A new adaptive grid generation by elliptic equations with orthogonality at all of the boundaries

A new adaptive grid generation procedure is proposed, which combines a previously developed method that used Anderson's adaptive grid scheme along with a method for controlling grid spacing and orthogonality on all of the boundaries. The proposed method assigns the desired grid stretching over the smooth region during initial grid system generation and before grid adaptation is performed. After properly interpreting the smoothing term of the weighting function, the desired grid stretching is added to the adaptive grid scheme. Several test cases illustrate the method's feasibility.     

Progress in grid generation via the advancing front technique

We describe recent extensions and improvements to the advancing front grid generation technique. These improvements target a range of applicability, speed and user friendliness. The range of applicability is enlarged by the ability to produce volumetric grids around thin surfaces (such as shells, membranes, fabrics or surfaces with cusps), the generation of high aspect ratio grids for Navier-Stokes applications, the generation of higher order triangular and tetrahedral elements, and the generation of quadrilateral and hexahedral elements. Speed improvements are the result of reduced search overheads, as well as vectorization and parallelization. User friendliness is enhanced by the ability to grid directly discrete data and simpler ways of specifying the desired element size and shape in space. Numerous examples are included that demonstrate the versatility and maturity that advancing front grid generators have achieved.     

Automatic mesh generation on a regular background grid

This paper presents and automatic mesh generation procedure on a 2D domain based on a regular background grid.The idea is to devise a robust mesh generation scheme with equal emphasis on quality and efficiency,Instead of using a traditional regular rectangular grid,a mesh of equilateral triangles is employed to ensure triangular element of the best quality will be preserved in the interior of the domain.As for the boundary,it is to be generated by a node/segment insertion process.Nodes are inserted into the background mesh one by one following the sequence of the domain boundary.The local strcture of the mesh is modified based on the Delaunay criterion with the introduction of each node.Those boundary segments.which are not produced in the phase of node insertion,will be recovered through a systematic element swap produced in the phase of node insertion will be recovered through a systematic element swap process.Two theorems will be presented and proved to set up the theoretical basic of the boundary recovery part.Examples will be presented to demonstrate the robustness and the quality of the mesh generated by the proposed technique.     

Adaptive tool-path generation of rapid prototyping for complex product models

Rapid prototyping (RP) provides an effective method for model verification and product development collaboration. A challenging research issue in RP is how to shorten the build time and improve the surface accuracy especially for complex product models. In this paper, systematic adaptive algorithms and strategies have been developed to address the challenge. A slicing algorithm has been first developed for directly slicing a Computer-Aided Design (CAD) model as a number of RP layers. Closed Non-Uniform Rational B-Spline (NURBS) curves have been introduced to represent the contours of the layers to maintain the surface accuracy of the CAD model. Based on it, a mixed and adaptive tool-path generation algorithm, which is aimed to optimize both the surface quality and fabrication efficiency in RP, has been then developed. The algorithm can generate contour tool-paths for the boundary of each RP sliced layer to reduce the surface errors of the model, and zigzag tool-paths for the internal area of the layer to speed up fabrication. In addition, based on developed build time analysis mathematical models, adaptive strategies have been devised to generate variable speeds for contour tool-paths to address the geometric characteristics in each layer to reduce build time, and to identify the best slope degree of zigzag tool-paths to further minimize the build time. In the end, case studies of complex product models have been used to validate and showcase the performance of the developed algorithms in terms of processing effectiveness and surface accuracy.     

Adaptive group scheduling mechanism using mobile agents in peer-to-peer grid computing environment

