orbe, Susan

This paper provides a detailed analysis of the asymptotic properties of a kernel estimator for a Seemingly Unrelated Regression Equations model with time-varying coefficients (tv-SURE) under very general conditions. Theoretical results together with a simulation study differentiates the cases...

Collocation methods for uncertainty quanti cation in PDE models with random data

KAUST Repository

Nobile, Fabio

2014-01-06

In this talk we consider Partial Differential Equations (PDEs) whose input data are modeled as random fields to account for their intrinsic variability or our lack of knowledge. After parametrizing the input random fields by finitely many independent random variables, we exploit the high regularity of the solution of the PDE as a function of the input random variables and consider sparse polynomial approximations in probability (Polynomial Chaos expansion) by collocation methods. We first address interpolatory approximations where the PDE is solved on a sparse grid of Gauss points in the probability space and the solutions thus obtained interpolated by multivariate polynomials. We present recent results on optimized sparse grids in which the selection of points is based on a knapsack approach and relies on sharp estimates of the decay of the coefficients of the polynomial chaos expansion of the solution. Secondly, we consider regression approaches where the PDE is evaluated on randomly chosen points in the probability space and a polynomial approximation constructed by the least square method. We present recent theoretical results on the stability and optimality of the approximation under suitable conditions between the number of sampling points and the dimension of the polynomial space. In particular, we show that for uniform random variables, the number of sampling point has to scale quadratically with the dimension of the polynomial space to maintain the stability and optimality of the approximation. Numerical results show that such condition is sharp in the monovariate case but seems to be over-constraining in higher dimensions. The regression technique seems therefore to be attractive in higher dimensions.

Development of a New Drag Coefficient Model for Oil and Gas ...

African Journals Online (AJOL)

Development of a New Drag Coefficient Model for Oil and Gas Multiphase Fluid Systems. ... PROMOTING ACCESS TO AFRICAN RESEARCH ... suspensions of solid particles are frequently encountered in many industrial processes including oil & gas production. ... EMAIL FREE FULL TEXT EMAIL FREE FULL TEXT

Low degree Earth's gravity coefficients determined from different space geodetic observations and climate models

Science.gov (United States)

Wińska, Małgorzata; Nastula, Jolanta

2017-04-01

Large scale mass redistribution and its transport within the Earth system causes changes in the Earth's rotation in space, gravity field and Earth's ellipsoid shape. These changes are observed in the ΔC21, ΔS21, and ΔC20 spherical harmonics gravity coefficients, which are proportional to the mass load-induced Earth rotational excitations. In this study, linear trend, decadal, inter-annual, and seasonal variations of low degree spherical harmonics coefficients of Earth's gravity field, determined from different space geodetic techniques, Gravity Recovery and Climate Experiment (GRACE), satellite laser ranging (SLR), Global Navigation Satellite System (GNSS), Earth rotation, and climate models, are examined. In this way, the contribution of each measurement technique to interpreting the low degree surface mass density of the Earth is shown. Especially, we evaluate an usefulness of several climate models from the Coupled Model Intercomparison Project phase 5 (CMIP5) to determine the low degree Earth's gravity coefficients using GRACE satellite observations. To do that, Terrestrial Water Storage (TWS) changes from several CMIP5 climate models are determined and then these simulated data are compared with the GRACE observations. Spherical harmonics ΔC21, ΔS21, and ΔC20 changes are calculated as the sum of atmosphere and ocean mass effect (GAC values) taken from GRACE and a land surface hydrological estimate from the selected CMIP5 climate models. Low degree Stokes coefficients of the surface mass density determined from GRACE, SLR, GNSS, Earth rotation measurements and climate models are compared to each other in order to assess their consistency. The comparison is done by using different types of statistical and signal processing methods.

Bottom friction models for shallow water equations: Manning’s roughness coefficient and small-scale bottom heterogeneity

Science.gov (United States)

Dyakonova, Tatyana; Khoperskov, Alexander

2018-03-01

The correct description of the surface water dynamics in the model of shallow water requires accounting for friction. To simulate a channel flow in the Chezy model the constant Manning roughness coefficient is frequently used. The Manning coefficient nM is an integral parameter which accounts for a large number of physical factors determining the flow braking. We used computational simulations in a shallow water model to determine the relationship between the Manning coefficient and the parameters of small-scale perturbations of a bottom in a long channel. Comparing the transverse water velocity profiles in the channel obtained in the models with a perturbed bottom without bottom friction and with bottom friction on a smooth bottom, we constructed the dependence of nM on the amplitude and spatial scale of perturbation of the bottom relief.

A Maximum Likelihood Approach to Determine Sensor Radiometric Response Coefficients for NPP VIIRS Reflective Solar Bands

Science.gov (United States)

Lei, Ning; Chiang, Kwo-Fu; Oudrari, Hassan; Xiong, Xiaoxiong

2011-01-01

Optical sensors aboard Earth orbiting satellites such as the next generation Visible/Infrared Imager/Radiometer Suite (VIIRS) assume that the sensors radiometric response in the Reflective Solar Bands (RSB) is described by a quadratic polynomial, in relating the aperture spectral radiance to the sensor Digital Number (DN) readout. For VIIRS Flight Unit 1, the coefficients are to be determined before launch by an attenuation method, although the linear coefficient will be further determined on-orbit through observing the Solar Diffuser. In determining the quadratic polynomial coefficients by the attenuation method, a Maximum Likelihood approach is applied in carrying out the least-squares procedure. Crucial to the Maximum Likelihood least-squares procedure is the computation of the weight. The weight not only has a contribution from the noise of the sensor s digital count, with an important contribution from digitization error, but also is affected heavily by the mathematical expression used to predict the value of the dependent variable, because both the independent and the dependent variables contain random noise. In addition, model errors have a major impact on the uncertainties of the coefficients. The Maximum Likelihood approach demonstrates the inadequacy of the attenuation method model with a quadratic polynomial for the retrieved spectral radiance. We show that using the inadequate model dramatically increases the uncertainties of the coefficients. We compute the coefficient values and their uncertainties, considering both measurement and model errors.

Quasi optimal and adaptive sparse grids with control variates for PDEs with random diffusion coefficient

KAUST Repository

Tamellini, Lorenzo

2016-01-05

In this talk we discuss possible strategies to minimize the impact of the curse of dimensionality effect when building sparse-grid approximations of a multivariate function u = u(y1, ..., yN ). More precisely, we present a knapsack approach , in which we estimate the cost and the error reduction contribution of each possible component of the sparse grid, and then we choose the components with the highest error reduction /cost ratio. The estimates of the error reduction are obtained by either a mixed a-priori / a-posteriori approach, in which we first derive a theoretical bound and then tune it with some inexpensive auxiliary computations (resulting in the so-called quasi-optimal sparse grids ), or by a fully a-posteriori approach (obtaining the so-called adaptive sparse grids ). This framework is very general and can be used to build quasi-optimal/adaptive sparse grids on bounded and unbounded domains (e.g. u depending on uniform and normal random distributions for yn), using both nested and non-nested families of univariate collocation points. We present some theoretical convergence results as well as numerical results showing the efficiency of the proposed approach for the approximation of the solution of elliptic PDEs with random diffusion coefficients. In this context, to treat the case of rough permeability fields in which a sparse grid approach may not be suitable, we propose to use the sparse grids as a control variate in a Monte Carlo simulation.

Measurement and modelling of mean activity coefficients of aqueous mixed electrolyte solution containing glycine

Energy Technology Data Exchange (ETDEWEB)

Dehghani, M.R. [Department of Chemical Engineering, Amirkabir University of Technology, Tehran (Iran, Islamic Republic of) ; Modarress, H. [Department of Chemical Engineering, Amirkabir University of Technology, Tehran (Iran, Islamic Republic of) ]. E-mail: hmodares@aut.ac.ir; Monirfar, M. [Department of Chemical Engineering, Amirkabir University of Technology, Tehran (Iran, Islamic Republic of)

2006-08-15

Electrochemical measurements were made on (H{sub 2}O + NaBr + K{sub 3}PO{sub 4} + glycine) mixtures at T = 298.15 K by using ion selective electrodes. The mean ionic activity coefficients of NaBr at molality 0.1 were determined at five K{sub 3}PO{sub 4} molalities (0.01, 0.03, 0.05, 0.07, and 0.1) mol . kg{sup -1}. The activity coefficients of glycine were evaluated from mean ionic activity coefficients of NaBr. The modified Pitzer equation was used to model the experimental data.

Isopiestic determination of the osmotic coefficient and vapour pressure of N-R-4-(N,N-dimethylamino)pyridinium tetrafluoroborate (R = C4H9, C5H11, C6H13) in the ethanol solution at T = 298.15 K

International Nuclear Information System (INIS)

Sardroodi, Jaber Jahanbin; Atabay, Maryam; Azamat, Jafar

2012-01-01

Highlights: ► The osmotic coefficients of the solutions of ionic liquid in ethanol have been measured. ► Measured osmotic coefficients were correlated using Pitzer, e-NRTL and NRF models and polynomial equation. ► Vapour pressures were evaluated from the correlated osmotic coefficients. - Abstract: Osmotic coefficients of the solutions of room temperature ionic liquid N-R-4-(N,N-dimethylamino)pyridinium tetrafluoroborate (R = C 4 H 9 , C 5 H 11 , C 6 H 13 ) in ethanol have been measured at T = 298.15 K by the isopiestic method. The experimental osmotic coefficients have been correlated using the ion interaction model of Pitzer, electrolyte non-random two liquid (e-NRTL) model of Chen, non-random factor (NRF) and a fourth-order polynomial in terms of molality. The vapour pressures of the solutions studied have been evaluated from the osmotic coefficients.

Intraclass Correlation Coefficients in Hierarchical Designs: Evaluation Using Latent Variable Modeling

Science.gov (United States)

Raykov, Tenko

2011-01-01

Interval estimation of intraclass correlation coefficients in hierarchical designs is discussed within a latent variable modeling framework. A method accomplishing this aim is outlined, which is applicable in two-level studies where participants (or generally lower-order units) are clustered within higher-order units. The procedure can also be…

Improved models for the prediction of activity coefficients in nearly athermal mixtures: Part I. Empirical modifications of free-volume models

DEFF Research Database (Denmark)

Kontogeorgis, Georgios M.; Coutsikos, Philipos; Tassios, Dimitrios

1994-01-01

Mixtures containing exclusively normal, branched and cyclic alkanes, as well as saturated hydrocarbon polymers (e.g. poly(ethylene) and poly(isobutylene)), are known to exhibit almost athermal behavior. Several new activity coefficient models containing both combinatorial and free-volume contribu......Mixtures containing exclusively normal, branched and cyclic alkanes, as well as saturated hydrocarbon polymers (e.g. poly(ethylene) and poly(isobutylene)), are known to exhibit almost athermal behavior. Several new activity coefficient models containing both combinatorial and free...

Spatially varying coefficient models in real estate: Eigenvector spatial filtering and alternative approaches

NARCIS (Netherlands)

Helbich, M; Griffith, D

2016-01-01

Real estate policies in urban areas require the recognition of spatial heterogeneity in housing prices to account for local settings. In response to the growing number of spatially varying coefficient models in housing applications, this study evaluated four models in terms of their spatial patterns

A Semiparametric Time Trend Varying Coefficients Model: With An Application to Evaluate Credit Rationing in U.S. Credit Market

OpenAIRE

Jingping Gu; Paula Hernandez-Verme

2009-01-01

In this paper, we propose a new semiparametric varying coefficient model which extends the existing semi-parametric varying coefficient models to allow for a time trend regressor with smooth coefficient function. We propose to use the local linear method to estimate the coefficient functions and we provide the asymptotic theory to describe the asymptotic distribution of the local linear estimator. We present an application to evaluate credit rationing in the U.S. credit market. Using U.S. mon...

A Semiparametric Time Trend Varying Coefficients Model: With An Application to Evaluate Credit Rationing in U.S. Credit Market

OpenAIRE

Qi Gao; Jingping Gu; Paula Hernandez-Verme

2012-01-01

In this paper, we propose a new semiparametric varying coefficient model which extends the existing semi-parametric varying coefficient models to allow for a time trend regressor with smooth coefficient function. We propose to use the local linear method to estimate the coefficient functions and we provide the asymptotic theory to describe the asymptotic distribution of the local linear estimator. We present an application to evaluate credit rationing in the U.S. credit market. Using U.S. mon...

A comparison of two indices for the intraclass correlation coefficient.

Science.gov (United States)

Shieh, Gwowen

2012-12-01

In the present study, we examined the behavior of two indices for measuring the intraclass correlation in the one-way random effects model: the prevailing ICC(1) (Fisher, 1938) and the corrected eta-squared (Bliese & Halverson, 1998). These two procedures differ both in their methods of estimating the variance components that define the intraclass correlation coefficient and in their performance of bias and mean squared error in the estimation of the intraclass correlation coefficient. In contrast with the natural unbiased principle used to construct ICC(1), in the present study it was analytically shown that the corrected eta-squared estimator is identical to the maximum likelihood estimator and the pairwise estimator under equal group sizes. Moreover, the empirical results obtained from the present Monte Carlo simulation study across various group structures revealed the mutual dominance relationship between their truncated versions for negative values. The corrected eta-squared estimator performs better than the ICC(1) estimator when the underlying population intraclass correlation coefficient is small. Conversely, ICC(1) has a clear advantage over the corrected eta-squared for medium and large magnitudes of population intraclass correlation coefficient. The conceptual description and numerical investigation provide guidelines to help researchers choose between the two indices for more accurate reliability analysis in multilevel research.

Development of a New Drag Coefficient Model for Oil and Gas ...

African Journals Online (AJOL)

Development of a New Drag Coefficient Model for Oil and Gas Multiphase Fluid Systems. ... a helpful Frequently Asked Questions about PDFs. Alternatively, you can download the PDF file directly to your computer, from where it can be opened using a PDF reader. To download the PDF, click the Download link above.

Compartment modelling in nuclear medicine: a new program for the determination of transfer coefficients

International Nuclear Information System (INIS)

Hallstadius, L.

1986-01-01

In many investigations concerning transport/exchange of matter in a natural system, e.g. functional studies in nuclear medicine, it is advantageous to relate experimental results to a model of the system. A new computer program is presented for the determination of linear transfer coefficients in a compartment model from experimentally observed time-compartment content curves. The program performs a least-square fit with the specified precision of the observed values as weight factors. The resulting uncertainty in the calculated transfer coefficients may also be assessed. The application of the program in nuclear medicine is demonstrated and discussed. (author)

Correlation factor, velocity autocorrelation function and frequency-dependent tracer diffusion coefficient

NARCIS (Netherlands)

Beijeren, H. van; Kehr, K.W.

1986-01-01

The correlation factor, defined as the ratio between the tracer diffusion coefficient in lattice gases and the diffusion coefficient for a corresponding uncorrelated random walk, is known to assume a very simple form under certain conditions. A simple derivation of this is given with the aid of

Tyre-road friction coefficient estimation based on tyre sensors and lateral tyre deflection: modelling, simulations and experiments

Science.gov (United States)

Hong, Sanghyun; Erdogan, Gurkan; Hedrick, Karl; Borrelli, Francesco

2013-05-01

The estimation of the tyre-road friction coefficient is fundamental for vehicle control systems. Tyre sensors enable the friction coefficient estimation based on signals extracted directly from tyres. This paper presents a tyre-road friction coefficient estimation algorithm based on tyre lateral deflection obtained from lateral acceleration. The lateral acceleration is measured by wireless three-dimensional accelerometers embedded inside the tyres. The proposed algorithm first determines the contact patch using a radial acceleration profile. Then, the portion of the lateral acceleration profile, only inside the tyre-road contact patch, is used to estimate the friction coefficient through a tyre brush model and a simple tyre model. The proposed strategy accounts for orientation-variation of accelerometer body frame during tyre rotation. The effectiveness and performance of the algorithm are demonstrated through finite element model simulations and experimental tests with small tyre slip angles on different road surface conditions.

Application of QMC methods to PDEs with random coefficients : a survey of analysis and implementation

KAUST Repository

Kuo, Frances; Dick, Josef; Le Gia, Thong; Nichols, James; Sloan, Ian; Graham, Ivan; Scheichl, Robert; Nuyens, Dirk; Schwab, Christoph

2016-01-01

have been written on this topic using a variety of methods. QMC methods are relatively new to this application area. I will consider different models for the randomness (uniform versus lognormal) and contrast different QMC algorithms (single-level

Osmotic and activity coefficients in the binary solutions of 1-butyl-3-methylimidazolium chloride and bromide in methanol or ethanol at T = 298.15 K from isopiestic measurements

International Nuclear Information System (INIS)

Sardroodi, Jaber Jahanbin; Azamat, Jafar; Atabay, Maryam

2011-01-01

Highlights: → The osmotic coefficients of the solutions of 1-butyl-3-methylimidazolium chloride and bromide in ethanol and methanol have been measured. → Measured osmotic coefficients were correlated using NRTL and Pitzer models. → Vapor pressures were evaluated from the correlated osmotic coefficients. → Model parameters have been interpreted in terms of ion-ion and ion-solvent interactions. - Abstract: Osmotic coefficients of the binary solutions of two room-temperature ionic liquids (1-butyl-3-methylimidazolium chloride and bromide) in methanol and ethanol have been measured at T = 298.15 K by the isopiestic method. The experimental osmotic coefficient data have been correlated using a forth-order polynomial in terms of (molality) 0.5 , with both, ion interaction model of Pitzer and electrolyte non-random two liquid (e-NRTL) model of Chen. The values of vapor pressures of above-mentioned solutions have been calculated from the osmotic coefficients. The model parameters fitted to the experimental osmotic coefficients have been used for prediction of the mean ionic activity coefficients of those ionic liquids in methanol and ethanol.

The random walk model of intrafraction movement

International Nuclear Information System (INIS)

Ballhausen, H; Reiner, M; Kantz, S; Belka, C; Söhn, M

2013-01-01

The purpose of this paper is to understand intrafraction movement as a stochastic process driven by random external forces. The hypothetically proposed three-dimensional random walk model has significant impact on optimal PTV margins and offers a quantitatively correct explanation of experimental findings. Properties of the random walk are calculated from first principles, in particular fraction-average population density distributions for displacements along the principal axes. When substituted into the established optimal margin recipes these fraction-average distributions yield safety margins about 30% smaller as compared to the suggested values from end-of-fraction Gaussian fits. Stylized facts of a random walk are identified in clinical data, such as the increase of the standard deviation of displacements with the square root of time. Least squares errors in the comparison to experimental results are reduced by about 50% when accounting for non-Gaussian corrections from the random walk model. (paper)

The random walk model of intrafraction movement.

Science.gov (United States)

Ballhausen, H; Reiner, M; Kantz, S; Belka, C; Söhn, M

2013-04-07

The purpose of this paper is to understand intrafraction movement as a stochastic process driven by random external forces. The hypothetically proposed three-dimensional random walk model has significant impact on optimal PTV margins and offers a quantitatively correct explanation of experimental findings. Properties of the random walk are calculated from first principles, in particular fraction-average population density distributions for displacements along the principal axes. When substituted into the established optimal margin recipes these fraction-average distributions yield safety margins about 30% smaller as compared to the suggested values from end-of-fraction gaussian fits. Stylized facts of a random walk are identified in clinical data, such as the increase of the standard deviation of displacements with the square root of time. Least squares errors in the comparison to experimental results are reduced by about 50% when accounting for non-gaussian corrections from the random walk model.

Endogeneity, Time-Varying Coefficients, and Incorrect vs. Correct Ways of Specifying the Error Terms of Econometric Models

Directory of Open Access Journals (Sweden)

P.A.V.B. Swamy

2017-02-01

Full Text Available Using the net effect of all relevant regressors omitted from a model to form its error term is incorrect because the coefficients and error term of such a model are non-unique. Non-unique coefficients cannot possess consistent estimators. Uniqueness can be achieved if; instead; one uses certain “sufficient sets” of (relevant regressors omitted from each model to represent the error term. In this case; the unique coefficient on any non-constant regressor takes the form of the sum of a bias-free component and omitted-regressor biases. Measurement-error bias can also be incorporated into this sum. We show that if our procedures are followed; accurate estimation of bias-free components is possible.

A fast collocation method for a variable-coefficient nonlocal diffusion model

Science.gov (United States)

Wang, Che; Wang, Hong

2017-02-01

We develop a fast collocation scheme for a variable-coefficient nonlocal diffusion model, for which a numerical discretization would yield a dense stiffness matrix. The development of the fast method is achieved by carefully handling the variable coefficients appearing inside the singular integral operator and exploiting the structure of the dense stiffness matrix. The resulting fast method reduces the computational work from O (N3) required by a commonly used direct solver to O (Nlog ⁡ N) per iteration and the memory requirement from O (N2) to O (N). Furthermore, the fast method reduces the computational work of assembling the stiffness matrix from O (N2) to O (N). Numerical results are presented to show the utility of the fast method.

A novel drag force coefficient model for gas–water two-phase flows under different flow patterns

Energy Technology Data Exchange (ETDEWEB)

Shang, Zhi, E-mail: shangzhi@tsinghua.org.cn

2015-07-15

Graphical abstract: - Highlights: • A novel drag force coefficient model was established. • This model realized to cover different flow patterns for CFD. • Numerical simulations were performed under wide range flow regimes. • Validations were carried out through comparisons to experiments. - Abstract: A novel drag force coefficient model has been developed to study gas–water two-phase flows. In this drag force coefficient model, the terminal velocities were calculated through the revised drift flux model. The revised drift flux is different from the traditional drift flux model because the natural curve movement of the bubble was revised through considering the centrifugal force. Owing to the revisions, the revised drift flux model was to extend to 3D. Therefore it is suitable for CFD applications. In the revised drift flux model, the different flow patterns of the gas–water two-phase flows were able to be considered. This model innovatively realizes the drag force being able to cover different flow patterns of gas–water two-phase flows on bubbly flow, slug flow, churn flow, annular flow and mist flow. Through the comparisons of the numerical simulations to the experiments in vertical upward and downward pipe flows, this model was validated.

Application of random effects to the study of resource selection by animals.

Science.gov (United States)

Gillies, Cameron S; Hebblewhite, Mark; Nielsen, Scott E; Krawchuk, Meg A; Aldridge, Cameron L; Frair, Jacqueline L; Saher, D Joanne; Stevens, Cameron E; Jerde, Christopher L

2006-07-01

1. Resource selection estimated by logistic regression is used increasingly in studies to identify critical resources for animal populations and to predict species occurrence. 2. Most frequently, individual animals are monitored and pooled to estimate population-level effects without regard to group or individual-level variation. Pooling assumes that both observations and their errors are independent, and resource selection is constant given individual variation in resource availability. 3. Although researchers have identified ways to minimize autocorrelation, variation between individuals caused by differences in selection or available resources, including functional responses in resource selection, have not been well addressed. 4. Here we review random-effects models and their application to resource selection modelling to overcome these common limitations. We present a simple case study of an analysis of resource selection by grizzly bears in the foothills of the Canadian Rocky Mountains with and without random effects. 5. Both categorical and continuous variables in the grizzly bear model differed in interpretation, both in statistical significance and coefficient sign, depending on how a random effect was included. We used a simulation approach to clarify the application of random effects under three common situations for telemetry studies: (a) discrepancies in sample sizes among individuals; (b) differences among individuals in selection where availability is constant; and (c) differences in availability with and without a functional response in resource selection. 6. We found that random intercepts accounted for unbalanced sample designs, and models with random intercepts and coefficients improved model fit given the variation in selection among individuals and functional responses in selection. Our empirical example and simulations demonstrate how including random effects in resource selection models can aid interpretation and address difficult assumptions

Desorption modeling of hydrophobic organic chemicals from plastic sheets using experimentally determined diffusion coefficients in plastics.

Science.gov (United States)

Lee, Hwang; Byun, Da-Eun; Kim, Ju Min; Kwon, Jung-Hwan

2018-01-01

To evaluate rate of migration from plastic debris, desorption of model hydrophobic organic chemicals (HOCs) from polyethylene (PE)/polypropylene (PP) films to water was measured using PE/PP films homogeneously loaded with the HOCs. The HOCs fractions remaining in the PE/PP films were compared with those predicted using a model characterized by the mass transfer Biot number. The experimental data agreed with the model simulation, indicating that HOCs desorption from plastic particles can generally be described by the model. For hexachlorocyclohexanes with lower plastic-water partition coefficients, desorption was dominated by diffusion in the plastic film, whereas desorption of chlorinated benzenes with higher partition coefficients was determined by diffusion in the aqueous boundary layer. Evaluation of the fraction of HOCs remaining in plastic films with respect to film thickness and desorption time showed that the partition coefficient between plastic and water is the most important parameter influencing the desorption half-life. Copyright © 2017 Elsevier Ltd. All rights reserved.

A random regret minimization model of travel choice

NARCIS (Netherlands)

Chorus, C.G.; Arentze, T.A.; Timmermans, H.J.P.

2008-01-01

Abstract This paper presents an alternative to Random Utility-Maximization models of travel choice. Our Random Regret-Minimization model is rooted in Regret Theory and provides several useful features for travel demand analysis. Firstly, it allows for the possibility that choices between travel

Random matrix models for phase diagrams

International Nuclear Information System (INIS)

Vanderheyden, B; Jackson, A D

2011-01-01

We describe a random matrix approach that can provide generic and readily soluble mean-field descriptions of the phase diagram for a variety of systems ranging from quantum chromodynamics to high-T c materials. Instead of working from specific models, phase diagrams are constructed by averaging over the ensemble of theories that possesses the relevant symmetries of the problem. Although approximate in nature, this approach has a number of advantages. First, it can be useful in distinguishing generic features from model-dependent details. Second, it can help in understanding the 'minimal' number of symmetry constraints required to reproduce specific phase structures. Third, the robustness of predictions can be checked with respect to variations in the detailed description of the interactions. Finally, near critical points, random matrix models bear strong similarities to Ginsburg-Landau theories with the advantage of additional constraints inherited from the symmetries of the underlying interaction. These constraints can be helpful in ruling out certain topologies in the phase diagram. In this Key Issues Review, we illustrate the basic structure of random matrix models, discuss their strengths and weaknesses, and consider the kinds of system to which they can be applied.

Creating, generating and comparing random network models with NetworkRandomizer.

Science.gov (United States)

Tosadori, Gabriele; Bestvina, Ivan; Spoto, Fausto; Laudanna, Carlo; Scardoni, Giovanni

2016-01-01

Biological networks are becoming a fundamental tool for the investigation of high-throughput data in several fields of biology and biotechnology. With the increasing amount of information, network-based models are gaining more and more interest and new techniques are required in order to mine the information and to validate the results. To fill the validation gap we present an app, for the Cytoscape platform, which aims at creating randomised networks and randomising existing, real networks. Since there is a lack of tools that allow performing such operations, our app aims at enabling researchers to exploit different, well known random network models that could be used as a benchmark for validating real, biological datasets. We also propose a novel methodology for creating random weighted networks, i.e. the multiplication algorithm, starting from real, quantitative data. Finally, the app provides a statistical tool that compares real versus randomly computed attributes, in order to validate the numerical findings. In summary, our app aims at creating a standardised methodology for the validation of the results in the context of the Cytoscape platform.

Organ dose conversion coefficients for voxel models of the reference male and female from idealized photon exposures

Science.gov (United States)

Schlattl, H.; Zankl, M.; Petoussi-Henss, N.

