基于波前法的参数曲面有限元网格生成算法

为克服参数曲面有限元网格生成中的单元形状映射畸变问题,提出一种曲面有限元网格自动生成算法.该算法由弹性矢量确定曲面上新节点的生成方向和空间位置,利用相应的参数域网格进行新单元拓扑相容性判断.在生成闭曲面网格时,通过添加参/虚边界棱边对闭曲面边界进行调整,确保闭曲面边界信息相对其参数域的完整性;在给出闭曲面极点初始化方法和适当设置单元边线段相等条件的基础上,该算法适用于各种不同形式闭曲面的网格自动生成.实验算例表明,文中算法可生成质量良好的参数曲面和组合面有限元网格.     

参数化曲面网格生成的气泡堆积法研究

结合微分几何理论知识,提出了一种参数曲面网格生成的气泡堆积算法。将曲面上的节点看作具有相互作用力的气泡,通过基于曲率的控制度量确定的节点间隔函数和弧长偏差因子来有效地控制网格尺寸,并借助三维桶结构建立和更新邻近气泡列表,当各气泡经动态模拟后达到力平衡状态时,连接气泡的中心就构成高质量的曲面网格。算例表明,生成的网格质量高、有很好的渐进性和对复杂曲面的适应性。     

残缺网格模型的快速B样条曲面重建

针对残缺的三角网格模型,提出一种将网格模型的散乱数据点转化为有序阵列点再进行B样条曲面快速重建的算法.首先确定最小二乘平面上的一个矩形参数域,再构造出一个平面阵列点列,并部分映射到三维网格上;然后利用空间阵列点的邻域信息估计4个角点的空间坐标,并构造径向基函数曲面,用于补充空间阵列点列中残缺的数据;最后利用有序点列拟合的高效性构造B样条曲面.实验结果表明:该算法速度快、拟合精度高、鲁棒性强,重建的曲面具有良好的光顺性和可延伸性,适用于逆向工程中对经过数据分割后的网格模型的自由曲面重建.     

球体空间数据组织和管理方法

为支持球体空间数据的快速检索及可视化仿真,提出了一套球体空间数据的组织和管理算法,并以太阳风数据为例进行了相关实验和分析.算法主要包括球体空间剖分和存储管理策略两部分.通过HTM-R层次化剖分方法将球体空间剖分为形状相似的网格,利用网格编码对数据进行索引,以达到快速搜索和定位数据的目的;利用剖分网格的多层次性建立球体数据的多层次模型,以支持数据的多分辨率显示,加快数据可视化速度.在空间剖分算法的基础上结合优化的存储管理策略进一步提高数据可视化速度.     

复杂曲面混合网格的生成算法

有限元网格质量的好坏对金属成形模拟的精度和效率有很大影响。提出了一种复杂曲面混合网格自动生成算法，该算法根据所要划分的网格密度形成初始化边界节点，逐步向内铺砌混合网格，直至布满整个区域。应用实践表明．该算法具有稳定、准确和速度快的特点，生成的网格在相邻曲面边界处不会产生裂缝与覆盖，很好地满足了金属成形模拟分析软件对网格划分的要求。     

基于映射法和Delaunay方法的曲面三角网格划分算法

提出一种曲面三角网格划分算法，该算法在曲面参数域中生成Delaunay类型的网格，然后将其映射到空间曲面，为了抵消映射过程中变形的影响，采用空椭圆准则代替传统的空间准则，并给出椭圆的构造算法以及椭圆圆心的定位方法，这些方法充分考虑到映射变形和求解速度，实验结果表明，该算法生成满意的曲面网格，具有一定的应用价值。     

基于黎曼度量的复杂参数曲面有限元网格生成方法

给出了三维空间的黎曼度量和曲面自身的黎曼度量相结合的三维复杂参数曲面自适应网格生成的改进波前推进算法.详细阐述了曲面参数域上任意一点的黎曼度量的计算和插值方法;采用可细化的栅格作为背景网格,在降低了程序实现的难度的同时提高了网格生成的速度;提出按层推进和按最短边推进相结合的方法,在保证边界网格质量的同时,提高曲面内部网格的质量.三维自适应黎曼度量的引入,提高了算法剖分复杂曲面的自适应性.算例表明,该算法对复杂曲面能够生成高质量的网格,而且整个算法具有很好的时间特性和可靠性.     

多裁剪自由曲面生成有限元网格的实现

论述了多裁剪自由曲面生成有限元曲面网格的几个关键技术.采用了推进波前法生成曲面网格,给出了核心算法;在曲面算法中运用了介于参数法与直接法之间的新方法.针对求解曲面上最优点的参数域反算问题,引入了切矢逆求方法,可使迭代次数大为降低.测试表明,该算法快速、稳定.对大型的多裁剪自由曲面生成的曲面有限元网格,可直接用于有限元计算.     

