Aeroelastic simulations using gridless boundary condition and small perturbation techniques

This paper examines the use of stationary Cartesian mesh for non-linear flutter computations involving complex geometries. The surface boundary conditions are implemented using reflected points which are determined via a gridless approach. The method uses a cloud of nodes in the vicinity of the surface to get a weighted-average of the flow properties using radial basis functions. To ensure computational efficiency and for local grid refinements, multigrid computations within an embedded grids framework are used. As the displacements of moving surfaces from their original position are typically small for flutter problems, a small perturbation boundary condition method is used to account for the moving surfaces. The method therefore does not require repeated grid re-generation for the deforming surfaces. The overall method is both accurate and robust. Computations of the well-known Onera M6 wing, RAE wing-body configuration, the AGARD 445.6 wing flutter test case show good accuracy and efficiencies. Simulations of the aeroelastic behavior of a complete fighter-type aircraft with wing tip missiles at high transonic speeds further demonstrate the practical usefulness of the present boundary conditions technique.     

三维Euler方程的隐式间断有限元算法

为了求解三维欧拉方程,对隐式时间离散格式间断有限元方法进行了研究。根据间断Galerkin有限元方法思想,构造内迭代SOR-LU-SGS隐式时间离散格式,结合当地时间步长技术、多重网格方法,实现了三维流场的计算。数值计算了ONERAM6机翼、大攻角尖前缘三角翼以及DLR-F4翼身组合体的亚声速绕流问题。结果表明,加入SOR内迭代步的LU-SGS隐式算法具有较大的优势,相较于GMRES算法所占用的内存少且收敛速度相当,是LU-SGS算法的三倍以上。针对三维算例,具有较好的稳定性和较高的收敛速度,能够给出准确的流场信息。与原方法相比,SOR-LU-SGS方法无论是在迭代步数上还是在CPU时间上,效率均有明显提高,适合于三维复杂流场计算。     

A Cascadic Multigrid Algorithm for Semilinear Indefinite Elliptic Problems

We propose a cascadic multigrid algorithm for a semilinear indefinite elliptic problem. We use a standard finite element discretization with piecewise linear finite elements. The arising nonlinear equations are solved by a cascadic organization of Newton's method with frozen derivative on a sequence of nested grids. This gives a simple version of a multigrid method without projections on coarser grids. The cascadic multigrid algorithm starts on a comparatively coarse grid where the number of unknowns is small enough to obtain an approximate solution within sufficiently high precision without substantial computational effort. On each finer grid we perform exactly one Newton step taking the approximate solution from the coarsest grid as initial guess. The linear Newton systems are solved iteratively by a Jacobi-type iteration with special parameters using the approximate solution from the previous grid as initial guess. We prove that for a sufficiently fine initial grid and for a sufficiently good start approximation the algorithm yields an approximate solution within the discretization error on the finest grid and that the method has multigrid complexity with logarithmic multiplier. Received February 1999, revised July 13, 1999     

机翼柱面梳状接头设计和参数优化

为解决工程实际中常规机翼梳状接头应力严重、结构偏重的问题,设计一种用于机翼结构对接的柱面梳状接头,并借助试验设计和Kriging代理模型技术提出其细节参数优化方法,应用试验设计法选取样本点,通过非线性有限元接触分析得到该样本点的响应,以此建立Kriging代理模型,并采用更新技术提高Kriging代理模型的精度;应用多岛遗传算法优化该代理模型并获得最优解.算例表明:采用该方法,机翼减重效果明显,优化效率提高.     

An incentive-based heuristic job scheduling algorithm for utility grids

Job scheduling in utility grids should take into account the incentives for both grid users and resource providers. However, most of existing studies on job scheduling in utility grids only address the incentive for one party, i.e., either the users or the resource providers. Very few studies on job scheduling in utility grids consider incentives for both parties, in which the cost, one of the most attractive incentives for users, is not addressed. In this paper, we study the job scheduling in utility grid by optimizing the incentives for both parties. We propose a multi-objective optimization approach, i.e., maximizing the successful execution rate of jobs and minimizing the combined cost (incentives for grid users), and minimizing the fairness deviation of profits (incentive for resource providers). The proposed multi-objective optimization approach could offer sufficient incentives for the two parties to stay and play in the utility grid. A heuristic scheduling algorithm called Cost-Greedy Price-Adjusting (CGPA) algorithm is developed to optimize the incentives for both parties. Simulation results show that the CGPA algorithm is effective and could lead to higher successful execution rate, lower combined cost and lower fairness deviation compared with some popular algorithms in most cases.     