2007-04-01

A new series of organ equivalent dose conversion coefficients for whole body external photon exposure is presented for a standardized couple of human voxel models, called Rex and Regina. Irradiations from broad parallel beams in antero-posterior, postero-anterior, left- and right-side lateral directions as well as from a 360° rotational source have been performed numerically by the Monte Carlo transport code EGSnrc. Dose conversion coefficients from an isotropically distributed source were computed, too. The voxel models Rex and Regina originating from real patient CT data comply in body and organ dimensions with the currently valid reference values given by the International Commission on Radiological Protection (ICRP) for the average Caucasian man and woman, respectively. While the equivalent dose conversion coefficients of many organs are in quite good agreement with the reference values of ICRP Publication 74, for some organs and certain geometries the discrepancies amount to 30% or more. Differences between the sexes are of the same order with mostly higher dose conversion coefficients in the smaller female model. However, much smaller deviations from the ICRP values are observed for the resulting effective dose conversion coefficients. With the still valid definition for the effective dose (ICRP Publication 60), the greatest change appears in lateral exposures with a decrease in the new models of at most 9%. However, when the modified definition of the effective dose as suggested by an ICRP draft is applied, the largest deviation from the current reference values is obtained in postero-anterior geometry with a reduction of the effective dose conversion coefficient by at most 12%.

Organ dose conversion coefficients for voxel models of the reference male and female from idealized photon exposures

International Nuclear Information System (INIS)

Schlattl, H; Zankl, M; Petoussi-Henss, N

2007-01-01

A new series of organ equivalent dose conversion coefficients for whole body external photon exposure is presented for a standardized couple of human voxel models, called Rex and Regina. Irradiations from broad parallel beams in antero-posterior, postero-anterior, left- and right-side lateral directions as well as from a 360 deg. rotational source have been performed numerically by the Monte Carlo transport code EGSnrc. Dose conversion coefficients from an isotropically distributed source were computed, too. The voxel models Rex and Regina originating from real patient CT data comply in body and organ dimensions with the currently valid reference values given by the International Commission on Radiological Protection (ICRP) for the average Caucasian man and woman, respectively. While the equivalent dose conversion coefficients of many organs are in quite good agreement with the reference values of ICRP Publication 74, for some organs and certain geometries the discrepancies amount to 30% or more. Differences between the sexes are of the same order with mostly higher dose conversion coefficients in the smaller female model. However, much smaller deviations from the ICRP values are observed for the resulting effective dose conversion coefficients. With the still valid definition for the effective dose (ICRP Publication 60), the greatest change appears in lateral exposures with a decrease in the new models of at most 9%. However, when the modified definition of the effective dose as suggested by an ICRP draft is applied, the largest deviation from the current reference values is obtained in postero-anterior geometry with a reduction of the effective dose conversion coefficient by at most 12%

Predictive multiscale computational model of shoe-floor coefficient of friction.

Science.gov (United States)

Moghaddam, Seyed Reza M; Acharya, Arjun; Redfern, Mark S; Beschorner, Kurt E

2018-01-03

Understanding the frictional interactions between the shoe and floor during walking is critical to prevention of slips and falls, particularly when contaminants are present. A multiscale finite element model of shoe-floor-contaminant friction was developed that takes into account the surface and material characteristics of the shoe and flooring in microscopic and macroscopic scales. The model calculates shoe-floor coefficient of friction (COF) in boundary lubrication regime where effects of adhesion friction and hydrodynamic pressures are negligible. The validity of model outputs was assessed by comparing model predictions to the experimental results from mechanical COF testing. The multiscale model estimates were linearly related to the experimental results (p < 0.0001). The model predicted 73% of variability in experimentally-measured shoe-floor-contaminant COF. The results demonstrate the potential of multiscale finite element modeling in aiding slip-resistant shoe and flooring design and reducing slip and fall injuries. Copyright © 2017 The Author(s). Published by Elsevier Ltd.. All rights reserved.

A random spatial network model based on elementary postulates

Science.gov (United States)

Karlinger, Michael R.; Troutman, Brent M.

1989-01-01

A model for generating random spatial networks that is based on elementary postulates comparable to those of the random topology model is proposed. In contrast to the random topology model, this model ascribes a unique spatial specification to generated drainage networks, a distinguishing property of some network growth models. The simplicity of the postulates creates an opportunity for potential analytic investigations of the probabilistic structure of the drainage networks, while the spatial specification enables analyses of spatially dependent network properties. In the random topology model all drainage networks, conditioned on magnitude (number of first-order streams), are equally likely, whereas in this model all spanning trees of a grid, conditioned on area and drainage density, are equally likely. As a result, link lengths in the generated networks are not independent, as usually assumed in the random topology model. For a preliminary model evaluation, scale-dependent network characteristics, such as geometric diameter and link length properties, and topologic characteristics, such as bifurcation ratio, are computed for sets of drainage networks generated on square and rectangular grids. Statistics of the bifurcation and length ratios fall within the range of values reported for natural drainage networks, but geometric diameters tend to be relatively longer than those for natural networks.

Autonomous estimation of Allan variance coefficients of onboard fiber optic gyro

International Nuclear Information System (INIS)

Song Ningfang; Yuan Rui; Jin Jing

2011-01-01

Satellite motion included in gyro output disturbs the estimation of Allan variance coefficients of fiber optic gyro on board. Moreover, as a standard method for noise analysis of fiber optic gyro, Allan variance has too large offline computational effort and data storages to be applied to online estimation. In addition, with the development of deep space exploration, it is urged that satellite requires more autonomy including autonomous fault diagnosis and reconfiguration. To overcome the barriers and meet satellite autonomy, we present a new autonomous method for estimation of Allan variance coefficients including rate ramp, rate random walk, bias instability, angular random walk and quantization noise coefficients. In the method, we calculate differences between angle increments of star sensor and gyro to remove satellite motion from gyro output, and propose a state-space model using nonlinear adaptive filter technique for quantities previously measured from offline data techniques such as the Allan variance method. Simulations show the method correctly estimates Allan variance coefficients, R = 2.7965exp-4 0 /h 2 , K = 1.1714exp-3 0 /h 1.5 , B = 1.3185exp-3 0 /h, N = 5.982exp-4 0 /h 0.5 and Q = 5.197exp-7 0 in real time, and tracks degradation of gyro performance from initail values, R = 0.651 0 /h 2 , K = 0.801 0 /h 1.5 , B = 0.385 0 /h, N = 0.0874 0 /h 0.5 and Q = 8.085exp-5 0 , to final estimations, R = 9.548 0 /h 2 , K = 9.524 0 /h 1.5 , B = 2.234 0 /h, N = 0.5594 0 /h 0.5 and Q = 5.113exp-4 0 , due to gamma radiation in space. The technique proposed here effectively isolates satellite motion, and requires no data storage and any supports from the ground.

Apparent scale correlations in a random multifractal process

DEFF Research Database (Denmark)

Cleve, Jochen; Schmiegel, Jürgen; Greiner, Martin

2008-01-01

We discuss various properties of a homogeneous random multifractal process, which are related to the issue of scale correlations. By design, the process has no built-in scale correlations. However, when it comes to observables like breakdown coefficients, which are based on a coarse......-graining of the multifractal field, scale correlations do appear. In the log-normal limit of the model process, the conditional distributions and moments of breakdown coefficients reproduce the observations made in fully developed small-scale turbulence. These findings help to understand several puzzling empirical details...

Bayesian dynamic modeling of time series of dengue disease case counts.

Science.gov (United States)

Martínez-Bello, Daniel Adyro; López-Quílez, Antonio; Torres-Prieto, Alexander

2017-07-01

The aim of this study is to model the association between weekly time series of dengue case counts and meteorological variables, in a high-incidence city of Colombia, applying Bayesian hierarchical dynamic generalized linear models over the period January 2008 to August 2015. Additionally, we evaluate the model's short-term performance for predicting dengue cases. The methodology shows dynamic Poisson log link models including constant or time-varying coefficients for the meteorological variables. Calendar effects were modeled using constant or first- or second-order random walk time-varying coefficients. The meteorological variables were modeled using constant coefficients and first-order random walk time-varying coefficients. We applied Markov Chain Monte Carlo simulations for parameter estimation, and deviance information criterion statistic (DIC) for model selection. We assessed the short-term predictive performance of the selected final model, at several time points within the study period using the mean absolute percentage error. The results showed the best model including first-order random walk time-varying coefficients for calendar trend and first-order random walk time-varying coefficients for the meteorological variables. Besides the computational challenges, interpreting the results implies a complete analysis of the time series of dengue with respect to the parameter estimates of the meteorological effects. We found small values of the mean absolute percentage errors at one or two weeks out-of-sample predictions for most prediction points, associated with low volatility periods in the dengue counts. We discuss the advantages and limitations of the dynamic Poisson models for studying the association between time series of dengue disease and meteorological variables. The key conclusion of the study is that dynamic Poisson models account for the dynamic nature of the variables involved in the modeling of time series of dengue disease, producing useful

Flow injection analysis simulations and diffusion coefficient determination by stochastic and deterministic optimization methods.

Science.gov (United States)

Kucza, Witold

2013-07-25

Stochastic and deterministic simulations of dispersion in cylindrical channels on the Poiseuille flow have been presented. The random walk (stochastic) and the uniform dispersion (deterministic) models have been used for computations of flow injection analysis responses. These methods coupled with the genetic algorithm and the Levenberg-Marquardt optimization methods, respectively, have been applied for determination of diffusion coefficients. The diffusion coefficients of fluorescein sodium, potassium hexacyanoferrate and potassium dichromate have been determined by means of the presented methods and FIA responses that are available in literature. The best-fit results agree with each other and with experimental data thus validating both presented approaches. Copyright © 2013 The Author. Published by Elsevier B.V. All rights reserved.

The coefficient of determination R2 and intra-class correlation coefficient from generalized linear mixed-effects models revisited and expanded.

Science.gov (United States)

Nakagawa, Shinichi; Johnson, Paul C D; Schielzeth, Holger

2017-09-01

The coefficient of determination R 2 quantifies the proportion of variance explained by a statistical model and is an important summary statistic of biological interest. However, estimating R 2 for generalized linear mixed models (GLMMs) remains challenging. We have previously introduced a version of R 2 that we called [Formula: see text] for Poisson and binomial GLMMs, but not for other distributional families. Similarly, we earlier discussed how to estimate intra-class correlation coefficients (ICCs) using Poisson and binomial GLMMs. In this paper, we generalize our methods to all other non-Gaussian distributions, in particular to negative binomial and gamma distributions that are commonly used for modelling biological data. While expanding our approach, we highlight two useful concepts for biologists, Jensen's inequality and the delta method, both of which help us in understanding the properties of GLMMs. Jensen's inequality has important implications for biologically meaningful interpretation of GLMMs, whereas the delta method allows a general derivation of variance associated with non-Gaussian distributions. We also discuss some special considerations for binomial GLMMs with binary or proportion data. We illustrate the implementation of our extension by worked examples from the field of ecology and evolution in the R environment. However, our method can be used across disciplines and regardless of statistical environments. © 2017 The Author(s).

Semivarying coefficient models for capture-recapture data: colony size estimation for the little penguin Eudyptula minor.

Science.gov (United States)

Stoklosa, Jakub; Dann, Peter; Huggins, Richard

2014-09-01

To accommodate seasonal effects that change from year to year into models for the size of an open population we consider a time-varying coefficient model. We fit this model to a capture-recapture data set collected on the little penguin Eudyptula minor in south-eastern Australia over a 25 year period using Jolly-Seber type estimators and nonparametric P-spline techniques. The time-varying coefficient model identified strong changes in the seasonal pattern across the years which we further examined using functional data analysis techniques. To evaluate the methodology we also conducted several simulation studies that incorporate seasonal variation. Copyright © 2014 Elsevier Inc. All rights reserved.

Random Coefficient Logit Model for Large Datasets

NARCIS (Netherlands)

C. Hernández-Mireles (Carlos); D. Fok (Dennis)

2010-01-01

textabstractWe present an approach for analyzing market shares and products price elasticities based on large datasets containing aggregate sales data for many products, several markets and for relatively long time periods. We consider the recently proposed Bayesian approach of Jiang et al [Jiang,

Modelling water evaporation during frying with an evaporation dependent heat transfer coefficient

NARCIS (Netherlands)

Koerten, van K.N.; Somsen, D.; Boom, R.M.; Schutyser, M.A.I.

2017-01-01

In this study a cylindrical crust-core frying model was developed including an evaporation rate dependent heat transfer coefficient. For this, we applied a Nusselt relation for cylindrical bodies and view the release of vapour bubbles during the frying process as a reversed fluidised bed. The

QSPR modeling of octanol/water partition coefficient for vitamins by optimal descriptors calculated with SMILES.

Science.gov (United States)

Toropov, A A; Toropova, A P; Raska, I

2008-04-01

Simplified molecular input line entry system (SMILES) has been utilized in constructing quantitative structure-property relationships (QSPR) for octanol/water partition coefficient of vitamins and organic compounds of different classes by optimal descriptors. Statistical characteristics of the best model (vitamins) are the following: n=17, R(2)=0.9841, s=0.634, F=931 (training set); n=7, R(2)=0.9928, s=0.773, F=690 (test set). Using this approach for modeling octanol/water partition coefficient for a set of organic compounds gives a model that is statistically characterized by n=69, R(2)=0.9872, s=0.156, F=5184 (training set) and n=70, R(2)=0.9841, s=0.179, F=4195 (test set).

Measurement and modeling of osmotic coefficients of binary mixtures (alcohol + 1,3-dimethylpyridinium methylsulfate) at T = 323.15 K

International Nuclear Information System (INIS)

Gomez, Elena; Calvar, Noelia; Dominguez, Angeles; Macedo, Eugenia A.

2011-01-01

Research highlights: → The osmotic coefficients of binary mixtures (alcohol + ionic liquid) were determined. → The measurements were carried out with a vapor pressure osmometer at 323.15 K. → The Pitzer-Archer, and the MNRTL models were used to correlate the experimental data. → Mean molal activity coefficients and excess Gibbs free energies were calculated. - Abstract: Measurement of osmotic coefficients of binary mixtures containing several primary and secondary alcohols (1-propanol, 2-propanol, 1-butanol, 2-butanol, and 1-pentanol) and the pyridinium-based ionic liquid 1,3-dimethylpyridinium methylsulfate were performed at T = 323.15 K using the vapor pressure osmometry technique, and from experimental data, vapor pressure, and activity coefficients were determined. The extended Pitzer model modified by Archer, and the NRTL model modified by Jaretun and Aly (MNRTL) were used to correlate the experimental osmotic coefficients, obtaining standard deviations lower than 0.017 and 0.054, respectively. From the parameters obtained with the extended Pitzer model modified by Archer, the mean molal activity coefficients and the excess Gibbs free energy for the studied binary mixtures were calculated. The effect of the cation is studied comparing the experimental results with those obtained for the ionic liquid 1,3-dimethylimidazolium methylsulfate.

Evaluation Procedures of Random Uncertainties in Theoretical Calculations of Cross Sections and Rate Coefficients

International Nuclear Information System (INIS)

Kokoouline, V.; Richardson, W.

2014-01-01

Uncertainties in theoretical calculations may include: • Systematic uncertainty: Due to applicability limits of the chosen model. • Random: Within a model, uncertainties of model parameters result in uncertainties of final results (such as cross sections). • If uncertainties of experimental and theoretical data are known, for the purpose of data evaluation (to produce recommended data), one should combine two data sets to produce the best guess data with the smallest possible uncertainty. In many situations, it is possible to assess the accuracy of theoretical calculations because theoretical models usually rely on parameters that are uncertain, but not completely random, i.e. the uncertainties of the parameters of the models are approximately known. If there are one or several such parameters with corresponding uncertainties, even if some or all parameters are correlated, the above approach gives a conceptually simple way to calculate uncertainties of final cross sections (uncertainty propagation). Numerically, the statistical approach to the uncertainty propagation could be computationally expensive. However, in situations, where uncertainties are considered to be as important as the actual cross sections (for data validation or benchmark calculations, for example), such a numerical effort is justified. Having data from different sources (say, from theory and experiment), a systematic statistical approach allows one to compare the data and produce “unbiased” evaluated data with improved uncertainties, if uncertainties of initial data from different sources are available. Without uncertainties, the data evaluation/validation becomes impossible. This is the reason why theoreticians should assess the accuracy of their calculations in one way or another. A statistical and systematic approach, similar to the described above, is preferable.

Lower Virial Coefficients of Primitive Models of Polar and Associating Fluids.

Czech Academy of Sciences Publication Activity Database

Rouha, M.; Nezbeda, Ivo

2007-01-01

Roč. 134, 1-3 (2007) , s. 107-110 Sp. Iss. SI ISSN 0167-7322 R&D Projects: GA AV ČR(CZ) IAA4072303; GA AV ČR(CZ) 1ET400720409 Institutional research plan: CEZ:AV0Z40720504 Keywords : primitive models * virial coefficients * metropolis like monte-carlo integration Subject RIV: CF - Physical ; Theoretical Chemistry Impact factor: 0.982, year: 2007

The development from kinetic coefficients of a predictive model for the growth of Eichhomia crassipes in the field. I. Generating kinetic coefficients for the model in greenhouse culture

Directory of Open Access Journals (Sweden)

C. F. Musil

1984-12-01

Full Text Available The kinetics of N- and P- limited growth of Eichhornia crassipes (Mart . Solms were investigated in greenhouse culture with the object of developing a model for predicting population sizes, yields, growth rates and frequencies and amounts of harvest, under varying conditions of nutrient loading and climate, to control both nutrient inputs and excessive growth in eutrophied aquatic systems. The kinetic coefficients, maximum specific growth rate (Umax, half saturation coefficient (Ks and yield coefficient (Yc were measured under N and P limitation in replicated batch culture experiments. Umax values and Ks concentrations derived under N limitation ranged from 5,37 to 8,86% d + and from 400 to 1 506 µg  N ℓ1respectively. Those derived under P limitation ranged from 4,51 to 10,89% d 1 and from 41 to 162 fig P ℓ1 respectively. Yc values (fresh mass basis determined ranged from 1 660 to 1 981 (87 to 98 dry mass basis for N and from 16 431 to 18 671 (867 to 980 dry mass basis for P. The reciprocals of Yc values (dry mass basis, expressed as percentages, adequately estimated the minimum limiting concentrations of N and P {% dry mass in the plant tissues. Kinetic coefficients determined are compared with those reported for algae. The experimental method used and results obtained are critically assessed.

Properties of Traffic Risk Coefficient

Science.gov (United States)

Tang, Tie-Qiao; Huang, Hai-Jun; Shang, Hua-Yan; Xue, Yu

2009-10-01

We use the model with the consideration of the traffic interruption probability (Physica A 387(2008)6845) to study the relationship between the traffic risk coefficient and the traffic interruption probability. The analytical and numerical results show that the traffic interruption probability will reduce the traffic risk coefficient and that the reduction is related to the density, which shows that this model can improve traffic security.

Practical methods to define scattering coefficients in a room acoustics computer model

DEFF Research Database (Denmark)

Zeng, Xiangyang; Christensen, Claus Lynge; Rindel, Jens Holger

2006-01-01

of obtaining the data becomes quite time consuming thus increasing the cost of design. In this paper, practical methods to define scattering coefficients, which is based on an approach of modeling surface scattering and scattering caused by limited size of surface as well as edge diffraction are presented...

A Generalized Random Regret Minimization Model

NARCIS (Netherlands)

Chorus, C.G.

2013-01-01

This paper presents, discusses and tests a generalized Random Regret Minimization (G-RRM) model. The G-RRM model is created by replacing a fixed constant in the attribute-specific regret functions of the RRM model, by a regret-weight variable. Depending on the value of the regret-weights, the G-RRM

Simulation of a directed random-walk model: the effect of pseudo-random-number correlations

OpenAIRE

Shchur, L. N.; Heringa, J. R.; Blöte, H. W. J.

1996-01-01

We investigate the mechanism that leads to systematic deviations in cluster Monte Carlo simulations when correlated pseudo-random numbers are used. We present a simple model, which enables an analysis of the effects due to correlations in several types of pseudo-random-number sequences. This model provides qualitative understanding of the bias mechanism in a class of cluster Monte Carlo algorithms.

Non-constant link tension coefficient in the tumbling-snake model subjected to simple shear

Science.gov (United States)

Stephanou, Pavlos S.; Kröger, Martin

2017-11-01

The authors of the present study have recently presented evidence that the tumbling-snake model for polymeric systems has the necessary capacity to predict the appearance of pronounced undershoots in the time-dependent shear viscosity as well as an absence of equally pronounced undershoots in the transient two normal stress coefficients. The undershoots were found to appear due to the tumbling behavior of the director u when a rotational Brownian diffusion term is considered within the equation of motion of polymer segments, and a theoretical basis concerning the use of a link tension coefficient given through the nematic order parameter had been provided. The current work elaborates on the quantitative predictions of the tumbling-snake model to demonstrate its capacity to predict undershoots in the time-dependent shear viscosity. These predictions are shown to compare favorably with experimental rheological data for both polymer melts and solutions, help us to clarify the microscopic origin of the observed phenomena, and demonstrate in detail why a constant link tension coefficient has to be abandoned.

Network clustering coefficient approach to DNA sequence analysis

Energy Technology Data Exchange (ETDEWEB)

Gerhardt, Guenther J.L. [Universidade Federal do Rio Grande do Sul-Hospital de Clinicas de Porto Alegre, Rua Ramiro Barcelos 2350/sala 2040/90035-003 Porto Alegre (Brazil); Departamento de Fisica e Quimica da Universidade de Caxias do Sul, Rua Francisco Getulio Vargas 1130, 95001-970 Caxias do Sul (Brazil); Lemke, Ney [Programa Interdisciplinar em Computacao Aplicada, Unisinos, Av. Unisinos, 950, 93022-000 Sao Leopoldo, RS (Brazil); Corso, Gilberto [Departamento de Biofisica e Farmacologia, Centro de Biociencias, Universidade Federal do Rio Grande do Norte, Campus Universitario, 59072 970 Natal, RN (Brazil)]. E-mail: corso@dfte.ufrn.br

2006-05-15

In this work we propose an alternative DNA sequence analysis tool based on graph theoretical concepts. The methodology investigates the path topology of an organism genome through a triplet network. In this network, triplets in DNA sequence are vertices and two vertices are connected if they occur juxtaposed on the genome. We characterize this network topology by measuring the clustering coefficient. We test our methodology against two main bias: the guanine-cytosine (GC) content and 3-bp (base pairs) periodicity of DNA sequence. We perform the test constructing random networks with variable GC content and imposed 3-bp periodicity. A test group of some organisms is constructed and we investigate the methodology in the light of the constructed random networks. We conclude that the clustering coefficient is a valuable tool since it gives information that is not trivially contained in 3-bp periodicity neither in the variable GC content.

Drag Coefficient Estimation in Orbit Determination

Science.gov (United States)

McLaughlin, Craig A.; Manee, Steve; Lichtenberg, Travis

2011-07-01

Drag modeling is the greatest uncertainty in the dynamics of low Earth satellite orbits where ballistic coefficient and density errors dominate drag errors. This paper examines fitted drag coefficients found as part of a precision orbit determination process for Stella, Starlette, and the GEOSAT Follow-On satellites from 2000 to 2005. The drag coefficients for the spherical Stella and Starlette satellites are assumed to be highly correlated with density model error. The results using MSIS-86, NRLMSISE-00, and NRLMSISE-00 with dynamic calibration of the atmosphere (DCA) density corrections are compared. The DCA corrections were formulated for altitudes of 200-600 km and are found to be inappropriate when applied at 800 km. The yearly mean fitted drag coefficients are calculated for each satellite for each year studied. The yearly mean drag coefficients are higher for Starlette than Stella, where Starlette is at a higher altitude. The yearly mean fitted drag coefficients for all three satellites decrease as solar activity decreases after solar maximum.

Regularity of the Interband Light Absorption Coefficient

Indian Academy of Sciences (India)

In this paper we consider the interband light absorption coefficient (ILAC), in a symmetric form, in the case of random operators on the -dimensional lattice. We show that the symmetrized version of ILAC is either continuous or has a component which has the same modulus of continuity as the density of states.

The random field Blume-Capel model revisited

Science.gov (United States)

Santos, P. V.; da Costa, F. A.; de Araújo, J. M.

2018-04-01

We have revisited the mean-field treatment for the Blume-Capel model under the presence of a discrete random magnetic field as introduced by Kaufman and Kanner (1990). The magnetic field (H) versus temperature (T) phase diagrams for given values of the crystal field D were recovered in accordance to Kaufman and Kanner original work. However, our main goal in the present work was to investigate the distinct structures of the crystal field versus temperature phase diagrams as the random magnetic field is varied because similar models have presented reentrant phenomenon due to randomness. Following previous works we have classified the distinct phase diagrams according to five different topologies. The topological structure of the phase diagrams is maintained for both H - T and D - T cases. Although the phase diagrams exhibit a richness of multicritical phenomena we did not found any reentrant effect as have been seen in similar models.

Random regression models for detection of gene by environment interaction

Directory of Open Access Journals (Sweden)

Meuwissen Theo HE

2007-02-01

Full Text Available Abstract Two random regression models, where the effect of a putative QTL was regressed on an environmental gradient, are described. The first model estimates the correlation between intercept and slope of the random regression, while the other model restricts this correlation to 1 or -1, which is expected under a bi-allelic QTL model. The random regression models were compared to a model assuming no gene by environment interactions. The comparison was done with regards to the models ability to detect QTL, to position them accurately and to detect possible QTL by environment interactions. A simulation study based on a granddaughter design was conducted, and QTL were assumed, either by assigning an effect independent of the environment or as a linear function of a simulated environmental gradient. It was concluded that the random regression models were suitable for detection of QTL effects, in the presence and absence of interactions with environmental gradients. Fixing the correlation between intercept and slope of the random regression had a positive effect on power when the QTL effects re-ranked between environments.

Solvation free energies and partition coefficients with the coarse-grained and hybrid all-atom/coarse-grained MARTINI models.

Science.gov (United States)

Genheden, Samuel

2017-10-01

We present the estimation of solvation free energies of small solutes in water, n-octanol and hexane using molecular dynamics simulations with two MARTINI models at different resolutions, viz. the coarse-grained (CG) and the hybrid all-atom/coarse-grained (AA/CG) models. From these estimates, we also calculate the water/hexane and water/octanol partition coefficients. More than 150 small, organic molecules were selected from the Minnesota solvation database and parameterized in a semi-automatic fashion. Using either the CG or hybrid AA/CG models, we find considerable deviations between the estimated and experimental solvation free energies in all solvents with mean absolute deviations larger than 10 kJ/mol, although the correlation coefficient is between 0.55 and 0.75 and significant. There is also no difference between the results when using the non-polarizable and polarizable water model, although we identify some improvements when using the polarizable model with the AA/CG solutes. In contrast to the estimated solvation energies, the estimated partition coefficients are generally excellent with both the CG and hybrid AA/CG models, giving mean absolute deviations between 0.67 and 0.90 log units and correlation coefficients larger than 0.85. We analyze the error distribution further and suggest avenues for improvements.

Solvation free energies and partition coefficients with the coarse-grained and hybrid all-atom/coarse-grained MARTINI models

Science.gov (United States)

Genheden, Samuel

2017-10-01

We present the estimation of solvation free energies of small solutes in water, n-octanol and hexane using molecular dynamics simulations with two MARTINI models at different resolutions, viz. the coarse-grained (CG) and the hybrid all-atom/coarse-grained (AA/CG) models. From these estimates, we also calculate the water/hexane and water/octanol partition coefficients. More than 150 small, organic molecules were selected from the Minnesota solvation database and parameterized in a semi-automatic fashion. Using either the CG or hybrid AA/CG models, we find considerable deviations between the estimated and experimental solvation free energies in all solvents with mean absolute deviations larger than 10 kJ/mol, although the correlation coefficient is between 0.55 and 0.75 and significant. There is also no difference between the results when using the non-polarizable and polarizable water model, although we identify some improvements when using the polarizable model with the AA/CG solutes. In contrast to the estimated solvation energies, the estimated partition coefficients are generally excellent with both the CG and hybrid AA/CG models, giving mean absolute deviations between 0.67 and 0.90 log units and correlation coefficients larger than 0.85. We analyze the error distribution further and suggest avenues for improvements.

