PZT陶瓷的断裂分析

与有限元法相比,无网格法由于只需节点不用单元而在压电分析中具有优越性。采用一个简单的包含有极化反转及电饱和影响的锆钛酸铅系压电陶瓷(PZT)的本构模型,以局部J积分作为断裂准则,应用再生核点法这一无网格数值法导出了作用电场与断裂载荷的关系曲线,该曲线的趋势与Park[1]的实验观察现象一致。计算程序采用面向对象方法实现。     

可拓知识空间和可拓知识网格模型(Ⅱ):可拓知识网格

第1部分中已介绍了可拓知识空间定义和相关操作，以及可拓知识空间关联函数计算方法。这一部分进一步建立可拓知识空间语义网、可拓知识网格和可拓知识网格服务，并给出实例和相关的分析讨论。     

An explicit finite difference method for finite-time observers

In this paper we present a numerical method for estimating the current state of a nonlinear control system. We use finite differences to discretize a modified version of the finite-time observer equations in James. The discretized equations are simple and easily programmed. The convergence and accuracy of the scheme is proved, and the scheme enjoys a number of important properties: availability of rate of convergence estimates, good robustness characteristics, and the ability to handle certain types of discontinuities in the observations. The major disadvantage is that the number of grid points required increases exponentially with the number of state dimensions.     

A method of identifying latent human errors in work systems

Work system improvements are implemented in various manufacturing processes to prevent problems caused by human errors. However, they are almost always applied to problems which have already occurred. This paper examines a method of identifying latent human errors existing within the work systems beforehand. A procedure for applying failure mode and effect analysis to this identification problem was defined based on over 1000 empirical errors: a work system decomposition criterion and fundamental error modes for listing latent human errors, and then applied to three practical manufacturing processes in order to evaluate its effectiveness.     

Prediction of swirling confined diffusion flame with a Monte Carlo and a presumed-PDF-model

This work aims to compare numerical results obtained by using the Monte Carlo composition-PDF method and a presumed-β-PDF in order to reveal their effects on the prediction of flow and scalar fields in swirling confined methane diffusion flame. Using the intrinsic low dimensional manifolds method for modelling the chemistry and a second moment closure for the turbulence, it is shown that both PDF-methods provide a similar accuracy level of the prediction of mean quantities. While the presumed-β-PDF performs using reasonable computational efforts, the Monte Carlo-PDF allows to capture well the turbulence-chemistry interaction and strong finite-chemistry effects such as local extinction.     

N.m.r. line shape-relaxation correlation analysis of bitumen and oil sands

The first results of the analysis of bitumen and oil sands using the recently developed n.m.r. spingrouping technique are presented. The n.m.r. relaxation experiments were carried out on bitumen, and on natural and dried oil sands samples. The results indicate that the spin-grouping can resolve and quantify several components of the samples studied. The bitumen and bitumen fraction of the oil sands are resolved according to their spin-spin relaxation times into three major groups: solid-like (rigid), solid-like (mobile) and semi-liquid. The water in the oil sands exists in two different environments. Tentatively one environment is assigned to be the bridges between the sand grains, while the other is assigned to be the clay surface. One can conclude that with spin grouping of complex mixtures the decomposition (in which components are resolved according to their dynamic state) is possible. The accuracy of such resolution is of the order of a few per cent.     

Salt-water up-coning during extraction of fresh water from a tropical island

Rainwater can collect in a lens-shaped region within the rock of a tropical island, and may be separated from the underlying salt water by a sharp interface. This paper presents a nonlinear theory for determining the shape of this interface. The island is assumed to be saturated with rain, and provision is made for the outflow of rain-water through the sides of the island. The effect of a bore well on the shape of the interface is investigated, and the problem is solved using a spectral method. An integral-equation method is also presented for the case when the island has infinite width.     

A note on the satisfaction of the boundary conditions for Chebyshev collocation methods in rectangular domains

The way boundary conditions are imposed when applying Chebyshev collocation methods to Poisson and biharmonic-type problems in rectangular domains is investigated. It is shown that careful selection of the number of collocation points leads to a linear system ofn linearly independent equations inn unknowns.     

A Bayesian propensity score adjustment for latent variable modeling and MCMC algorithm

The estimation of the differences among groups in observational studies is frequently inaccurate owing to a bias caused by differences in the distributions of covariates. In order to estimate the average treatment effects when the treatment variable is binary, Rosenbaum and Rubin [1983. The central role of the propensity score in observational studies for causal effects. Biometrika 70, 41-55] proposed an adjustment method for pre-treatment variables using propensity scores. Imbens [2000. The role of the propensity score in estimating dose-response functions. Biometrika 87, 706-710] extended the propensity score methodology for estimation of average treatment effects with multivalued treatments.However, these studies focused only on estimating the marginal mean structure. In many substantive sciences such as the biological and social sciences, a general estimation method is required to deal with more complex analyses other than regression, such as testing group differences on latent variables. For latent variable models, the EM algorithm or the traditional Monte Carlo methods are necessary. However, in propensity score adjustment, these methods cannot be used because the full distribution is not specified.In this paper, we propose a quasi-Bayesian estimation method for general parametric models that integrate out the distributions of covariates using propensity scores. Although the proposed Bayes estimates are shown to be consistent, they can be calculated by existing Markov chain Monte Carlo methods such as Gibbs sampler. The proposed method is useful to estimate parameters in latent variable models, while the previous methods were unable to provide valid estimates for complex models such as latent variable models.We also illustrated the procedure using the data obtained from the US National Longitudinal Survey of Children and Youth (NLSY1979-2002) for estimating the effect of maternal smoking during pregnancy on the development of the child's cognitive functioning.