矩量法研究平面波导点缺陷引起的散射损耗

对平面波导工艺过程里出现的点缺陷,如气泡、灰尘颗粒等对平面波导内光场造成的散射提供了一种简单而又实用的计算方法。计算基于格林函数方法,并利用矩量法求解积分方程,采用分块矩阵优化算法,使得算法的计算时间直接与点缺陷大小相关,提高了效率。证明了一定大小的点缺陷在特定的波长处会产生很大的散射损耗,证明点缺陷的散射损耗依赖于缺陷大小和光学性质而与其在波导中的位置无直接关系。以二氧化硅平面波导为例,分析了对中心波长1．55μm的入射光场,分别存在气泡和灰尘颗粒两种点缺陷时,散射损耗随点缺陷大小的关系特性,指出工艺过程特别应该避免某些孔径的点缺陷。     

平板混合层流动中两相脉动关联矩的大涡模拟

在气粒两相平板混合层流动中,对气相流动采用大涡模拟,对颗粒相流动采用轨道模拟,研究了两相脉动关联矩。由两相各自瞬时速度出发可以直接获得两相脉动关联矩的统计结果。模拟获得的颗粒相一阶矩、二阶矩以及两相脉动关联矩与实验结果定量符合,表明基于细观模拟是不通过模型获得和研究两相脉动关联矩的可行途径。     

Extended Fisher-Kolmogorov系统的渐近吸引子

考虑了ExtendedFisher-Kolmogorov系统的解的长时间行为,构造了一个有限维解序列即该系统的渐近吸引子,证明了它在长时间后无限趋于方程的整体吸引子,并给出了渐近吸引子的维数估计.     

积分微分方程的一个高精度导数恢复公式

A highly accurate derivative recovery formula is presented for the korder finite element approximations to integro-differential equations. This formula possesses O(h^k l) order of superconvergence on the whole domain in L∞ norm and O(h^2k) order of ultraconvergence at the mesh points, respectively, and the same type of results are demonstrated for the semi-discrete finite element approximates solutions of Sobolev equations.     

Structural Characterization of Volatile Components of Rosa Banksiae Ait for Estimation and Prediction of Their Linear Retention Indices and Retention Times

The molecular electronegativity-distance vector （MEDV） was used to describe the molecular structure of volatile components of Rosa banksiae Ait, and QSRR model was built up by use of multiple linear regression （MLR）. Furthermore, in virtue of variable screening by the stepwise multiple regression technique, the QSRR models of 10 and 6 variables and linear retention index （LRI） 10, 7 and 6 varieables were built up by combinating MEDV with the Ultra2 column GC retention time （tR） of 53 volatile components of Rosa Banksiae Air. The multiple correlation coefficients （R） of modeling calculation values of QSRR model were 0.906, 0.906, 0.949, 0.943 and 0.949, respectively. The cross-verification multiple correlation coefficients （RCV） were 0.903, 0.904, 0.867, 0.901 and 0.904, respectively. The results show that the models constructed could provide estimation stability and favorable predictive ability.     

A novel correlation for estimation of hydrate forming condition of natural gases

An inherent problem with natural gas production or transmission is the formation of gas hydrates, which can lead to safety hazards to production/ transportation systems and to substantial economic risks. Therefore, an understanding of conditions where hydrates form is necessary to overcome hydrate related issues. Over the years, several models requiring more complicated and longer computations have been proposed for the prediction of hydrate formation conditions of natural gases. For these reasons, it is essential to develop a reliable and simple-to-use method for oil and gas practitioners. The purpose of this study is to formulate a novel empirical correlation for rapid estimation of hydrate formation condition of sweet natural gases. The developed correlation holds for wide range of temperatures (265–298 K), pressures (1200 to 40000 kPa) and molecular weights (16−29). New proposed correlation shows consistently accurate results across proposed pressure, temperature and molecular weight ranges. This consistency could not be matched by any of the widely accepted existing correlations within the investigated range. For all conditions, new correlation showed average absolute deviation to be less than 0.2% and provided much better results than the widely accepted existing correlations.     

Carleman Estimates for Parabolic Equations with Nonhomogeneous Boundary Conditions

The authors prove a new Carleman estimate for general linear second order parabolic equation with nonhomogeneous boundary conditions. On the basis of this estimate, improved Carleman estimates for the Stokes system and for a system of parabolic equations with a penalty term are obtained. This system can be viewed as an approximation of the Stokes system.     

Efficient estimation for semiparametric varying- coefficient partially linear regression models with current status data

This article considers a semiparametric varying-coefficient partially linear regression model with current status data. The semiparametric varying-coefficient partially linear regression model which is a generalization of the partially linear regression model and varying-coefficient regression model that allows one to explore the possibly nonlinear effect of a certain covariate on the response variable. A Sieve maximum likelihood estimation method is proposed and the asymptotic properties of the proposed estimators are discussed. Under some mild conditions, the estimators are shown to be strongly consistent. The convergence rate of the estimator for the unknown smooth function is obtained and the estimator for the unknown parameter is shown to be asymptotically efficient and normally distributed. Simulation studies are conducted to examine the small-sample properties of the proposed estimates and a real dataset is used to illustrate our approach.     

New differential properties of sup-type functions

In this paper, we study the directional derivative, subderivative, and subdifferential of sup-type functions without any compactness assumption on the index set. As applications, we provide an estimate of the Lipschitz modulus for sup-type functions.     

A note on parameter estimations of panel vector autoregressive models with intercorrelation

This note considers parameter estimation for panel vector autoregressive models with intercorrelation. Conditional least squares estimators are derived and the asymptotic normality is established. A simulation is carried out for illustration.