Virial Coefficients for the Liquid Argon

Science.gov (United States)

Korth, Micheal; Kim, Saesun

2014-03-01

We begin with a geometric model of hard colliding spheres and calculate probability densities in an iterative sequence of calculations that lead to the pair correlation function. The model is based on a kinetic theory approach developed by Shinomoto, to which we added an interatomic potential for argon based on the model from Aziz. From values of the pair correlation function at various values of density, we were able to find viral coefficients of liquid argon. The low order coefficients are in good agreement with theoretical hard sphere coefficients, but appropriate data for argon to which these results might be compared is difficult to find.

Emergent randomness in the Jaynes-Cummings model

International Nuclear Information System (INIS)

Garraway, B M; Stenholm, S

2008-01-01

We consider the well-known Jaynes-Cummings model and ask if it can display randomness. As a solvable Hamiltonian system, it does not display chaotic behaviour in the ordinary sense. Here, however, we look at the distribution of values taken up during the total time evolution. This evolution is determined by the eigenvalues distributed as the square roots of integers and leads to a seemingly erratic behaviour. That this may display a random Gaussian value distribution is suggested by an exactly provable result by Kac. In order to reach our conclusion we use the Kac model to develop tests for the emergence of a Gaussian. Even if the consequent double limits are difficult to evaluate numerically, we find definite indications that the Jaynes-Cummings case also produces a randomness in its value distributions. Numerical methods do not establish such a result beyond doubt, but our conclusions are definite enough to suggest strongly an unexpected randomness emerging in a dynamic time evolution

Comparison of different models for the determination of the absorption and scattering coefficients of thermal barrier coatings

International Nuclear Information System (INIS)

Wang, Li; Eldridge, Jeffrey I.; Guo, S.M.

2014-01-01

The thermal radiative properties of thermal barrier coatings (TBCs) are becoming more important as the inlet temperatures of advanced gas-turbine engines are continuously being pushed higher in order to improve efficiency. To determine the absorption and scattering coefficients of TBCs, four-flux, two-flux and Kubelka–Munk models were introduced and used to characterize the thermal radiative properties of plasma-sprayed yttria-stabilized zirconia (YSZ) coatings. The results show that the absorption coefficient of YSZ is extremely low for wavelengths 200 μm suggests that when the coating thickness is larger than around twice the average scattering distance, the collimated flux can be simply treated as a diffuse flux inside the coating, and thus the two-flux model can be used to determine the absorption and scattering coefficients as a simplification of the four-flux model

Analytical Modeling Of The Steinmetz Coefficient For Single-Phase Transformer Eddy Current Loss Prediction

Directory of Open Access Journals (Sweden)

T. Aly Saandy

2015-08-01

Full Text Available Abstract This article presents to an analytical calculation methodology of the Steinmetz coefficient applied to the prediction of Eddy current loss in a single-phase transformer. Based on the electrical circuit theory the active power consumed by the core is expressed analytically in function of the electrical parameters as resistivity and the geometrical dimensions of the core. The proposed modeling approach is established with the duality parallel series. The required coefficient is identified from the empirical Steinmetz data based on the experimented active power expression. To verify the relevance of the model validations both by simulations with two in two different frequencies and measurements were carried out. The obtained results are in good agreement with the theoretical approach and the practical results.

Critical Behavior of the Annealed Ising Model on Random Regular Graphs

Science.gov (United States)

Can, Van Hao

2017-11-01

In Giardinà et al. (ALEA Lat Am J Probab Math Stat 13(1):121-161, 2016), the authors have defined an annealed Ising model on random graphs and proved limit theorems for the magnetization of this model on some random graphs including random 2-regular graphs. Then in Can (Annealed limit theorems for the Ising model on random regular graphs, arXiv:1701.08639, 2017), we generalized their results to the class of all random regular graphs. In this paper, we study the critical behavior of this model. In particular, we determine the critical exponents and prove a non standard limit theorem stating that the magnetization scaled by n^{3/4} converges to a specific random variable, with n the number of vertices of random regular graphs.

Stochastic modeling of phosphorus transport in the Three Gorges Reservoir by incorporating variability associated with the phosphorus partition coefficient

Energy Technology Data Exchange (ETDEWEB)

Huang, Lei; Fang, Hongwei; Xu, Xingya; He, Guojian; Zhang, Xuesong; Reible, Danny

2017-08-01

Phosphorus (P) fate and transport plays a crucial role in the ecology of rivers and reservoirs in which eutrophication is limited by P. A key uncertainty in models used to help manage P in such systems is the partitioning of P to suspended and bed sediments. By analyzing data from field and laboratory experiments, we stochastically characterize the variability of the partition coefficient (Kd) and derive spatio-temporal solutions for P transport in the Three Gorges Reservoir (TGR). We formulate a set of stochastic partial different equations (SPDEs) to simulate P transport by randomly sampling Kd from the measured distributions, to obtain statistical descriptions of the P concentration and retention in the TGR. The correspondence between predicted and observed P concentrations and P retention in the TGR combined with the ability to effectively characterize uncertainty suggests that a model that incorporates the observed variability can better describe P dynamics and more effectively serve as a tool for P management in the system. This study highlights the importance of considering parametric uncertainty in estimating uncertainty/variability associated with simulated P transport.

Estimating safety effects of pavement management factors utilizing Bayesian random effect models.

Science.gov (United States)

Jiang, Ximiao; Huang, Baoshan; Zaretzki, Russell L; Richards, Stephen; Yan, Xuedong

2013-01-01

Previous studies of pavement management factors that relate to the occurrence of traffic-related crashes are rare. Traditional research has mostly employed summary statistics of bidirectional pavement quality measurements in extended longitudinal road segments over a long time period, which may cause a loss of important information and result in biased parameter estimates. The research presented in this article focuses on crash risk of roadways with overall fair to good pavement quality. Real-time and location-specific data were employed to estimate the effects of pavement management factors on the occurrence of crashes. This research is based on the crash data and corresponding pavement quality data for the Tennessee state route highways from 2004 to 2009. The potential temporal and spatial correlations among observations caused by unobserved factors were considered. Overall 6 models were built accounting for no correlation, temporal correlation only, and both the temporal and spatial correlations. These models included Poisson, negative binomial (NB), one random effect Poisson and negative binomial (OREP, ORENB), and two random effect Poisson and negative binomial (TREP, TRENB) models. The Bayesian method was employed to construct these models. The inference is based on the posterior distribution from the Markov chain Monte Carlo (MCMC) simulation. These models were compared using the deviance information criterion. Analysis of the posterior distribution of parameter coefficients indicates that the pavement management factors indexed by Present Serviceability Index (PSI) and Pavement Distress Index (PDI) had significant impacts on the occurrence of crashes, whereas the variable rutting depth was not significant. Among other factors, lane width, median width, type of terrain, and posted speed limit were significant in affecting crash frequency. The findings of this study indicate that a reduction in pavement roughness would reduce the likelihood of traffic

A random effects meta-analysis model with Box-Cox transformation.

Science.gov (United States)

Yamaguchi, Yusuke; Maruo, Kazushi; Partlett, Christopher; Riley, Richard D

2017-07-19

In a random effects meta-analysis model, true treatment effects for each study are routinely assumed to follow a normal distribution. However, normality is a restrictive assumption and the misspecification of the random effects distribution may result in a misleading estimate of overall mean for the treatment effect, an inappropriate quantification of heterogeneity across studies and a wrongly symmetric prediction interval. We focus on problems caused by an inappropriate normality assumption of the random effects distribution, and propose a novel random effects meta-analysis model where a Box-Cox transformation is applied to the observed treatment effect estimates. The proposed model aims to normalise an overall distribution of observed treatment effect estimates, which is sum of the within-study sampling distributions and the random effects distribution. When sampling distributions are approximately normal, non-normality in the overall distribution will be mainly due to the random effects distribution, especially when the between-study variation is large relative to the within-study variation. The Box-Cox transformation addresses this flexibly according to the observed departure from normality. We use a Bayesian approach for estimating parameters in the proposed model, and suggest summarising the meta-analysis results by an overall median, an interquartile range and a prediction interval. The model can be applied for any kind of variables once the treatment effect estimate is defined from the variable. A simulation study suggested that when the overall distribution of treatment effect estimates are skewed, the overall mean and conventional I 2 from the normal random effects model could be inappropriate summaries, and the proposed model helped reduce this issue. We illustrated the proposed model using two examples, which revealed some important differences on summary results, heterogeneity measures and prediction intervals from the normal random effects model. The

A random effects meta-analysis model with Box-Cox transformation

Directory of Open Access Journals (Sweden)

Yusuke Yamaguchi

2017-07-01

Full Text Available Abstract Background In a random effects meta-analysis model, true treatment effects for each study are routinely assumed to follow a normal distribution. However, normality is a restrictive assumption and the misspecification of the random effects distribution may result in a misleading estimate of overall mean for the treatment effect, an inappropriate quantification of heterogeneity across studies and a wrongly symmetric prediction interval. Methods We focus on problems caused by an inappropriate normality assumption of the random effects distribution, and propose a novel random effects meta-analysis model where a Box-Cox transformation is applied to the observed treatment effect estimates. The proposed model aims to normalise an overall distribution of observed treatment effect estimates, which is sum of the within-study sampling distributions and the random effects distribution. When sampling distributions are approximately normal, non-normality in the overall distribution will be mainly due to the random effects distribution, especially when the between-study variation is large relative to the within-study variation. The Box-Cox transformation addresses this flexibly according to the observed departure from normality. We use a Bayesian approach for estimating parameters in the proposed model, and suggest summarising the meta-analysis results by an overall median, an interquartile range and a prediction interval. The model can be applied for any kind of variables once the treatment effect estimate is defined from the variable. Results A simulation study suggested that when the overall distribution of treatment effect estimates are skewed, the overall mean and conventional I 2 from the normal random effects model could be inappropriate summaries, and the proposed model helped reduce this issue. We illustrated the proposed model using two examples, which revealed some important differences on summary results, heterogeneity measures and

Approximating prediction uncertainty for random forest regression models

Science.gov (United States)

John W. Coulston; Christine E. Blinn; Valerie A. Thomas; Randolph H. Wynne

2016-01-01

Machine learning approaches such as random forest have increased for the spatial modeling and mapping of continuous variables. Random forest is a non-parametric ensemble approach, and unlike traditional regression approaches there is no direct quantification of prediction error. Understanding prediction uncertainty is important when using model-based continuous maps as...

Rebound coefficient of collisionless gas in a rigid vessel. A model of reflection of field-reversed configuration

International Nuclear Information System (INIS)

Takaku, Yuichi; Hamada, Shigeo

1996-01-01

A system of collisionless neutral gas contained in a rigid vessel is considered as a simple model of reflection of field-reversed configuration (FRC) plasma by a magnetic mirror. The rebound coefficient of the system is calculated as a function of the incident speed of the vessel normalized by the thermal velocity of the gas before reflection. The coefficient is compared with experimental data of FIX (Osaka U.) and FRX-C/T(Los Alamos N.L.). Agreement is good for this simple model. Interesting is that the rebound coefficient takes the smallest value (∼0.365) as the incident speed tends to zero and approaches unity as it tends to infinity. This behavior is reverse to that expected for a system with collision dominated fluid instead of collisionless gas. By examining the rebound coefficient, therefore, it could be successfully inferred whether the ion mean free path in each experiment was longer or shorter than the plasma length. (author)

Compensatory and non-compensatory multidimensional randomized item response models

NARCIS (Netherlands)

Fox, J.P.; Entink, R.K.; Avetisyan, M.

2014-01-01

Randomized response (RR) models are often used for analysing univariate randomized response data and measuring population prevalence of sensitive behaviours. There is much empirical support for the belief that RR methods improve the cooperation of the respondents. Recently, RR models have been

REE Partition Coefficients from Synthetic Diogenite-Like Enstatite and the Implications of Petrogenetic Modeling

Science.gov (United States)

Schwandt, C. S.; McKay, G. A.

1996-01-01

Determining the petrogenesis of eucrites (basaltic achondrites) and diogenites (orthopyroxenites) and the possible links between the meteorite types was initiated 30 years ago by Mason. Since then, most investigators have worked on this question. A few contrasting theories have emerged, with the important distinction being whether or not there is a direct genetic link between eucrites and diogenites. One theory suggests that diogenites are cumulates resulting from the fractional crystallization of a parent magma with the eucrites crystallizing, from the residual magma after separation from the diogenite cumulates. Another model proposes that diogenites are cumulates formed from partial melts derived from a source region depleted by the prior generation of eucrite melts. It has also been proposed that the diogenites may not be directly linked to the eucrites and that they are cumulates derived from melts that are more orthopyroxene normative than the eucrites. This last theory has recently received more analytical and experimental support. One of the difficulties with petrogenetic modeling is that it requires appropriate partition coefficients for modeling because they are dependent on temperature, pressure, and composition. For this reason, we set out to determine minor- and trace-element partition coefficients for diogenite-like orthopyroxene. We have accomplished this task and now have enstatite/melt partition coefficients for Al, Cr, Ti, La, Ce, Nd, Sm, Eu, Dy, Er, Yb, and La.

Optimized Finite-Difference Coefficients for Hydroacoustic Modeling

Science.gov (United States)

Preston, L. A.

2014-12-01

Responsible utilization of marine renewable energy sources through the use of current energy converter (CEC) and wave energy converter (WEC) devices requires an understanding of the noise generation and propagation from these systems in the marine environment. Acoustic noise produced by rotating turbines, for example, could adversely affect marine animals and human-related marine activities if not properly understood and mitigated. We are utilizing a 3-D finite-difference acoustic simulation code developed at Sandia that can accurately propagate noise in the complex bathymetry in the near-shore to open ocean environment. As part of our efforts to improve computation efficiency in the large, high-resolution domains required in this project, we investigate the effects of using optimized finite-difference coefficients on the accuracy of the simulations. We compare accuracy and runtime of various finite-difference coefficients optimized via criteria such as maximum numerical phase speed error, maximum numerical group speed error, and L-1 and L-2 norms of weighted numerical group and phase speed errors over a given spectral bandwidth. We find that those coefficients optimized for L-1 and L-2 norms are superior in accuracy to those based on maximal error and can produce runtimes of 10% of the baseline case, which uses Taylor Series finite-difference coefficients at the Courant time step limit. We will present comparisons of the results for the various cases evaluated as well as recommendations for utilization of the cases studied. Sandia National Laboratories is a multi-program laboratory managed and operated by Sandia Corporation, a wholly owned subsidiary of Lockheed Martin Corporation, for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-AC04-94AL85000.

Painleve analysis and transformations for a generalized two-dimensional variable-coefficient Burgers model from fluid mechanics, acoustics and cosmic-ray astrophysics

International Nuclear Information System (INIS)

Wei, Guang-Mei

2006-01-01

Generalized two-dimensional variable-coefficient Burgers model is of current value in fluid mechanics, acoustics and cosmic-ray astrophysics. In this paper, Painleve analysis leads to the constraints on the variable coefficients for such a model to pass the Painleve test and to an auto-Baecklund transformation. Moreover, four transformations from this model are constructed, to the standard two-dimensional and one-dimensional Burgers models with the relevant constraints on the variable coefficients via symbolic computation. By virtue of the given transformations the properties and solutions of this model can be obtained from those of the standard two-dimensional and one-dimensional ones

A numerical evaluation of prediction accuracy of CO2 absorber model for various reaction rate coefficients

Directory of Open Access Journals (Sweden)

Shim S.M.

2012-01-01

Full Text Available The performance of the CO2 absorber column using mono-ethanolamine (MEA solution as chemical solvent are predicted by a One-Dimensional (1-D rate based model in the present study. 1-D Mass and heat balance equations of vapor and liquid phase are coupled with interfacial mass transfer model and vapor-liquid equilibrium model. The two-film theory is used to estimate the mass transfer between the vapor and liquid film. Chemical reactions in MEA-CO2-H2O system are considered to predict the equilibrium pressure of CO2 in the MEA solution. The mathematical and reaction kinetics models used in this work are calculated by using in-house code. The numerical results are validated in the comparison of simulation results with experimental and simulation data given in the literature. The performance of CO2 absorber column is evaluated by the 1-D rate based model using various reaction rate coefficients suggested by various researchers. When the rate of liquid to gas mass flow rate is about 8.3, 6.6, 4.5 and 3.1, the error of CO2 loading and the CO2 removal efficiency using the reaction rate coefficients of Aboudheir et al. is within about 4.9 % and 5.2 %, respectively. Therefore, the reaction rate coefficient suggested by Aboudheir et al. among the various reaction rate coefficients used in this study is appropriate to predict the performance of CO2 absorber column using MEA solution. [Acknowledgement. This research was supported by the Basic Science Research Program through the National Research Foundation of Korea (NRF, funded by the Ministry of Education, Science and Technology (2011-0017220].

The Best Model of the Swiss Banknote Data -Validation by the 95% CI of coefficients and t-test of discriminant scores

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Shuichi Shinmura

2016-06-01

Full Text Available The discriminant analysis is not the inferential statistics since there are no equations for standard error (SE of error rate and discriminant coefficient based on the normal distribution. In this paper, we proposed the “k-fold cross validation for small sample” and can obtain the 95% confidence interval (CI of error rates and discriminant coefficients. This method is the computer-intensive approach by statistical and mathematical programming (MP software such as JMP and LINGO. By the proposed approach, we can choose the best model with the minimum mean of error rate in the validation samples (Minimum M2 Standard. In this research, we examine the sixteen linear separable models of Swiss banknote data by eight linear discriminant functions (LDFs. M2 of the best model of Revised IP-OLDF is the smallest value of all models. We find all coefficients of six Revised IP-OLDF among sixteen models rejected by the 95% CI of discriminant coefficients (Discriminant coefficient standard. We compare t-values of the discriminant scores. The t-value of the best model has the maximum values among sixteen models (Maximum t-value Standard. Moreover, we can conclude that all standards support the best model of Revised IP-OLDF.

A cluster expansion approach to exponential random graph models

International Nuclear Information System (INIS)

Yin, Mei

2012-01-01

The exponential family of random graphs are among the most widely studied network models. We show that any exponential random graph model may alternatively be viewed as a lattice gas model with a finite Banach space norm. The system may then be treated using cluster expansion methods from statistical mechanics. In particular, we derive a convergent power series expansion for the limiting free energy in the case of small parameters. Since the free energy is the generating function for the expectations of other random variables, this characterizes the structure and behavior of the limiting network in this parameter region

Estimating Reaction Rate Coefficients Within a Travel-Time Modeling Framework

Energy Technology Data Exchange (ETDEWEB)

Gong, R [Georgia Institute of Technology; Lu, C [Georgia Institute of Technology; Luo, Jian [Georgia Institute of Technology; Wu, Wei-min [Stanford University; Cheng, H. [Stanford University; Criddle, Craig [Stanford University; Kitanidis, Peter K. [Stanford University; Gu, Baohua [ORNL; Watson, David B [ORNL; Jardine, Philip M [ORNL; Brooks, Scott C [ORNL

2011-03-01

A generalized, efficient, and practical approach based on the travel-time modeling framework is developed to estimate in situ reaction rate coefficients for groundwater remediation in heterogeneous aquifers. The required information for this approach can be obtained by conducting tracer tests with injection of a mixture of conservative and reactive tracers and measurements of both breakthrough curves (BTCs). The conservative BTC is used to infer the travel-time distribution from the injection point to the observation point. For advection-dominant reactive transport with well-mixed reactive species and a constant travel-time distribution, the reactive BTC is obtained by integrating the solutions to advective-reactive transport over the entire travel-time distribution, and then is used in optimization to determine the in situ reaction rate coefficients. By directly working on the conservative and reactive BTCs, this approach avoids costly aquifer characterization and improves the estimation for transport in heterogeneous aquifers which may not be sufficiently described by traditional mechanistic transport models with constant transport parameters. Simplified schemes are proposed for reactive transport with zero-, first-, nth-order, and Michaelis-Menten reactions. The proposed approach is validated by a reactive transport case in a two-dimensional synthetic heterogeneous aquifer and a field-scale bioremediation experiment conducted at Oak Ridge, Tennessee. The field application indicates that ethanol degradation for U(VI)-bioremediation is better approximated by zero-order reaction kinetics than first-order reaction kinetics.

Measurements and modeling of gain coefficients for neodymium laser glasses

International Nuclear Information System (INIS)

Linford, G.J.; Saroyan, R.A.; Trenholme, J.B.; Weber, M.J.

1979-01-01

Small-signal gain coefficients are reported for neodymium in silicate, phosphate, fluorophosphate, and fluoroberyllate laser glasses. Measurements were made in a disk amplifier under identical conditions. Using spectroscopic data as the input, amplifier gain is calculated as a fucntion of flashlamp energy, pumping pulse duration, disk thickness, and Nd-doping. The agreement between predicted and measured gains is generally with ;plus or minus;10 percent, consistent with experimental uncertainties in the model and the parameters used. The operating conditions which optimize amplifier performance and efficiency for a given laser glass may be found using spectroscopic data alone. This process can be extended to derive the most cost-effective staging of amplifier chains for fusion lasers. A discussion of the model and examples of calculations are presented

Organ dose conversion coefficients based on a voxel mouse model and MCNP code for external photon irradiation.

Science.gov (United States)

Zhang, Xiaomin; Xie, Xiangdong; Cheng, Jie; Ning, Jing; Yuan, Yong; Pan, Jie; Yang, Guoshan

2012-01-01

A set of conversion coefficients from kerma free-in-air to the organ absorbed dose for external photon beams from 10 keV to 10 MeV are presented based on a newly developed voxel mouse model, for the purpose of radiation effect evaluation. The voxel mouse model was developed from colour images of successive cryosections of a normal nude male mouse, in which 14 organs or tissues were segmented manually and filled with different colours, while each colour was tagged by a specific ID number for implementation of mouse model in Monte Carlo N-particle code (MCNP). Monte Carlo simulation with MCNP was carried out to obtain organ dose conversion coefficients for 22 external monoenergetic photon beams between 10 keV and 10 MeV under five different irradiation geometries conditions (left lateral, right lateral, dorsal-ventral, ventral-dorsal, and isotropic). Organ dose conversion coefficients were presented in tables and compared with the published data based on a rat model to investigate the effect of body size and weight on the organ dose. The calculated and comparison results show that the organ dose conversion coefficients varying the photon energy exhibits similar trend for most organs except for the bone and skin, and the organ dose is sensitive to body size and weight at a photon energy approximately <0.1 MeV.

Modeling of thermal expansion coefficient of perovskite oxide for solid oxide fuel cell cathode

Science.gov (United States)

Heydari, F.; Maghsoudipour, A.; Alizadeh, M.; Khakpour, Z.; Javaheri, M.

2015-09-01

Artificial intelligence models have the capacity to eliminate the need for expensive experimental investigation in various areas of manufacturing processes, including the material science. This study investigates the applicability of adaptive neuro-fuzzy inference system (ANFIS) approach for modeling the performance parameters of thermal expansion coefficient (TEC) of perovskite oxide for solid oxide fuel cell cathode. Oxides (Ln = La, Nd, Sm and M = Fe, Ni, Mn) have been prepared and characterized to study the influence of the different cations on TEC. Experimental results have shown TEC decreases favorably with substitution of Nd3+ and Mn3+ ions in the lattice. Structural parameters of compounds have been determined by X-ray diffraction, and field emission scanning electron microscopy has been used for the morphological study. Comparison results indicated that the ANFIS technique could be employed successfully in modeling thermal expansion coefficient of perovskite oxide for solid oxide fuel cell cathode, and considerable savings in terms of cost and time could be obtained by using ANFIS technique.

A varying coefficient model to measure the effectiveness of mass media anti-smoking campaigns in generating calls to a Quitline.

Science.gov (United States)

Bui, Quang M; Huggins, Richard M; Hwang, Wen-Han; White, Victoria; Erbas, Bircan

2010-01-01

Anti-smoking advertisements are an effective population-based smoking reduction strategy. The Quitline telephone service provides a first point of contact for adults considering quitting. Because of data complexity, the relationship between anti-smoking advertising placement, intensity, and time trends in total call volume is poorly understood. In this study we use a recently developed semi-varying coefficient model to elucidate this relationship. Semi-varying coefficient models comprise parametric and nonparametric components. The model is fitted to the daily number of calls to Quitline in Victoria, Australia to estimate a nonparametric long-term trend and parametric terms for day-of-the-week effects and to clarify the relationship with target audience rating points (TARPs) for the Quit and nicotine replacement advertising campaigns. The number of calls to Quitline increased with the TARP value of both the Quit and other smoking cessation advertisement; the TARP values associated with the Quit program were almost twice as effective. The varying coefficient term was statistically significant for peak periods with little or no advertising. Semi-varying coefficient models are useful for modeling public health data when there is little or no information on other factors related to the at-risk population. These models are well suited to modeling call volume to Quitline, because the varying coefficient allowed the underlying time trend to depend on fixed covariates that also vary with time, thereby explaining more of the variation in the call model.

Modeling of the Interminiband Absorption Coefficient in InGaN Quantum Dot Superlattices

Directory of Open Access Journals (Sweden)

Giovanni Giannoccaro

2016-01-01

Full Text Available In this paper, a model to estimate minibands and theinterminiband absorption coefficient for a wurtzite (WZ indium gallium nitride (InGaN self-assembled quantum dot superlattice (QDSL is developed. It considers a simplified cuboid shape for quantum dots (QDs. The semi-analytical investigation starts from evaluation through the three-dimensional (3D finite element method (FEM simulations of crystal mechanical deformation derived from heterostructure lattice mismatch under spontaneous and piezoelectric polarization effects. From these results, mean values in QDs and barrier regions of charge carriers’ electric potentials and effective masses for the conduction band (CB and three valence sub-bands for each direction are evaluated. For the minibands’ investigation, the single-particle time-independent Schrödinger equation in effective mass approximation is decoupled in three directions and resolved using the one-dimensional (1D Kronig–Penney model. The built-in electric field is also considered along the polar axis direction, obtaining Wannier–Stark ladders. Then, theinterminiband absorption coefficient in thermal equilibrium for transverse electric (TE and magnetic (TM incident light polarization is calculated using Fermi’s golden rule implementation based on a numerical integration into the first Brillouin zone. For more detailed results, an absorption coefficient component related to superlattice free excitons is also introduced. Finally, some simulation results, observations and comments are given.

Energy coefficients for a propeller series

DEFF Research Database (Denmark)

Olsen, Anders Smærup

2004-01-01

The efficiency for a propeller is calculated by energy coefficients. These coefficients are related to four types of losses, i.e. the axial, the rotational, the frictional, and the finite blade number loss, and one gain, i.e. the axial gain. The energy coefficients are derived by use...... of the potential theory with the propeller modelled as an actuator disk. The efficiency based on the energy coefficients is calculated for a propeller series. The results show a good agreement between the efficiency based on the energy coefficients and the efficiency obtained by a vortex-lattice method....

An efficient algorithm for generating random number pairs drawn from a bivariate normal distribution

Science.gov (United States)

Campbell, C. W.

1983-01-01

An efficient algorithm for generating random number pairs from a bivariate normal distribution was developed. Any desired value of the two means, two standard deviations, and correlation coefficient can be selected. Theoretically the technique is exact and in practice its accuracy is limited only by the quality of the uniform distribution random number generator, inaccuracies in computer function evaluation, and arithmetic. A FORTRAN routine was written to check the algorithm and good accuracy was obtained. Some small errors in the correlation coefficient were observed to vary in a surprisingly regular manner. A simple model was developed which explained the qualities aspects of the errors.

Computer simulations of the random barrier model

DEFF Research Database (Denmark)

Schrøder, Thomas; Dyre, Jeppe

2002-01-01

A brief review of experimental facts regarding ac electronic and ionic conduction in disordered solids is given followed by a discussion of what is perhaps the simplest realistic model, the random barrier model (symmetric hopping model). Results from large scale computer simulations are presented...

Randomized Item Response Theory Models

NARCIS (Netherlands)

Fox, Gerardus J.A.

