钢丝绳结构及工艺集成设计系统

针对钢丝绳实际生产需要,提出基于钢丝绳结构理论设计基础的结构与工艺集成设计系统框架,建立钢丝绳结构设计、性能分析及间隙计算的理论模型,并利用相关数据进行理论值与实际值分析,完成钢丝绳性能参数的敏感性分析模型和理论修正模型,为钢丝绳结构设计与工艺设计的并行处理提供了理论上的指导,最终实现钢丝绳的智能设计与制造

Construction of habitat suitability models (HSMs) for benthic macroinvertebrate and their applications to instream environmental flows: A case study in Xiangxi River of Three Gorges Reservior region, China

Based on a long-term ecological monitoring, the present study chose the most dominant benthic macroinvertebrate (Baetis spp.) as target organisms in Xiangxi River, built the habitat suitability models (HSMs) for water depth, current velocity and substrate, respectively, which is the first aquatic organisms model for habitat suitability in the Chinese Mainland with a long-term consecutive in situ measurement. In order to protect the biointegrity and function of the river ecosystem, the theory system of instream environmental flow should be categorized into three hierarchies, namely minimum required instream flow (hydrological level), minimum instream environmental flow (biospecies level), and optimum instream environmental flow (ecosystem level). These three hierarchies of instream environmental flow models were then constructed with the hydrological and weighted usable area (WUA) method. The results show that the minimum required instream flow of Xiangxi River calculated by the Tennant method (10% of the mean annual flow) was 0.615 m(3) s(-1); the minimum instream environmental flow accounted for 19.22% of the mean annual flow (namely 1.182 m(3) s(-1)), which was the damaged river channel. ow in the dry season; and 42.91% of the mean annual flow (namely 2.639 m(3) s(-1)) should be viewed as the optimum instream environmental flow in order to protect the health of the river ecosystem, maintain the instream biodiversity, and reduce the impact of small hydropower stations nearby the Xiangxi River. We recommend that the hydrological and biological methods can help establish better instream environmental. ow models and design best management practices for use in the small hydropower station project. (C) 2008 National Natural Science Foundation of China and Chinese Academy of Sciences. Published by Elsevier Limited and Science in China Press. All rights reserved.

Discussion on the basic mathematical models of neurons - Double synaptic weight neuron in general-purpose neurocomputer, theory and application

Based on the introduction of the traditional mathematical models of neurons in general-purpose neurocomputer, a novel all-purpose mathematical model-Double synaptic weight neuron (DSWN) is presented, which can simulate all kinds of neuron architectures, including Radial-Basis-Function (RBF) and Back-propagation (BP) models, etc. At the same time, this new model is realized using hardware and implemented in the new CASSANN-II neurocomputer that can be used to form various types of neural networks with multiple mathematical models of neurons. In this paper, the flexibility of the new model has also been described in constructing neural networks and based on the theory of Biomimetic pattern recognition (BPR) and high-dimensional space covering, a recognition system of omni directionally oriented rigid objects on the horizontal surface and a face recognition system had been implemented on CASSANN-H neurocomputer. The result showed DSWN neural network has great potential in pattern recognition.

Theory and Application of the Transient Injection Well Test

Based on the theory of the pumping well test, the transient injection well test was suggested in this paper. The design method and the scope of application are discussed in detail. The mathematical models are developed for the short-time and long-time transient injection test respectively. A double logarithm type curve matching method was introduced for analyzing the field transient injection test data. A set of methods for the transient injection test design, experiment performance and data analysis were established. Some field tests were analyzed, and the results show that the test model and method are suitable for the transient injection test and can be used to deal with the real engineering problems.

Statistical analysis of synthetic earthquake catalogs generated by models with various levels of fault zone disorder

The stress release model, a stochastic version of the elastic rebound theory, is applied to the large events from four synthetic earthquake catalogs generated by models with various levels of disorder in distribution of fault zone strength (Ben-Zion, 1996) They include models with uniform properties (U), a Parkfield-type asperity (A), fractal brittle properties (F), and multi-size-scale heterogeneities (M). The results show that the degree of regularity or predictability in the assumed fault properties, based on both the Akaike information criterion and simulations, follows the order U, F, A, and M, which is in good agreement with that obtained by pattern recognition techniques applied to the full set of synthetic data. Data simulated from the best fitting stress release models reproduce, both visually and in distributional terms, the main features of the original catalogs. The differences in character and the quality of prediction between the four cases are shown to be dependent on two main aspects: the parameter controlling the sensitivity to departures from the mean stress level and the frequency-magnitude distribution, which differs substantially between the four cases. In particular, it is shown that the predictability of the data is strongly affected by the form of frequency-magnitude distribution, being greatly reduced if a pure Gutenburg-Richter form is assumed to hold out to high magnitudes.