Peer-to-peer grid computing is an attractive computing paradigm for high throughput applications. However, both volatility due to the autonomy of volunteers (i.e., resource providers) and the heterogeneous properties of volunteers are challenging problems in the scheduling procedure. Therefore, it is necessary to develop a scheduling mechanism that adapts to a dynamic peer-to-peer grid computing environment. In this paper, we propose a Mobile Agent based Adaptive Group Scheduling Mechanism (MAAGSM). The MAAGSM classifies and constructs volunteer groups to perform a scheduling mechanism according to the properties of volunteers such as volunteer autonomy failures, volunteer availability, and volunteering service time. In addition, the MAAGSM exploits a mobile agent technology to adaptively conduct various scheduling, fault tolerance, and replication algorithms suitable for each volunteer group. Furthermore, we demonstrate that the MAAGSM improves performance by evaluating the scheduling mechanism in Korea@Home. SungJin Choi is a Ph.D. student in the Department of Computer Science and Engineering at Korea University. His research interests include mobile agent, peer-to-peer computing, grid computing, and distributed systems. Mr. Choi received a M.S. in computer science from Korea University. He is a student member of the IEEE. MaengSoon Baik is a senior research member at the SAMSUNG SDS Research & Develop Center. His research interests include mobile agent, grid computing, server virtualization, storage virtualization, and utility computing. Dr. Baik received a Ph.D. in computer science from Korea University. JoonMin Gil is a professor in the Department of Computer Science Education at Catholic University of Daegu, Korea. His recent research interests include grid computing, distributed and parallel computing, Internet computing, P2P networks, and wireless networks. Dr. Gil received his Ph.D. in computer science from Korea University. He is a member of the IEEE and the IEICE. SoonYoung Jung is a professor in the Department of Computer Science Education at Korea University. His research interests include grid computing, web-based education systems, database systems, knowledge management systems, and mobile computing. Dr. Jung received his Ph.D. in computer science from Korea University. ChongSun Hwang is a professor in the Department of Computer Science and Engineering at Korea University. His research interests include distributed systems, distributed algorithms, and mobile computing. Dr. Hwang received a Ph.D. in statistics and computer science from the University of Georgia.     

面向系统动态可靠性的自适应目标代码生成方法

随着社会的快速发展,人们对嵌入式智能设备的依赖程度越来越高。嵌入式系统工作在体积受限的封闭环境中,运算部件、存储单元等相关元器件体积小集成度高,不同工作环境、不同使用频度对电子元器件的可靠性将产生重要影响。针对嵌入式系统工作过程中的动态可靠性,提出了面向系统动态可靠性的自适应目标代码生成方法。该方法借助于决策树学习算法,构建了系统可靠性评估模型;并以此为指导,设计了多路径目标代码生成方法。使得系统能够根据实际工作状态信息,自适应的最佳的执行路径,以避免系统资源使用的不均衡,提高各运算部件的可靠性。实验表明,该方法将程序对单个处理器最高使用率由80%以上降到了30%以内,将内存单元最大最小访问比例由157.3降到了15.4,有效均衡了各处理器核和内存单元的使用。     

基于循环神经网络的正交网格的自动化生成算法

随着计算机图形学、工业设计、自然科学等领域的飞速发展,对高质量的科学计算方法的需求随之增大,而这些科学计算的方法离不开高质量的网格生成算法。对于常用的正交网格生成算法,是否能减少计算量以及是否能降低的人工干预等问题仍是它们所面临的主要挑战。针对这些挑战,对于单连通的目标区域,提出了基于循环神经网络之一的长短期记忆网络（LSTM）和Schwarz-Christoffel共形映射（SC映射）的正交网格自动化生成算法。首先,利用基于SC映射的Gridgen-c工具的基本条件将网格生成问题转换为一个带线性限制条件的整数规划问题。接着,利用预处理后的GADM数据集和LSTM训练获得能计算目标多边形区域每个顶点转角类型的概率的分类器。该分类器可以大幅度降低整数规划问题的时间复杂度,使该问题能被自动化且快速地求解。最后以简单图形区域、动画图形区域、地理边界区域为样例,进行网格生成实验。结果表明：对于简单图形区域,所提算法均能达到最优解;而对于具有复杂边界的动画图形区域和地理边界区域,实例网格结果表明,所提算法能使这些目标区域的计算量分别降低88.42%和91.16%,且能自动化地生成较好的正交网格。     

一种基于散列链的自适应网格安全路由协议

LEACH(Low Energy Adaptive Clustering Hierarchy)路由协议是无线传感器网络拓扑控制中最具代表性和重要性的算法之一。针对LEACH路由协议簇头分布不均匀,节点死亡率高,易产生路由空洞及其所面临安全威胁等问题,提出一种基于散列链的区域划分网格自治安全路由协议LEACH-SEED。剔除低能量节点入选簇头的权利,改进簇头选举机制,簇头选举完成之后,每个簇头节点随机从散列链组成的密钥池中分配q个链密钥,其他节点利用单向哈希函数和伪随机函数生成通信密钥,网络遭受攻击后利用网格自治和待选簇头身份标识编号进行网络恢复。实验结果表明,改进的分簇算法能有效地降低节点死亡率,增强抗攻击能力,提高数据融合度,延长网络生存时间。     