2005-01-01

The randomized response (RR) technique is often used to obtain answers on sensitive questions. A new method is developed to measure latent variables using the RR technique because direct questioning leads to biased results. Within the RR technique is the probability of the true response modeled by

Determination of Partition Coefficients of Selected Model Migrants between Polyethylene and Polypropylene and Nanocomposite Polypropylene

Directory of Open Access Journals (Sweden)

Pablo Otero-Pazos

2016-01-01

Full Text Available Studies on nanoparticles have focused the attention of the researchers because they can produce nanocomposites that exhibit unexpected hybrid properties. Polymeric materials are commonly used in food packaging, but from the standpoint of food safety, one of the main concerns on the use of these materials is the potential migration of low molecular substances from the packaging into the food. The key parameters of this phenomenon are the diffusion and partition coefficients. Studies on migration from food packaging with nanomaterials are very scarce. This study is focused on the determination of partition coefficients of different model migrants between the low-density polyethylene (LDPE and polypropylene (PP and between LDPE and nanocomposite polypropylene (naPP. The results show that the incorporation of nanoparticles in polypropylene increases the mass transport of model migrants from LDPE to naPP. This quantity of migrants absorbed into PP and naPP depends partially on the nature of the polymer and slightly on the chemical features of the migrant. Relation (RPP/naPP between partition coefficient KLDPE/PP and partition coefficient KLDPE/naPP at 60°C and 80°C shows that only BHT at 60°C has a RPP/naPP less than 1. On the other hand, bisphenol A has the highest RPP/naPP with approximately 50 times more.

Autonomous estimation of Allan variance coefficients of onboard fiber optic gyro

Energy Technology Data Exchange (ETDEWEB)

Song Ningfang; Yuan Rui; Jin Jing, E-mail: rayleing@139.com [School of Instrumentation Science and Opto-electronics Engineering, Beihang University, Beijing 100191 (China)

2011-09-15

Satellite motion included in gyro output disturbs the estimation of Allan variance coefficients of fiber optic gyro on board. Moreover, as a standard method for noise analysis of fiber optic gyro, Allan variance has too large offline computational effort and data storages to be applied to online estimation. In addition, with the development of deep space exploration, it is urged that satellite requires more autonomy including autonomous fault diagnosis and reconfiguration. To overcome the barriers and meet satellite autonomy, we present a new autonomous method for estimation of Allan variance coefficients including rate ramp, rate random walk, bias instability, angular random walk and quantization noise coefficients. In the method, we calculate differences between angle increments of star sensor and gyro to remove satellite motion from gyro output, and propose a state-space model using nonlinear adaptive filter technique for quantities previously measured from offline data techniques such as the Allan variance method. Simulations show the method correctly estimates Allan variance coefficients, R = 2.7965exp-4 {sup 0}/h{sup 2}, K = 1.1714exp-3 {sup 0}/h{sup 1.5}, B = 1.3185exp-3 {sup 0}/h, N = 5.982exp-4 {sup 0}/h{sup 0.5} and Q = 5.197exp-7 {sup 0} in real time, and tracks degradation of gyro performance from initail values, R = 0.651 {sup 0}/h{sup 2}, K = 0.801 {sup 0}/h{sup 1.5}, B = 0.385 {sup 0}/h, N = 0.0874 {sup 0}/h{sup 0.5} and Q = 8.085exp-5 {sup 0}, to final estimations, R = 9.548 {sup 0}/h{sup 2}, K = 9.524 {sup 0}/h{sup 1.5}, B = 2.234 {sup 0}/h, N = 0.5594 {sup 0}/h{sup 0.5} and Q = 5.113exp-4 {sup 0}, due to gamma radiation in space. The technique proposed here effectively isolates satellite motion, and requires no data storage and any supports from the ground.

A Bayesian random effects discrete-choice model for resource selection: Population-level selection inference

Science.gov (United States)

Thomas, D.L.; Johnson, D.; Griffith, B.

2006-01-01

Modeling the probability of use of land units characterized by discrete and continuous measures, we present a Bayesian random-effects model to assess resource selection. This model provides simultaneous estimation of both individual- and population-level selection. Deviance information criterion (DIC), a Bayesian alternative to AIC that is sample-size specific, is used for model selection. Aerial radiolocation data from 76 adult female caribou (Rangifer tarandus) and calf pairs during 1 year on an Arctic coastal plain calving ground were used to illustrate models and assess population-level selection of landscape attributes, as well as individual heterogeneity of selection. Landscape attributes included elevation, NDVI (a measure of forage greenness), and land cover-type classification. Results from the first of a 2-stage model-selection procedure indicated that there is substantial heterogeneity among cow-calf pairs with respect to selection of the landscape attributes. In the second stage, selection of models with heterogeneity included indicated that at the population-level, NDVI and land cover class were significant attributes for selection of different landscapes by pairs on the calving ground. Population-level selection coefficients indicate that the pairs generally select landscapes with higher levels of NDVI, but the relationship is quadratic. The highest rate of selection occurs at values of NDVI less than the maximum observed. Results for land cover-class selections coefficients indicate that wet sedge, moist sedge, herbaceous tussock tundra, and shrub tussock tundra are selected at approximately the same rate, while alpine and sparsely vegetated landscapes are selected at a lower rate. Furthermore, the variability in selection by individual caribou for moist sedge and sparsely vegetated landscapes is large relative to the variability in selection of other land cover types. The example analysis illustrates that, while sometimes computationally intense, a

93-106, 2015 93 Multilevel random effect and marginal models

African Journals Online (AJOL)

Multilevel random effect and marginal models for longitudinal data ... and random effect models that take the correlation among measurements of the same subject ... comparing the level of redness, pain and irritability ... clinical trial evaluating the safety profile of a new .... likelihood-based methods to compare models and.

Enhancement of heat transfer coefficient multi-metallic nanofluid with ANFIS modeling for thermophysical properties

Directory of Open Access Journals (Sweden)

Balla Hyder H.

2015-01-01

Full Text Available Cu and Zn-water nanofluid is a suspension of the Cu and Zn nanoparticles with the size 50 nm in the water base fluid for different volume fractions to enhance its Thermophysical properties. The determination and measuring the enhancement of Thermophysical properties depends on many limitations. Nanoparticles were suspended in a base fluid to prepare a nanofluid. A coated transient hot wire apparatus was calibrated after the building of the all systems. The vibro-viscometer was used to measure the dynamic viscosity. The measured dynamic viscosity and thermal conductivity with all parameters affected on the measurements such as base fluids thermal conductivity, volume factions, and the temperatures of the base fluid were used as input to the Artificial Neural Fuzzy inference system to modeling both dynamic viscosity and thermal conductivity of the nanofluids. Then, the ANFIS modeling equations were used to calculate the enhancement in heat transfer coefficient using CFD software. The heat transfer coefficient was determined for flowing flow in a circular pipe at constant heat flux. It was found that the thermal conductivity of the nanofluid was highly affected by the volume fraction of nanoparticles. A comparison of the thermal conductivity ratio for different volume fractions was undertaken. The heat transfer coefficient of nanofluid was found to be higher than its base fluid. Comparisons of convective heat transfer coefficients for Cu and Zn nanofluids with the other correlation for the nanofluids heat transfer enhancement are presented. Moreover, the flow demonstrates anomalous enhancement in heat transfer nanofluids.

Ising model of a randomly triangulated random surface as a definition of fermionic string theory

International Nuclear Information System (INIS)

Bershadsky, M.A.; Migdal, A.A.

1986-01-01

Fermionic degrees of freedom are added to randomly triangulated planar random surfaces. It is shown that the Ising model on a fixed graph is equivalent to a certain Majorana fermion theory on the dual graph. (orig.)

Effects of large rate coefficients for ion-polar neutral reactions on chemical models of dense interstellar clouds

International Nuclear Information System (INIS)

Herbst, E.; Leung, C.M.; Rensselaer Polytechnic Institute, Troy, NY)

1986-01-01

Pseudo-time-dependent models of the gas phase chemistry of dense interstellar clouds have been run with large rate coefficients for reactions between ions and polar neutral species, as advocated by Adams, Smith, and Clary. The higher rate coefficients normally lead to a reduction in both the peak and steady state abundances of polar neutrals, which can be as large as an order of magnitude but is more often smaller. Other differences between the results of these models and previous results are also discussed. 38 references

Negative power coefficient on PHWRs with CARA fuel

International Nuclear Information System (INIS)

Lestani, H.A.; González, H.J.; Florido, P.C.

2014-01-01

Highlights: • A PHWR fuel was optimized to obtain a negative power coefficient. • Fuel cost, being a measure of design investment efficiency, was optimized. • Influence on power coefficient of geometrical and economical parameters’ was studied. • Different neutronic absorbers were studied; pure absorbers can be used. • Thermal and economical models were developed to complement neutronic assessment. - Abstract: A study of power coefficient of reactivity in heavy water reactors is made analyzing the reactivity components of fuels with several modifications oriented at reducing the coefficient. A cell model is used for neutronics calculations; a non-linear two dimensional model is used to evaluate the thermal changes that follow a power change; and a levelized unit energy cost model is used to assess the economical feasibility of the design changes introduced to reduce power coefficient. The necessity of modelling all the aforementioned quantities in a coupled scheme is stressed, as a strong interdependence was found. A series of design changes complied with a negative power coefficient of reactivity, with a feasible power radial distribution and with low refuelling cost. Some investigation lines that exceed the fuel cell study and deal with the plant operation are marked as potentially addressing the stable operation of big heavy water reactors

Estimating a graphical intra-class correlation coefficient (GICC) using multivariate probit-linear mixed models.

Science.gov (United States)

Yue, Chen; Chen, Shaojie; Sair, Haris I; Airan, Raag; Caffo, Brian S

2015-09-01

Data reproducibility is a critical issue in all scientific experiments. In this manuscript, the problem of quantifying the reproducibility of graphical measurements is considered. The image intra-class correlation coefficient (I2C2) is generalized and the graphical intra-class correlation coefficient (GICC) is proposed for such purpose. The concept for GICC is based on multivariate probit-linear mixed effect models. A Markov Chain Monte Carlo EM (mcm-cEM) algorithm is used for estimating the GICC. Simulation results with varied settings are demonstrated and our method is applied to the KIRBY21 test-retest dataset.

Assessing the reliability of predictive activity coefficient models for molecules consisting of several functional groups

Directory of Open Access Journals (Sweden)

R. P. Gerber

2013-03-01

Full Text Available Currently, the most successful predictive models for activity coefficients are those based on functional groups such as UNIFAC. In contrast, these models require a large amount of experimental data for the determination of their parameter matrix. A more recent alternative is the models based on COSMO, for which only a small set of universal parameters must be calibrated. In this work, a recalibrated COSMO-SAC model was compared with the UNIFAC (Do model employing experimental infinite dilution activity coefficient data for 2236 non-hydrogen-bonding binary mixtures at different temperatures. As expected, UNIFAC (Do presented better overall performance, with a mean absolute error of 0.12 ln-units against 0.22 for our COSMO-SAC implementation. However, in cases involving molecules with several functional groups or when functional groups appear in an unusual way, the deviation for UNIFAC was 0.44 as opposed to 0.20 for COSMO-SAC. These results show that COSMO-SAC provides more reliable predictions for multi-functional or more complex molecules, reaffirming its future prospects.

Random matrices and random difference equations

International Nuclear Information System (INIS)

Uppuluri, V.R.R.

1975-01-01

Mathematical models leading to products of random matrices and random difference equations are discussed. A one-compartment model with random behavior is introduced, and it is shown how the average concentration in the discrete time model converges to the exponential function. This is of relevance to understanding how radioactivity gets trapped in bone structure in blood--bone systems. The ideas are then generalized to two-compartment models and mammillary systems, where products of random matrices appear in a natural way. The appearance of products of random matrices in applications in demography and control theory is considered. Then random sequences motivated from the following problems are studied: constant pulsing and random decay models, random pulsing and constant decay models, and random pulsing and random decay models

Efficient sampling of complex network with modified random walk strategies

Science.gov (United States)

Xie, Yunya; Chang, Shuhua; Zhang, Zhipeng; Zhang, Mi; Yang, Lei

2018-02-01

We present two novel random walk strategies, choosing seed node (CSN) random walk and no-retracing (NR) random walk. Different from the classical random walk sampling, the CSN and NR strategies focus on the influences of the seed node choice and path overlap, respectively. Three random walk samplings are applied in the Erdös-Rényi (ER), Barabási-Albert (BA), Watts-Strogatz (WS), and the weighted USAir networks, respectively. Then, the major properties of sampled subnets, such as sampling efficiency, degree distributions, average degree and average clustering coefficient, are studied. The similar conclusions can be reached with these three random walk strategies. Firstly, the networks with small scales and simple structures are conducive to the sampling. Secondly, the average degree and the average clustering coefficient of the sampled subnet tend to the corresponding values of original networks with limited steps. And thirdly, all the degree distributions of the subnets are slightly biased to the high degree side. However, the NR strategy performs better for the average clustering coefficient of the subnet. In the real weighted USAir networks, some obvious characters like the larger clustering coefficient and the fluctuation of degree distribution are reproduced well by these random walk strategies.

Dose coefficients in pediatric and adult abdominopelvic CT based on 100 patient models

Science.gov (United States)

Tian, Xiaoyu; Li, Xiang; Segars, W. Paul; Frush, Donald P.; Paulson, Erik K.; Samei, Ehsan

2013-12-01

Recent studies have shown the feasibility of estimating patient dose from a CT exam using CTDIvol-normalized-organ dose (denoted as h), DLP-normalized-effective dose (denoted as k), and DLP-normalized-risk index (denoted as q). However, previous studies were limited to a small number of phantom models. The purpose of this work was to provide dose coefficients (h, k, and q) across a large number of computational models covering a broad range of patient anatomy, age, size percentile, and gender. The study consisted of 100 patient computer models (age range, 0 to 78 y.o.; weight range, 2-180 kg) including 42 pediatric models (age range, 0 to 16 y.o.; weight range, 2-80 kg) and 58 adult models (age range, 18 to 78 y.o.; weight range, 57-180 kg). Multi-detector array CT scanners from two commercial manufacturers (LightSpeed VCT, GE Healthcare; SOMATOM Definition Flash, Siemens Healthcare) were included. A previously-validated Monte Carlo program was used to simulate organ dose for each patient model and each scanner, from which h, k, and q were derived. The relationships between h, k, and q and patient characteristics (size, age, and gender) were ascertained. The differences in conversion coefficients across the scanners were further characterized. CTDIvol-normalized-organ dose (h) showed an exponential decrease with increasing patient size. For organs within the image coverage, the average differences of h across scanners were less than 15%. That value increased to 29% for organs on the periphery or outside the image coverage, and to 8% for distributed organs, respectively. The DLP-normalized-effective dose (k) decreased exponentially with increasing patient size. For a given gender, the DLP-normalized-risk index (q) showed an exponential decrease with both increasing patient size and patient age. The average differences in k and q across scanners were 8% and 10%, respectively. This study demonstrated that the knowledge of patient information and CTDIvol/DLP values may

Dose coefficients in pediatric and adult abdominopelvic CT based on 100 patient models

International Nuclear Information System (INIS)

Tian, Xiaoyu; Samei, Ehsan; Li, Xiang; Segars, W Paul; Frush, Donald P; Paulson, Erik K

2013-01-01

Recent studies have shown the feasibility of estimating patient dose from a CT exam using CTDI vol -normalized-organ dose (denoted as h), DLP-normalized-effective dose (denoted as k), and DLP-normalized-risk index (denoted as q). However, previous studies were limited to a small number of phantom models. The purpose of this work was to provide dose coefficients (h, k, and q) across a large number of computational models covering a broad range of patient anatomy, age, size percentile, and gender. The study consisted of 100 patient computer models (age range, 0 to 78 y.o.; weight range, 2–180 kg) including 42 pediatric models (age range, 0 to 16 y.o.; weight range, 2–80 kg) and 58 adult models (age range, 18 to 78 y.o.; weight range, 57–180 kg). Multi-detector array CT scanners from two commercial manufacturers (LightSpeed VCT, GE Healthcare; SOMATOM Definition Flash, Siemens Healthcare) were included. A previously-validated Monte Carlo program was used to simulate organ dose for each patient model and each scanner, from which h, k, and q were derived. The relationships between h, k, and q and patient characteristics (size, age, and gender) were ascertained. The differences in conversion coefficients across the scanners were further characterized. CTDI vol -normalized-organ dose (h) showed an exponential decrease with increasing patient size. For organs within the image coverage, the average differences of h across scanners were less than 15%. That value increased to 29% for organs on the periphery or outside the image coverage, and to 8% for distributed organs, respectively. The DLP-normalized-effective dose (k) decreased exponentially with increasing patient size. For a given gender, the DLP-normalized-risk index (q) showed an exponential decrease with both increasing patient size and patient age. The average differences in k and q across scanners were 8% and 10%, respectively. This study demonstrated that the knowledge of patient information and CTDI vol

Criticality and entanglement in random quantum systems

International Nuclear Information System (INIS)

Refael, G; Moore, J E

2009-01-01

We review studies of entanglement entropy in systems with quenched randomness, concentrating on universal behavior at strongly random quantum critical points. The disorder-averaged entanglement entropy provides insight into the quantum criticality of these systems and an understanding of their relationship to non-random ('pure') quantum criticality. The entanglement near many such critical points in one dimension shows a logarithmic divergence in subsystem size, similar to that in the pure case but with a different universal coefficient. Such universal coefficients are examples of universal critical amplitudes in a random system. Possible measurements are reviewed along with the one-particle entanglement scaling at certain Anderson localization transitions. We also comment briefly on higher dimensions and challenges for the future.

Zero-inflated count models for longitudinal measurements with heterogeneous random effects.

Science.gov (United States)

Zhu, Huirong; Luo, Sheng; DeSantis, Stacia M

2017-08-01

Longitudinal zero-inflated count data arise frequently in substance use research when assessing the effects of behavioral and pharmacological interventions. Zero-inflated count models (e.g. zero-inflated Poisson or zero-inflated negative binomial) with random effects have been developed to analyze this type of data. In random effects zero-inflated count models, the random effects covariance matrix is typically assumed to be homogeneous (constant across subjects). However, in many situations this matrix may be heterogeneous (differ by measured covariates). In this paper, we extend zero-inflated count models to account for random effects heterogeneity by modeling their variance as a function of covariates. We show via simulation that ignoring intervention and covariate-specific heterogeneity can produce biased estimates of covariate and random effect estimates. Moreover, those biased estimates can be rectified by correctly modeling the random effects covariance structure. The methodological development is motivated by and applied to the Combined Pharmacotherapies and Behavioral Interventions for Alcohol Dependence (COMBINE) study, the largest clinical trial of alcohol dependence performed in United States with 1383 individuals.

The hard-core model on random graphs revisited

International Nuclear Information System (INIS)

Barbier, Jean; Krzakala, Florent; Zhang, Pan; Zdeborová, Lenka

2013-01-01

We revisit the classical hard-core model, also known as independent set and dual to vertex cover problem, where one puts particles with a first-neighbor hard-core repulsion on the vertices of a random graph. Although the case of random graphs with small and very large average degrees respectively are quite well understood, they yield qualitatively different results and our aim here is to reconciliate these two cases. We revisit results that can be obtained using the (heuristic) cavity method and show that it provides a closed-form conjecture for the exact density of the densest packing on random regular graphs with degree K ≥ 20, and that for K > 16 the nature of the phase transition is the same as for large K. This also shows that the hard-code model is the simplest mean-field lattice model for structural glasses and jamming

Application of Poisson random effect models for highway network screening.

Science.gov (United States)

Jiang, Ximiao; Abdel-Aty, Mohamed; Alamili, Samer

2014-02-01

In recent years, Bayesian random effect models that account for the temporal and spatial correlations of crash data became popular in traffic safety research. This study employs random effect Poisson Log-Normal models for crash risk hotspot identification. Both the temporal and spatial correlations of crash data were considered. Potential for Safety Improvement (PSI) were adopted as a measure of the crash risk. Using the fatal and injury crashes that occurred on urban 4-lane divided arterials from 2006 to 2009 in the Central Florida area, the random effect approaches were compared to the traditional Empirical Bayesian (EB) method and the conventional Bayesian Poisson Log-Normal model. A series of method examination tests were conducted to evaluate the performance of different approaches. These tests include the previously developed site consistence test, method consistence test, total rank difference test, and the modified total score test, as well as the newly proposed total safety performance measure difference test. Results show that the Bayesian Poisson model accounting for both temporal and spatial random effects (PTSRE) outperforms the model that with only temporal random effect, and both are superior to the conventional Poisson Log-Normal model (PLN) and the EB model in the fitting of crash data. Additionally, the method evaluation tests indicate that the PTSRE model is significantly superior to the PLN model and the EB model in consistently identifying hotspots during successive time periods. The results suggest that the PTSRE model is a superior alternative for road site crash risk hotspot identification. Copyright © 2013 Elsevier Ltd. All rights reserved.

Random matrix model for disordered conductors

Indian Academy of Sciences (India)

In the interpretation of transport properties of mesoscopic systems, the multichannel ... One defines the random matrix model with N eigenvalues 0. λТ ..... With heuristic arguments, using the ideas pertaining to Dyson Coulomb gas analogy,.

Analog model for quantum gravity effects: phonons in random fluids.

Science.gov (United States)

Krein, G; Menezes, G; Svaiter, N F

2010-09-24

We describe an analog model for quantum gravity effects in condensed matter physics. The situation discussed is that of phonons propagating in a fluid with a random velocity wave equation. We consider that there are random fluctuations in the reciprocal of the bulk modulus of the system and study free phonons in the presence of Gaussian colored noise with zero mean. We show that, in this model, after performing the random averages over the noise function a free conventional scalar quantum field theory describing free phonons becomes a self-interacting model.

Random Interchange of Magnetic Connectivity

Science.gov (United States)

Matthaeus, W. H.; Ruffolo, D. J.; Servidio, S.; Wan, M.; Rappazzo, A. F.

2015-12-01

Magnetic connectivity, the connection between two points along a magnetic field line, has a stochastic character associated with field lines random walking in space due to magnetic fluctuations, but connectivity can also change in time due to dynamical activity [1]. For fluctuations transverse to a strong mean field, this connectivity change be caused by stochastic interchange due to component reconnection. The process may be understood approximately by formulating a diffusion-like Fokker-Planck coefficient [2] that is asymptotically related to standard field line random walk. Quantitative estimates are provided, for transverse magnetic field models and anisotropic models such as reduced magnetohydrodynamics. In heliospheric applications, these estimates may be useful for understanding mixing between open and close field line regions near coronal hole boundaries, and large latitude excursions of connectivity associated with turbulence. [1] A. F. Rappazzo, W. H. Matthaeus, D. Ruffolo, S. Servidio & M. Velli, ApJL, 758, L14 (2012) [2] D. Ruffolo & W. Matthaeus, ApJ, 806, 233 (2015)

Detailed Analysis of Amplitude and Slope Diffraction Coefficients for knife-edge structure in S-UTD-CH Model

Directory of Open Access Journals (Sweden)

Eray Arik

2017-03-01

Full Text Available In urban, rural and indoor applications, diffraction mechanism is very important to predict the field strength and calculate the coverage accurately. The diffraction mechanism takes place on NLOS (non-line-of-sight cases like rooftop, vertex, corner, edge and sharp surfaces. S-UTD-CH model computes three type of electromagnetic wave incidence such as direct, reflected and diffracted waves, respectively. As obstacles in diffraction geometry are in the same or closer height, contribution of the diffraction mechanism is dominant. To predict the diffracted fields accurately, amplitude and slope diffraction coefficients and the derivative of these coefficients have to be taken correctly. In this paper, all the derivations about diffraction coefficients are made for knife edge type structures and extensive simulations are performed in order to analyze the amplitude and diffraction coefficients. In plane angle diffraction, contributions of amplitude and slope diffraction coefficient are maxima.

Comparison of four large-eddy simulation research codes and effects of model coefficient and inflow turbulence in actuator-line-based wind turbine modeling

DEFF Research Database (Denmark)

Martínez-Tossas, Luis A.; Churchfield, Matthew J.; Yilmaz, Ali Emre

2018-01-01

to match closely for all codes. The value of the Smagorinsky coefficient in the subgrid-scale turbulence model is shown to have a negligible effect on the time-averaged loads along the blades. Conversely, the breakdown location of the wake is strongly dependent on the Smagorinsky coefficient in uniform...... coefficient has a negligible effect on the wake profiles. It is concluded that for LES of wind turbines and wind farms using ALM, careful implementation and extensive cross-verification among codes can result in highly reproducible predictions. Moreover, the characteristics of the inflow turbulence appear...

Modeling random combustion of lycopodium particles and gas

Directory of Open Access Journals (Sweden)

M Bidabadi

2016-06-01

Full Text Available The random modeling combustion of lycopodium particles has been researched by many authors. In this paper, we extend this model and we also generate a different method by analyzing the effect of random distributed sources of combustible mixture. The flame structure is assumed to consist of a preheat-vaporization zone, a reaction zone and finally a post flame zone. We divide the preheat zone to different parts. We assumed that there is different distribution of particles in sections which are really random. Meanwhile, it is presumed that the fuel particles vaporize first to yield gaseous fuel. In other words, most of the fuel particles are vaporized at the end of the preheat zone. It is assumed that the Zel’dovich number is large; therefore, the reaction term in preheat zone is negligible. In this work, the effect of random distribution of particles in the preheat zone on combustion characteristics such as burning velocity, flame temperature for different particle radius is obtained.

Development of a model to calculate the overall heat transfer coefficient of greenhouse covers

Energy Technology Data Exchange (ETDEWEB)

Rasheed, A.; Lee, J. W.; Lee, H.L.

2017-07-01

A Building Energy Simulation (BES) model based on TRNSYS, was developed to investigate the overall heat transfer coefficient (U-value) of greenhouse covers including polyethylene (PE), polycarbonate (PC), polyvinyl chloride (PVC), and horticultural glass (HG). This was used to determine the influences of inside-to-outside temperature difference, wind speed, and night sky radiation on the U-values of these materials. The model was calibrated using published values of the inside and outside convective heat transfer coefficients. Validation of the model was demonstrated by the agreement between the computed and experimental results for a single-layer PE film. The results from the BES model showed significant changes in U-value in response to variations in weather parameters and the use of single or double layer greenhouse covers. It was found that the U-value of PC, PVC, and HG was 9%, 4%, and 15% lower, respectively, than that for PE. In addition, by using double glazing a 34% reduction in heat loss was noted. For the given temperature U-value increases as wind speed increases. The slopes at the temperature differences of 20, 30, 40, and 50 °C, were approximately 0.3, 0.5, 0.7, and 0.9, respectively. The results agree with those put forward by other researchers. Hence, the presented model is reliable and can play a valuable role in future work on greenhouse energy modelling.

First-principles calculations of impurity diffusion coefficients in dilute Mg alloys using the 8-frequency model

International Nuclear Information System (INIS)

Ganeshan, S.; Hector, L.G.; Liu, Z.-K.

2011-01-01

Research highlights: → Implemented the eight frequency model for impurity diffusion in hexagonal metals. → Model inputs were energetics/vibrational properties from first princples. → Predicted diffusion coefficients for Al, Ca, Zn and Sn impurity diffusion in Mg. → Successful prediction of partial correlation factors and jump frequencies. → Good agreement between calculated and experimental results. - Abstract: Diffusion in dilute Mg-X alloys, where X denotes Al, Zn, Sn and Ca impurities, was investigated with first-principles density functional theory in the local density approximation. Impurity diffusion coefficients were computed as a function of temperature using the 8-frequency model which provided the relevant impurity and solvent (Mg) jump frequencies and correlation factors. Minimum energy pathways for impurity diffusion and associated saddle point structures were computed with the climbing image nudged elastic band method. Vibrational properties were obtained with the supercell (direct) method for lattice dynamics. Calculated diffusion coefficients were compared with available experimental data. For diffusion between basal planes, we find D Mg-Ca > D Mg-Zn > D Mg-Sn > D Mg-Al, where D is the diffusion coefficient. For diffusion within a basal plane, the same trend holds except that D Mg-Zn overlaps with D Mg-Al at high temperatures and D Mg-Sn at low temperatures. These trends were explored with charge density contours in selected planes of each Mg-X alloy, the variation of the activation energy for diffusion with the atomic radius of each impurity and the electronic density of states. The theoretical methodology developed herein can be applied to impurity diffusion in other hexagonal materials.