Study of three elastic-plastic constitutive models by non-proportional finite deformations of OFHC copper

Experimental stress-strain data of OFHC copper first under torsion to 13% and then under torsion-tension to about 10% are used to study the characteristics of three elastic-plastic constitutive models: Chaboche's super-positional nonlinear model, Dafalias and Popov's two surface model and Watanabe and Atluri's version of the endochronic model. The three models, originally oriented for infinitesimal deformation, have been extended for finite deformation. The results show (a) the Mises-type yield surface used in the three models brings about significant departure of the predictions from the experimental data; (b) Chaboche's and Dafalias' models are easier than Watanabe and Atluri's model in determining the material parameters in them, and (c) Chaboche's and Watanabe & Atluri's models produce almost the same prediction to the data, while Dafalias' model cannot accurately predict the plastic deformations when a loading path changes in its direction. Copyright (C) 1996 Elsevier Science Ltd

Deformation Of Pdms Membrane And Microcantilever By A Water Droplet: Comparison Between Mooney-Rivlin And Linear Elastic Constitutive Models

In this paper, we studied the role of vertical component Of Surface tension of a water droplet on the deformation of membranes and microcantilevers (MCLs) widely used in lab-on-a-chip and micro-and nano-electromechanical system (MEMS/NEMS). Firstly, a membrane made of a rubber-like material, poly(dimethylsiloxane) (PDMS), was considered. The deformation was investigated using the Mooney-Rivlin (MR) model and the linear elastic constitutive relation, respectively. By comparison between the numerical solutions with two different models, we found that the simple linear elastic model is accurate enough to describe such kind of problem, which would be quite convenient for engineering applications. Furthermore, based on small-deflection beam theory, the effect of a liquid droplet on the deflection of a MCL was also studied. The free-end deflection of the MCL was investigated by considering different cases like a cylindrical droplet, a spherical droplet centered on the MCL and a spherical droplet arbitrarily positioned on the MCL. Numerical simulations demonstrated that the deflection might not be neglected, and showed good agreement with our theoretical analyses. (C) 2008 Elsevier Inc. All rights reserved.

Stocking models of Chinese mitten crab (Eriocheir japonica sinensis) in Yangtze lakes

The fanning of Chinese mitten crab, a quality aquatic product in China and neighbouring Asian countries, has been developing rapidly in China since last decade. It reached a total yield of 3.4 X 10(5) tonnes in 2002. Due to the successive over-stocking year after year, many lakes in the mid-lower Yangtze Basin, the main farming area, are under deterioration, leading to a reduction of crab yield and quality, and, subsequently, a loss of fanning profits. Aiming at a normal development of crab culture and the sustainable use of lakes, an annual investigation dealing with lake environmental factors in relation to stocked crab populations was carried out at 20 farms in 4 lakes. The results show that the submersed macrophyte biomass (B-Mac) is the key factor affecting annual crab yield (CY). Using the ratio of Secchi depth to mean depth (Z(SD)/Z(M)), an easily measured parameter closely correlated to BMac, as driving variable, 10 regression models of maximal crab yields were generated (r(2) ranging 0.49-0.81). Based on the theory of MSY (Maximum Sustainable Yield), in combination with body-weight (BW) and recapture rate (RR) of adult crabs, a general optimal stocking model was eventually formulated. All models are simple and easy to operate. Comments on their applications and prospects are given in brief. (c) 2006 Elsevier B.V. All rights reserved.

Environmental threats to children's health in Southeast Asia and the Western Pacific

The Southeast Asia and Western Pacific regions contain half of the world's children and are among the most rapidly industrializing regions of the globe. Environmental threats to children's health are widespread and are multiplying as nations in the area undergo industrial development and pass through the epidemiologic transition. These environmental hazards range from traditional threats such as bacterial contamination of drinking water and wood smoke in poorly ventilated dwellings to more recently introduced chemical threats such as asbestos construction materials; arsenic in groundwater; methyl isocyanate in Bhopal, India; untreated manufacturing wastes released to landfills; chlorinated hydrocarbon and organophosphorous pesticides; and atmospheric lead emissions from the combustion of leaded gasoline. To address these problems, pediatricians, environmental health scientists, and public health workers throughout Southeast Asia and the Western Pacific have begun to build local and national research and prevention programs in children's environmental health. Successes have been achieved as a result of these efforts: A cost-effective system for producing safe drinking water at the village level has been devised in India; many nations have launched aggressive antismoking campaigns; and Thailand, the Philippines, India, and Pakistan have all begun to reduce their use of lead in gasoline, with resultant declines in children's blood lead levels. The International Conference on Environmental Threats to the Health of Children, held in Bangkok, Thailand, in March 2002, brought together more than 300 representatives from 35 countries and organizations to increase awareness on environmental health hazards affecting children in these regions and throughout the world. The conference, a direct result of the Environmental Threats to the Health of Children meeting held in Manila in April 2000, provided participants with the latest scientific data on children's vulnerability to environmental hazards and models for future policy and public health discussions on ways to improve children's health. The Bangkok Statement, a pledge resulting from the conference proceedings, is an important first step in creating a global alliance committed to developing active and innovative national and international networks to promote and protect children's environmental health.