三维有限差分计算中大规模网格生成及显示技术

针对爆炸与冲击问题并行仿真计算软件PMMIC-3D（Parallel Multi-Material in Cell 3D）的计算网格为正交六面体网格的特点,开发与PMMIC-3D接口统一的可对任意复杂三维实体模型进行大规模有限差分网格生成的三维前处理软件MESH-3D.MESH-3D采用CSG和STL模型两种建模方式进行复杂实体建模,并采用基于边的整体切片算法,借鉴计算机图形学中的扫描线填充算法完成三维有限差分网格划分.在绘制网格时,删除网格单元的公共面,大大缩短计算时间和减少存储空间,实现对网格的快速消隐显示.MESH-3D可实现百亿量级网格单元的生成和显示.三维前处理软件MESH-3D的开发有力地支持爆炸与冲击问题的仿真计算.     

孤岛智能配电网下的快速自动发电控制机组一致性协同控制算法

由于可再生能源随机性、间歇性的特征和智能电网"即插即用"的要求,传统的集中式AGC控制方法面临诸多挑战,分布自治与集中协调已成为智能配电网的未来发展方向.为此,本文提出了一种基于等微增率的AGC机组一致性协同控制算法,解决了孤岛智能配电网的频率自治与协同控制问题;并提出了一种"虚拟一致性变量"的概念,用于解决AGC机组功率越限导致的拓扑变化问题和实现AGC机组的"即插即用";同时,在智能配电网发生负荷扰动的情况下,为保证所有机组在新的工况下仍能达到最优经济运行,建立了AGC功率分配与短期经济调度的协同目标.最后搭建了包含多种分布式电源及多个微网的智能配电网模型,仿真表明:与传统集中控制方法相比,一致性协同算法动态优化速度快,收敛鲁棒性强,能有效解决孤岛智能配电网的频率自治与协同控制问题.     

Adaptive occupancy grid mapping with clusters

In this article, we describe an algorithm for acquiring occupancy grid maps with mobile robots. The standard occupancy grid mapping developed by Elfes and Moravec in the mid-1980s decomposes the high-dimensional mapping problem into many one-dimensional estimation problems, which are then tackled independently. Because of the independencies between neighboring grid cells, this often generates maps that are inconsistent with the sensor data. To overcome this, we propose a cluster that is a set of cells. The cells in the clusters are tackled dependently with another occupancy grid mapping with an expectation maximization (EM) algorithm. The occupancy grid mapping with an EM algorithm yields more consistent maps, especially in the cluster. As we use the mapping algorithm adaptively with clusters according to the sensor measurements, our mapping algorithm is faster and more accurate than previous mapping algorithms. This work was presented in part at the 10th International Symposium on Artificial Life and Robotics, Oita, Japan, February 4–6, 2005     

一类高度非线性网格生成方程的迭代求解方法

在[1]中第170页指出,对于变分方法导出的一类高度非线性的守恒型网格生成方程,采用通常的Picard迭代方法无法正确求解.本文构造了一种新的Picard迭代求解方法,数值结果表明这一方法较好地解决了此类方程的求解问题.     

智能电网分代研究

智能电网的分代研究有助于把握和引导智能电网的发展趋势。文章首先从人类智能出发,溯源了智能电网的智能本质,分析了人类智能的发展阶段,指出人工智能是对人类智能的模拟、延伸和扩展,智能电网是人工智能在传统电网中的应用;其次,在智能电网的本质基础上,提出了智能电网分代的原则和标准,建立了智能电网分代模型,并将智能电网划分为自感知、自适应、自趋优三代智能电网;最后,探讨了智能电网分代的社会经济意义。     

