Measurement of enterprise knowledge by state characterization

Abstract: Enterprise production is becoming more and more knowledge oriented nowadays and knowledge management is playing a key role in making commercial profit and maintaining enterprise competence. Knowledge characterization and measurement are the bases of knowledge management, and this paper aims to develop a method for characterizing and measuring knowledge in a comprehensive and practical way. Knowledge in its static state is modelled as a vector, whose values vary with the situation, and changes in state are modelled as a finite state machine.     

双边开关磁阻直线电动机的设计

介绍了双边开关磁阻直线电动机(LSRM)的组成、工作原理及其尺寸设计方法,给出了LSRM样机的尺寸设计结果,并采用有限元法分析LSRM磁场分布规律,进行磁场分段计算,从而得到了最大电感、最小电感和相绕组匝数。测试结果表明,该LSRM样机启动力较大且出力不受电流方向影响,但也存在出力有脉动和噪声较大等问题,该问题可通过优化结构设计和控制算法解决。     

The geometric element transformation method for mixed mesh smoothing

The geometric element transformation method (GETMe) is a geometry-based smoothing method for mixed and non-mixed meshes. It is based on a simple geometric transformation applicable to elements bounded by polygons with an arbitrary number of nodes. The transformation, if applied iteratively, leads to a regularization of the polygons. Global mesh smoothing is accomplished by averaging the new node positions obtained by local element transformations. Thereby, the choice of transformation parameters as well as averaging weights can be based on the element quality which leads to high quality results. In this paper, a concept of an enhanced transformation approach is presented and a proof for the regularizing effect of the transformation based on eigenpolygons is given. Numerical examples confirm that the GETMe approach leads to superior mesh quality if compared to other geometry-based methods. In terms of quality it can even compete with optimization-based techniques, despite being conceptually significantly simpler.     

Algorithm,software, and hardware optimizations for Delaunay mesh generation on simultaneous multithreaded architectures

This article focuses on the optimization of PCDM, a parallel, two-dimensional (2D) Delaunay mesh generation application, and its interaction with parallel architectures based on simultaneous multithreading (SMT) processors. We first present the step-by-step effect of a series of optimizations on performance. These optimizations improve the performance of PCDM by up to a factor of six. They target issues that very often limit the performance of scientific computing codes. We then evaluate the interaction of PCDM with a real SMT-based SMP system, using both high-level metrics, such as execution time, and low-level information from hardware performance counters.     

基于GML的市政道路管理模型

区别于传统的道路数据模型,基于地理标记语言（GML）的市政道路模型面向市政道路组成元素管理。分析市政道路组成元素的特点以及管理部门对市政道路管理的需求,依据GML的核心模式,建立面向管理领域的市政道路设施的空间属性一体化模型,并对该道路模型的应用前景进行分析。     

面向对象的非线性有限元软件框架设计

阐述面向对象的非线性有限元软件框架设计,在前人成果的基础上,力求软件框架更灵活、更完善。采用模型分析方法与有限元模型分离的方式,明确描述各类之间的依赖关系以及相互之间的传递消息过程,建立非线性有限元软件的框架结构。增加有限元软件的模块化、代码的重用性和易扩展性,解决长期以来存在于非线性有限元开发的一个重要难题。     

Finite Element Analysis of 6300 Deep Groove Ball Bearing

Rolling bearing is widely used in mechanical support, its general components are the inner ring, outer ring, the ball, retainer etc.. Now many companies in developed countries and university in the rolling bearing as the research object, and has made great progress in design theory, the experiment method and production technology etc. We will use the finite element ANSYS to establish the model of deep groove ball bearing. Through the contact analysis, we can get the contact stress between the rings and balls, strain, contact state, penetration, sliding distance and the friction stress distribution. These values are compared to the theoretical values with Hertz theory, and they have better consistency, provide the good theoretical basis for the optimization design of rolling bearings.     

A parallel preconditioned conjugate gradient solution method for finite element problems with coarse–fine mesh formulation

The object of this paper is a parallel preconditioned conjugate gradient iterative solver for finite element problems with coarse-mesh/fine-mesh formulation. An efficient preconditioner is easily derived from the multigrid stiffness matrix. The method has been implemented, for the sake of comparison, both on a IBM-RISC590 and on a Quadrics-QH1, a massive parallel SIMD machine with 128 processors. Examples of solutions of simple linear elastic problems on rectangular grids are presented and convergence and parallel performance are discussed.     

有限构模器的扩展及其在形式化方法中的应用

规约在软件开发和验证中占有重要地位,对于以一阶逻辑为基础的规约,可以利用有限模型构造技术对其执行并测试,文中研究规约中某些特性的处理,包括存在量词以及二元关系析传递闭包,对已有的一个构模工具进行扩充,发现了文献中的若干错误。     

Simulation and fabrication of piezoresistive membrane type MEMS strain sensors

Two piezoresistive (n-polysilicon) strain sensors on a thin Si₃N₄/SiO₂ membrane with improved sensitivity were successfully fabricated by using MEMS technology. The primary difference between the two designs was the number of strips of the polysilicon patterns. For each design, a doped n-polysilicon sensing element was patterned over a thin 3 μm Si₃N₄/SiO₂ membrane. A 1000×1000 μm² window in the silicon wafer was etched to free the thin membrane from the silicon wafer. The intent of this design was to fabricate a flexible MEMS strain sensor similar in function to a commercial metal foil strain gage. A finite element model of this geometry indicates that strains in the membrane will be higher than strains in the surrounding silicon. The values of nominal resistance of the single strip sensor and the multi-strip sensor were 4.6 and 8.6 kΩ, respectively. To evaluate thermal stability and sensing characteristics, the temperature coefficient of resistance [TCR=(ΔR/R₀)/ΔT] and the gage factor [GF=(ΔR/R₀)/] for each design were evaluated. The sensors were heated on a hot plate to measure the TCR. The sensors were embedded in a vinyl ester epoxy plate to determine the sensor sensitivity. The TCR was 7.5×10⁻⁴ and 9.5×10⁻⁴/°C for the single strip and the multi-strip pattern sensors. The gage factor was as high as 15 (bending) and 13 (tension) for the single strip sensor, and 4 (bending) and 21 (tension) for the multi-strip sensor. The sensitivity of these MEMS sensors is much higher than the sensitivity of commercial metal foil strain gages and strain gage alloys.