On the slow motion of a sphere in fluids with non-constant viscosities

We study a slowly moving sphere in fluids where the viscosity depends upon factors such as shear-rate, temperature and pressure, with the flow field approximated by the Stokes flow past a sphere. We derive an expression for the stresses generated in the fluid due to these various factors. This gives us information about both, the force imposed by the fluid upon the sphere and also the reaction force due to the sphere upon the fluid, referred to as the stress density. The values of the force and stress density are numerically computed in each of the cases and analyzed for various values of the flow and material parameters. Our computations show interesting variations in the distribution of stress density in the fluid for the various cases and also give us valuable information about the effect of walls. Our calculations also indicate that particle heating or cooling can serve as a significant control parameter since the drag force upon the sphere increases dramatically for a cold particle and can be reduced considerably upon heating it.     

A Bayesian Nonparametric Mixture Measurement Error Model With Application to Spatial Density Estimation Using Mobile Positioning Data With Multi-Accuracy and Multi-Coverage

Abstract

The development of mobile network technologies has made it possible to collect location data of mobile devices through various positioning technologies. The location data can be used to estimate the spatial density of mobile devices, which in turn can be used by mobile service providers to plan for network capacity improvements. The two most prevalent positioning technologies are the assisted global positioning system (AGPS) and cell tower triangulation (CTT) methods. AGPS data provide more accurate location information than CTT data but can cover only a fraction of mobile devices, while CTT data can cover all mobile devices. Motivated by this problem, we propose a Bayesian nonparametric mixture measurement error model to estimate the spatial density function by integrating both noise-free data (i.e., AGPS data) and data contaminated with measurement errors (i.e., CTT data). The proposed model estimates the true latent locations from contaminated data, and the estimated latent locations, combined with noise-free data, are used to infer the model parameters. We model the true density function using a Dirichlet process (DP) mixture model with a bivariate beta distribution for the mixture kernel and a DP prior for the mixing distribution. The use of bivariate beta distributions for the mixture kernel allows the density function to have various shapes with a bounded support. Moreover, the use of a DP prior for the mixing distribution allows the number of mixture components to be determined automatically without being specified in advance. Therefore, the proposed model is very flexible. We demonstrate the effective performance of the proposed model via simulated and real-data examples.     

Pulsed NMR studies in solid H2. I. Solid echoes and nuclear spin-spin relaxation times after a two-pulse sequence

We describe a systematic pulsed NMR study on several solid H₂ samples with ortho concentration X between 10% and 70% at temperatures between 0.08 and 2 K, where the intramolecular dipole-dipole interaction is the dominant spin-spin interaction. Nuclear spin echoes from a two-pulse sequence are studied using a rf phase-coherent spectrometer and they show the quasiquadrupolar nature of the echo formations. A density matrix method applied to the system of ortho-H₂ molecules can account for most of the observed properties of the echoes. From the decay of the echo envelope we obtain information on the static intermolecular nuclear interactions and the local inhomogeneous magnetic field distribution. Details of the density matrix calculation are presented in an appendix.     

Quantitative evaluation on 3D fetus morphology via X-ray grating based imaging technique

Synchrotron-based X-ray phase sensitive micro-tomography techniques enable to visualize detailed three-dimensional (3D) insight into nondestructive inner-structure of biomedical samples. Different phase sensitive mechanisms have been employed for discrimination of tissue's tiny density variations in biomedical research. We effectively visualized and analyzed the phase-contrast experimental results of X-ray grating-based imaging, based on grating interferometry with phase stepping, by using transgenic mouse fetus. We quantitatively measured and evaluated the contrast-to-noise ratio or the mass density resolution, spatial resolution, radiation dose, and figure of merit of X-ray grating-based imaging technique in biomedical research respectively. Moreover, the complex coherent degrees of light source were duly taken into account in the analysis of spatial resolution. In addition, the mass density distribution of soft biomedical specimens can be estimated using our presented method preliminarily. For most soft tissue and organ observation, this work provides explicit guidelines to help future synchrotron users obtain the quantitative image information, suitable for their specific biomedical research.     