A generalized model via random walks for information filtering

Energy Technology Data Exchange (ETDEWEB)

Ren, Zhuo-Ming, E-mail: zhuomingren@gmail.com [Department of Physics, University of Fribourg, Chemin du Musée 3, CH-1700, Fribourg (Switzerland); Chongqing Institute of Green and Intelligent Technology, Chinese Academy of Sciences, ChongQing, 400714 (China); Kong, Yixiu [Department of Physics, University of Fribourg, Chemin du Musée 3, CH-1700, Fribourg (Switzerland); Shang, Ming-Sheng, E-mail: msshang@cigit.ac.cn [Chongqing Institute of Green and Intelligent Technology, Chinese Academy of Sciences, ChongQing, 400714 (China); Zhang, Yi-Cheng [Department of Physics, University of Fribourg, Chemin du Musée 3, CH-1700, Fribourg (Switzerland)

2016-08-06

There could exist a simple general mechanism lurking beneath collaborative filtering and interdisciplinary physics approaches which have been successfully applied to online E-commerce platforms. Motivated by this idea, we propose a generalized model employing the dynamics of the random walk in the bipartite networks. Taking into account the degree information, the proposed generalized model could deduce the collaborative filtering, interdisciplinary physics approaches and even the enormous expansion of them. Furthermore, we analyze the generalized model with single and hybrid of degree information on the process of random walk in bipartite networks, and propose a possible strategy by using the hybrid degree information for different popular objects to toward promising precision of the recommendation. - Highlights: • We propose a generalized recommendation model employing the random walk dynamics. • The proposed model with single and hybrid of degree information is analyzed. • A strategy with the hybrid degree information improves precision of recommendation.

A generalized model via random walks for information filtering

International Nuclear Information System (INIS)

Ren, Zhuo-Ming; Kong, Yixiu; Shang, Ming-Sheng; Zhang, Yi-Cheng

2016-01-01

There could exist a simple general mechanism lurking beneath collaborative filtering and interdisciplinary physics approaches which have been successfully applied to online E-commerce platforms. Motivated by this idea, we propose a generalized model employing the dynamics of the random walk in the bipartite networks. Taking into account the degree information, the proposed generalized model could deduce the collaborative filtering, interdisciplinary physics approaches and even the enormous expansion of them. Furthermore, we analyze the generalized model with single and hybrid of degree information on the process of random walk in bipartite networks, and propose a possible strategy by using the hybrid degree information for different popular objects to toward promising precision of the recommendation. - Highlights: • We propose a generalized recommendation model employing the random walk dynamics. • The proposed model with single and hybrid of degree information is analyzed. • A strategy with the hybrid degree information improves precision of recommendation.

Asymptotic properties of Pearson's rank-variate correlation coefficient under contaminated Gaussian model.

Science.gov (United States)

Ma, Rubao; Xu, Weichao; Zhang, Yun; Ye, Zhongfu

2014-01-01

This paper investigates the robustness properties of Pearson's rank-variate correlation coefficient (PRVCC) in scenarios where one channel is corrupted by impulsive noise and the other is impulsive noise-free. As shown in our previous work, these scenarios that frequently encountered in radar and/or sonar, can be well emulated by a particular bivariate contaminated Gaussian model (CGM). Under this CGM, we establish the asymptotic closed forms of the expectation and variance of PRVCC by means of the well known Delta method. To gain a deeper understanding, we also compare PRVCC with two other classical correlation coefficients, i.e., Spearman's rho (SR) and Kendall's tau (KT), in terms of the root mean squared error (RMSE). Monte Carlo simulations not only verify our theoretical findings, but also reveal the advantage of PRVCC by an example of estimating the time delay in the particular impulsive noise environment.

Modeling and data analysis of the NASA-WSTF frictional heating apparatus - Effects of test parameters on friction coefficient

Science.gov (United States)

Zhu, Sheng-Hu; Stoltzfus, Joel M.; Benz, Frank J.; Yuen, Walter W.

1988-01-01

A theoretical model is being developed jointly by the NASA White Sands Test Facility (WSTF) and the University of California at Santa Barbara (UCSB) to analyze data generated from the WSTF frictional heating test facility. Analyses of the data generated in the first seconds of the frictional heating test are shown to be effective in determining the friction coefficient between the rubbing interfaces. Different friction coefficients for carobn steel and Monel K-500 are observed. The initial condition of the surface is shown to affect only the initial value of the friction coefficient but to have no significant influence on the average steady-state friction coefficient. Rotational speed and the formation of oxide film on the rotating surfaces are shown to have a significant effect on the friction coefficient.

A random energy model for size dependence : recurrence vs. transience

NARCIS (Netherlands)

Külske, Christof

1998-01-01

We investigate the size dependence of disordered spin models having an infinite number of Gibbs measures in the framework of a simplified 'random energy model for size dependence'. We introduce two versions (involving either independent random walks or branching processes), that can be seen as

A kinetic model for chemical reactions without barriers: transport coefficients and eigenmodes

International Nuclear Information System (INIS)

Alves, Giselle M; Kremer, Gilberto M; Marques, Wilson Jr; Soares, Ana Jacinta

2011-01-01

The kinetic model of the Boltzmann equation proposed in the work of Kremer and Soares 2009 for a binary mixture undergoing chemical reactions of symmetric type which occur without activation energy is revisited here, with the aim of investigating in detail the transport properties of the reactive mixture and the influence of the reaction process on the transport coefficients. Accordingly, the non-equilibrium solutions of the Boltzmann equations are determined through an expansion in Sonine polynomials up to the first order, using the Chapman–Enskog method, in a chemical regime for which the reaction process is close to its final equilibrium state. The non-equilibrium deviations are explicitly calculated for what concerns the thermal–diffusion ratio and coefficients of shear viscosity, diffusion and thermal conductivity. The theoretical and formal analysis developed in the present paper is complemented with some numerical simulations performed for different concentrations of reactants and products of the reaction as well as for both exothermic and endothermic chemical processes. The results reveal that chemical reactions without energy barrier can induce an appreciable influence on the transport properties of the mixture. Oppositely to the case of reactions with activation energy, the coefficients of shear viscosity and thermal conductivity become larger than those of an inert mixture when the reactions are exothermic. An application of the non-barrier model and its detailed transport picture are included in this paper, in order to investigate the dynamics of the local perturbations on the constituent number densities, and velocity and temperature of the whole mixture, induced by spontaneous internal fluctuations. It is shown that for the longitudinal disturbances there exist two hydrodynamic sound modes, one purely diffusive hydrodynamic mode and one kinetic mode

A kinetic model for chemical reactions without barriers: transport coefficients and eigenmodes

Science.gov (United States)

Alves, Giselle M.; Kremer, Gilberto M.; Marques, Wilson, Jr.; Jacinta Soares, Ana

2011-03-01

The kinetic model of the Boltzmann equation proposed in the work of Kremer and Soares 2009 for a binary mixture undergoing chemical reactions of symmetric type which occur without activation energy is revisited here, with the aim of investigating in detail the transport properties of the reactive mixture and the influence of the reaction process on the transport coefficients. Accordingly, the non-equilibrium solutions of the Boltzmann equations are determined through an expansion in Sonine polynomials up to the first order, using the Chapman-Enskog method, in a chemical regime for which the reaction process is close to its final equilibrium state. The non-equilibrium deviations are explicitly calculated for what concerns the thermal-diffusion ratio and coefficients of shear viscosity, diffusion and thermal conductivity. The theoretical and formal analysis developed in the present paper is complemented with some numerical simulations performed for different concentrations of reactants and products of the reaction as well as for both exothermic and endothermic chemical processes. The results reveal that chemical reactions without energy barrier can induce an appreciable influence on the transport properties of the mixture. Oppositely to the case of reactions with activation energy, the coefficients of shear viscosity and thermal conductivity become larger than those of an inert mixture when the reactions are exothermic. An application of the non-barrier model and its detailed transport picture are included in this paper, in order to investigate the dynamics of the local perturbations on the constituent number densities, and velocity and temperature of the whole mixture, induced by spontaneous internal fluctuations. It is shown that for the longitudinal disturbances there exist two hydrodynamic sound modes, one purely diffusive hydrodynamic mode and one kinetic mode.

Inter-annual and spatial variability of Hamon potential evapotranspiration model coefficients

Science.gov (United States)

McCabe, Gregory J.; Hay, Lauren E.; Bock, Andy; Markstrom, Steven L.; Atkinson, R. Dwight

2015-01-01

Monthly calibrated values of the Hamon PET coefficient (C) are determined for 109,951 hydrologic response units (HRUs) across the conterminous United States (U.S.). The calibrated coefficient values are determined by matching calculated mean monthly Hamon PET to mean monthly free-water surface evaporation. For most locations and months the calibrated coefficients are larger than the standard value reported by Hamon. The largest changes in the coefficients were for the late winter/early spring and fall months, whereas the smallest changes were for the summer months. Comparisons of PET computed using the standard value of C and computed using calibrated values of C indicate that for most of the conterminous U.S. PET is underestimated using the standard Hamon PET coefficient, except for the southeastern U.S.

Uncertainties in Cancer Risk Coefficients for Environmental Exposure to Radionuclides. An Uncertainty Analysis for Risk Coefficients Reported in Federal Guidance Report No. 13

Energy Technology Data Exchange (ETDEWEB)

Pawel, David [U.S. Environmental Protection Agency; Leggett, Richard Wayne [ORNL; Eckerman, Keith F [ORNL; Nelson, Christopher [U.S. Environmental Protection Agency

2007-01-01

Federal Guidance Report No. 13 (FGR 13) provides risk coefficients for estimation of the risk of cancer due to low-level exposure to each of more than 800 radionuclides. Uncertainties in risk coefficients were quantified in FGR 13 for 33 cases (exposure to each of 11 radionuclides by each of three exposure pathways) on the basis of sensitivity analyses in which various combinations of plausible biokinetic, dosimetric, and radiation risk models were used to generate alternative risk coefficients. The present report updates the uncertainty analysis in FGR 13 for the cases of inhalation and ingestion of radionuclides and expands the analysis to all radionuclides addressed in that report. The analysis indicates that most risk coefficients for inhalation or ingestion of radionuclides are determined within a factor of 5 or less by current information. That is, application of alternate plausible biokinetic and dosimetric models and radiation risk models (based on the linear, no-threshold hypothesis with an adjustment for the dose and dose rate effectiveness factor) is unlikely to change these coefficients by more than a factor of 5. In this analysis the assessed uncertainty in the radiation risk model was found to be the main determinant of the uncertainty category for most risk coefficients, but conclusions concerning the relative contributions of risk and dose models to the total uncertainty in a risk coefficient may depend strongly on the method of assessing uncertainties in the risk model.

Estimating temperature reactivity coefficients by experimental procedures combined with isothermal temperature coefficient measurements and dynamic identification

International Nuclear Information System (INIS)

Tsuji, Masashi; Aoki, Yukinori; Shimazu, Yoichiro; Yamasaki, Masatoshi; Hanayama, Yasushi

2006-01-01

A method to evaluate the moderator coefficient (MTC) and the Doppler coefficient through experimental procedures performed during reactor physics tests of PWR power plants is proposed. This method combines isothermal temperature coefficient (ITC) measurement experiments and reactor power transient experiments at low power conditions for dynamic identification. In the dynamic identification, either one of temperature coefficients can be determined in such a way that frequency response characteristics of the reactivity change observed by a digital reactivity meter is reproduced from measured data of neutron count rate and the average coolant temperature. The other unknown coefficient can also be determined by subtracting the coefficient obtained from the dynamic identification from ITC. As the proposed method can directly estimate the Doppler coefficient, the applicability of the conventional core design codes to predict the Doppler coefficient can be verified for new types of fuels such as mixed oxide fuels. The digital simulation study was carried out to show the feasibility of the proposed method. The numerical analysis showed that the MTC and the Doppler coefficient can be estimated accurately and even if there are uncertainties in the parameters of the reactor kinetics model, the accuracies of the estimated values are not seriously impaired. (author)

LIMB-DARKENING COEFFICIENTS FOR ECLIPSING WHITE DWARFS

Energy Technology Data Exchange (ETDEWEB)

Gianninas, A.; Strickland, B. D.; Kilic, Mukremin [Homer L. Dodge Department of Physics and Astronomy, University of Oklahoma, 440 W. Brooks St., Norman, OK 73019 (United States); Bergeron, P., E-mail: alexg@nhn.ou.edu, E-mail: benstrickland@ou.edu, E-mail: kilic@ou.edu, E-mail: bergeron@astro.umontreal.ca [Departement de Physique, Universite de Montreal, C.P. 6128, Succ. Centre-Ville, Montreal, Quebec H3C 3J7 (Canada)

2013-03-20

We present extensive calculations of linear and nonlinear limb-darkening coefficients as well as complete intensity profiles appropriate for modeling the light-curves of eclipsing white dwarfs. We compute limb-darkening coefficients in the Johnson-Kron-Cousins UBVRI photometric system as well as the Large Synoptic Survey Telescope (LSST) ugrizy system using the most up to date model atmospheres available. In all, we provide the coefficients for seven different limb-darkening laws. We describe the variations of these coefficients as a function of the atmospheric parameters, including the effects of convection at low effective temperatures. Finally, we discuss the importance of having readily available limb-darkening coefficients in the context of present and future photometric surveys like the LSST, Palomar Transient Factory, and the Panoramic Survey Telescope and Rapid Response System (Pan-STARRS). The LSST, for example, may find {approx}10{sup 5} eclipsing white dwarfs. The limb-darkening calculations presented here will be an essential part of the detailed analysis of all of these systems.

LIMB-DARKENING COEFFICIENTS FOR ECLIPSING WHITE DWARFS

International Nuclear Information System (INIS)

Gianninas, A.; Strickland, B. D.; Kilic, Mukremin; Bergeron, P.

2013-01-01

We present extensive calculations of linear and nonlinear limb-darkening coefficients as well as complete intensity profiles appropriate for modeling the light-curves of eclipsing white dwarfs. We compute limb-darkening coefficients in the Johnson-Kron-Cousins UBVRI photometric system as well as the Large Synoptic Survey Telescope (LSST) ugrizy system using the most up to date model atmospheres available. In all, we provide the coefficients for seven different limb-darkening laws. We describe the variations of these coefficients as a function of the atmospheric parameters, including the effects of convection at low effective temperatures. Finally, we discuss the importance of having readily available limb-darkening coefficients in the context of present and future photometric surveys like the LSST, Palomar Transient Factory, and the Panoramic Survey Telescope and Rapid Response System (Pan-STARRS). The LSST, for example, may find ∼10 5 eclipsing white dwarfs. The limb-darkening calculations presented here will be an essential part of the detailed analysis of all of these systems.

Heat and mass transfer coefficients and modeling of infrared drying of banana slices

Directory of Open Access Journals (Sweden)

Fernanda Machado Baptestini

Full Text Available ABSTRACT Banana is one of the most consumed fruits in the world, having a large part of its production performed in tropical countries. This product possesses a wide range of vitamins and minerals, being an important component of the alimentation worldwide. However, the shelf life of bananas is short, thus requiring procedures to prevent the quality loss and increase the shelf life. One of these procedures widely used is drying. This work aimed to study the infrared drying process of banana slices (cv. Prata and determine the heat and mass transfer coefficients of this process. In addition, effective diffusion coefficient and relationship between ripening stages of banana and drying were obtained. Banana slices at four different ripening stages were dried using a dryer with infrared heating source with four different temperatures (65, 75, 85, and 95 ºC. Midilli model was the one that best represented infrared drying of banana slices. Heat and mass transfer coefficients varied, respectively, between 46.84 and 70.54 W m-2 K-1 and 0.040 to 0.0632 m s-1 for temperature range, at the different ripening stages. Effective diffusion coefficient ranged from 1.96 to 3.59 × 10-15 m² s-1. Activation energy encountered were 16.392, 29.531, 23.194, and 25.206 kJ mol-1 for 2nd, 3rd, 5th, and 7th ripening stages, respectively. Ripening stages did not affect the infrared drying of bananas.

LiDAR based prediction of forest biomass using hierarchical models with spatially varying coefficients

Science.gov (United States)

Babcock, Chad; Finley, Andrew O.; Bradford, John B.; Kolka, Randall K.; Birdsey, Richard A.; Ryan, Michael G.

2015-01-01

Many studies and production inventory systems have shown the utility of coupling covariates derived from Light Detection and Ranging (LiDAR) data with forest variables measured on georeferenced inventory plots through regression models. The objective of this study was to propose and assess the use of a Bayesian hierarchical modeling framework that accommodates both residual spatial dependence and non-stationarity of model covariates through the introduction of spatial random effects. We explored this objective using four forest inventory datasets that are part of the North American Carbon Program, each comprising point-referenced measures of above-ground forest biomass and discrete LiDAR. For each dataset, we considered at least five regression model specifications of varying complexity. Models were assessed based on goodness of fit criteria and predictive performance using a 10-fold cross-validation procedure. Results showed that the addition of spatial random effects to the regression model intercept improved fit and predictive performance in the presence of substantial residual spatial dependence. Additionally, in some cases, allowing either some or all regression slope parameters to vary spatially, via the addition of spatial random effects, further improved model fit and predictive performance. In other instances, models showed improved fit but decreased predictive performance—indicating over-fitting and underscoring the need for cross-validation to assess predictive ability. The proposed Bayesian modeling framework provided access to pixel-level posterior predictive distributions that were useful for uncertainty mapping, diagnosing spatial extrapolation issues, revealing missing model covariates, and discovering locally significant parameters.

A methodology for the parametric modelling of the flow coefficients and flow rate in hydraulic valves

International Nuclear Information System (INIS)

Valdés, José R.; Rodríguez, José M.; Saumell, Javier; Pütz, Thomas

2014-01-01

Highlights: • We develop a methodology for the parametric modelling of flow in hydraulic valves. • We characterize the flow coefficients with a generic function with two parameters. • The parameters are derived from CFD simulations of the generic geometry. • We apply the methodology to two cases from the automotive brake industry. • We validate by comparing with CFD results varying the original dimensions. - Abstract: The main objective of this work is to develop a methodology for the parametric modelling of the flow rate in hydraulic valve systems. This methodology is based on the derivation, from CFD simulations, of the flow coefficient of the critical restrictions as a function of the Reynolds number, using a generalized square root function with two parameters. The methodology is then demonstrated by applying it to two completely different hydraulic systems: a brake master cylinder and an ABS valve. This type of parametric valve models facilitates their implementation in dynamic simulation models of complex hydraulic systems

THE DETERMINATION OF BETA COEFFICIENTS OF PUBLICLY-HELD COMPANIES BY A REGRESSION MODEL AND AN APPLICATION ON PRIVATE FIRMS

Directory of Open Access Journals (Sweden)

METİN KAMİL ERCAN

2013-06-01

Full Text Available It is possible to determine the value of private companies by means of suggestions and assumptions derived from their financial statements. However, there comes out a serious problem in the determination of equity costs of these private companies using Capital Assets Pricing Model (CAPM as beta coefficients are unknown or unavailable. In this study, firstly, a regression model that represents the relationship between the beta coefficients and financial statements’ Variables of publicly-held companies will be developed. Then, this model will be tested and applied on private companies.

Signal intensity of normal breast tissue at MR mammography on midfield: Applying a random coefficient model evaluating the effect of doubling the contrast dose

Energy Technology Data Exchange (ETDEWEB)

Marklund, Mette [Parker Institute: Imaging Unit, Frederiksberg Hospital (Denmark)], E-mail: mm@frh.regionh.dk; Christensen, Robin [Parker Institute: Musculoskeletal Statistics Unit, Frederiksberg Hospital (Denmark)], E-mail: robin.christensen@frh.regionh.dk; Torp-Pedersen, Soren [Parker Institute: Imaging Unit, Frederiksberg Hospital (Denmark)], E-mail: stp@frh.regionh.dk; Thomsen, Carsten [Department of Radiology, Rigshospitalet, University of Copenhagen (Denmark)], E-mail: carsten.thomsen@rh.regionh.dk; Nolsoe, Christian P. [Department of Radiology, Koge Hospital (Denmark)], E-mail: cnolsoe@dadlnet.dk

2009-01-15

Purpose: To prospectively investigate the effect on signal intensity (SI) of healthy breast parenchyma on magnetic resonance mammography (MRM) when doubling the contrast dose from 0.1 to 0.2 mmol/kg bodyweight. Materials and methods: Informed consent and institutional review board approval were obtained. Twenty-five healthy female volunteers (median age: 24 years (range: 21-37 years) and median bodyweight: 65 kg (51-80 kg)) completed two dynamic MRM examinations on a 0.6 T open scanner. The inter-examination time was 24 h (23.5-25 h). The following sequences were applied: axial T2W TSE and an axial dynamic T1W FFED, with a total of seven frames. At day 1, an i.v. gadolinium (Gd) bolus injection of 0.1 mmol/kg bodyweight (Omniscan) (low) was administered. On day 2, the contrast dose was increased to 0.2 mmol/kg (high). Injection rate was 2 mL/s (day 1) and 4 mL/s (day 2). Any use of estrogen containing oral contraceptives (ECOC) was recorded. Post-processing with automated subtraction, manually traced ROI (region of interest) and recording of the SI was performed. A random coefficient model was applied. Results: We found an SI increase of 24.2% and 40% following the low and high dose, respectively (P < 0.0001); corresponding to a 65% (95% CI: 37-99%) SI increase, indicating a moderate saturation. Although not statistically significant (P = 0.06), the results indicated a tendency, towards lower maximal SI in the breast parenchyma of ECOC users compared to non-ECOC users. Conclusion: We conclude that the contrast dose can be increased from 0.1 to 0.2 mmol/kg bodyweight, if a better contrast/noise relation is desired but increasing the contrast dose above 0.2 mmol/kg bodyweight is not likely to improve the enhancement substantially due to the moderate saturation observed. Further research is needed to determine the impact of ECOC on the relative enhancement ratio, and further studies are needed to determine if a possible use of ECOC should be considered a compromising

Signal intensity of normal breast tissue at MR mammography on midfield: Applying a random coefficient model evaluating the effect of doubling the contrast dose

International Nuclear Information System (INIS)

Marklund, Mette; Christensen, Robin; Torp-Pedersen, Soren; Thomsen, Carsten; Nolsoe, Christian P.

2009-01-01

Purpose: To prospectively investigate the effect on signal intensity (SI) of healthy breast parenchyma on magnetic resonance mammography (MRM) when doubling the contrast dose from 0.1 to 0.2 mmol/kg bodyweight. Materials and methods: Informed consent and institutional review board approval were obtained. Twenty-five healthy female volunteers (median age: 24 years (range: 21-37 years) and median bodyweight: 65 kg (51-80 kg)) completed two dynamic MRM examinations on a 0.6 T open scanner. The inter-examination time was 24 h (23.5-25 h). The following sequences were applied: axial T2W TSE and an axial dynamic T1W FFED, with a total of seven frames. At day 1, an i.v. gadolinium (Gd) bolus injection of 0.1 mmol/kg bodyweight (Omniscan) (low) was administered. On day 2, the contrast dose was increased to 0.2 mmol/kg (high). Injection rate was 2 mL/s (day 1) and 4 mL/s (day 2). Any use of estrogen containing oral contraceptives (ECOC) was recorded. Post-processing with automated subtraction, manually traced ROI (region of interest) and recording of the SI was performed. A random coefficient model was applied. Results: We found an SI increase of 24.2% and 40% following the low and high dose, respectively (P < 0.0001); corresponding to a 65% (95% CI: 37-99%) SI increase, indicating a moderate saturation. Although not statistically significant (P = 0.06), the results indicated a tendency, towards lower maximal SI in the breast parenchyma of ECOC users compared to non-ECOC users. Conclusion: We conclude that the contrast dose can be increased from 0.1 to 0.2 mmol/kg bodyweight, if a better contrast/noise relation is desired but increasing the contrast dose above 0.2 mmol/kg bodyweight is not likely to improve the enhancement substantially due to the moderate saturation observed. Further research is needed to determine the impact of ECOC on the relative enhancement ratio, and further studies are needed to determine if a possible use of ECOC should be considered a compromising

A study on improvement of analytical prediction model for spacer grid pressure loss coefficients

International Nuclear Information System (INIS)

Lim, Jonh Seon

2002-02-01

Nuclear fuel assemblies used in the nuclear power plants consist of the nuclear fuel rods, the control rod guide tubes, an instrument guide tube, spacer grids,a bottom nozzle, a top nozzle. The spacer grid is the most important component of the fuel assembly components for thermal hydraulic and mechanical design and analyses. The spacer grids fixed with the guide tubes support the fuel rods and have the very important role to activate thermal energy transfer by the coolant mixing caused to the turbulent flow and crossflow in the subchannels. In this paper, the analytical spacer grid pressure loss prediction model has been studied and improved by considering the test section wall to spacer grid gap pressure loss independently and applying the appropriate friction drag coefficient to predict pressure loss more accurately at the low Reynolds number region. The improved analytical model has been verified based on the hydraulic pressure drop test results for the spacer grids of three types with 5x5, 16x16, 17x17 arrays, respectively. The pressure loss coefficients predicted by the improved analytical model are coincident with those test results within ±12%. This result shows that the improved analytical model can be used for research and design change of the nuclear fuel assembly

Effects of random noise in a dynamical model of love

Energy Technology Data Exchange (ETDEWEB)

Xu Yong, E-mail: hsux3@nwpu.edu.cn [Department of Applied Mathematics, Northwestern Polytechnical University, Xi' an 710072 (China); Gu Rencai; Zhang Huiqing [Department of Applied Mathematics, Northwestern Polytechnical University, Xi' an 710072 (China)

2011-07-15

Highlights: > We model the complexity and unpredictability of psychology as Gaussian white noise. > The stochastic system of love is considered including bifurcation and chaos. > We show that noise can both suppress and induce chaos in dynamical models of love. - Abstract: This paper aims to investigate the stochastic model of love and the effects of random noise. We first revisit the deterministic model of love and some basic properties are presented such as: symmetry, dissipation, fixed points (equilibrium), chaotic behaviors and chaotic attractors. Then we construct a stochastic love-triangle model with parametric random excitation due to the complexity and unpredictability of the psychological system, where the randomness is modeled as the standard Gaussian noise. Stochastic dynamics under different three cases of 'Romeo's romantic style', are examined and two kinds of bifurcations versus the noise intensity parameter are observed by the criteria of changes of top Lyapunov exponent and shape of stationary probability density function (PDF) respectively. The phase portraits and time history are carried out to verify the proposed results, and the good agreement can be found. And also the dual roles of the random noise, namely suppressing and inducing chaos are revealed.

Effects of random noise in a dynamical model of love

International Nuclear Information System (INIS)

Xu Yong; Gu Rencai; Zhang Huiqing

2011-01-01

Highlights: → We model the complexity and unpredictability of psychology as Gaussian white noise. → The stochastic system of love is considered including bifurcation and chaos. → We show that noise can both suppress and induce chaos in dynamical models of love. - Abstract: This paper aims to investigate the stochastic model of love and the effects of random noise. We first revisit the deterministic model of love and some basic properties are presented such as: symmetry, dissipation, fixed points (equilibrium), chaotic behaviors and chaotic attractors. Then we construct a stochastic love-triangle model with parametric random excitation due to the complexity and unpredictability of the psychological system, where the randomness is modeled as the standard Gaussian noise. Stochastic dynamics under different three cases of 'Romeo's romantic style', are examined and two kinds of bifurcations versus the noise intensity parameter are observed by the criteria of changes of top Lyapunov exponent and shape of stationary probability density function (PDF) respectively. The phase portraits and time history are carried out to verify the proposed results, and the good agreement can be found. And also the dual roles of the random noise, namely suppressing and inducing chaos are revealed.