基于黎曼度量参数曲面四边形网格生成方法及UG 实现

论文给出了基于黎曼度量的参数曲面网格生成的改进铺砖算法。阐述了曲 面自身的黎曼度量,并且运用黎曼度量计算二维参数域上单元节点的位置,从而使映射到三 维物理空间的四边形网格形状良好。文中对原有铺砖法相交处理进行了改进,在运用铺砖法 的同时调用UG-NX 强大的二次开发库函数获取相应的信息,直接在UG-NX 模型的表面生 成四边形网格。算例表明,该法能在曲面上生成质量好的网格。     

基于空间网格表面距离的插值曲面

主要讨论基于空间网格表面距离的插值曲面.定义了一种空间网格表面距离,基于空间网格表 面距离,给出了两种定义在空间网格上的插值曲面：基于网格表面距离的径向基函数插值曲 面和基于网格表面距离的Kriging插值曲面,讨论了曲面的无穷阶光滑性,给出了一种计算网 格表面距离的折线跟踪算法.作为整体曲面,此类插值曲面与网格表面形状较为相符,比较适 合于局部插值与参数估计,如梯度、法方向的估计等计算.     

Reconstruction of 2D polygonal curves and 3D triangular surfaces via clustering of Delaunay circles/spheres

A simple and efficient method is presented in this paper to reliably reconstruct 2D polygonal curves and 3D triangular surfaces from discrete points based on the respective clustering of Delaunay circles and spheres. A Delaunay circle is the circumcircle of a Delaunay triangle in the 2D space, and a Delaunay sphere is the circumsphere of a Delaunay tetrahedron in the 3D space. The basic concept of the presented method is that all the incident Delaunay circles/spheres of a point are supposed to be clustered into two groups along the original curve/surface with satisfactory point density. The required point density is considered equivalent to that of meeting the well-documented r-sampling condition. With the clustering of Delaunay circles/spheres at each point, an initial partial mesh can be generated. An extrapolation heuristic is then applied to reconstructing the remainder mesh, often around sharp corners. This leads to the unique benefit of the presented method that point density around sharp corners does not have to be infinite. Implementation results have shown that the presented method can correctly reconstruct 2D curves and 3D surfaces for known point cloud data sets employed in the literature.     

基于骨架关节点约束的交互式局部变形

利用广义元球变形技术,提出一种基于骨架关节点约束的交互式局部变形方法。该方法提取多边形网格模型的骨架关节点并结合模型骨架图结构确定骨架关节点对应的局部区域,计算三维网格点到骨架节点的欧式距离,将约束区域的最大欧氏距离作为约束半径,得到各骨架节点对应的势函数值,通过控制骨架节点的空间位置给出三角形面片点的新坐标位置。实验结果表明,该方法有效保持多边形网络模型的局部特征,并确保了模型变形的直观性和高效性。     

An in-core grid index for transferring finite element data across dissimilar meshes

The simulation of a manufacturing process chain with the finite element method requires the selection of an appropriate finite element solver, element type and mesh density for each process of the chain. When the simulation results of one step are needed in a subsequent one, they have to be interpolated and transferred to another model. This paper presents an in-core grid index that can be created on a mesh represented by a list of nodes/elements. Finite element data can thus be transferred across different models in a process chain by mapping nodes or elements in indexed meshes. For each nodal or integration point of the target mesh, the index on the source mesh is searched for a specific node or element satisfying certain conditions, based on the mapping method. The underlying space of an indexed mesh is decomposed into a grid of variable-sized cells. The index allows local searches to be performed in a small subset of the cells, instead of linear searches in the entire mesh which are computationally expensive. This work focuses on the implementation and computational efficiency of indexing, searching and mapping. An experimental evaluation on medium-sized meshes suggests that the combination of index creation and mapping using the index is much faster than mapping through sequential searches.     

A study on the performance of local search versus population-based methods for mesh router nodes placement problem

Node placement problems have been long investigated in the optimization field due to numerous applications in facility location, logistics, services, etc. Such problems are attracting again the attention of researchers now from the networking domain, and more especially from Wireless Mesh Networks (WMNs) field. Indeed, the placement of mesh routers nodes appears to be crucial for the performance and operability of WMNs, in terms of network connectivity and stability. However, node placement problems are known for their hardness in solving them to optimality, and therefore heuristics methods are approached to near-optimally solve such problems. In this work we evaluate the performance of different heuristic methods in order to judge on their suitability of solving mesh router nodes problem. We have selected methods from two different families, namely, local search methods (Hill Climbing and Simulated Annealing) and population-based methods (Genetic Algorithms). The former are known for their capability to exploit the solution space by constructing a path of visited solutions, while the later methods use a population of individuals aiming to largely explore the solution space. In both cases, a bi-objective optimization consisting in the maximization of the size of the giant component in the mesh routers network (for measuring network connectivity) and that of user coverage are considered. In the experimental evaluation, we have used a benchmark of instances??varying from small to large size??generated using different distributions of mesh node clients (Uniform, Normal, Exponential and Weibull).     