Ghost-cell method for analysis of inviscid three-dimensional flows on Cartesian-grids

The present paper deals with the implementation of non-penetration boundary conditions at solid walls for three-dimensional inviscid flow computations on Cartesian grids. The crux of the method is the curvature-corrected symmetry technique (CCST) developed by the present authors for body-fitted grids. The method introduces ghost cells near the boundaries whose values are developed from an assumed flow-field model in vicinity of the wall consisting of a vortex flow, with locally symmetric distribution of entropy and total enthalpy. In three dimensions this procedure is implemented in the so-called “osculating plane”. This method was shown to be substantially more accurate than traditional surface boundary condition approaches. This improved boundary condition is adapted to a Cartesian mesh formulation, which we have termed the “ghost-cell method”. In this approach, all cell centers exterior to the body are computed with fluxes at the six surrounding cell faces, without any cut cell. A multiple-valued point technique is used to compute sharp edges. The merits of the ghost-cell method for three-dimensional inviscid flow computations are established by computing compressible and transonic flows about a sphere, an oblate and a prolate spheroid, a cylindrical wing with an end-plate, the ONERA M6 wing and detailed comparison to body-fitted grid computations and to published data. The computed results show the surface non-penetration condition to be satisfied in the limit of vanishing cell size and the method to be second-order accurate in space. The comparison with body-fitted results proves that the accuracy is comparable to the accuracy of CCST computations on body-fitted grids and remarkably superior to body-fitted computations based on traditional pressure extrapolation, non-penetration boundary conditions. In addition, we prove that the results are independent of the position of the body with respect to the grid. Finally, we show that the ONERA M6 wing results compare very well with published data.     

基于Hilbert曲线的近似k-最近邻查询算法

在低维空间中R树的查询效率较高,而在高维空间中其性能急剧恶化,降维成为解决问题的关键。利用Hilbert曲线的降维特性,该文提出基于Hilbert曲线近似k-最近邻查询算法AKNN,分析近似k-最近邻的误差。实验结果表明算法在执行时间上优于线性扫描和基于R树最短优先查询算法,近似解的质量较好。     

基于对象集合的空间关键词查询

在进行空间关键词查询时,有时需要查找一组既紧凑且离查询点最近、又覆盖查询关键词且对象个数很少的对象,而现有的查询方法通常只能返回包含所有查询关键词的单个空间对象。为此,提出了解决此类查询问题的近似查询算法和精确查询算法。首先给出了这类查询问题的形式化定义,以及描述对象集合质量的代价函数,并对代价函数进行了归一化处理;然后在近似查询算法中采用基于IR-tree的最佳优先搜索策略进行剪枝,有效缩减了查询候选空间;在精确查询算法中采用基于IR-tree的广度优先搜索策略查找包含查询关键词的对象,以达到降低查询处理代价的目的。实验结果表明,近似算法的查询效率明显优于精确算法,且能获得非常精确的查询结果。     

散焦模糊的畸变QR barcode图像复原技术

根据散焦模糊的QR barcode(QR码)图像特点,采用自适应阈值方法滤除模糊效应,通过轮廓查找算法初步定位4个顶点和消除噪声,利用2次反透视变换结合双切线逼近的方法初步复原图像,使用自适应栅格划分法进行中心点采样,得到最终的复原图.实验结果证明:该方法简单易行,对散焦模糊或具有复杂背景的QR码图像的复原取得了较好的效果.     

基于Zipf分布的网格密度峰值聚类算法

网格密度峰值聚类在兼顾密度峰值聚类算法可识别任意形状类簇的基础上,通过数据集的网格化简化整体计算量,成为当前备受关注的聚类方法.针对大规模数据,如何进一步区分稠密与稀疏网格,减少网格密度峰值聚类中参与计算的非空网格代表点的数量是解决“网格灾难”的关键.结合以网格密度为变量的概率密度分布呈现出类Zipf分布的特点,提出一种基于Zipf分布的网格密度峰值聚类算法.首先计算所有非空网格的密度并映射为Zipf分布,根据对应的Zipf分布筛选出稠密中心网格和稀疏边缘网格;然后仅对稠密中心网格进行密度峰值聚类,在自适应确定潜在聚类中心的同时减少欧氏距离的计算量,降低算法复杂度;最后通过对稀疏边缘网格的处理,进一步优化类簇边界并提高聚类精度.人工数据集和UCI数据集下的实验结果表明,所提出算法对大规模、类簇交叉数据的聚类具有明显优势,能够在保证聚类精度的同时降低时间复杂度.     