Integrable properties of a variable-coefficient Korteweg-de Vries model from Bose-Einstein condensates and fluid dynamics

International Nuclear Information System (INIS)

Zhang Chunyi; Gao Yitian; Meng Xianghua; Li Juan; Xu Tao; Wei Guangmei; Zhu Hongwu

2006-01-01

The phenomena of the trapped Bose-Einstein condensates related to matter waves and nonlinear atom optics can be governed by a variable-coefficient Korteweg-de Vries (vc-KdV) model with additional terms contributed from the inhomogeneity in the axial direction and the strong transverse confinement of the condensate, and such a model can also be used to describe the water waves propagating in a channel with an uneven bottom and/or deformed walls. In this paper, with the help of symbolic computation, the bilinear form for the vc-KdV model is obtained and some exact solitonic solutions including the N-solitonic solution in explicit form are derived through the extended Hirota method. We also derive the auto-Baecklund transformation, nonlinear superposition formula, Lax pairs and conservation laws of this model. Finally, the integrability of the variable-coefficient model and the characteristic of the nonlinear superposition formula are discussed

Extensive Investigations on Bio-Inspired Trust and Reputation Model over Hops Coefficient Factor in Distributed Wireless Sensor Networks

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Vinod Kumar Verma

2014-08-01

Full Text Available Resource utilization requires a substantial consideration for a trust and reputation model to be deployed within a wireless sensor network (WSN. In the evaluation, our attention is focused on the effect of hops coefficient factor estimation on WSN with bio-inspired trust and reputation model (BTRM. We present the state-of-the-art system level evaluation of accuracy and path length of sensor node operations for their current and average scenarios. Additionally, we emphasized over the energy consumption evaluation for static, dynamic and oscillatory modes of BTRM-WSN model. The performance of the hops coefficient factor for our proposed framework is evaluated via analytic bounds and numerical simulations.

Using Random Forest Models to Predict Organizational Violence

Science.gov (United States)

Levine, Burton; Bobashev, Georgly

2012-01-01

We present a methodology to access the proclivity of an organization to commit violence against nongovernment personnel. We fitted a Random Forest model using the Minority at Risk Organizational Behavior (MAROS) dataset. The MAROS data is longitudinal; so, individual observations are not independent. We propose a modification to the standard Random Forest methodology to account for the violation of the independence assumption. We present the results of the model fit, an example of predicting violence for an organization; and finally, we present a summary of the forest in a "meta-tree,"

Alternative model of random surfaces

International Nuclear Information System (INIS)

Ambartzumian, R.V.; Sukiasian, G.S.; Savvidy, G.K.; Savvidy, K.G.

1992-01-01

We analyse models of triangulated random surfaces and demand that geometrically nearby configurations of these surfaces must have close actions. The inclusion of this principle drives us to suggest a new action, which is a modified Steiner functional. General arguments, based on the Minkowski inequality, shows that the maximal distribution to the partition function comes from surfaces close to the sphere. (orig.)

Random incidence absorption coefficients of porous absorbers based on local and extended reaction models

DEFF Research Database (Denmark)

Jeong, Cheol-Ho

2011-01-01

resistivity and the absorber thickness on the difference between the two surface reaction models are examined and discussed. For a porous absorber backed by a rigid surface, the local reaction models give errors of less than 10% if the thickness exceeds 120 mm for a flow resistivity of 5000 Nm-4s. As the flow...... incidence acoustical characteristics of typical building elements made of porous materials assuming extended and local reaction. For each surface reaction, five well-established wave propagation models, the Delany-Bazley, Miki, Beranek, Allard-Champoux, and Biot model, are employed. Effects of the flow...... resistivity doubles, a decrease in the required thickness by 25 mm is observed to achieve the same amount of error. For an absorber backed by an air gap, the thickness ratio between the material and air cavity is important. If the absorber thickness is approximately 40% of the cavity depth, the local reaction...

Predicting cyclohexane/water distribution coefficients for the SAMPL5 challenge using MOSCED and the SMD solvation model

Science.gov (United States)

Diaz-Rodriguez, Sebastian; Bozada, Samantha M.; Phifer, Jeremy R.; Paluch, Andrew S.

2016-11-01

We present blind predictions using the solubility parameter based method MOSCED submitted for the SAMPL5 challenge on calculating cyclohexane/water distribution coefficients at 298 K. Reference data to parameterize MOSCED was generated with knowledge only of chemical structure by performing solvation free energy calculations using electronic structure calculations in the SMD continuum solvent. To maintain simplicity and use only a single method, we approximate the distribution coefficient with the partition coefficient of the neutral species. Over the final SAMPL5 set of 53 compounds, we achieved an average unsigned error of 2.2± 0.2 log units (ranking 15 out of 62 entries), the correlation coefficient ( R) was 0.6± 0.1 (ranking 35), and 72± 6 % of the predictions had the correct sign (ranking 30). While used here to predict cyclohexane/water distribution coefficients at 298 K, MOSCED is broadly applicable, allowing one to predict temperature dependent infinite dilution activity coefficients in any solvent for which parameters exist, and provides a means by which an excess Gibbs free energy model may be parameterized to predict composition dependent phase-equilibrium.

Monte Carlo based diffusion coefficients for LMFBR analysis

International Nuclear Information System (INIS)

Van Rooijen, Willem F.G.; Takeda, Toshikazu; Hazama, Taira

2010-01-01

A method based on Monte Carlo calculations is developed to estimate the diffusion coefficient of unit cells. The method uses a geometrical model similar to that used in lattice theory, but does not use the assumption of a separable fundamental mode used in lattice theory. The method uses standard Monte Carlo flux and current tallies, and the continuous energy Monte Carlo code MVP was used without modifications. Four models are presented to derive the diffusion coefficient from tally results of flux and partial currents. In this paper the method is applied to the calculation of a plate cell of the fast-spectrum critical facility ZEBRA. Conventional calculations of the diffusion coefficient diverge in the presence of planar voids in the lattice, but our Monte Carlo method can treat this situation without any problem. The Monte Carlo method was used to investigate the influence of geometrical modeling as well as the directional dependence of the diffusion coefficient. The method can be used to estimate the diffusion coefficient of complicated unit cells, the limitation being the capabilities of the Monte Carlo code. The method will be used in the future to confirm results for the diffusion coefficient obtained of the Monte Carlo code. The method will be used in the future to confirm results for the diffusion coefficient obtained with deterministic codes. (author)

To be and not to be: scale correlations in random multifractal processes

DEFF Research Database (Denmark)

Cleve, Jochen; Schmiegel, Jürgen; Greiner, Martin

We discuss various properties of a random multifractal process, which are related to the issue of scale correlations. By design, the process is homogeneous, non-conservative and has no built-in scale correlations. However, when it comes to observables like breakdown coefficients, which are based...... on a coarse-graining of the multifractal field, scale correlations do appear. In the log-normal limit of the model process, the conditional distributions and moments of breakdown coefficients reproduce the observations made in fully developed small-scale turbulence. These findings help to understand several...

Premium Pricing of Liability Insurance Using Random Sum Model

Directory of Open Access Journals (Sweden)

Mujiati Dwi Kartikasari

2017-03-01

Full Text Available Premium pricing is one of important activities in insurance. Nonlife insurance premium is calculated from expected value of historical data claims. The historical data claims are collected so that it forms a sum of independent random number which is called random sum. In premium pricing using random sum, claim frequency distribution and claim severity distribution are combined. The combination of these distributions is called compound distribution. By using liability claim insurance data, we analyze premium pricing using random sum model based on compound distribution

High-order dynamic modeling and parameter identification of structural discontinuities in Timoshenko beams by using reflection coefficients

Science.gov (United States)

Fan, Qiang; Huang, Zhenyu; Zhang, Bing; Chen, Dayue

2013-02-01

Properties of discontinuities, such as bolt joints and cracks in the waveguide structures, are difficult to evaluate by either analytical or numerical methods due to the complexity and uncertainty of the discontinuities. In this paper, the discontinuity in a Timoshenko beam is modeled with high-order parameters and then these parameters are identified by using reflection coefficients at the discontinuity. The high-order model is composed of several one-order sub-models in series and each sub-model consists of inertia, stiffness and damping components in parallel. The order of the discontinuity model is determined based on the characteristics of the reflection coefficient curve and the accuracy requirement of the dynamic modeling. The model parameters are identified through the least-square fitting iteration method, of which the undetermined model parameters are updated in iteration to fit the dynamic reflection coefficient curve with the wave-based one. By using the spectral super-element method (SSEM), simulation cases, including one-order discontinuities on infinite- and finite-beams and a two-order discontinuity on an infinite beam, were employed to evaluate both the accuracy of the discontinuity model and the effectiveness of the identification method. For practical considerations, effects of measurement noise on the discontinuity parameter identification are investigated by adding different levels of noise to the simulated data. The simulation results were then validated by the corresponding experiments. Both the simulation and experimental results show that (1) the one-order discontinuities can be identified accurately with the maximum errors of 6.8% and 8.7%, respectively; (2) and the high-order discontinuities can be identified with the maximum errors of 15.8% and 16.2%, respectively; and (3) the high-order model can predict the complex discontinuity much more accurately than the one-order discontinuity model.

Random matrix approach to plasmon resonances in the random impedance network model of disordered nanocomposites

Science.gov (United States)

Olekhno, N. A.; Beltukov, Y. M.

2018-05-01

Random impedance networks are widely used as a model to describe plasmon resonances in disordered metal-dielectric and other two-component nanocomposites. In the present work, the spectral properties of resonances in random networks are studied within the framework of the random matrix theory. We have shown that the appropriate ensemble of random matrices for the considered problem is the Jacobi ensemble (the MANOVA ensemble). The obtained analytical expressions for the density of states in such resonant networks show a good agreement with the results of numerical simulations in a wide range of metal filling fractions 0

Defining Dogma: Quantifying Crystalloid Hemodilution in a Prospective Randomized Control Trial with Blood Donation as a Model for Hemorrhage.

Science.gov (United States)

Ross, Samuel Wade; Christmas, A Britton; Fischer, Peter E; Holway, Haley; Seymour, Rachel; Huntington, Ciara R; Heniford, B Todd; Sing, Ronald F

2018-06-04

The concept of hemodilution after blood loss and crystalloid infusion is a surgical maxim that remains unproven in humans. We sought to quantify the effect of hemodilution after crystalloid administration in voluntary blood donors as a model for acute hemorrhage. A prospective, randomized control trial was conducted in conjunction with community blood drives. Donors were randomized to receive no IV fluid(noIVF), two liters normal saline(NS), or two liters lactated ringers(LR) after blood donation. Blood samples were taken before donation of 500 mL of blood, immediately after donation, and following IV fluid administration. Hemoglobin(Hgb) was measured at each time point. Hgb between time points were compared between groups using standard statistical tests and the Bonferroni correction for multiple comparisons. Statistical significance was set at p≤0.0167. Of 165 patients consented, 157 patients completed the study. Average pre-donation Hgb was 14.3 g/dL. There was no difference in the mean Hgb levels after blood donation between the three groups(p>0.05). Compared to the control group, there was a significant drop in Hgb in the crystalloid infused groups from the post-donation level to post-resuscitation(13.2 vs 12.1 vs 12.2 g/dL, pdonation Hgb - hemorrhage Hgb drop - equilibration hemoglobin drop - resuscitation Hgb drop)=MeanPre-donation Hgb - [(EBL/TBV)*l] - [(EBL/TBV)*h] - [(VR/TBV)*r], l = 5.111g/dL = blood loss coefficient, h=6.722 g/dL=equilibration coefficient, r= 2.617g/dL= resuscitation coefficient. This study proves the concept of hemodilution and derived a mathematical relationship between blood loss and resuscitation. This data may help to estimate response of hemoglobin levels to blood loss and fluid resuscitation in clinical practice. Copyright © 2018. Published by Elsevier Inc.

Criticality coefficient calculation for a small PWR using Monte Carlo Transport Code

Energy Technology Data Exchange (ETDEWEB)

Trombetta, Debora M.; Su, Jian, E-mail: dtrombetta@nuclear.ufrj.br, E-mail: sujian@nuclear.ufrj.br [Coordenacao dos Programas de Pos-Graduacao em Engenharia (COPPE/UFRJ), Rio de Janeiro, RJ (Brazil); Chirayath, Sunil S., E-mail: sunilsc@tamu.edu [Department of Nuclear Engineering and Nuclear Security Science and Policy Institute, Texas A and M University, TX (United States)

2015-07-01

Computational models of reactors are increasingly used to predict nuclear reactor physics parameters responsible for reactivity changes which could lead to accidents and losses. In this work, preliminary results for criticality coefficient calculation using the Monte Carlo transport code MCNPX were presented for a small PWR. The computational modeling developed consists of the core with fuel elements, radial reflectors, and control rods inside a pressure vessel. Three different geometries were simulated, a single fuel pin, a fuel assembly and the core, with the aim to compare the criticality coefficients among themselves.The criticality coefficients calculated were: Doppler Temperature Coefficient, Coolant Temperature Coefficient, Coolant Void Coefficient, Power Coefficient, and Control Rod Worth. The coefficient values calculated by the MCNP code were compared with literature results, showing good agreement with reference data, which validate the computational model developed and allow it to be used to perform more complex studies. Criticality Coefficient values for the three simulations done had little discrepancy for almost all coefficients investigated, the only exception was the Power Coefficient. Preliminary results presented show that simple modelling as a fuel assembly can describe changes at almost all the criticality coefficients, avoiding the need of a complex core simulation. (author)

Incorporation of velocity-dependent restitution coefficient and particle surface friction into kinetic theory for modeling granular flow cooling.

Science.gov (United States)

Duan, Yifei; Feng, Zhi-Gang

2017-12-01

Kinetic theory (KT) has been successfully used to model rapid granular flows in which particle interactions are frictionless and near elastic. However, it fails when particle interactions become frictional and inelastic. For example, the KT is not able to accurately predict the free cooling process of a vibrated granular medium that consists of inelastic frictional particles under microgravity. The main reason that the classical KT fails to model these flows is due to its inability to account for the particle surface friction and its inelastic behavior, which are the two most important factors that need be considered in modeling collisional granular flows. In this study, we have modified the KT model that is able to incorporate these two factors. The inelasticity of a particle is considered by establishing a velocity-dependent expression for the restitution coefficient based on many experimental studies found in the literature, and the particle friction effect is included by using a tangential restitution coefficient that is related to the particle friction coefficient. Theoretical predictions of the free cooling process by the classical KT and the improved KT are compared with the experimental results from a study conducted on an airplane undergoing parabolic flights without the influence of gravity [Y. Grasselli, G. Bossis, and G. Goutallier, Europhys. Lett. 86, 60007 (2009)10.1209/0295-5075/86/60007]. Our results show that both the velocity-dependent restitution coefficient and the particle surface friction are important in predicting the free cooling process of granular flows; the modified KT model that integrates these two factors is able to improve the simulation results and leads to better agreement with the experimental results.

The Analytical Objective Hysteresis Model (AnOHM v1.0: methodology to determine bulk storage heat flux coefficients

Directory of Open Access Journals (Sweden)

T. Sun

2017-07-01

Full Text Available The net storage heat flux (ΔQS is important in the urban surface energy balance (SEB but its determination remains a significant challenge. The hysteresis pattern of the diurnal relation between the ΔQS and net all-wave radiation (Q∗ has been captured in the Objective Hysteresis Model (OHM parameterization of ΔQS. Although successfully used in urban areas, the limited availability of coefficients for OHM hampers its application. To facilitate use, and enhance physical interpretations of the OHM coefficients, an analytical solution of the one-dimensional advection–diffusion equation of coupled heat and liquid water transport in conjunction with the SEB is conducted, allowing development of AnOHM (Analytical Objective Hysteresis Model. A sensitivity test of AnOHM to surface properties and hydrometeorological forcing is presented using a stochastic approach (subset simulation. The sensitivity test suggests that the albedo, Bowen ratio and bulk transfer coefficient, solar radiation and wind speed are most critical. AnOHM, driven by local meteorological conditions at five sites with different land use, is shown to simulate the ΔQS flux well (RMSE values of ∼ 30 W m−2. The intra-annual dynamics of OHM coefficients are explored. AnOHM offers significant potential to enhance modelling of the surface energy balance over a wider range of conditions and land covers.

Probability based calibration of pressure coefficients

DEFF Research Database (Denmark)

Hansen, Svend Ole; Pedersen, Marie Louise; Sørensen, John Dalsgaard

2015-01-01

Normally, a consistent basis for calculating partial factors focuses on a homogeneous reliability index neither depending on which material the structure is constructed of nor the ratio between the permanent and variable actions acting on the structure. Furthermore, the reliability index should n...... the characteristic shape coefficients are based on mean values as specified in background documents to the Eurocodes. Importance of hidden safeties judging the reliability is discussed for wind actions on low-rise structures....... not depend on the type of variable action. A probability based calibration of pressure coefficients have been carried out using pressure measurements on the standard CAARC building modelled on scale of 1:383. The extreme pressures measured on the CAARC building model in the wind tunnel have been fitted.......3, the Eurocode partial factor of 1.5 for variable actions agrees well with the inherent uncertainties of wind actions when the pressure coefficients are determined using wind tunnel test results. The increased bias and uncertainty when pressure coefficients mainly are based on structural codes lead to a larger...

Implications of NGA for NEHRP site coefficients

Science.gov (United States)

Borcherdt, Roger D.

2012-01-01

Three proposals are provided to update tables 11.4-1 and 11.4-2 of Minimum Design Loads for Buildings and Other Structures (7-10), by the American Society of Civil Engineers (2010) (ASCE/SEI 7-10), with site coefficients implied directly by NGA (Next Generation Attenuation) ground motion prediction equations (GMPEs). Proposals include a recommendation to use straight-line interpolation to infer site coefficients at intermediate values of ̅vs (average shear velocity). Site coefficients are recommended to ensure consistency with ASCE/SEI 7-10 MCER (Maximum Considered Earthquake) seismic-design maps and simplified site-specific design spectra procedures requiring site classes with associated tabulated site coefficients and a reference site class with unity site coefficients. Recommended site coefficients are confirmed by independent observations of average site amplification coefficients inferred with respect to an average ground condition consistent with that used for the MCER maps. The NGA coefficients recommended for consideration are implied directly by the NGA GMPEs and do not require introduction of additional models.

Recent developments in exponential random graph (p*) models for social networks

NARCIS (Netherlands)

Robins, Garry; Snijders, Tom; Wang, Peng; Handcock, Mark; Pattison, Philippa

This article reviews new specifications for exponential random graph models proposed by Snijders et al. [Snijders, T.A.B., Pattison, P., Robins, G.L., Handcock, M., 2006. New specifications for exponential random graph models. Sociological Methodology] and demonstrates their improvement over

Multiobjective Two-Stage Stochastic Programming Problems with Interval Discrete Random Variables

Directory of Open Access Journals (Sweden)

S. K. Barik

2012-01-01

Full Text Available Most of the real-life decision-making problems have more than one conflicting and incommensurable objective functions. In this paper, we present a multiobjective two-stage stochastic linear programming problem considering some parameters of the linear constraints as interval type discrete random variables with known probability distribution. Randomness of the discrete intervals are considered for the model parameters. Further, the concepts of best optimum and worst optimum solution are analyzed in two-stage stochastic programming. To solve the stated problem, first we remove the randomness of the problem and formulate an equivalent deterministic linear programming model with multiobjective interval coefficients. Then the deterministic multiobjective model is solved using weighting method, where we apply the solution procedure of interval linear programming technique. We obtain the upper and lower bound of the objective function as the best and the worst value, respectively. It highlights the possible risk involved in the decision-making tool. A numerical example is presented to demonstrate the proposed solution procedure.

GRACE gravity field modeling with an investigation on correlation between nuisance parameters and gravity field coefficients

Science.gov (United States)

Zhao, Qile; Guo, Jing; Hu, Zhigang; Shi, Chuang; Liu, Jingnan; Cai, Hua; Liu, Xianglin

2011-05-01

The GRACE (Gravity Recovery And Climate Experiment) monthly gravity models have been independently produced and published by several research institutions, such as Center for Space Research (CSR), GeoForschungsZentrum (GFZ), Jet Propulsion Laboratory (JPL), Centre National d’Etudes Spatiales (CNES) and Delft Institute of Earth Observation and Space Systems (DEOS). According to their processing standards, above institutions use the traditional variational approach except that the DEOS exploits the acceleration approach. The background force models employed are rather similar. The produced gravity field models generally agree with one another in the spatial pattern. However, there are some discrepancies in the gravity signal amplitude between solutions produced by different institutions. In particular, 10%-30% signal amplitude differences in some river basins can be observed. In this paper, we implemented a variant of the traditional variational approach and computed two sets of monthly gravity field solutions using the data from January 2005 to December 2006. The input data are K-band range-rates (KBRR) and kinematic orbits of GRACE satellites. The main difference in the production of our two types of models is how to deal with nuisance parameters. This type of parameters is necessary to absorb low-frequency errors in the data, which are mainly the aliasing and instrument errors. One way is to remove the nuisance parameters before estimating the geopotential coefficients, called NPARB approach in the paper. The other way is to estimate the nuisance parameters and geopotential coefficients simultaneously, called NPESS approach. These two types of solutions mainly differ in geopotential coefficients from degree 2 to 5. This can be explained by the fact that the nuisance parameters and the gravity field coefficients are highly correlated, particularly at low degrees. We compare these solutions with the official and published ones by means of spectral analysis. It is

SDSS-II: Determination of shape and color parameter coefficients for SALT-II fit model

Energy Technology Data Exchange (ETDEWEB)

Dojcsak, L.; Marriner, J.; /Fermilab

2010-08-01

In this study we look at the SALT-II model of Type IA supernova analysis, which determines the distance moduli based on the known absolute standard candle magnitude of the Type IA supernovae. We take a look at the determination of the shape and color parameter coefficients, {alpha} and {beta} respectively, in the SALT-II model with the intrinsic error that is determined from the data. Using the SNANA software package provided for the analysis of Type IA supernovae, we use a standard Monte Carlo simulation to generate data with known parameters to use as a tool for analyzing the trends in the model based on certain assumptions about the intrinsic error. In order to find the best standard candle model, we try to minimize the residuals on the Hubble diagram by calculating the correct shape and color parameter coefficients. We can estimate the magnitude of the intrinsic errors required to obtain results with {chi}{sup 2}/degree of freedom = 1. We can use the simulation to estimate the amount of color smearing as indicated by the data for our model. We find that the color smearing model works as a general estimate of the color smearing, and that we are able to use the RMS distribution in the variables as one method of estimating the correct intrinsic errors needed by the data to obtain the correct results for {alpha} and {beta}. We then apply the resultant intrinsic error matrix to the real data and show our results.

Entanglement dynamics in random media

Science.gov (United States)

Menezes, G.; Svaiter, N. F.; Zarro, C. A. D.

2017-12-01

We study how the entanglement dynamics between two-level atoms is impacted by random fluctuations of the light cone. In our model the two-atom system is envisaged as an open system coupled with an electromagnetic field in the vacuum state. We employ the quantum master equation in the Born-Markov approximation in order to describe the completely positive time evolution of the atomic system. We restrict our investigations to the situation in which the atoms are coupled individually to two spatially separated cavities, one of which displays the emergence of light-cone fluctuations. In such a disordered cavity, we assume that the coefficients of the Klein-Gordon equation are random functions of the spatial coordinates. The disordered medium is modeled by a centered, stationary, and Gaussian process. We demonstrate that disorder has the effect of slowing down the entanglement decay. We conjecture that in a strong-disorder environment the mean life of entangled states can be enhanced in such a way as to almost completely suppress quantum nonlocal decoherence.

Breakdown coefficients and scaling properties of rain fields

Directory of Open Access Journals (Sweden)

D. Harris

1998-01-01

Full Text Available The theory of scale similarity and breakdown coefficients is applied here to intermittent rainfall data consisting of time series and spatial rain fields. The probability distributions (pdf of the logarithm of the breakdown coefficients are the principal descriptor used. Rain fields are distinguished as being either multiscaling or multiaffine depending on whether the pdfs of breakdown coefficients are scale similar or scale dependent, respectively. Parameter  estimation techniques are developed which are applicable to both multiscaling and multiaffine fields. The scale parameter (width, σ, of the pdfs of the log-breakdown coefficients is a measure of the intermittency of a field. For multiaffine fields, this scale parameter is found to increase with scale in a power-law fashion consistent with a bounded-cascade picture of rainfall modelling. The resulting power-law exponent, H, is indicative of the smoothness of the field. Some details of breakdown coefficient analysis are addressed and a theoretical link between this analysis and moment scaling analysis is also presented. Breakdown coefficient properties of cascades are also investigated in the context of parameter estimation for modelling purposes.

Simultaneous Description of Activity Coefficients and Solubility with eCPA

DEFF Research Database (Denmark)

Schlaikjer, Anders; Thomsen, Kaj; Kontogeorgis, Georgios

2017-01-01

with salt specific parameters. The focus is on accurate description of the salt solubility, and low deviation correlations are obtained for all salts investigated. The inclusion of the solubility data in the parametrization has, compared to parameters only parametrized to osmotic coefficients and activity...... coefficients, not significantly affected the deviations of the osmotic coefficients and activity coefficients. The average deviations of the activity coefficient does increase slightly and it was found that the increase in deviations was almost entirely due to reduced accuracy at high temperature and high...... molality. The model is, furthermore, compared to the activity coefficient model, Extended UNIQUAC. It is shown that the eCPA provides more accurate solubility description at higher temperatures than Extended UNIQUAC but also that Extended UNIQUAC is slightly better at describing the activity coefficients...

Disorder Identification in Hysteresis Data: Recognition Analysis of the Random-Bond-Random-Field Ising Model

International Nuclear Information System (INIS)

Ovchinnikov, O. S.; Jesse, S.; Kalinin, S. V.; Bintacchit, P.; Trolier-McKinstry, S.

2009-01-01

An approach for the direct identification of disorder type and strength in physical systems based on recognition analysis of hysteresis loop shape is developed. A large number of theoretical examples uniformly distributed in the parameter space of the system is generated and is decorrelated using principal component analysis (PCA). The PCA components are used to train a feed-forward neural network using the model parameters as targets. The trained network is used to analyze hysteresis loops for the investigated system. The approach is demonstrated using a 2D random-bond-random-field Ising model, and polarization switching in polycrystalline ferroelectric capacitors.

A random walk model for evaluating clinical trials involving serial observations.

Science.gov (United States)

Hopper, J L; Young, G P

1988-05-01

For clinical trials where the variable of interest is ordered and categorical (for example, disease severity, symptom scale), and where measurements are taken at intervals, it might be possible to achieve a greater discrimination between the efficacy of treatments by modelling each patient's progress as a stochastic process. The random walk is a simple, easily interpreted model that can be fitted by maximum likelihood using a maximization routine with inference based on standard likelihood theory. In general the model can allow for randomly censored data, incorporates measured prognostic factors, and inference is conditional on the (possibly non-random) allocation of patients. Tests of fit and of model assumptions are proposed, and application to two therapeutic trials of gastroenterological disorders are presented. The model gave measures of the rate of, and variability in, improvement for patients under different treatments. A small simulation study suggested that the model is more powerful than considering the difference between initial and final scores, even when applied to data generated by a mechanism other than the random walk model assumed in the analysis. It thus provides a useful additional statistical method for evaluating clinical trials.

Time-varying coefficient vector autoregressions model based on dynamic correlation with an application to crude oil and stock markets

International Nuclear Information System (INIS)

Lu, Fengbin; Qiao, Han; Wang, Shouyang; Lai, Kin Keung; Li, Yuze

2017-01-01

This paper proposes a new time-varying coefficient vector autoregressions (VAR) model, in which the coefficient is a linear function of dynamic lagged correlation. The proposed model allows for flexibility in choices of dynamic correlation models (e.g. dynamic conditional correlation generalized autoregressive conditional heteroskedasticity (GARCH) models, Markov-switching GARCH models and multivariate stochastic volatility models), which indicates that it can describe many types of time-varying causal effects. Time-varying causal relations between West Texas Intermediate (WTI) crude oil and the US Standard and Poor’s 500 (S&P 500) stock markets are examined by the proposed model. The empirical results show that their causal relations evolve with time and display complex characters. Both positive and negative causal effects of the WTI on the S&P 500 in the subperiods have been found and confirmed by the traditional VAR models. Similar results have been obtained in the causal effects of S&P 500 on WTI. In addition, the proposed model outperforms the traditional VAR model.