一种逐周期条纹背景自适应去除算法

利用傅里叶轮廓术(FTP)可实现对单帧光栅投影条纹图像的相位提取,恢复被测物体三维信息;该方法具有实时性高的特点,但在频域滤波时易受到不均匀背景分量的干扰;现有投影条纹图背景去除方法在遇到条纹图背景分量不均匀时,存在去除效果差,严重影响重建精度的问题;针对该问题,通过实验发现单个条纹周期内的背景分量变化很小,可近似作为常量处理;结合两次希尔伯特变换能有效去除信号直流分量且保持相位信息稳定的特性,提出一种自适应的分周期条纹背景滤除方法;该方法首先对光栅投影图像中的条纹峰值进行提取,分割出逐个条纹周期;再对逐条纹周期分别进行两次希尔伯特变换,自动去除该周期内的背景分量,实现条纹背景分量的逐周期自适应去除;该方法能有效克服条纹投影图像背景分量不均匀的问题;实验结果表明,该方法相对于傅里叶轮廓术可更好地消除条纹背景分量影响,对复杂表面物体的重建异常点少,精度优于0.1 mm.     

六角网格上的直线生成算法

经研究表明,屏幕上的点最佳分布是按六角网格形式分布的,文中首先讨论了六角网格的特点,并从图形图象处理的角度分析了它伯优点,然后提出了在六角网格上的直线生成算法,此算法仅用了整数运算。     

Adaptive generation of surfaces in volume data

A widespread approach to generating polygonal approximations of iso-surfaces or contour surfaces in volume data is the socalled marching-cubes algorithm. This algorithm, however, has the disadvantage that the number of polygonal chains generated is considerable. The splitting-box algorithm presented here reduces the number of polygonal chains by adapting their size to the shape of the surface. The resulting polygonal chains offer a wide spectrum for representing the contour surface. An exact representation is achieved by a new type of generic patches calculated from the polygonal chains. Approximations of different quality may be obtained by combining the algorithm generating the patches with simple triangulations.     

Digital Topology on Adaptive Octree Grids

The theory of digital topology is used in many different image processing and computer graphics algorithms. Most of the existing theories apply to uniform cartesian grids, and they are not readily extensible to new algorithms targeting at adaptive cartesian grids. This article provides a rigorous extension of the classical digital topology framework for adaptive octree grids, including the characterization of adjacency, connected components, and simple points. Motivating examples, proofs of the major propositions, and algorithm pseudocodes are provided.

基于自适应滤波器的时频分析

采用最小方差原则和梯度下降方法, 经过旋转变换, 获得频率参数和带宽参数可调的自适应二维线性正弦跟踪滤波器, 实现信号跟随与幅值估计. 把多个跟踪器并联, 形成带宽可调的多频点梳状滤波器, 得到多维线性常系数微分动力系统. 用不变原理证明梳状滤波器是一致渐近稳定的. 用拉普拉斯变换导出频率特性, 单正弦输入时为向量形式, 针对多正弦分量时为频率特性矩阵. 当输入信号所有正弦分量的频率都等于梳状滤波器频率参数时, 本算法能够同时准确跟随所有分量及其幅值. 分析了算法的频域格栅效应以及带宽参数对稳态精度的影响, 通过仿真说明了算法的有效性.     

基于自适应拥挤网格的多目标粒子群算法

粒子群算法求解多目标问题极易收敛到伪Parct。前沿(等价于单目标优化问题中的局部最优解),并且收敛速度较慢。鉴于此,提出一种基于自适应拥挤网格的多目标粒子群算法(ACG-MOPSO)。其特点包括:利用自适应网格和拥挤距离确定外部存档中粒子的密度,并利用密度信息维持外部存档的规模;利用外部存档中非劣解的密度和拥挤距离信息确定全局最优粒子,提升粒子向Parcto前沿收敛的概率。模拟结果表明该算法在求解多目标问题上要优于其它算法。     

Automating test generation for discrete event oriented embedded systems

A method for the automatic generation of test scenarios from the behavioral requirements of a system is presented in this paper. The generated suite of test scenarios validates the system design or implementation against the requirements. The approach proposed here uses a requirements model and a set of four algorithms. The requirements model is an executable model of the proposed system defined in a deterministic state-based modeling formalism. Each action in the requirements model that changes the state of the model is identified with a unique requirement identifier. The scenario generation algorithms perform controlled simulations of the requirements model in order to generate a suite of test scenarios applicable for black box testing. Measurements of several metrics on the scenario generation algorithms have been collected using prototype tools.