Three-Dimensional Network Model And Its Parameter Calibration

A material model, whose framework is parallel spring-bundles oriented in 3-D space, is proposed. Based on a discussion of the discrete schemes and optimum discretization of the solid angles, a 3-D network cell consisted of one-dimensional components is developed with its geometrical and physical parameters calibrated. It is proved that the 3-D network model is able to exactly simulate materials with arbitrary Poisson ratio from 0 to 1/2, breaking through the limit that the previous models in the literature are only suitable for materials with Poisson ratio from 0 to 1/3. A simplified model is also proposed to realize high computation accuracy within low computation cost. Examples demonstrate that the 3-D network model has particular superiority in the simulation of short-fiber reinforced composites.

Comparisons of static, quasi-static and dynamic 3D porous media scale network models for two-phase immiscible flow in porous media

A dynamic 3D pore-scale network model is formulated for investigating the effect of interfacial tension and oil-water viscosity during chemical flooding. The model takes into account both viscous and capillary forces in analyzing the impact of chemical properties on flow behavior or displacement configuration, while the static model with conventional invasion percolation algorithm incorporates the capillary pressure only. From comparisons of simulation results from these models. it indicates that the static pore scale network model can be used successfully when the capillary number is low. With the capillary increases due to the enhancement of water viscosity or decrease of interfacial tension, only the quasi-static and dynamic model can give insight into the displacement mechanisms.

Processing network models of energy/environment systems

Processing networks are a variant of the standard linear programming network model which are especially useful for optimizing industrial energy/environment systems. Modelling advantages include an intuitive diagrammatic representation and the ability to incorporate all forms of energy and pollutants in a single integrated linear network model. Added advantages include increased speed of solution and algorithms supporting formulation. The paper explores their use in modelling the energy and pollution control systems in large industrial plants. The pollution control options in an ethylene production plant are analyzed as an example. PROFLOW, a computer tool for the formulation, analysis, and solution of processing network models, is introduced.

Using the RBFN model and GIS technique to assess wind erosion hazard of inner Mongolia, China

Soil wind erosion is the primary process and the main driving force for land desertification and sand-dust storms in and and semi-arid areas of Northern China. While many researchers have studied this issue, this study quantified the various indicators of soil wind erosion, using the GIS technology to extract the spatial data and to construct a RBFN (Radial Basis Function Network) model for Inner Mongolia. By calibrating sample data of the different levels of wind erosion hazard, the model parameters were established, and then the assessment of wind erosion hazard. Results show that in the southern parts of Inner Mongolia wind erosion hazards are very severe, counties in the middle regions of Inner Mongolia vary from moderate to severe, and in eastern are slight. Comparison of the results with other research shows conformity with actual conditions, proving the reasonability and applicability of the RBFN model. Copyright (C) 2007 John Wiley & Sons, Ltd.

Prediction of molar absorptivities of color reagents during their color reactions with cerium using multiple regression analysis and neural network

A quantitative structure-property study has been made on the relationship between molar absorptivities (epsilon) of asymmetrical phosphone bisazo derivatives of chromotropic acid and their color reactions with cerium by multiple regression analysis and neural network. The new topological indices A(x1) - A(x3) suggested in our laboratory and molecular connectivity indices of 43 compounds have been calculated. The results obtained from the two methods are compared. The neural network model is superior to the regression analysis technique and gave a prediction which was sufficiently accurate to estimate the molar absorptivities of color reagents during their color reactions with cerium.

A pseudo-plastic engagement effect on the toughening of discontinuous fiber-reinforced brittle composites

In brittle composites, such as whisker reinforced ceramics, the sliding of reinforcing fibers against the frictional resistance of matrix is of a pseudo-plastic deformation mechanism. High aspect-ratio whiskers possess larger pseudo-plastic deformation ability but are usually sparse, while, low aspect-ratio ones were distributed widely in the matrix and show low pseudo-plastic deformation ability (engagement effect), also. A comparative investigation was carried out in present study based on a multi-scale network model. The results indicate that the effect of low aspect-ratio whiskers is of most importance. Improving the engagement coefficient by raising the compactness of material seems a more practical way for optimization of discontinuous fiber-reinforced brittle composites in the present technological condition.

Damage Localization, Sensitivity of Energy Release and the Catastrophe Transition

Large earthquakes can be viewed as catastrophic ruptures in the earth’s crust. There are two common features prior to the catastrophe transition in heterogeneous media. One is damage localization and the other is critical sensitivity; both of which are related to a cascade of damage coalescence. In this paper, in an attempt to reveal the physics underlying the catastrophe transition, analytic analysis based on mean-field approximation of a heterogeneous medium as well as numerical simulations using a network model are presented. Both the emergence of damage localization and the sensitivity of energy release are examined to explore the inherent statistical precursors prior to the eventual catastrophic rupture. Emergence of damage localization, as predicted by the mean-field analysis, is consistent with observations of the evolution of damage patterns. It is confirmed that precursors can be extracted from the time-series of energy release according to its sensitivity to increasing crustal stress. As a major result, present research indicates that the catastrophe transition and the critical point hypothesis (CPH) of earthquakes are interrelated. The results suggest there may be two cross-checking precursors of large earthquakes: damage localization and critical sensitivity.