Correcting the systematic error of the density functional theory calculation: the alternate combination approach of genetic algorithm and neural network

The alternate combinational approach of genetic algorithm and neural network (AGANN) has been presented to correct the systematic error of the density functional theory (DFT) calculation. It treats the DFT as a black box and models the error through external statistical information. As a demonstration, the AGANN method has been applied in the correction of the lattice energies from the DFT calculation for 72 metal halides and hydrides. Through the AGANN correction, the mean absolute value of the relative errors of the calculated lattice energies to the experimental values decreases from 4.93% to 1.20% in the testing set. For comparison, the neural network approach reduces the mean value to 2.56%. And for the common combinational approach of genetic algorithm and neural network, the value drops to 2.15%. The multiple linear regression method almost has no correction effect here.

Double synaptic weight neuron theory and its application

In this paper, a novel mathematical model of neuron-Double Synaptic Weight Neuron (DSWN)(l) is presented. The DSWN can simulate many kinds of neuron architectures, including Radial-Basis-Function (RBF), Hyper Sausage and Hyper Ellipsoid models, etc. Moreover, this new model has been implemented in the new CASSANN-II neurocomputer that can be used to form various types of neural networks with multiple mathematical models of neurons. The flexibility of the DSWN has also been described in constructing neural networks. Based on the theory of Biomimetic Pattern Recognition (BPR) and high-dimensional space covering, a recognition system of omni directionally oriented rigid objects on the horizontal surface and a face recognition system had been implemented on CASSANN-II neurocomputer. In these two special cases, the result showed DSWN neural network had great potential in pattern recognition.

Information geometry theory of high-dimension space and application for speaker independent continuous digit speech recognition

In the light of descriptive geometry and notions in set theory, this paper re-defines the basic elements in space such as curve and surface and so on, presents some fundamental notions with respect to the point cover based on the High-dimension space (HDS) point covering theory, finally takes points from mapping part of speech signals to HDS, so as to analyze distribution information of these speech points in HDS, and various geometric covering objects for speech points and their relationship. Besides, this paper also proposes a new algorithm for speaker independent continuous digit speech recognition based on the HDS point dynamic searching theory without end-points detection and segmentation. First from the different digit syllables in real continuous digit speech, we establish the covering area in feature space for continuous speech. During recognition, we make use of the point covering dynamic searching theory in HDS to do recognition, and then get the satisfying recognized results. At last, compared to HMM (Hidden Markov models)-based method, from the development trend of the comparing results, as sample amount increasing, the difference of recognition rate between two methods will decrease slowly, while sample amount approaching to be very large, two recognition rates all close to 100% little by little. As seen from the results, the recognition rate of HDS point covering method is higher than that of in HMM (Hidden Markov models) based method, because, the point covering describes the morphological distribution for speech in HDS, whereas HMM-based method is only a probability distribution, whose accuracy is certainly inferior to point covering.

Cognitive models in biomimetic pattern cognition

We describe a new model which is based on the concept of cognizing theory. The method identifies subsets of the data which are embedded in arbitrary oriented lower dimensional space. We definite k-mean covering, and study its property. Covering subsets of points are repeatedly sampled to construct trial geometry space of various dimensions. The sampling corresponding to the feature space having the best cognition ability between a mode near zero and the rest is selected and the data points are partitioned on the basis of the best cognition ability. The repeated sampling then continues recursively on each block of the data. We propose this algorithm based on cognition models. The experimental results for face recognition demonstrate that the correct rejection rate of the test samples excluded in the classes of training samples is very high and effective.

Trace theory

The concept of traces has been introduced for describing non-sequential behaviour of concurrent systems via its sequential observations. Traces represent concurrent processes in the same way as strings represent sequential ones. The theory of traces can be used as a tool for reasoning about nets and it is hoped that applying this theory one can get a calculus of the concurrent processes anologous to that available for sequential systems. The following topics will be discussed: algebraic properties of traces, trace models of some concurrency phenomena, fixed-point calculus for finding the behaviour of nets, modularity, and some applications of the presented theory.

Biomimetic (topological) pattern recognition - A new model of pattern recognition theory and its application

A new theoretical model of Pattern Recognition principles was proposed, which is based on "matter cognition" instead of "matter classification" in traditional statistical Pattern Recognition. This new model is closer to the function of human being, rather than traditional statistical Pattern Recognition using "optimal separating" as its main principle. So the new model of Pattern Recognition is called the Biomimetic Pattern Recognition (BPR)(1). Its mathematical basis is placed on topological analysis of the sample set in the high dimensional feature space. Therefore, it is also called the Topological Pattern Recognition (TPR). The fundamental idea of this model is based on the fact of the continuity in the feature space of any one of the certain kinds of samples. We experimented with the Biomimetic Pattern Recognition (BPR) by using artificial neural networks, which act through covering the high dimensional geometrical distribution of the sample set in the feature space. Onmidirectionally cognitive tests were done on various kinds of animal and vehicle models of rather similar shapes. For the total 8800 tests, the correct recognition rate is 99.87%. The rejection rate is 0.13% and on the condition of zero error rates, the correct rate of BPR was much better than that of RBF-SVM.