Time-varying coefficient vector autoregressions model based on dynamic correlation with an application to crude oil and stock markets

Energy Technology Data Exchange (ETDEWEB)

Lu, Fengbin, E-mail: fblu@amss.ac.cn [Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing 100190 (China); Qiao, Han, E-mail: qiaohan@ucas.ac.cn [School of Economics and Management, University of Chinese Academy of Sciences, Beijing 100190 (China); Wang, Shouyang, E-mail: sywang@amss.ac.cn [School of Economics and Management, University of Chinese Academy of Sciences, Beijing 100190 (China); Lai, Kin Keung, E-mail: mskklai@cityu.edu.hk [Department of Management Sciences, City University of Hong Kong (Hong Kong); Li, Yuze, E-mail: richardyz.li@mail.utoronto.ca [Department of Industrial Engineering, University of Toronto (Canada)

2017-01-15

This paper proposes a new time-varying coefficient vector autoregressions (VAR) model, in which the coefficient is a linear function of dynamic lagged correlation. The proposed model allows for flexibility in choices of dynamic correlation models (e.g. dynamic conditional correlation generalized autoregressive conditional heteroskedasticity (GARCH) models, Markov-switching GARCH models and multivariate stochastic volatility models), which indicates that it can describe many types of time-varying causal effects. Time-varying causal relations between West Texas Intermediate (WTI) crude oil and the US Standard and Poor’s 500 (S&P 500) stock markets are examined by the proposed model. The empirical results show that their causal relations evolve with time and display complex characters. Both positive and negative causal effects of the WTI on the S&P 500 in the subperiods have been found and confirmed by the traditional VAR models. Similar results have been obtained in the causal effects of S&P 500 on WTI. In addition, the proposed model outperforms the traditional VAR model.

Smooth random change point models.

Science.gov (United States)

van den Hout, Ardo; Muniz-Terrera, Graciela; Matthews, Fiona E

2011-03-15

Change point models are used to describe processes over time that show a change in direction. An example of such a process is cognitive ability, where a decline a few years before death is sometimes observed. A broken-stick model consists of two linear parts and a breakpoint where the two lines intersect. Alternatively, models can be formulated that imply a smooth change between the two linear parts. Change point models can be extended by adding random effects to account for variability between subjects. A new smooth change point model is introduced and examples are presented that show how change point models can be estimated using functions in R for mixed-effects models. The Bayesian inference using WinBUGS is also discussed. The methods are illustrated using data from a population-based longitudinal study of ageing, the Cambridge City over 75 Cohort Study. The aim is to identify how many years before death individuals experience a change in the rate of decline of their cognitive ability. Copyright © 2010 John Wiley & Sons, Ltd.

CONSISTENCY UNDER SAMPLING OF EXPONENTIAL RANDOM GRAPH MODELS.

Science.gov (United States)

Shalizi, Cosma Rohilla; Rinaldo, Alessandro

2013-04-01

The growing availability of network data and of scientific interest in distributed systems has led to the rapid development of statistical models of network structure. Typically, however, these are models for the entire network, while the data consists only of a sampled sub-network. Parameters for the whole network, which is what is of interest, are estimated by applying the model to the sub-network. This assumes that the model is consistent under sampling , or, in terms of the theory of stochastic processes, that it defines a projective family. Focusing on the popular class of exponential random graph models (ERGMs), we show that this apparently trivial condition is in fact violated by many popular and scientifically appealing models, and that satisfying it drastically limits ERGM's expressive power. These results are actually special cases of more general results about exponential families of dependent random variables, which we also prove. Using such results, we offer easily checked conditions for the consistency of maximum likelihood estimation in ERGMs, and discuss some possible constructive responses.

Money creation process in a random redistribution model

Science.gov (United States)

Chen, Siyan; Wang, Yougui; Li, Keqiang; Wu, Jinshan

2014-01-01

In this paper, the dynamical process of money creation in a random exchange model with debt is investigated. The money creation kinetics are analyzed by both the money-transfer matrix method and the diffusion method. From both approaches, we attain the same conclusion: the source of money creation in the case of random exchange is the agents with neither money nor debt. These analytical results are demonstrated by computer simulations.

Exact solutions to a nonlinear dispersive model with variable coefficients

International Nuclear Information System (INIS)

Yin Jun; Lai Shaoyong; Qing Yin

2009-01-01

A mathematical technique based on an auxiliary differential equation and the symbolic computation system Maple is employed to investigate a prototypical and nonlinear K(n, n) equation with variable coefficients. The exact solutions to the equation are constructed analytically under various circumstances. It is shown that the variable coefficients and the exponent appearing in the equation determine the quantitative change in the physical structures of the solutions.

Prediction of Partition Coefficients of Organic Compounds for SPME/PDMS

Directory of Open Access Journals (Sweden)

Liao Hsuan-Yu

2016-01-01

Full Text Available The partition coefficients of 51 organic compounds between SPME/PDMS and gas were compiled from the literature sources in this study. The effect of physicochemical properties and descriptors on the partitioning process of partition coefficients was explicated by the correlation analysis. The PDMS-gas partition coefficients were well correlated to the molecular weight of organic compounds (r = 0.832, p < 0.05. An empirical model, consisting of the molecular weight and the polarizability, was developed to appropriately predict the partition coefficients of organic compounds. The empirical model for estimating the PDMS-gas partition coefficient will contribute to the practical applications of the SPME technique.

Random walk of passive tracers among randomly moving obstacles.

Science.gov (United States)

Gori, Matteo; Donato, Irene; Floriani, Elena; Nardecchia, Ilaria; Pettini, Marco

2016-04-14

This study is mainly motivated by the need of understanding how the diffusion behavior of a biomolecule (or even of a larger object) is affected by other moving macromolecules, organelles, and so on, inside a living cell, whence the possibility of understanding whether or not a randomly walking biomolecule is also subject to a long-range force field driving it to its target. By means of the Continuous Time Random Walk (CTRW) technique the topic of random walk in random environment is here considered in the case of a passively diffusing particle among randomly moving and interacting obstacles. The relevant physical quantity which is worked out is the diffusion coefficient of the passive tracer which is computed as a function of the average inter-obstacles distance. The results reported here suggest that if a biomolecule, let us call it a test molecule, moves towards its target in the presence of other independently interacting molecules, its motion can be considerably slowed down.

Diagnosing cysts with correlation coefficient images from 2-dimensional freehand elastography.

Science.gov (United States)

Booi, Rebecca C; Carson, Paul L; O'Donnell, Matthew; Richards, Michael S; Rubin, Jonathan M

2007-09-01

We compared the diagnostic potential of using correlation coefficient images versus elastograms from 2-dimensional (2D) freehand elastography to characterize breast cysts. In this preliminary study, which was approved by the Institutional Review Board and compliant with the Health Insurance Portability and Accountability Act, we imaged 4 consecutive human subjects (4 cysts, 1 biopsy-verified benign breast parenchyma) with freehand 2D elastography. Data were processed offline with conventional 2D phase-sensitive speckle-tracking algorithms. The correlation coefficient in the cyst and surrounding tissue was calculated, and appearances of the cysts in the correlation coefficient images and elastograms were compared. The correlation coefficient in the cysts was considerably lower (14%-37%) than in the surrounding tissue because of the lack of sufficient speckle in the cysts, as well as the prominence of random noise, reverberations, and clutter, which decorrelated quickly. Thus, the cysts were visible in all correlation coefficient images. In contrast, the elastograms associated with these cysts each had different elastographic patterns. The solid mass in this study did not have the same high decorrelation rate as the cysts, having a correlation coefficient only 2.1% lower than that of surrounding tissue. Correlation coefficient images may produce a more direct, reliable, and consistent method for characterizing cysts than elastograms.

Modeling of the substrate and product transfer coefficients for ethanol fermentation

International Nuclear Information System (INIS)

Zerajic, S.; Grbavcic, Z.; Savkovic-Stevanovic, J.

2008-01-01

The transfer phenomena of the substrate and product for ethanol fermentation with immobilized biocatalyst were investigated. Fermentation was carried out with a biocatalyst consisting of Ca-alginate gel in the form of two-layer spherical beads in anaerobic conditions. The determination of kinetic parameters was achieved by fitting bioreaction progress curves to the experimental data. The calculation of the diffusion coefficients was performed by numerical methods for experimental conditions. Finally, the glucose and ethanol transfer coefficients are defined and determined, using the effective diffusion coefficients. (Abstract Copyright [2008], Wiley Periodicals, Inc.)

Stochastic equilibria of an asset pricing model with heterogeneous beliefs and random dividends

NARCIS (Netherlands)

Zhu, M.; Wang, D.; Guo, M.

2011-01-01

We investigate dynamical properties of a heterogeneous agent model with random dividends and further study the relationship between dynamical properties of the random model and those of the corresponding deterministic skeleton, which is obtained by setting the random dividends as their constant mean

Ergodicity for the Randomly Forced 2D Navier-Stokes Equations

International Nuclear Information System (INIS)

Kuksin, Sergei; Shirikyan, Armen

2001-01-01

We study space-periodic 2D Navier-Stokes equations perturbed by an unbounded random kick-force. It is assumed that Fourier coefficients of the kicks are independent random variables all of whose moments are bounded and that the distributions of the first N 0 coefficients (where N 0 is a sufficiently large integer) have positive densities against the Lebesgue measure. We treat the equation as a random dynamical system in the space of square integrable divergence-free vector fields. We prove that this dynamical system has a unique stationary measure and study its ergodic properties

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

Science.gov (United States)

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

Cluster structure in the correlation coefficient matrix can be characterized by abnormal eigenvalues

Science.gov (United States)

Nie, Chun-Xiao

2018-02-01

In a large number of previous studies, the researchers found that some of the eigenvalues of the financial correlation matrix were greater than the predicted values of the random matrix theory (RMT). Here, we call these eigenvalues as abnormal eigenvalues. In order to reveal the hidden meaning of these abnormal eigenvalues, we study the toy model with cluster structure and find that these eigenvalues are related to the cluster structure of the correlation coefficient matrix. In this paper, model-based experiments show that in most cases, the number of abnormal eigenvalues of the correlation matrix is equal to the number of clusters. In addition, empirical studies show that the sum of the abnormal eigenvalues is related to the clarity of the cluster structure and is negatively correlated with the correlation dimension.

Marginal and Random Intercepts Models for Longitudinal Binary Data with Examples from Criminology

Science.gov (United States)

Long, Jeffrey D.; Loeber, Rolf; Farrington, David P.

2009-01-01

Two models for the analysis of longitudinal binary data are discussed: the marginal model and the random intercepts model. In contrast to the linear mixed model (LMM), the two models for binary data are not subsumed under a single hierarchical model. The marginal model provides group-level information whereas the random intercepts model provides…

Quantum random oracle model for quantum digital signature

Science.gov (United States)

Shang, Tao; Lei, Qi; Liu, Jianwei

2016-10-01

The goal of this work is to provide a general security analysis tool, namely, the quantum random oracle (QRO), for facilitating the security analysis of quantum cryptographic protocols, especially protocols based on quantum one-way function. QRO is used to model quantum one-way function and different queries to QRO are used to model quantum attacks. A typical application of quantum one-way function is the quantum digital signature, whose progress has been hampered by the slow pace of the experimental realization. Alternatively, we use the QRO model to analyze the provable security of a quantum digital signature scheme and elaborate the analysis procedure. The QRO model differs from the prior quantum-accessible random oracle in that it can output quantum states as public keys and give responses to different queries. This tool can be a test bed for the cryptanalysis of more quantum cryptographic protocols based on the quantum one-way function.

Random-Effects Models for Meta-Analytic Structural Equation Modeling: Review, Issues, and Illustrations

Science.gov (United States)

Cheung, Mike W.-L.; Cheung, Shu Fai

2016-01-01

Meta-analytic structural equation modeling (MASEM) combines the techniques of meta-analysis and structural equation modeling for the purpose of synthesizing correlation or covariance matrices and fitting structural equation models on the pooled correlation or covariance matrix. Both fixed-effects and random-effects models can be defined in MASEM.…

Random isotropic one-dimensional XY-model

Science.gov (United States)

Gonçalves, L. L.; Vieira, A. P.

1998-01-01

The 1D isotropic s = ½XY-model ( N sites), with random exchange interaction in a transverse random field is considered. The random variables satisfy bimodal quenched distributions. The solution is obtained by using the Jordan-Wigner fermionization and a canonical transformation, reducing the problem to diagonalizing an N × N matrix, corresponding to a system of N noninteracting fermions. The calculations are performed numerically for N = 1000, and the field-induced magnetization at T = 0 is obtained by averaging the results for the different samples. For the dilute case, in the uniform field limit, the magnetization exhibits various discontinuities, which are the consequence of the existence of disconnected finite clusters distributed along the chain. Also in this limit, for finite exchange constants J A and J B, as the probability of J A varies from one to zero, the saturation field is seen to vary from Γ A to Γ B, where Γ A(Γ B) is the value of the saturation field for the pure case with exchange constant equal to J A(J B) .

Accounting for Missing Correlation Coefficients in Fixed-Effects MASEM.

Science.gov (United States)

Jak, Suzanne; Cheung, Mike W-L

2018-01-01

Meta-analytic structural equation modeling (MASEM) is increasingly applied to advance theories by synthesizing existing findings. MASEM essentially consists of two stages. In Stage 1, a pooled correlation matrix is estimated based on the reported correlation coefficients in the individual studies. In Stage 2, a structural model (such as a path model) is fitted to explain the pooled correlations. Frequently, the individual studies do not provide all the correlation coefficients between the research variables. In this study, we modify the currently optimal MASEM-method to deal with missing correlation coefficients, and compare its performance with existing methods. This study is the first to evaluate the performance of fixed-effects MASEM methods under different levels of missing correlation coefficients. We found that the often used univariate methods performed very poorly, while the multivariate methods performed well overall.

Studies in astronomical time series analysis: Modeling random processes in the time domain

Science.gov (United States)

Scargle, J. D.

1979-01-01

Random process models phased in the time domain are used to analyze astrophysical time series data produced by random processes. A moving average (MA) model represents the data as a sequence of pulses occurring randomly in time, with random amplitudes. An autoregressive (AR) model represents the correlations in the process in terms of a linear function of past values. The best AR model is determined from sampled data and transformed to an MA for interpretation. The randomness of the pulse amplitudes is maximized by a FORTRAN algorithm which is relatively stable numerically. Results of test cases are given to study the effects of adding noise and of different distributions for the pulse amplitudes. A preliminary analysis of the optical light curve of the quasar 3C 273 is given.

Measurement of infinite dilution activity coefficient and application of modified ASOG model for solvent-polymer systems

Energy Technology Data Exchange (ETDEWEB)

Choi, B.; Choi, J. [Kwangwoon University, Seoul (Korea, Republic of); Tochigi, K.; Kojima, K. [Nihon University, Tokyo (Japan)

1996-04-20

A gas chromatographic method was used in order to measure vapor-liquid equilibria for solvent (1)-polymer (2) systems in which the polymers were polystyrene, poly(a-methyl) styrene and the advents were benzene toluene cyclohexane methylisobutylketone, ethylacetate, and vinylacetate. The activity coefficients of solvents for solvent (1)-polymer (2) systems were measured at infinite dilution and the modified ASOG (Analytical Solution of Group) model was suggested to describe vapor-liquid equilibria of those systems within a range of temperatures 423.15K through 498.15K. The model consists of the original ASOG and the free volume term. An external degree of freedom in the free volume term empirically became to a C1={alpha}+{beta}/T as a function of temperature. Each tern in the modified ASOG model is based on the weight fraction. The external degree of freedom in the model was estimated by experimental data within a range of temperatures. As a result of doing it the infinite dilution activity coefficients calculated were agreed with the experimental data within an error of 0.1%. 27 refs., 3 figs., 7 tabs.

Diffusion of dilute gas in arrays of randomly distributed, vertically aligned, high-aspect-ratio cylinders

Directory of Open Access Journals (Sweden)

Wojciech Szmyt

2017-01-01

Full Text Available In this work we modelled the diffusive transport of a dilute gas along arrays of randomly distributed, vertically aligned nanocylinders (nanotubes or nanowires as opposed to gas diffusion in long pores, which is described by the well-known Knudsen theory. Analytical expressions for (i the gas diffusion coefficient inside such arrays, (ii the time between collisions of molecules with the nanocylinder walls (mean time of flight, (iii the surface impingement rate, and (iv the Knudsen number of such a system were rigidly derived based on a random-walk model of a molecule that undergoes memoryless, diffusive reflections from nanocylinder walls assuming the molecular regime of gas transport. It can be specifically shown that the gas diffusion coefficient inside such arrays is inversely proportional to the areal density of cylinders and their mean diameter. An example calculation of a diffusion coefficient is delivered for a system of titanium isopropoxide molecules diffusing between vertically aligned carbon nanotubes. Our findings are important for the correct modelling and optimisation of gas-based deposition techniques, such as atomic layer deposition or chemical vapour deposition, frequently used for surface functionalisation of high-aspect-ratio nanocylinder arrays in solar cells and energy storage applications. Furthermore, gas sensing devices with high-aspect-ratio nanocylinder arrays and the growth of vertically aligned carbon nanotubes need the fundamental understanding and precise modelling of gas transport to optimise such processes.

A generalized model via random walks for information filtering

Science.gov (United States)

Ren, Zhuo-Ming; Kong, Yixiu; Shang, Ming-Sheng; Zhang, Yi-Cheng

2016-08-01

There could exist a simple general mechanism lurking beneath collaborative filtering and interdisciplinary physics approaches which have been successfully applied to online E-commerce platforms. Motivated by this idea, we propose a generalized model employing the dynamics of the random walk in the bipartite networks. Taking into account the degree information, the proposed generalized model could deduce the collaborative filtering, interdisciplinary physics approaches and even the enormous expansion of them. Furthermore, we analyze the generalized model with single and hybrid of degree information on the process of random walk in bipartite networks, and propose a possible strategy by using the hybrid degree information for different popular objects to toward promising precision of the recommendation.

Gas-particle partitioning of semi-volatile organics on organic aerosols using a predictive activity coefficient model: analysis of the effects of parameter choices on model performance

Science.gov (United States)

Chandramouli, Bharadwaj; Jang, Myoseon; Kamens, Richard M.

The partitioning of a diverse set of semivolatile organic compounds (SOCs) on a variety of organic aerosols was studied using smog chamber experimental data. Existing data on the partitioning of SOCs on aerosols from wood combustion, diesel combustion, and the α-pinene-O 3 reaction was augmented by carrying out smog chamber partitioning experiments on aerosols from meat cooking, and catalyzed and uncatalyzed gasoline engine exhaust. Model compositions for aerosols from meat cooking and gasoline combustion emissions were used to calculate activity coefficients for the SOCs in the organic aerosols and the Pankow absorptive gas/particle partitioning model was used to calculate the partitioning coefficient Kp and quantitate the predictive improvements of using the activity coefficient. The slope of the log K p vs. log p L0 correlation for partitioning on aerosols from meat cooking improved from -0.81 to -0.94 after incorporation of activity coefficients iγ om. A stepwise regression analysis of the partitioning model revealed that for the data set used in this study, partitioning predictions on α-pinene-O 3 secondary aerosol and wood combustion aerosol showed statistically significant improvement after incorporation of iγ om, which can be attributed to their overall polarity. The partitioning model was sensitive to changes in aerosol composition when updated compositions for α-pinene-O 3 aerosol and wood combustion aerosol were used. The octanol-air partitioning coefficient's ( KOA) effectiveness as a partitioning correlator over a variety of aerosol types was evaluated. The slope of the log K p- log K OA correlation was not constant over the aerosol types and SOCs used in the study and the use of KOA for partitioning correlations can potentially lead to significant deviations, especially for polar aerosols.

Modelling the stochastic nature of the available coefficient of friction at footwear-floor interfaces.

Science.gov (United States)

Gragg, Jared; Klose, Ellison; Yang, James

2017-07-01

The available coefficient of friction (ACOF) is a measure of the friction available between two surfaces, which for human gait would be the footwear-floor interface. It is often compared to the required coefficient of friction (RCOF) to determine the likelihood of a slip in gait. Both the ACOF and RCOF are stochastic by nature meaning that neither should be represented by a deterministic value, such as the sample mean. Previous research has determined that the RCOF can be modelled well by either the normal or lognormal distributions, but previous research aimed at determining an appropriate distribution for the ACOF was inconclusive. This study focuses on modelling the stochastic nature of the ACOF by fitting eight continuous probability distributions to ACOF data for six scenarios. In addition, the data were used to study the effect that a simple housekeeping action such as sweeping could have on the ACOF. Practitioner Summary: Previous research aimed at determining an appropriate distribution for the ACOF was inconclusive. The study addresses this issue as well as looking at the effect that an act such as sweeping has on the ACOF.

Lamplighter model of a random copolymer adsorption on a line

Directory of Open Access Journals (Sweden)

L.I. Nazarov

2014-09-01

Full Text Available We present a model of an AB-diblock random copolymer sequential self-packaging with local quenched interactions on a one-dimensional infinite sticky substrate. It is assumed that the A-A and B-B contacts are favorable, while A-B are not. The position of a newly added monomer is selected in view of the local contact energy minimization. The model demonstrates a self-organization behavior with the nontrivial dependence of the total energy, E (the number of unfavorable contacts, on the number of chain monomers, N: E ~ N^3/4 for quenched random equally probable distribution of A- and B-monomers along the chain. The model is treated by mapping it onto the "lamplighter" random walk and the diffusion-controlled chemical reaction of X+X → 0 type with the subdiffusive motion of reagents.

Longitudinal dispersion coefficients for numerical modeling of groundwater solute transport in heterogeneous formations.

Science.gov (United States)

Lee, Jonghyun; Rolle, Massimo; Kitanidis, Peter K

2017-09-15

Most recent research on hydrodynamic dispersion in porous media has focused on whole-domain dispersion while other research is largely on laboratory-scale dispersion. This work focuses on the contribution of a single block in a numerical model to dispersion. Variability of fluid velocity and concentration within a block is not resolved and the combined spreading effect is approximated using resolved quantities and macroscopic parameters. This applies whether the formation is modeled as homogeneous or discretized into homogeneous blocks but the emphasis here being on the latter. The process of dispersion is typically described through the Fickian model, i.e., the dispersive flux is proportional to the gradient of the resolved concentration, commonly with the Scheidegger parameterization, which is a particular way to compute the dispersion coefficients utilizing dispersivity coefficients. Although such parameterization is by far the most commonly used in solute transport applications, its validity has been questioned. Here, our goal is to investigate the effects of heterogeneity and mass transfer limitations on block-scale longitudinal dispersion and to evaluate under which conditions the Scheidegger parameterization is valid. We compute the relaxation time or memory of the system; changes in time with periods larger than the relaxation time are gradually leading to a condition of local equilibrium under which dispersion is Fickian. The method we use requires the solution of a steady-state advection-dispersion equation, and thus is computationally efficient, and applicable to any heterogeneous hydraulic conductivity K field without requiring statistical or structural assumptions. The method was validated by comparing with other approaches such as the moment analysis and the first order perturbation method. We investigate the impact of heterogeneity, both in degree and structure, on the longitudinal dispersion coefficient and then discuss the role of local dispersion

Radionuclides distribution coefficient of soil to soil-solution

International Nuclear Information System (INIS)

1990-06-01

The present book addresses various issues related with the coefficient of radionuclides distribution between soil and soil solution. It consists of six sections and two appendices. The second section, following an introductory one, describes the definition of the coefficient and a procedures of its calculation. The third section deals with the application of the distribution coefficient to the prediction of movements of radionuclides through soil. Various methods for measuring the coefficient are described in the fourth section. The next section discusses a variety of factors (physical and chemical) that can affect the distribution coefficient. Measurements of the coefficient for different types of oils are listed in the sixth section. An appendix is attached to the book to show various models that can be helpful in applying the coefficient of distribution of radionuclides moving from soil into agricultural plants. (N.K.)

Application of the resonating Hartree-Fock random phase approximation to the Lipkin model

International Nuclear Information System (INIS)

Nishiyama, S.; Ishida, K.; Ido, M.

1996-01-01

We have applied the resonating Hartree-Fock (Res-HF) approximation to the exactly solvable Lipkin model by utilizing a newly developed orbital-optimization algorithm. The Res-HF wave function was superposed by two Slater determinants (S-dets) which give two corresponding local energy minima of monopole ''deformations''. The self-consistent Res-HF calculation gives an excellent ground-state correlation energy. There exist excitations due to small vibrational fluctuations of the orbitals and mixing coefficients around their stationary values. They are described by a new approximation called the resonating Hartree-Fock random phase approximation (Res-HF RPA). Matrices of the second-order variation of the Res-HF energy have the same structures as those of the Res-HF RPA's matrices. The quadratic steepest descent of the Res-HF energy in the orbital optimization is considered to include certainly both effects of RPA-type fluctuations up to higher orders and their mode-mode couplings. It is a very important and interesting task to apply the Res-HF RPA to the Lipkin model with the use of the stationary values and to prove the above argument. It turns out that the Res-HF RPA works far better than the usual HF RPA and the renormalized one. We also show some important features of the Res-HF RPA. (orig.)

Random effect selection in generalised linear models

DEFF Research Database (Denmark)

Denwood, Matt; Houe, Hans; Forkman, Björn

We analysed abattoir recordings of meat inspection codes with possible relevance to onfarm animal welfare in cattle. Random effects logistic regression models were used to describe individual-level data obtained from 461,406 cattle slaughtered in Denmark. Our results demonstrate that the largest...

Annealed central limit theorems for the ising model on random graphs

NARCIS (Netherlands)

Giardinà, C.; Giberti, C.; van der Hofstad, R.W.; Prioriello, M.L.

2016-01-01

The aim of this paper is to prove central limit theorems with respect to the annealed measure for the magnetization rescaled by √N of Ising models on random graphs. More precisely, we consider the general rank-1 inhomogeneous random graph (or generalized random graph), the 2-regular configuration

Single-cluster dynamics for the random-cluster model

NARCIS (Netherlands)

Deng, Y.; Qian, X.; Blöte, H.W.J.

2009-01-01

We formulate a single-cluster Monte Carlo algorithm for the simulation of the random-cluster model. This algorithm is a generalization of the Wolff single-cluster method for the q-state Potts model to noninteger values q>1. Its results for static quantities are in a satisfactory agreement with those

Non intrusive measurement of the convective heat transfer coefficient

Energy Technology Data Exchange (ETDEWEB)

Rebay, M.; Mebarki, G.; Padet, J. [Reims Univ., Reims (France). Faculty of Science, GRESPI Thermomechanical Lab; Arfaoui, A. [Reims Univ., Reims (France). Faculty of Science, GRESPI Thermomechanical Lab; Tunis Univ., Tunis (Tunisia). Faculty of Science, EL MANAR, LETTM; Maad, B.R. [Tunis Univ., Tunis (Tunisia). Faculty of Science, EL MANAR, LETTM

2010-07-01

The efficiency of cooling methods in thermal systems such as radiators and heat exchangers must be improved in order to enhance performance. The evaluation of the heat transfer coefficients between a solid and a fluid is necessary for the control and the dimensioning of thermal systems. In this study, the pulsed photothermal method was used to measure the convective heat transfer coefficient on a solid-fluid interface, notably between an air flow and a heated slab mounted on a PVC flat plate. This configuration simulated the electronic air-cooling inside enclosures and racks. The influence of the deflector's inclination angle on the enhancement of heat transfer was investigated using 2 newly developed identification models. The first model was based on a constant heat transfer coefficient during the pulsed experiment, while the second, improved model was based on a variable heat transfer coefficient. The heat transfer coefficient was deduced from the evolution of the transient temperature induced by a sudden deposit of a luminous energy on the front face of the slab. Temperature evolutions were derived by infrared thermography, a camera for cartography and a detector for precise measurement in specific locations. The results show the improvement of measurement accuracies when using a model that considers the temporal evolution of the convective heat transfer coefficient. The deflection of air flow on the upper surface of the heated slab demonstrated better cooling of the slab by the deflection of air flow. 11 refs., 1 tab., 8 figs.