基于人工神经网络的油水旋流分离器分离性能预测

采用改进的BP神经网络模型模拟水力旋流器的油水分离过程.根据水力旋流器的实际运行条件,确定旋流器模型设计中的优化神经网络结构,将遗传算法用于优化三层BP神经网络的初始权重,采用PRP共轭梯度法优化BP算法.结果表明,采用人工神经网络模型预测油水分离水力旋流器的分离性能是切实可行的,它能成功地模拟旋流器的分离过程,进而实现旋流器操作控制的优化.

三维链网模型及其应用

基于质点间相互作用，按照质点间连线的取向统计材料的应变能，提出了材料的三维链网模型，论述了数值计算中的优化离散方式，并得到了相应的最优立体角取值。标定了模型的几何、物理参数。通过典型算例比较了三维链网模型与有限元方法及剪滞模型的预测结果，验证了三维链网模型具有与有限元同等水平的求解能力和计算精度。

非均质材料损伤破坏的数值模拟软件开发及强韧化机理研究

本文针对平面链网模型与空间链网模型，发展了模拟非均质材料的数值软件，旨在分析材料的损伤破坏特征，寻找材料细观结构同宏观力学行为之间的相互联系，探讨材料强韧化机理以及评估材料的力学性能。采用可视化技术设计的具有交互式功能的图象用户界面，能根据具体材料对象构造特定材料模型来分析其力学行为与服役能力。初步结果表明，无论是材料弹性阶段的性质还是损伤演化阶段材料中裂纹的萌生、扩展、汇集和材料的最终失效等现象都与已有的理论结果及试验结果符合得很好。另外，本文还对材料的强韧化机理作了探索。

基于人工神经网络的大量程光纤实时距离干涉测量仪

提出了一种基于人工神经网络的全光纤化大量程实时距离干涉测量仪．采用双正弦相位调制方法，即通过同时调制半导体激光器的波长和干涉仪的光程差实现外差测量。为了扩大干涉仪的测量范围和消除输出信号中的交叉敏感，采用人工神经网络进行信号处理，把两路经过初步解调的干涉信号作为输入样本，物体距离的实际值作为输出样本，对神经网络进行训练，以使其具有良好的推广能力．实验结果表明神经网络的使用不仅扩大了距离的测量范围而且提高了测量精度．

Modular Organization in a Cell: Concepts and Applications

Network biology is conceptualized as an interdisciplinary field, lying at the intersection among graph theory, statistical mechanics and biology. Great efforts have been made to promote the concept of network biology and its various applications in life s

Prediction and elucidation of the population dynamics of Microcystis spp. in Lake Dianchi (China) by means of artificial neural networks

Lake Dianchi is a shallow and turbid lake, located in Southwest China. Since 1985, Lake Dianchi has experienced severe cyanabacterial blooms (dominated by Microcystis spp.). In extreme cases, the algal cell densities have exceeded three billion cells per liter. To predict and elucidate the population dynamics ofMicrocystis spp. in Lake Dianchi, a neural network based model was developed. The correlation coefficient (R 2) between the predicted algal concentrations by the model and the observed values was 0.911. Sensitivity analysis was performed to clarify the algal dynamics to the changes of environmental factors. The results of a sensitivity analysis of the neural network model suggested that small increases in pH could cause significantly reduced algal abundance. Further investigations on raw data showed that the response of Microcystis spp. concentration to pH increase was dependent on algal biomass and pH level. When Microcystis spp. population and pH were moderate or low, the response of Microcystis spp. population would be more likely to be positive in Lake Dianchi; contrarily, Microcystis spp. population in Lake Dianchi would be more likely to show negative response to pH increase when Microcystis spp. population and pH were high. The paper concluded that the extremely high concentration of algal population and high pH could explain the distinctive response of Microcystis spp. population to +1 SD (standard deviation) pH increase in Lake Dianchi. And the paper also elucidated the algal dynamics to changes of other environmental factors. One SD increase of water temperature (WT) had strongest positive relationship with Microcystis spp. biomass. Chemical oxygen demand (COD) and total phosphorus (TP) had strong positive effect on Microcystis spp. abundance while total nitrogen (TN), biological oxygen demand in five days (BOD5), and dissolved oxygen had only weak relationship with Microcystis spp. concentration. And transparency (Tr) had moderate positive relationship with Microcystis spp. concentration.

基于改进网络模型的大时滞网络拥塞控制算法

　随着对网络拥塞控制的深入研究,出现了许多有关网络流量的控制理论及网络模型.Misra等人于2000年基于流体流(fluidflow)理论提出的模型被研究人员广为采用.但模型在推导过程中的一些近似却使得模型对网络行为描述不精确.本文对此从理论和实验结果两方面进行了详细分析,并对原模型进行了改进.基于改进的模型,把一种PID(ProportionalIntegralDifferential)及类PID设计方法用于AQM(ActiveQueueManagement)控制器的设计.对比仿真结果表明,该算法具有更好的性能.