某高架桥分岔处局部应力分析

对某高架桥分岔处局部应力进行仿真分析。按照实际施工过程,考虑最不利计算荷载,根据平截面假定,分别对钢梁单独受力和钢-混凝土组合梁两种工况进行计算。结果表明分岔处整体受力良好,安全储备大。     

新型复合吸附干燥剂的吸附动力学特性研究

研制的一种由粗孔球形硅胶和氯化钙组成的新型复合吸附干燥剂SiO2.xH2O.yCaC l2与常用的干燥剂相比具有更好的吸水除湿性能.采用理论分析与实验验证的方法分析了新型复合吸附剂的吸附动力学特性及其影响因素,并建立了传质数学模型.研究结果表明,外扩散过程是传质的主要阻力,增大风速、减小吸附剂颗粒直径是减少传质阻力的有效措施.     

硅藻土-聚丙烯酰胺系高吸水性复合材料的研制

以丙烯酸和硅藻土为原料，用溶液法合成复合高吸水性树脂，同时对影响聚合产物吸水量的各种因素进行了研究．结果表明，当硅藻土、淀粉、NaOH、引发剂和交联剂的加入量的质量分数分别为30％、30％、60％、1．5％及0．03％时，制得的超吸水性复合材料的吸水量最高，可达611g/g．硅藻土作为一种功能填料，改善了复合材料的综合吸水性能．     

钢-混凝土双面结合梁界面在集中荷载作用下的滑移表达

钢-混凝土双面结合梁在内支座负弯矩区设置下翼缘钢筋混凝土板,并通过剪力连接件与钢梁共同作用,从而提高了梁的刚度和承载力。运用基本力学方法对钢-混凝土双面结合梁在使用荷载作用阶段的滑移效应进行探索性分析,推导得到集中荷载作用下负弯矩区上、下界面滑移及滑移应变沿梁长分布的表达式。     

硕士研究生入学面试评价方法研究

本文根据硕士研究生入学面试的要求,建立了一套硕士研究生入学面试评价指标体系,给出了各评价指标的权重系数,并提出了应用模糊综合评价方法与加法合成法相结合进行硕士研究生入学面试评分的方法。     

Orthogonally Blocked Mixture Experiments in Ellipsoidal Restricted Regions

In practical situations involving mixtures formed from several ingredients, interest is sometimes centered on the response in an ellipsoidal neighborhood around a standard formulation. We show that standard, orthogonally blocked, response surface designs, defined on a q ? 1 dimensional unit sphere, may be transformed into similarly orthogonally blocked q-ingredient mixture designs defined within an ellipsoid centered at the standard formulation. The method is illustrated using several examples of mixture experiments with three, four, and five ingredients, arranged in two, three, or four orthogonal blocks, obtained by projecting standard central composite designs and Box–Behnken designs into the ellipsoidal mixture region. Rotations of the resulting designs within the ellipsoidal regions are also considered.     

Construction of uniform designs for mixture experiments with complex constraints

Abstract

Mixture experiments have attracted increasingly attention due to their great practical value in production and living, while uniform designs over irregular experimental regions have become a hot topic in the area of experimental designs in the past two decades. Noting that the experimental region of a mixture experiment with q components under some constraints is in fact a (q ? 1)-dimensional geometry, this article proposes a new method for searching nearly uniform designs for mixture experiments with any complex constraints. Two examples with some tables and figures are given to illustrate this method.     

Sequential procedures in identification

In this paper we study the problem of identifying a popula-tion with one of the two populations, with an aim to control both types of errors. We assume that the populations are normal with unknown means, but with unit variance. We have cited examples from anthropological studies where our formulation of the problem fits in quite nicely. We observe that SPRT’s based on the maximal invariant may not terminate with probability one. Simulation studies reported here show a substantial saving in the average number of samples compared to the best invariant fixed sample test.     

Weighted local linear composite quantile estimation for the case of general error distributions

It is known that for nonparametric regression, local linear composite quantile regression (local linear CQR) is a more competitive technique than classical local linear regression since it can significantly improve estimation efficiency under a class of non-normal and symmetric error distributions. However, this method only applies to symmetric errors because, without symmetric condition, the estimation bias is non-negligible and therefore the resulting estimator is inconsistent. In this paper, we propose a weighted local linear CQR method for general error conditions. This method applies to both symmetric and asymmetric random errors. Because of the use of weights, the estimation bias is eliminated asymptotically and the asymptotic normality is established. Furthermore, by minimizing asymptotic variance, the optimal weights are computed and consequently the optimal estimate (the most efficient estimate) is obtained. By comparing relative efficiency theoretically or numerically, we can ensure that the new estimation outperforms the local linear CQR estimation. Finite sample behaviors conducted by simulation studies further illustrate the theoretical findings.     

Composite Marginal Likelihoods to the Normal Bradley-Terry Model

Inference in generalized linear mixed models with crossed random effects is often made cumbersome by the high-dimensional intractable integrals involved in the marginal likelihood. This article presents two inferential approaches based on the marginal composite likelihood for the normal Bradley-Terry model. The two approaches are illustrated by a simulation study to evaluate their performance. Thereafter, the asymptotic variances of the estimated variance component are compared.