Time-varying coefficient vector autoregressions model based on dynamic correlation with an application to crude oil and stock markets.

Science.gov (United States)

Lu, Fengbin; Qiao, Han; Wang, Shouyang; Lai, Kin Keung; Li, Yuze

2017-01-01

This paper proposes a new time-varying coefficient vector autoregressions (VAR) model, in which the coefficient is a linear function of dynamic lagged correlation. The proposed model allows for flexibility in choices of dynamic correlation models (e.g. dynamic conditional correlation generalized autoregressive conditional heteroskedasticity (GARCH) models, Markov-switching GARCH models and multivariate stochastic volatility models), which indicates that it can describe many types of time-varying causal effects. Time-varying causal relations between West Texas Intermediate (WTI) crude oil and the US Standard and Poor's 500 (S&P 500) stock markets are examined by the proposed model. The empirical results show that their causal relations evolve with time and display complex characters. Both positive and negative causal effects of the WTI on the S&P 500 in the subperiods have been found and confirmed by the traditional VAR models. Similar results have been obtained in the causal effects of S&P 500 on WTI. In addition, the proposed model outperforms the traditional VAR model. Copyright © 2016 Elsevier Ltd. All rights reserved.

Gossip in Random Networks

Science.gov (United States)

Malarz, K.; Szvetelszky, Z.; Szekf, B.; Kulakowski, K.

2006-11-01

We consider the average probability X of being informed on a gossip in a given social network. The network is modeled within the random graph theory of Erd{õ}s and Rényi. In this theory, a network is characterized by two parameters: the size N and the link probability p. Our experimental data suggest three levels of social inclusion of friendship. The critical value pc, for which half of agents are informed, scales with the system size as N-gamma with gamma approx 0.68. Computer simulations show that the probability X varies with p as a sigmoidal curve. Influence of the correlations between neighbors is also evaluated: with increasing clustering coefficient C, X decreases.

A dynamic random effects multinomial logit model of household car ownership

DEFF Research Database (Denmark)

Bue Bjørner, Thomas; Leth-Petersen, Søren

2007-01-01

Using a large household panel we estimate demand for car ownership by means of a dynamic multinomial model with correlated random effects. Results suggest that the persistence in car ownership observed in the data should be attributed to both true state dependence and to unobserved heterogeneity...... (random effects). It also appears that random effects related to single and multiple car ownership are correlated, suggesting that the IIA assumption employed in simple multinomial models of car ownership is invalid. Relatively small elasticities with respect to income and car costs are estimated...

Stochastic modeling of friction force and vibration analysis of a mechanical system using the model

International Nuclear Information System (INIS)

Kang, Won Seok; Choi, Chan Kyu; Yoo, Hong Hee

2015-01-01

The squeal noise generated from a disk brake or chatter occurred in a machine tool primarily results from friction-induced vibration. Since friction-induced vibration is usually accompanied by abrasion and lifespan reduction of mechanical parts, it is necessary to develop a reliable analysis model by which friction-induced vibration phenomena can be accurately analyzed. The original Coulomb's friction model or the modified Coulomb friction model employed in most commercial programs employs deterministic friction coefficients. However, observing friction phenomena between two contact surfaces, one may observe that friction coefficients keep changing due to the unevenness of contact surface, temperature, lubrication and humidity. Therefore, in this study, friction coefficients are modeled as random parameters that keep changing during the motion of a mechanical system undergoing friction force. The integrity of the proposed stochastic friction model was validated by comparing the analysis results obtained by the proposed model with experimental results.

A single-level random-effects cross-lagged panel model for longitudinal mediation analysis.

Science.gov (United States)

Wu, Wei; Carroll, Ian A; Chen, Po-Yi

2017-12-06

Cross-lagged panel models (CLPMs) are widely used to test mediation with longitudinal panel data. One major limitation of the CLPMs is that the model effects are assumed to be fixed across individuals. This assumption is likely to be violated (i.e., the model effects are random across individuals) in practice. When this happens, the CLPMs can potentially yield biased parameter estimates and misleading statistical inferences. This article proposes a model named a random-effects cross-lagged panel model (RE-CLPM) to account for random effects in CLPMs. Simulation studies show that the RE-CLPM outperforms the CLPM in recovering the mean indirect and direct effects in a longitudinal mediation analysis when random effects exist in the population. The performance of the RE-CLPM is robust to a certain degree, even when the random effects are not normally distributed. In addition, the RE-CLPM does not produce harmful results when the model effects are in fact fixed in the population. Implications of the simulation studies and potential directions for future research are discussed.

Modeling Concordance Correlation Coefficient for Longitudinal Study Data

Science.gov (United States)

Ma, Yan; Tang, Wan; Yu, Qin; Tu, X. M.

2010-01-01

Measures of agreement are used in a wide range of behavioral, biomedical, psychosocial, and health-care related research to assess reliability of diagnostic test, psychometric properties of instrument, fidelity of psychosocial intervention, and accuracy of proxy outcome. The concordance correlation coefficient (CCC) is a popular measure of…

Probabilistic flood inundation mapping at ungauged streams due to roughness coefficient uncertainty in hydraulic modelling

Science.gov (United States)

Papaioannou, George; Vasiliades, Lampros; Loukas, Athanasios; Aronica, Giuseppe T.

2017-04-01

Probabilistic flood inundation mapping is performed and analysed at the ungauged Xerias stream reach, Volos, Greece. The study evaluates the uncertainty introduced by the roughness coefficient values on hydraulic models in flood inundation modelling and mapping. The well-established one-dimensional (1-D) hydraulic model, HEC-RAS is selected and linked to Monte-Carlo simulations of hydraulic roughness. Terrestrial Laser Scanner data have been used to produce a high quality DEM for input data uncertainty minimisation and to improve determination accuracy on stream channel topography required by the hydraulic model. Initial Manning's n roughness coefficient values are based on pebble count field surveys and empirical formulas. Various theoretical probability distributions are fitted and evaluated on their accuracy to represent the estimated roughness values. Finally, Latin Hypercube Sampling has been used for generation of different sets of Manning roughness values and flood inundation probability maps have been created with the use of Monte Carlo simulations. Historical flood extent data, from an extreme historical flash flood event, are used for validation of the method. The calibration process is based on a binary wet-dry reasoning with the use of Median Absolute Percentage Error evaluation metric. The results show that the proposed procedure supports probabilistic flood hazard mapping at ungauged rivers and provides water resources managers with valuable information for planning and implementing flood risk mitigation strategies.

Statistical Models for Sediment/Detritus and Dissolved Absorption Coefficients in Coastal Waters of the Northern Gulf of Mexico

National Research Council Canada - National Science Library

Green, Rebecca E; Gould, Jr., Richard W; Ko, Dong S

2008-01-01

... (CDOM) absorption coefficients from physical hydrographic and atmospheric properties. The models were developed for northern Gulf of Mexico shelf waters using multi-year satellite and physical data...

The reverse effects of random perturbation on discrete systems for single and multiple population models

International Nuclear Information System (INIS)

Kang, Li; Tang, Sanyi

2016-01-01

Highlights: • The discrete single species and multiple species models with random perturbation are proposed. • The complex dynamics and interesting bifurcation behavior have been investigated. • The reverse effects of random perturbation on discrete systems have been discussed and revealed. • The main results can be applied for pest control and resources management. - Abstract: The natural species are likely to present several interesting and complex phenomena under random perturbations, which have been confirmed by simple mathematical models. The important questions are: how the random perturbations influence the dynamics of the discrete population models with multiple steady states or multiple species interactions? and is there any different effects for single species and multiple species models with random perturbation? To address those interesting questions, we have proposed the discrete single species model with two stable equilibria and the host-parasitoid model with Holling type functional response functions to address how the random perturbation affects the dynamics. The main results indicate that the random perturbation does not change the number of blurred orbits of the single species model with two stable steady states compared with results for the classical Ricker model with same random perturbation, but it can strength the stability. However, extensive numerical investigations depict that the random perturbation does not influence the complexities of the host-parasitoid models compared with the results for the models without perturbation, while it does increase the period of periodic orbits doubly. All those confirm that the random perturbation has a reverse effect on the dynamics of the discrete single and multiple population models, which could be applied in reality including pest control and resources management.

Hydrodynamic Coefficients Identification and Experimental Investigation for an Underwater Vehicle

Directory of Open Access Journals (Sweden)

Shaorong XIE

2014-02-01

Full Text Available Hydrodynamic coefficients are the foundation of unmanned underwater vehicles modeling and controller design. In order to reduce identification complexity and acquire necessary hydrodynamic coefficients for controllers design, the motion of the unmanned underwater vehicle was separated into vertical motion and horizontal motion models. Hydrodynamic coefficients were regarded as mapping parameters from input forces and moments to output velocities and acceleration of the unmanned underwater vehicle. The motion models of the unmanned underwater vehicle were nonlinear and Genetic Algorithm was adopted to identify those hydrodynamic coefficients. To verify the identification quality, velocities and acceleration of the unmanned underwater vehicle was measured using inertial sensor under the same conditions as Genetic Algorithm identification. Curves similarity between measured velocities and acceleration and those identified by Genetic Algorithm were used as optimizing standard. It is found that the curves similarity were high and identified hydrodynamic coefficients of the unmanned underwater vehicle satisfied the measured motion states well.

Modeling of chromosome intermingling by partially overlapping uniform random polygons.

Science.gov (United States)

Blackstone, T; Scharein, R; Borgo, B; Varela, R; Diao, Y; Arsuaga, J

2011-03-01

During the early phase of the cell cycle the eukaryotic genome is organized into chromosome territories. The geometry of the interface between any two chromosomes remains a matter of debate and may have important functional consequences. The Interchromosomal Network model (introduced by Branco and Pombo) proposes that territories intermingle along their periphery. In order to partially quantify this concept we here investigate the probability that two chromosomes form an unsplittable link. We use the uniform random polygon as a crude model for chromosome territories and we model the interchromosomal network as the common spatial region of two overlapping uniform random polygons. This simple model allows us to derive some rigorous mathematical results as well as to perform computer simulations easily. We find that the probability that one uniform random polygon of length n that partially overlaps a fixed polygon is bounded below by 1 − O(1/√n). We use numerical simulations to estimate the dependence of the linking probability of two uniform random polygons (of lengths n and m, respectively) on the amount of overlapping. The degree of overlapping is parametrized by a parameter [Formula: see text] such that [Formula: see text] indicates no overlapping and [Formula: see text] indicates total overlapping. We propose that this dependence relation may be modeled as f (ε, m, n) = [Formula: see text]. Numerical evidence shows that this model works well when [Formula: see text] is relatively large (ε ≥ 0.5). We then use these results to model the data published by Branco and Pombo and observe that for the amount of overlapping observed experimentally the URPs have a non-zero probability of forming an unsplittable link.

A kinetic model of droplet heating and evaporation: Effects of inelastic collisions and a non-unity evaporation coefficient

KAUST Repository

Sazhin, Sergei S.

2013-01-01

The previously developed kinetic model for droplet heating and evaporation into a high pressure air is generalised to take into account the combined effects of inelastic collisions between molecules in the kinetic region, a non-unity evaporation coefficient and temperature gradient inside droplets. It is pointed out that for the parameters typical for Diesel engine-like conditions, the heat flux in the kinetic region is a linear function of the vapour temperature at the outer boundary of this region, but practically does not depend on vapour density at this boundary for all models, including and not including the effects of inelastic collisions, and including and not including the effects of a non-unity evaporation coefficient. For any given temperature at the outer boundary of the kinetic region the values of the heat flux are shown to decrease with increasing numbers of internal degrees of freedom of the molecules. The rate of this decrease is strong for small numbers of these degrees of freedom but negligible when the number of these degrees exceeds 20. This allows us to restrict the analysis to the first 20 arbitrarily chosen degrees of freedom of n-dodecane molecules when considering the effects of inelastic collisions. The mass flux at this boundary decreases almost linearly with increasing vapour density at the same location for all above-mentioned models. For any given vapour density at the outer boundary of the kinetic region the values of the mass flux are smaller for the model, taking into account the contribution of internal degrees of freedom, than for the model ignoring these degrees of freedom. It is shown that the effects of inelastic collisions lead to stronger increase in the predicted droplet evaporation time in Diesel engine-like conditions relative to the hydrodynamic model, compared with the similar increase predicted by the kinetic model considering only elastic collisions. The effects of a non-unity evaporation coefficient are shown to be

Axially symmetric reconstruction of plasma emission and absorption coefficients

International Nuclear Information System (INIS)

Yang Lixin; Jia Hui; Yang Jiankun; Li Xiujian; Chen Shaorong; Liu Xishun

2013-01-01

A layered structure imaging model is developed in order to reconstruct emission coefficients and absorption coefficients simultaneously, in laser fusion core plasma diagnostics. A novel axially symmetric reconstruction method that utilizes the LM (Levenberg-Marquardt) nonlinear least squares minimization algorithm is proposed based on the layered structure. Numerical simulation results demonstrate that the proposed method is sufficiently accurate to reconstruct emission coefficients and absorption coefficients, and when the standard deviation of noise is 0.01, the errors of emission coefficients and absorption coefficients are 0.17, 0.22, respectively. Furthermore, this method could perform much better on reconstruction effect compared with traditional inverse Abel transform algorithms. (authors)

Activity coefficients of electrons and holes in semiconductors

International Nuclear Information System (INIS)

Orazem, M.E.; Newman, J.

1984-01-01

Dilute-solution transport equations with constant activity coefficients are commonly used to model semiconductors. These equations are consistent with a Boltzmann distribution and are invalid in regions where the species concentration is close to the respective site concentration. A more rigorous treatment of transport in a semiconductor requires activity coefficients which are functions of concentration. Expressions are presented for activity coefficients of electrons and holes in semiconductors for which conduction- and valence-band energy levels are given by the respective bandedge energy levels. These activity coefficients are functions of concentration and are thermodynamically consistent. The use of activity coefficients in macroscopic transport relationships allows a description of electron transport in a manner consistent with the Fermi-Dirac distribution

Molecular radiotherapy: the NUKFIT software for calculating the time-integrated activity coefficient.

Science.gov (United States)

Kletting, P; Schimmel, S; Kestler, H A; Hänscheid, H; Luster, M; Fernández, M; Bröer, J H; Nosske, D; Lassmann, M; Glatting, G

2013-10-01

Calculation of the time-integrated activity coefficient (residence time) is a crucial step in dosimetry for molecular radiotherapy. However, available software is deficient in that it is either not tailored for the use in molecular radiotherapy and/or does not include all required estimation methods. The aim of this work was therefore the development and programming of an algorithm which allows for an objective and reproducible determination of the time-integrated activity coefficient and its standard error. The algorithm includes the selection of a set of fitting functions from predefined sums of exponentials and the choice of an error model for the used data. To estimate the values of the adjustable parameters an objective function, depending on the data, the parameters of the error model, the fitting function and (if required and available) Bayesian information, is minimized. To increase reproducibility and user-friendliness the starting values are automatically determined using a combination of curve stripping and random search. Visual inspection, the coefficient of determination, the standard error of the fitted parameters, and the correlation matrix are provided to evaluate the quality of the fit. The functions which are most supported by the data are determined using the corrected Akaike information criterion. The time-integrated activity coefficient is estimated by analytically integrating the fitted functions. Its standard error is determined assuming Gaussian error propagation. The software was implemented using MATLAB. To validate the proper implementation of the objective function and the fit functions, the results of NUKFIT and SAAM numerical, a commercially available software tool, were compared. The automatic search for starting values was successfully tested for reproducibility. The quality criteria applied in conjunction with the Akaike information criterion allowed the selection of suitable functions. Function fit parameters and their standard

Some Limits Using Random Slope Models to Measure Academic Growth

Directory of Open Access Journals (Sweden)

Daniel B. Wright

2017-11-01

Full Text Available Academic growth is often estimated using a random slope multilevel model with several years of data. However, if there are few time points, the estimates can be unreliable. While using random slope multilevel models can lower the variance of the estimates, these procedures can produce more highly erroneous estimates—zero and negative correlations with the true underlying growth—than using ordinary least squares estimates calculated for each student or school individually. An example is provided where schools with increasing graduation rates are estimated to have negative growth and vice versa. The estimation is worse when the underlying data are skewed. It is recommended that there are at least six time points for estimating growth if using a random slope model. A combination of methods can be used to avoid some of the aberrant results if it is not possible to have six or more time points.

Application of Mathematical Models for Determination of Microorganisms Growth Rate Kinetic Coefficients for Wastewater Treatment Plant Evaluation

Directory of Open Access Journals (Sweden)

Mohammad Delnavaz

2017-06-01

Conclusion: Evaluation of Y, kd, k0 and Ks parameters in operation of Ekbatan wastewater treatment plant showed that ASM1 model could well determine the coefficients and therefore the conditions of biological treatment is appropriate.

Utility based maintenance analysis using a Random Sign censoring model

International Nuclear Information System (INIS)

Andres Christen, J.; Ruggeri, Fabrizio; Villa, Enrique

2011-01-01

Industrial systems subject to failures are usually inspected when there are evident signs of an imminent failure. Maintenance is therefore performed at a random time, somehow dependent on the failure mechanism. A competing risk model, namely a Random Sign model, is considered to relate failure and maintenance times. We propose a novel Bayesian analysis of the model and apply it to actual data from a water pump in an oil refinery. The design of an optimal maintenance policy is then discussed under a formal decision theoretic approach, analyzing the goodness of the current maintenance policy and making decisions about the optimal maintenance time.

Molecular radiotherapy: The NUKFIT software for calculating the time-integrated activity coefficient

Energy Technology Data Exchange (ETDEWEB)

Kletting, P.; Schimmel, S.; Luster, M. [Klinik für Nuklearmedizin, Universität Ulm, Ulm 89081 (Germany); Kestler, H. A. [Research Group Bioinformatics and Systems Biology, Institut für Neuroinformatik, Universität Ulm, Ulm 89081 (Germany); Hänscheid, H.; Fernández, M.; Lassmann, M. [Klinik für Nuklearmedizin, Universität Würzburg, Würzburg 97080 (Germany); Bröer, J. H.; Nosske, D. [Bundesamt für Strahlenschutz, Fachbereich Strahlenschutz und Gesundheit, Oberschleißheim 85764 (Germany); Glatting, G. [Medical Radiation Physics/Radiation Protection, Medical Faculty Mannheim, Heidelberg University, Mannheim 68167 (Germany)

2013-10-15

Purpose: Calculation of the time-integrated activity coefficient (residence time) is a crucial step in dosimetry for molecular radiotherapy. However, available software is deficient in that it is either not tailored for the use in molecular radiotherapy and/or does not include all required estimation methods. The aim of this work was therefore the development and programming of an algorithm which allows for an objective and reproducible determination of the time-integrated activity coefficient and its standard error.Methods: The algorithm includes the selection of a set of fitting functions from predefined sums of exponentials and the choice of an error model for the used data. To estimate the values of the adjustable parameters an objective function, depending on the data, the parameters of the error model, the fitting function and (if required and available) Bayesian information, is minimized. To increase reproducibility and user-friendliness the starting values are automatically determined using a combination of curve stripping and random search. Visual inspection, the coefficient of determination, the standard error of the fitted parameters, and the correlation matrix are provided to evaluate the quality of the fit. The functions which are most supported by the data are determined using the corrected Akaike information criterion. The time-integrated activity coefficient is estimated by analytically integrating the fitted functions. Its standard error is determined assuming Gaussian error propagation. The software was implemented using MATLAB.Results: To validate the proper implementation of the objective function and the fit functions, the results of NUKFIT and SAAM numerical, a commercially available software tool, were compared. The automatic search for starting values was successfully tested for reproducibility. The quality criteria applied in conjunction with the Akaike information criterion allowed the selection of suitable functions. Function fit

Fuzziness and randomness in an optimization framework

International Nuclear Information System (INIS)

Luhandjula, M.K.

1994-03-01

This paper presents a semi-infinite approach for linear programming in the presence of fuzzy random variable coefficients. As a byproduct a way for dealing with optimization problems including both fuzzy and random data is obtained. Numerical examples are provided for the sake of illustration. (author). 13 refs

New constraints on modelling the random magnetic field of the MW

Energy Technology Data Exchange (ETDEWEB)

Beck, Marcus C.; Nielaba, Peter [Department of Physics, University of Konstanz, Universitätsstr. 10, D-78457 Konstanz (Germany); Beck, Alexander M.; Dolag, Klaus [University Observatory Munich, Scheinerstr. 1, D-81679 Munich (Germany); Beck, Rainer [Max Planck Institute for Radioastronomy, Auf dem Hügel 69, D-53121 Bonn (Germany); Strong, Andrew W., E-mail: marcus.beck@uni-konstanz.de, E-mail: abeck@usm.uni-muenchen.de, E-mail: rbeck@mpifr-bonn.mpg.de, E-mail: dolag@usm.uni-muenchen.de, E-mail: aws@mpe.mpg.de, E-mail: peter.nielaba@uni-konstanz.de [Max Planck Institute for Extraterrestrial Physics, Giessenbachstr. 1, D-85748 Garching (Germany)

2016-05-01

We extend the description of the isotropic and anisotropic random component of the small-scale magnetic field within the existing magnetic field model of the Milky Way from Jansson and Farrar, by including random realizations of the small-scale component. Using a magnetic-field power spectrum with Gaussian random fields, the NE2001 model for the thermal electrons and the Galactic cosmic-ray electron distribution from the current GALPROP model we derive full-sky maps for the total and polarized synchrotron intensity as well as the Faraday rotation-measure distribution. While previous work assumed that small-scale fluctuations average out along the line-of-sight or which only computed ensemble averages of random fields, we show that these fluctuations need to be carefully taken into account. Comparing with observational data we obtain not only good agreement with 408 MHz total and WMAP7 22 GHz polarized intensity emission maps, but also an improved agreement with Galactic foreground rotation-measure maps and power spectra, whose amplitude and shape strongly depend on the parameters of the random field. We demonstrate that a correlation length of 0≈22 pc (05 pc being a 5σ lower limit) is needed to match the slope of the observed power spectrum of Galactic foreground rotation-measure maps. Using multiple realizations allows us also to infer errors on individual observables. We find that previously-used amplitudes for random and anisotropic random magnetic field components need to be rescaled by factors of ≈0.3 and 0.6 to account for the new small-scale contributions. Our model predicts a rotation measure of −2.8±7.1 rad/m{sup 2} and 04.4±11. rad/m{sup 2} for the north and south Galactic poles respectively, in good agreement with observations. Applying our model to deflections of ultra-high-energy cosmic rays we infer a mean deflection of ≈3.5±1.1 degree for 60 EeV protons arriving from CenA.

Varying Coefficient Panel Data Model in the Presence of Endogenous Selectivity and Fixed Effects

OpenAIRE

Malikov, Emir; Kumbhakar, Subal C.; Sun, Yiguo

2013-01-01

This paper considers a flexible panel data sample selection model in which (i) the outcome equation is permitted to take a semiparametric, varying coefficient form to capture potential parameter heterogeneity in the relationship of interest, (ii) both the outcome and (parametric) selection equations contain unobserved fixed effects and (iii) selection is generalized to a polychotomous case. We propose a two-stage estimator. Given consistent parameter estimates from the selection equation obta...

Analytical prediction of fuel assembly spacer grid loss coefficient

International Nuclear Information System (INIS)

Lim, J. S.; Nam, K. I.; Park, S. K.; Kwon, J. T.; Park, W. J.

2002-01-01

The analytical prediction model of the fuel assembly spacer grid pressure loss coefficient has been studied. The pressure loss of gap between the test section wall and spacer grid was separated from the current model and the different friction drag coefficient on spacer straps from high Reynolds number region were used to low Reynolds number region. The analytical model has been verified based on the hydraulic pressure drop test results for the spacer grids of three types for 5x5, 16x16(or 17x17) arrays. The analytical model predicts the pressure loss coefficients obtained from test results within the maximum errors of 12% and 7% for 5x5 test bundle and full size bundle, respectively, at Reynolds number 500,000 of the core operating condition. This result shows that the analytical model can be used for research and design change of the nuclear fuel assembly

A random walk model to evaluate autism

Science.gov (United States)

Moura, T. R. S.; Fulco, U. L.; Albuquerque, E. L.

2018-02-01

A common test administered during neurological examination in children is the analysis of their social communication and interaction across multiple contexts, including repetitive patterns of behavior. Poor performance may be associated with neurological conditions characterized by impairments in executive function, such as the so-called pervasive developmental disorders (PDDs), a particular condition of the autism spectrum disorders (ASDs). Inspired in these diagnosis tools, mainly those related to repetitive movements and behaviors, we studied here how the diffusion regimes of two discrete-time random walkers, mimicking the lack of social interaction and restricted interests developed for children with PDDs, are affected. Our model, which is based on the so-called elephant random walk (ERW) approach, consider that one of the random walker can learn and imitate the microscopic behavior of the other with probability f (1 - f otherwise). The diffusion regimes, measured by the Hurst exponent (H), is then obtained, whose changes may indicate a different degree of autism.

Connectivity ranking of heterogeneous random conductivity models

Science.gov (United States)

Rizzo, C. B.; de Barros, F.

2017-12-01

To overcome the challenges associated with hydrogeological data scarcity, the hydraulic conductivity (K) field is often represented by a spatial random process. The state-of-the-art provides several methods to generate 2D or 3D random K-fields, such as the classic multi-Gaussian fields or non-Gaussian fields, training image-based fields and object-based fields. We provide a systematic comparison of these models based on their connectivity. We use the minimum hydraulic resistance as a connectivity measure, which it has been found to be strictly correlated with early time arrival of dissolved contaminants. A computationally efficient graph-based algorithm is employed, allowing a stochastic treatment of the minimum hydraulic resistance through a Monte-Carlo approach and therefore enabling the computation of its uncertainty. The results show the impact of geostatistical parameters on the connectivity for each group of random fields, being able to rank the fields according to their minimum hydraulic resistance.

Accumulator and random-walk models of psychophysical discrimination: a counter-evaluation.

Science.gov (United States)

Vickers, D; Smith, P

1985-01-01

In a recent assessment of models of psychophysical discrimination, Heath criticises the accumulator model for its reliance on computer simulation and qualitative evidence, and contrasts it unfavourably with a modified random-walk model, which yields exact predictions, is susceptible to critical test, and is provided with simple parameter-estimation techniques. A counter-evaluation is presented, in which the approximations employed in the modified random-walk analysis are demonstrated to be seriously inaccurate, the resulting parameter estimates to be artefactually determined, and the proposed test not critical. It is pointed out that Heath's specific application of the model is not legitimate, his data treatment inappropriate, and his hypothesis concerning confidence inconsistent with experimental results. Evidence from adaptive performance changes is presented which shows that the necessary assumptions for quantitative analysis in terms of the modified random-walk model are not satisfied, and that the model can be reconciled with data at the qualitative level only by making it virtually indistinguishable from an accumulator process. A procedure for deriving exact predictions for an accumulator process is outlined.

A cellular automata model of traffic flow with variable probability of randomization

International Nuclear Information System (INIS)

Zheng Wei-Fan; Zhang Ji-Ye

2015-01-01

Research on the stochastic behavior of traffic flow is important to understand the intrinsic evolution rules of a traffic system. By introducing an interactional potential of vehicles into the randomization step, an improved cellular automata traffic flow model with variable probability of randomization is proposed in this paper. In the proposed model, the driver is affected by the interactional potential of vehicles before him, and his decision-making process is related to the interactional potential. Compared with the traditional cellular automata model, the modeling is more suitable for the driver’s random decision-making process based on the vehicle and traffic situations in front of him in actual traffic. From the improved model, the fundamental diagram (flow–density relationship) is obtained, and the detailed high-density traffic phenomenon is reproduced through numerical simulation. (paper)