A comparative study of numerical solutions to non-linear discrete crack modelling of concrete beams involving sharp snap-back

Numerical problems are often encountered in modelling crack propagation in concrete beams using non-linear finite element (FE) analysis, especially when sharp snap-back behaviour in load-displacement relations occurs. This paper firstly identifies 16 arc-length control based numerical strategies based on extensive literature review. They are then used to carefully model the structural behaviour of a four-point single notched shear beam using discrete crack modelling approach in which cracks are represented by interface elements with bilinear softening constitutive laws. Based on extensive FE analyses, detailed comparisons of the merits and demerits of these numerical algorithms are then made. The results indicate that the effectiveness and efficiency of different algorithms may vary considerably from one to another, with the local arc-length based procedures in conjunction with tangential stiffness strategy and reversible unloading model being the most robust.     

A new iterative order reduction (IOR) method for eigensolutions of large structures

Order reduction is a computationally efficient method to estimate some lowest eigenvalues and the corresponding eigenvectors of large structural systems by reducing the order of the original model to a smaller one. But its accuracy is limited to a small range of frequencies that depends on the selection of the retained degrees of freedom. This paper proposes a new iterative order reduction (IOR) technique to obtain accurately the eigensolutions of large structural systems. The technique retains all the inertia terms associated with the removed degrees of freedom. This hence leads to the reduced mass matrix being in an iterated form and the reduced stiffness matrix constant. From these mass and stiffness matrices, the eigensolutions of the reduced system can be obtained iteratively. On convergence the reduced system reproduces the eigensolutions of the original structure. A proof of the convergence property is also presented. Applications of the method to a practical GARTEUR structure as well as a plate have demonstrated that the proposed method is comparable to the commonly used Subspace Iteration method in terms of numerical accuracy. Moreover, it has been found that the proposed method is computationally more efficient than the Subspace Iteration method. Copyright © 2003 John Wiley & Sons, Ltd.     

降低发电装置CO2排放的对策初探

分析了老式与新式发电装置每度电产生CO_2的量,并提出了相应的对策。     

基于Multisim8的压控振荡电路仿真分析

介绍了Multisim8的仿真功能的特点，并通过实例说明了用Multisim8进行仿真分析的具体方法，简单介绍了如何设置参数和进行仿真操作。     

Relating catalyst structure and composition to the water–gas shift activity of Cu–Zn-based mixed-oxide catalysts

In order to investigate the effect of cerium oxide on Cu–Zn-based mixed-oxide catalysts four catalyst samples were characterized by means of XRD, in situ XANES and thermogravimetric analysis. The activity of the catalyst samples was tested for the forward water–gas shift reaction. Cerium oxide was found to increase the crystallinity of the ZnO phase indicating a segregation of the Cu and ZnO phases. The TOF of the water–gas shift reaction based on chemisorption data was found to be independent of composition and preparation conditions of the four catalyst samples. In contrast, the catalyst stability depends on composition and preparation conditions. Cerium oxide impregnated before calcination of the hydrotalcite-based Cu–Zn precursors leads to a more stable water–gas shift catalyst.     

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.     

Robustness of classification rules that incorporate additional information

The discrimination problem for two normal populations with the same covariance matrix when additional information on the population is available is considered. A study of the robustness properties against training sample contamination of classification rules that incorporate this additional information is performed. These rules have received recently attention where their total misclassification probability (TMP) is proved to be lower than Fisher's linear discriminant rule. The results of a simulation study on the TMP which compares the behaviour of the new rules against Fisher's rule and some of its robustified versions under different types of contamination are presented. These results show that the rules that incorporate the additional information not only have lower TMP, but they also prevent against some types of contamination. In order to achieve prevention from all types of contamination a robustifed version of these rules is recommended.     

比较法在房地产开发中的应用

对"比较法"原理和应用情况进行了分析,说明其在房地产开发中能够科学地预测房地产的价格和收益,从而提高财务分析的科学性和权威性,为项目决策提供科学依据,以促进"比较法"在房地产开发中的应用。     

Life cycle of hydroprocessing catalysts and total catalyst management

Hydroprocessing catalysts based on Ni, Co, Mo and W are used in various refinery processing applications where several deactivation mechanisms become of importance (coke formation, active phase sintering, metals deposition, poisoning) in the catalyst's life cycle. The life cycle of commercial hydroprocessing catalysts is very complex and includes the catalyst production, sulfidation, use, oxidative regeneration followed by re-sulfidation and reuse or, if reuse is not possible, recycling or disposal. To understand the changes in catalyst properties taking place during a life cycle, the catalyst quality in the different stages can be best monitored by using advanced analytical techniques. The catalyst's life cycle is further complicated by numerous technical, environmental and organizational issues involved. In principle, different companies can be involved in each of the life cycle steps. Leading catalyst manufacturers, together with specialized firms, offer refineries a total catalyst management concept, starting with the purchase of the fresh catalyst and ending with its final recycling or disposal. Total catalyst management includes a broad range of services, ensuring optimal timing during the change-out process, reliable, smooth and safe operations, minimal downtime and maximum catalyst and unit performance.     

Techno-economic study of different alternatives for biodiesel production

Biodiesel has become an attractive diesel fuel substitute due to its environmental benefits since it can be made from renewable resource. However, the high costs surrounding biodiesel production remains the main problem in making it competitive in the fuel market either as a blend or as a neat fuel. More than 80% of the production cost is associated with the feedstock itself and consequently, efforts are focused on developing technologies capable of using lower-cost feedstocks, such as recycled cooking oils and wastes from animal or vegetable oil processing operations.