Generation of tetrahedral mesh of variable element size by sphere packing over an unbounded 3D domain

This paper describes an algorithm for the generation of tetrahedral mesh of specified element size over an unbounded three-dimensional domain. Starting from an arbitrary point in space (defined as the origin) and guided by the concept of advancing front, spheres of size compatible with the specified element size are packed tightly together one by one to form a cluster of spheres of different sizes. The compactness of the cluster of spheres is achieved by packing spheres at a site closest to the origin in a densest manner with tangent but no overlapping with as many other spheres as possible. In view of these criteria, a rotational mechanism between spheres is innovated, which allows the newly inserted sphere to follow the path by rotation between existing spheres until the lowest point is reached. The centres of the packing spheres provide ideal locations for Delaunay point insertion to form a triangulation of tetrahedral elements of size compatible with the specified value. Spheres of random size distribution or of size specified by a node spacing function are packed by the proposed algorithm. In all test examples, high-quality tetrahedral elements of size consistent with the specified node spacing are generated. The process is fast and robust, and the time complexity for mesh generation is expected to be almost linear; however, in the present implementation, a quasi-linear time relationship is observed as a search for the nearest node on the front is proposed in the sphere packing process. The memory requirement has been kept to a minimum as no additional data structure other than the adjacency relationship of the tetrahedral elements as required by the Delaunay triangulation is stored. The structure of the advancing frontal surface needs not be explicitly constructed nor updated as it is simply not required in the sphere packing process.     

Iterative construction of Dupin cyclide characteristic circles using non-stationary Iterated Function Systems (IFS)

A Dupin cyclide can be defined, in two different ways, as the envelope of an one-parameter family of oriented spheres. Each family of spheres can be seen as a conic in the space of spheres. In this paper, we propose an algorithm to compute a characteristic circle of a Dupin cyclide from a point and the tangent at this point in the space of spheres. Then, we propose iterative algorithms (in the space of spheres) to compute (in 3D space) some characteristic circles of a Dupin cyclide which blends two particular canal surfaces. As a singular point of a Dupin cyclide is a point at infinity in the space of spheres, we use the massic points defined by Fiorot. As we subdivide conic arcs, these algorithms are better than the previous algorithms developed by Garnier and Gentil.     

Variable mesh optimization for continuous optimization problems

Population-based meta-heuristics are algorithms that can obtain very good results for complex continuous optimization problems in a reduced amount of time. These search algorithms use a population of solutions to maintain an acceptable diversity level during the process, thus their correct distribution is crucial for the search. This paper introduces a new population meta-heuristic called “variable mesh optimization” (VMO), in which the set of nodes (potential solutions) are distributed as a mesh. This mesh is variable, because it evolves to maintain a controlled diversity (avoiding solutions too close to each other) and to guide it to the best solutions (by a mechanism of resampling from current nodes to its best neighbour). This proposal is compared with basic population-based meta-heuristics using a benchmark of multimodal continuous functions, showing that VMO is a competitive algorithm.     

无线传感器网络三维APIT网格化算法

针对无线传感器网络中APIT算法只能在二维平面范围内应用的限制,提出了3D-GPIT算法,通过在最佳三角形内点测试算法的基础上进行三维空间的延拓,依靠基于四面体测试的方法获得未知节点估算区域的优选集,再利用三维网格方法优化计算。在100 m×100 m×100 m空间区域内,通过逐次改变给定参数进行定位仿真。结果显示在三维空间定位有着通信开销低、精度较高的优势。     

A neural network model to develop actions in urban complex systems represented by 2D meshes

The main idea of this work is to present a tool which may be useful to generate a mesh of points where urban actions may be taken after analysing and understanding complex urban situations. By the word complex we mean urban concentrations without precise limits and without a recognizable geometry pattern. In these situations, it is very hard for the architects to understand the system. Therefore, it is very difficult to define an action plan for this type of urban situations. What we propose is an adaptation of a neural network algorithm to work in the context of urban networks. Our objective is to develop a strategy to change this weakness of sparse urban development by activating public spaces with new meanings. A new 2D triangle mesh simplification model is introduced with the central property of preserving the shape of the original mesh. The mathematical model presented consists of a self-organizing algorithm whose objective is to generate the positions of the nodes of the simplified mesh; afterwards, a triangulation algorithm is carried out to reconstruct the triangles of the new simplified mesh. With this algorithm, it is possible to perform specific actions in an urban space, because the urban territory can be considered as a complex mesh with nodes and edges. A real example of an urban action is shown with the introduction of a wireless network in a residential area.     

基于内容的网格生成算法

在基于模型的编码技术中,选择合适的网络模型对提高模糊的运动估计精度、编码效率和得到高质量的解码图像都是至关重要的。本文提出的基于图像内容的自适应网络模型生成算法,首先利用数学形态学中的水线算法把编码图像分割成许多纹理一致的区域,所分割的区域反映了图像的结构、轮廓和边界;再对这些区域的边界进行多边形拟合,得到多边形各个边的端点作为网格模型的节点,以这些节点为基础就能生成一个Ｄｅｌａｕｎａｙ三角形网格