Zonal finite-volume computations of incompressible flows

The paper addresses convection modelling and flow field zoning procedures destined for finite-volume methods for incompressible steady-state flows with irregular boundaries. A composite oscillation-damping algorithm which is capable of yielding bounded and low diffusive solutions is used to approximate the convection terms of transport equations. To deal with complex geometries, a zonal procedure is introduced into an advanced finite-volume method that uses general non-orthogonal and non-staggered grids. The solution domain is divided into simple subregions each covered by a separate mesh. The flow is solved for concurrently in each of the different zones, and information exchange among the zones is realized through overlapping the grids in the vicinity of the zonal interfaces. The zonal procedure enables the finite-volume method to handle those domains which are extremely difficult to cover with a single grid. Applications to a range of laminar elliptic problems demonstrate the capability of the method for predicting complex flows.     

The lazy sweep ray casting algorithm for rendering irregular grids

Lazy sweep ray casting is a fast algorithm for rendering general irregular grids. It is based on the sweep-plane paradigm, and it is able to accelerate ray casting for rendering irregular grids, including disconnected and nonconvex unstructured irregular grids (even with holes) with a rendering cost that decreases as the “disconnectedness” decreases. The algorithm is carefully tailored to exploit spatial coherence even if the image resolution differs substantially from the object space resolution. Lazy sweep ray casting has several desirable properties, including its generality, (depth-sorting) accuracy, low memory consumption, speed, simplicity of implementation and portability (e.g. no hardware dependencies). We establish the practicality of our method through experimental results based on our implementation, which is shown to be substantially faster (by up to two orders of magnitude) than other algorithms implemented in software. We also provide theoretical results, both lower and upper bounds, on the complexity of ray casting of irregular grids     

一种内河海事无人艇路径规划算法设计与仿真

为了解决内河海事无人艇路径规划问题,提出了一种基于电子江图的路径遍历算法。该算法以分层的电子江图为基础,运用全局路径规划和局部路径规划的方法寻找近似可航路径。运用栅格法在复杂多变的内河环境中选择可航区域,运用Voronoi图对动态物标或可视为质点的碍航物建立航行路径集;将可航区域（或轻微碍航区域）与航行路径集公共区域记为可航路径;并运用贝塞尔曲线和二次规划数学方法进行优化。Matlab仿真结果表明,当障碍物位置坐标不同或目的地位置坐标不同时均可以生成近似可航路径;生成的不同近似可航路径均能被优化为最优安全可航路径,所以建立的环境模型以及使用的路径规划算法是有效、可行的。     

Using interpolation to improve path planning: The Field D* algorithm

We present an interpolation‐based planning and replanning algorithm for generating low‐cost paths through uniform and nonuniform resolution grids. Most grid‐based path planners use discrete state transitions that artificially constrain an agent's motion to a small set of possible headings (e.g., 0, π/4, π/2, etc.). As a result, even “optimal” grid‐based planners produce unnatural, suboptimal paths. Our approach uses linear interpolation during planning to calculate accurate path cost estimates for arbitrary positions within each grid cell and produce paths with a range of continuous headings. Consequently, it is particularly well suited to planning low‐cost trajectories for mobile robots. In this paper, we introduce a version of the algorithm for uniform resolution grids and a version for nonuniform resolution grids. Together, these approaches address two of the most significant shortcomings of grid‐based path planning: the quality of the paths produced and the memory and computational requirements of planning over grids. We demonstrate our approaches on a number of example planning problems, compare them to related algorithms, and present several implementations on real robotic systems.     

Distributed multi-join query processing in data grids

Query processing in data grids is a difficult issue due to the heterogeneous, unpredictable and volatile behaviors of the grid resources. Applying join operations on remote relations in data grids is a unique and interesting problem. However, to the best of our knowledge, little is done to date on multi-join query processing in data grids. An approach for processing multi-join queries is proposed in this paper. Firstly, a relation-reduction algorithm for reducing the sizes of operand relations is presented in order to minimize data transmission cost among grid nodes. Then, a method for scheduling computer nodes in data grids is devised to parallel process multi-join queries. Thirdly, an innovative method is developed to efficiently execute join operations in a pipeline fashion. Finally, a complete algorithm for processing multi-join queries is given. Analytical and experimental results show the effectiveness and efficiency of the proposed approach.     