Determination of the amount of information at the output of a digital angle converter

An information approach to estimation of precision of digital angle converters is proposed. The method is based on estimating the amount of information of individual code combinations. It is shown that an analytic expression for the density distribution function of information can be obtained.Translated from Izmeritel'naya Tekhnika, No. 1, pp. 14–15, January, 1995.     

Spin drift–diffusion transport and its applications in semiconductors

We study theoretically the propagation and distribution of electron spin density in semiconductors within the drift–diffusion model in an external electric field. From the solution of the spin drift–diffusion equation, we derive the expressions for spin currents in the down-stream (DS) and up-stream (US) directions. We find that drift and diffusion currents contribute to the spin current and there is an electric field, called the drift–diffusion crossover field, where the drift and diffusion mechanisms contribute equally to the spin current in the DS direction, and that the spin current in the US direction vanishes when the electric field is very large. We calculate the drift–diffusion crossover field and show that the intrinsic spin diffusion length in a semiconductor can be determined directly from it if the temperature, electron density and both the temperature and electron density, respectively, are known for nondegenerate, highly degenerate and degenerate systems. The results will be useful in obtaining transport properties of the electron’s spin in semiconductors, the essential information for spintronic technology.     

Systematic study on the influence of growth parameters on island density exponent,size distribution and scaling behaviour

We present the Monte Carlo simulation of submonolayer film growth during molecular beam epitaxy (MBE) at low temperature. We have made systematic study to see how the parameters diffusion to flux ratio (D/F), diffusional anisotropy (DA) and sticking anisotropy influences on island density exponent (χ), size distribution and scaling behaviour. We have found that, as diffusional anisotropy changes from DA = 1 to DA = ∝, the density exponent changes from χ = 0.34 ± 0.01 to 0.28 ± 0.01 for isotropic sticking case but when sticking is anisotropic the density exponent changes from χ = 0.31 ± 0.01 to 0.24 ± 0.01. The influence produced by DA on island size distribution is observed to depend on D/F ratio and sticking anisotropy. Depending on DA values and D/F ratio, the size distribution is also observed to be insensitive to the change in diffusional anisotropy. We also study the influence of diffusional anisotropy on scaling function for two sticking anisotropy condition. The scaling behaviour of island size distribution is observed to be not affected by all diffusional anisotropy as well as sticking anisotropy condition.     

Evaluation of the reliability of determining coordinates in navigation systems corrected for digital road maps

An approach is suggested for determining the reliability of incidentally corrected terrestrial navigation system information without presuming finding in explicit form the empirical distribution density of navigation parameter errors. __________ Translated from Izmeritel’naya Tekhnika, No. 5, pp. 35–39, May, 2007.     

Unfolding Particle Size Distributions

This paper treats the unfolding problem of estimating the density distribution of particles dispersed in a three-dimensional specimen. A general framework is set in terms of a probabilistic model for the distribution of a discrete number of particle sizes with prescribed shapes which are sampled and observed by processes capable of being modeled. The general formulation allows density estimates and standard deviation estimates for each particle size in the distribution to be made with data from observational processes that may distort or truncate the sampled information. The method is related to the earlier works on unfolding or estimating the density distribution of spherical particles sectioned by planar probes. The method is also used to develop a more accurate estimate for the density distribution of spherical voids where the observational process is the indirect microscopy of a replicated surface.     

