一种廉价实用的双积分A/D转换器

介绍用51单片机和通用分立器件构成的双积分A／D转换器，文中给出了详细的源程序清单。     

Inference for pth‐order random coefficient integer‐valued autoregressive processes

Abstract. A pth‐order random coefficient integer‐valued autoregressive [RCINAR(p)] model is proposed for count data. Stationarity and ergodicity properties are established. Maximum likelihood, conditional least squares, modified quasi‐likelihood and generalized method of moments are used to estimate the model parameters. Asymptotic properties of the estimators are derived. Simulation results on the comparison of the estimators are reported. The models are applied to two real data sets.     

土石坝无粘性粗粒料填筑标准和质量评价探讨

土石坝无粘性粗粒料填筑标准往往根据经验确定,而施工质量主要是通过碾压参数控制,理论依据不足。最大干密度和已建工程实践证明表面振动器法最大干密度与实际填筑干密度基本相等,可以直接指导设计和施工,据此提出了设计和施工控制标准;从砂砾石料、堆石料等无粘性粗粒料的特性探讨了填筑标准的适用范围,利用干密度与<5 mm粒径含量关系和填筑干密度,可以准确及时地对照填筑标准作出填筑质量评价结果。     

2，6-萘二甲酸二甲酯在有机溶剂中溶解度的测定与关联

Solubility of dimethyl-2,6-naphthalene dicarboxylate in acetic acid, N,N-dimethylfonnamide, N,N-dimethyl acetamide, dimethyl sulphoxide, and N-methyl-2-ketopyrrolidine were determined using a dynamic method. The measured systems were correlated by UNIFAC group contribution method. A new main group （aromatic ester, ACCOO） was defined to express the activity coefficients of the aromatic ester. New interaction parameters of the ACCOO group were expressed as the first-order function of temperature and were determined from the experimental data. The calculated results for the new interaction parameters were satisfactory. The measured systems were also correlated with the Wilson and 2-h models, and the results were compared with those of the UNIFAC model.     

Restricted overlapping balancing domain decomposition methods and restricted coarse problems for the Helmholtz problem

Overlapping balancing domain decomposition methods and their combination with restricted additive Schwarz methods are proposed for the Helmholtz equation. These new methods also extend previous work on non-overlapping balancing domain decomposition methods toward simplifying their coarse problems and local solvers. They also extend restricted Schwarz methods, originally designed to overlapping domain decomposition and Dirichlet local solvers, to the case of non-overlapping domain decomposition and/or Neumann and Sommerfeld local solvers. Finally, we introduce coarse spaces based on partitions of unity and planes waves, and show how oblique projection coarse problems can be designed from restricted additive Schwarz methods. Numerical tests are presented.     

Stress analysis of pin-loaded woven-glass fiber reinforced epoxy laminate conveying chain components

The aim of this study is to examine the effects of various loading conditions on the stress of a pin-loaded woven-glass fiber reinforced epoxy laminate conveying chain component. A numerical and experimental study was carried out to determine the stress distribution of composite conveying chain components used to convey loads. For the experimental study, an apparatus was developed to simulate chain components in real motion. Two different working conditions of the chain component were investigated. The first condition represents the movement of the chain components without loading. In the second condition, the chain component touches and moves the load. The commercial finite element package ANSYS was used to perform the numerical analysis using a three dimensional eight-noded layered structural solid elements. Chain tensile forces were loaded through pins and chosen as 250, 500, 750, 1000 and 1250 N for the two conditions of chain components. Experimental and numerical studies were compared and discussed for two conditions and five different tensile forces. A good agreement between experimental results and numerical predictions is obtained.     

Simulation of macroscopic material behavior for uniaxial fiber-matrix composites, using a DAE-approach

The macroscopic deformation behavior of a fiber-reinforced aluminum-boron composite is investigated. Different periodic and random arrangements of the microstructure are considered with macroscopic hardening behavior due to the evolution of plastic zones on the microscale being taken into account.

For the solution of the initial boundary value problem, a non-standard algorithm is applied. It consists of the direct solution of the whole set of equations, treating all variables as global quantities. Together with a higher order time integration method (BDF2), an automatic step size control is used in the FEM calculations.     

Genetically optimized fuzzy polynomial neural networks with fuzzy set-based polynomial neurons

In this paper, we propose and investigate a new category of neurofuzzy networks—fuzzy polynomial neural networks (FPNN) endowed with fuzzy set-based polynomial neurons (FSPNs) We develop a comprehensive design methodology involving mechanisms of genetic optimization, and genetic algorithms (GAs) in particular. The conventional FPNNs developed so far are based on the mechanisms of self-organization, fuzzy neurocomputing, and evolutionary optimization. The design of the network exploits the FSPNs as well as the extended group method of data handling (GMDH). Let us stress that in the previous development strategies some essential parameters of the networks (such as the number of input variables, the order of the polynomial, the number of membership functions, and a collection of the specific subset of input variables) being available within the network are provided by the designer in advance and kept fixed throughout the overall development process. This restriction may hamper a possibility of developing an optimal architecture of the model. The design proposed in this study addresses this issue. The augmented and genetically developed FPNN (gFPNN) results in a structurally optimized structure and comes with a higher level of flexibility in comparison to the one we encounter in the conventional FPNNs. The GA-based design procedure being applied at each layer of the FPNN leads to the selection of the most suitable nodes (or FSPNs) available within the FPNN. In the sequel, two general optimization mechanisms are explored. First, the structural optimization is realized via GAs whereas the ensuing detailed parametric optimization is carried out in the setting of a standard least square method-based learning. The performance of the gFPNN is quantified through experimentation in which we use a number of modeling benchmarks—synthetic and experimental data being commonly used in fuzzy or neurofuzzy modeling. The obtained results demonstrate the superiority of the proposed networks over the models existing in the references.     

国家粮储库屋面防水APP卷材施工技术

针对国家粮食储备库的特点，就屋面防水APP卷材热熔法施工的施工准备及工艺流程进行了介绍，提出了具体的施工技术要点及质量通病的防治措施，取得了良好的施工效果。     

高坝风险分析的事件树法

新世纪一批高坝将要在我国开工建设,这对我国的水电能源及国民经济的发展有着不可估量的作用,而高坝建设中,安全性是需要首先保证的。目前对高坝的风险分析方法有主观概率法、客观概率法等。从系统工程的角度出发,采用事件树方法对高坝的风险进行了探索研究,并给出了算例以说明该方法的有效性和实用性。