预测气液两相分层流界面剪切应力的新方法

针对水平管气液两相分层流界面剪切应力的预测，建立了基于计算流体力学（CFD）方法的剪切滑移壁面模 型，即将气液界面处理为固定的具有均匀剪切应力的水平滑移壁面。利用FLUENT 软件模拟了气相流动，气液界面采 用剪切滑移壁面边界条件，通过对比实验测量的气相流场分布得到气速和界面剪切收敛值，并由收敛值拟合得到界 面摩擦因子与气相雷诺数的关联式。应用这一关联式的预测结果与实验间接测量值吻合较好，并且在气、液相雷诺 数9 4006ReG650 000 和21 0006ReL630 000 范围内优于Taitel 和Dukler 与Sidi-Ali 和Gatignol 模型。表明剪切滑移壁 面模型可以有效地控制关键参数，提高预测效率和精度，为CFD 方法预测气液两相分层流界面剪切应力提供了新的 思路。     

Distance sampling methodology

We consider the method of distance sampling described by Buckland, Anderson, Burnham and Laake in 1993. We explore the properties of the methodology in simple cases chosen to allow direct and accessible comparisons of distance sampling in the design- and model-based frameworks. In particular, we obtain expressions for the bias and variance of the distance sampling estimator of object density and for the expected value of the recommended analytic variance estimator within each framework. These results enable us to clarify aspects of the performance of the methodology which may be of interest to users and potential users of distance sampling.     

Estimating the Size of a Subdomain: An Application in Auditing

This article suggests an alternative to the ratio estimator for estimating the total size of a subdomain of a population. The application that served as the genesis for this work is from auditing. The problem is to estimate the total of sales transactions that are not tax exempt from an audit sample of the population of nontaxed sales transactions. A superpopulation approach, which models the unit's probability of belonging to the subdomain as a function of its size, leads to a family of estimators. The simplest member of this famiiy is one in which that function is specified to be a constant. The optimal estimator for this model performs markedly better than the ratio estimator when the assumption is true and often performs better when it is not, though in that case it is biased. Stratification is shown to reduce this bias and at the same time make the ratio estimator more similar to the optimal estimator. A simulation experiment shows that the theoretical advantages hold in a real audit population.     

The Estimation of Dynamic Bivariate Mixture Models

Watanabe estimated the dynamic bivariate mixture models introduced by Tauchen and Pitts and modified by Andersen using a Bayesian method via Markov chain Monte Carlo techniques. Based on a maximum likelihood method via efficient importance sampling, Liesenfeld and Richard obtained estimates that are significantly different from those of Watanabe. This note corrects the error in the multimove sampler used by Watanabe and reproduces all analyses in the work of Watanabe using a corrected multimove sampler. The estimates using the correct multimove sampler are found to be close to those obtained by Liesenfeld and Richard.     

Bivariate exponential-type distributions with linear regression

Let Xbe a bivariate exponential-type random vector (BIDLIKAR, PATIL (1968)), than it is proved:

1. If P(X ≥0) = 1 is valid, then Xhas linear regression to both directions if and only if Xpossesses a symmetric Γ-distribution.

2. Xpossesses linear regression to both directions with constant regression coefficients (independent of the parameter vector ? of the exponential-type distribution (BIDLIKAR, PATIL (1968)) if and only if Xis normal distributed.     

Effect of systematic sampling on arima models

Given a general homogeneous non-stationary autoregressive integrated moving average process ARIMA(p,d,q), the corresponding model for the subseries obtained by a systematic sampling is derived. The article then shows that the sampled subseries approaches approximately to an integrated moving average process IMA(d,l), l≤(d-l), regardless of the autoregressive and moving average structures in the original series. In particular, the sampled subseries from an ARIMA (p,l,q) process approaches approximately to a simple random walk model.     

The general class of chain estimators for the ratio of two means using double sampling

A wider class of chain based estimators for the ratio of two means of a finite population has been proposed by using two auxiliary variables. Singh et al.(1994) is a particular case of this class.     

A generalized improvement procedure for variance bounds for minimum variance unbiased estimator in inverse sampling

New bounds are obtained for the variance of the minimum variance unbiased estimator of p i n inverse sampling. A generalized procedure for further improving the bounds is also discussed.     

A general class of hierarchical ordinal regression models with applications to correlated roc analysis

The authors discuss a general class of hierarchical ordinal regression models that includes both location and scale parameters, allows link functions to be selected adaptively as finite mixtures of normal cumulative distribution functions, and incorporates flexible correlation structures for the latent scale variables. Exploiting the well‐known correspondence between ordinal regression models and parametric ROC (Receiver Operating Characteristic) curves makes it possible to use a hierarchical ROC (HROC) analysis to study multilevel clustered data in diagnostic imaging studies. The authors present a Bayesian approach to model fitting using Markov chain Monte Carlo methods and discuss HROC applications to the analysis of data from two diagnostic radiology studies involving multiple interpreters.     

On designing an acceptance sampling plan for the Pareto lifetime model

In this paper, the design of reliability sampling plans for the Pareto lifetime model under progressive Type-II right censoring is considered. Sampling plans are derived using the decision theoretic approach with a suitable loss or cost function that consists of sampling cost, rejection cost, and acceptance cost. The decision rule is based on the estimated reliability function. Plans are constructed within the Bayesian context using the natural conjugate prior. Simulations for evaluating the Bayes risk are carried out and the optimal sampling plans are reported for various sample sizes, observed number of failures and removal probabilities.