Resolution analysis of ionospheric tomography systems

One of the most recent applications for tomographic imaging is the measurement of the electron density distribution in the ionosphere. This imaging system is a unique and challenging tomographic system because of the physical constraints of the system and the nature of the electron density distribution. To fully understand the potential and limitations of this imaging system, analysis of the resolving capabilities is needed. This article provides a review of current analysis methods for both system evaluation and characterization of the effects of individual degradation parameters. This article also presents a study of the effect of system configuration on the information content of projections.©1994 John Wiley & Sons Inc     

Physics-Based Visualization of Dense Natural Clouds. II. Cloud-Rendering Algorithm

We discuss the representation of aerosol-scattering properties, boundary information, and the use of these results in line-of-sight rendering applications for visualization of a modeled atmosphere based on a discrete ordinates three-dimensional radiative-transport method. The outputs of the radiative-transfer model provide spatial and angular distributions of limiting path radiance, given an input density distribution and external illumination conditions. We discuss the determination of the direct attenuated radiance, integrated path radiance, and background radiance for each pixel in the rendered scene. Orthographic and perspective projection approaches for displaying these results are described, and sample images are shown.     

An NDE Methodology to Predict Density in Green-State Powder Metallurgy Compacts

Extensive work at PMRC has established a clear correlation between green-state density and electric conductivity of P/M parts. By monitoring a static electric current flow through the pre-sintered P/M sample and recording the voltage response over its surface, sufficient information can be gathered to predict the density profile throughout the sample volume. In this paper, the formulation and implementation of a novel numerical forward and inverse formulation will be presented that is capable of relating DC voltage measurements to green-state density distributions. It will be shown that this methodology is applicable to both lubricated and lubricant-free compacts. We will present a general forward solution that enables the calculation of three-dimensional surface voltages for a given set of boundary conditions and a known conductivity/density distribution throughout the P/M sample. This formulation is particularly useful for the development of new sensors and measurement arrangements, since it permits the optimization of current injection patterns and voltage probe locations. Our novel inverse solution adjusts the conductivity/density profile so as to determine the conductivity distribution that matches most closely a given set of voltage data on the surface. Practical measurements with a range of green-state P/M samples will underscore the success and usefulness of this modeling approach.     

Scaling of diffractive and refractive lenses for optical computing and interconnections

We discuss both numerically and analytically how the space-bandwidth product and the information density of lenses scale as functions of their diameter and f-number over many orders of magnitude. This information may be useful for the design of optical computing and interconnection systems. For diffractive lenses, cost is defined as the number of resolution elements the lithographic production system must have; the relationship of this quantity to the space-bandwidth product and information density is also given.     

A Nonparametric Kernel Approach to Interval-Valued Data Analysis

This article concerns datasets in which variables are in the form of intervals, which are obtained by aggregating information about variables from a larger dataset. We propose to view the observed set of hyper-rectangles as an empirical histogram, and to use a Gaussian kernel type estimator to approximate its underlying distribution in a nonparametric way. We apply this idea to both univariate density estimation and regression problems. Unlike many existing methods used in regression analysis, the proposed method can estimate the conditional distribution of the response variable for any given set of predictors even when some of them are not interval-valued. Empirical studies show that the proposed approach has a great flexibility in various scenarios with complex relationships between the location and width of intervals of the response and predictor variables.     

目标联合状态类型密度表示的跟踪门技术

大多数传统的跟踪门技术仅使用目标的运动学量测信息,在多目标、多杂波跟踪场景中会导致较大的关联不确定性。考虑到属性传感器可以获取目标的类型信息,提出了基于目标联合状态类型概率密度的跟踪门方法。首先给出目标状态与类型的联合概率密度表示,从而导出以类为条件的跟踪门构建方法。为了适用于实时的非线性跟踪系统,门限的计算采用了基于仿真的算法。场景 1显示如果目标的量测预测密度为偏斜函数时,基于仿真的门限算法可以获得最优的跟踪门;场景 2为地面编队目标的跟踪过程。与使用传统的跟踪门相比,以类为条件的跟踪门技术在很大程度上提高了目标量测到航迹的关联率。     

Inference for two-parameter Rayleigh competing risks data under generalized progressive hybrid censoring

In this paper, a competing risks model based on the generalized progressive hybrid censored two-parameter Rayleigh distributions is studied under the assumption that the lifetime distributions of failure causes are identically distributed with same location and different scale parameters. We obtain maximum likelihood estimates of unknown parameters with associated existence uniqueness. The approximate confidence intervals are constructed using the asymptotic distribution of maximum likelihood estimates via the observed information matrix. Further, Bayes point estimates and the highest probability density credible intervals of unknown parameters are presented, and the Gibbs sampling technique is used to approximate corresponding estimates. A Monte Carlo simulation study is conducted to compare the accuracy of proposed estimates. Finally, a real-life example is presented for illustration purpose.     