Recent experiences with error estimation and adaptivity, Part II: Error estimation for h-adaptive approximations on grids of triangles and quadrilaterals

In Part I, residual and flux projection error estimators for finite element approximations of scalar elliptic problems were reviewed; numerical studies on the performance of these estimators were presented for finite element approximations of the solution of Poisson's equation on uniform grids of hierarchic triangles of order p (1 p 7). Here further numerical experiments are given which also include error estimators for the vector-valued problem of plane elastostatics and implementations for h-adaptive grids of triangles and quadrilaterals which are constructed using an algorithm of equidistribution of error coupled with h-refinement or h-remeshing schemes. A detailed numerical study of several flux-projectors for h-adaptive grids of bilinear and biquadratic quadrilaterals is conducted; a flux equilibration iteration, which may be employed in some cases to improve flux projection estimates, is also included. FAor the case of grids of quadrilaterals, several versions of the element residual estimators, which differ by the approximate flux employed for the calculation of the boundary integral term in the definition of the local problems, are compared. The numerical experiments confirm the good overall performance of residual estimates and indicate that flux projection estimates, which are now operational in several commercial codes, may be divergent when they are employed to estimate the error in even order h-adaptive approximations.     

基于遗传算法的有向无环图画图算法

在研究了现有画有向无环图的主要方法的基础上提出一种基于遗传算法的有向无环图画图算法,将一般有向无环图的画图问题转换为函数优化问题,用遗传算法求目标函数最优解的近似值。实验表明此算法具有算法统一、方法简单、容易实现、易于修改,并且具有自适应、自学习和易于并行化的特点。     

Job scheduling and processor allocation for grid computing on metacomputers

Scheduling is a fundamental issue in achieving high performance on metacomputers and computational grids. For the first time, the job scheduling problem for grid computing on metacomputers is studied as a combinatorial optimization problem. A cost model is proposed for modeling communication heterogeneity on computational grids. A processor allocation algorithm is developed which always finds an optimal processor allocation that minimizes the effective execution time of a job when the job is being scheduled. It is proven that the list scheduling (LS) algorithm can achieve reasonable worst-case performance bound in grid environments supporting distributed supercomputing with large applications. We compare the performance of various job scheduling and processor allocation algorithms for grid computing on metacomputers. We evaluate the performance of 128 combinations of two job scheduling algorithms, four initial job ordering strategies, four processor allocation algorithms, and four metacomputers by extensive simulation. It is found that the combination of largest job first (LJF) initial job ordering and minimum effective execution time (MEET) or largest machine first (LMF) processor allocation algorithm yields the best average-case performance, and the choice of FCFS and LS depends on the range of job sizes. It is also observed that communication heterogeneity does have significant impact on schedule lengths.     

Fast Approximation of Laplace‐Beltrami Eigenproblems

The spectrum and eigenfunctions of the Laplace‐Beltrami operator are at the heart of effective schemes for a variety of problems in geometry processing. A burden attached to these spectral methods is that they need to numerically solve a large‐scale eigenvalue problem, which results in costly precomputation. In this paper, we address this problem by proposing a fast approximation algorithm for the lowest part of the spectrum of the Laplace‐Beltrami operator. Our experiments indicate that the resulting spectra well‐approximate reference spectra, which are computed with state‐of‐the‐art eigensolvers. Moreover, we demonstrate that for different applications that comparable results are produced with the approximate and the reference spectra and eigenfunctions. The benefits of the proposed algorithm are that the cost for computing the approximate spectra is just a fraction of the cost required for numerically solving the eigenvalue problems, the storage requirements are reduced and evaluation times are lower. Our approach can help to substantially reduce the computational burden attached to spectral methods for geometry processing.     

基于深度强化学习的智能电网RAN切片策略

随着智能电网的不断发展,电力服务种类的多样化引出了不同的服务需求.5G中的网络切片技术,可以为智能电网提供虚拟化无线专用网络,以应对智能电网安全性、可靠性、时延性等方面的诸多挑战.考虑到智能电网的差异化服务特性,本文旨在使用深度强化学习(DRL)来解决智能电网的无线接入网(RAN)切片的资源分配问题.文章首先回顾了智能电网的背景以及网络切片技术的相关研究,随后分析了智能电网的RAN切片模型,并且提出了一种基于DRL的切片分配策略.仿真表明,本文所提出的算法能够在降低成本的同时,最大限度地满足智能电网在RAN侧的资源分配需求.