A SIMULATION OF THE FATIGUE CRACK PROCESS IN TYPE 304 STAINLESS STEEL AT 538°C

Abstract— Quantitative information, such as the initiation period, growth and coalescence behaviour, statistical distributions of crack length, density of cracks, distribution patterns and crack growth properties, were obtained from fatigue tests on type 304 stainless steel at 538°C in a previous study. Using this information as input data and a condition for the connection and interactions of cracks, a statistical simulation and life prediction due to the high temperature fatigue crack growth process was performed and illustrated as output on a two-dimensional graphical display.     

Analytical Modeling of Open-Circuit Air-Gap Field Distributions in Multisegment and Multilayer Interior Permanent-Magnet Machines

We present a simple lumped magnetic circuit model for interior permanent-magnet (IPM) machines with multisegment and multilayer permanent magnets. We derived analytically the open-circuit air-gap field distribution, average air-gap flux density, and leakage fluxes. To verify the developed models and analytical method, we adopted finite-element analysis (FEA). We show that for prototype machines, the errors between the FEA and analytically predicted results are $≪$1% for multisegment IPM machines and $≪$ 2% for multilayer IPM machines. By utilizing the developed lumped magnetic circuit models, the IPM machines can be optimized for maximum fundamental and minimum total harmonic distortion of the air-gap flux density distribution.      

The information of ambiguity

The phase space characteristics of a quantum state are best captured by the Wigner distribution. This displays transparently the diagonality information of the density matrix. The complementary function offering transparently the off-diagonal elements is captured by a function called the S-function, or the ambiguity. In carrying the maximal information about the quantum coherences it represents the uncertainties or ambiguity of the diagonal information. Mathematically this is manifested in its role as the phase space moment generating function. Formally it complements the information in the Wigner function. These formal relations provide the starting point for the present investigations. As a measure of quantum uncertainties, ambiguity may be used to define a probability measure on the off-diagonality. The mathematical and physical consistency of this view is presented in this paper. For a pure state, we find the extraordinary result that such distributions are their own Fourier transforms. The physical interpretation of this distribution as a carrier of classical signal fuzziness suggests the introduction of heuristic approximations to the observational uncertainties. We illustrate the properties and interpretation of the ambiguity function by some specific examples. We find that for smooth, ‘Gaussian-like’ distributions, the heuristic considerations provide good approximations. On the other hand, representing quantum interferences, the ambiguity serves as the most positive probe for the ultimate quantum structures which have been called sub-Planckian. They are interesting because it has been argued that such structures are physically observable.     

Tests of Pore-Size Distributions Deduced from Inversion of Simulated and Real Adsorption Data

An adsorption isotherm provides indirect information about the geometry of the host material and its interaction with the adsorbed fluid. This paper presents a critical study of the “inversion” of experimental data to elucidate desired information about this geometry. Using Ar and H₂ as representative classical and quantum fluids and a carbon slit-pore geometry, we compare the accuracy of isotherms derived from non-local density functional theory with isotherms from grand canonical Monte Carlo simulations, using a quantum-corrected potential for H₂. We determine the pore size distributions (PSDs) for a series of model and experimental materials by inverting the adsorption integral equation, with the goal of probing the ability of the inversion procedure to reproduce faithfully the input pore size distribution and ascertain the reality of anomalous gaps often deduced in the literature. Drawing from the GCMC simulations, we then explore the concept of effective porous materials, or ‘iso-PSDs’, which have similar adsorption isotherms, despite very different pore size distributions.