Temperature solution in multi-dimensional multi-layer bodies

Mathematical steps leading to computation of the temperature field in multi-dimensional, multi-layer bodies are described and numerical results for two-layer bodies are presented. The presentations include boundary conditions of the first, second, and third kind. Included in this paper is a table to assist in computing eigenvalues. Also, modifications are made to account for the contribution of contact resistance. An efficient computational scheme for calculating the eigenvalues is discussed and numerical results are presented. For multi-dimensional, multi-layer bodies, the eigenfunctions may have real or imaginary eigenvalues. The complete solution must include the contribution of imaginary eigenvalues; otherwise, the information will be erroneous. A procedure is introduced that places a bound on the location of each eigenvalue.     

Use of a residual distribution Euler solver to study the occurrence of transonic flow in Wells turbine rotor blades

 The aim of the present study is to investigate the occurrence of transonic flow in several cascade geometries and blade sections that have been considered in the design of Wells turbine rotor blades. The calculations were performed using an implicit Euler solver for two-dimensional flow. The numerical method uses a multi-dimensional upwind matrix residual distribution scheme formulated on a new symmetrized form of the Euler equations, both in time and in space, that decouples the entropy and the enthalpy equations. Second-order accurate steady-state solutions where obtained using a compact three-point stencil. The results show that unwanted transonic flow may occur in the turbine rotor at relatively low mean-flow Mach numbers. Received: 29 November 2001 / Accepted: 28 May 2002     

A two-level discretisation algorithm for the efficient solution of higher-dimensional population balance models

The increasing range of complex applications that call for population balances based models motivates the development of efficient and robust solution techniques. Several contemporary applications mandate the consideration of multi-dimensional population balances, accounting for the non-homogeneous and/or wide distribution of particle populations among several state variables (internal coordinates). This article presents an efficient and novel solution technique for multi-dimensional population balance models, inspired by the underlying physics of the problem and the dictates of the relevant rate processes in the population balance in terms of the accuracy of the solutions.     

城市公共空间共鸣环境的多维度研究及其理论框架建构

该文从心理学、社会学、管理学等多学科理论视角出发,首先指出城市公共空间共鸣环境的营造是城市设计的重要目标,进而对应共鸣环境的三个理论层次:使用个体与环境的共鸣、不同使用群体与环境的共鸣、不同利益群体的共鸣,从认知与行为、需求与社会、社会与管理三个方向,进行多维度理论研究.最后从空间秩序和运行保障两个层面建构出共鸣环境的...     

The time-marching method of fundamental solutions for wave equations

In this paper, a meshless numerical algorithm is developed for the solution of multi-dimensional wave equations with complicated domains. The proposed numerical method, which is truly meshless and quadrature-free, is based on the Houbolt finite difference (FD) scheme, the method of the particular solutions (MPS) and the method of fundamental solutions (MFS). The wave equation is transformed into a Poisson-type equation with a time-dependent loading after the time domain is discretized by the Houbolt FD scheme. The Houbolt method is used to avoid the difficult problem of dealing with time evolution and the initial conditions to form the linear algebraic system. The MPS and MFS are then coupled to analyze the governing Poisson equation at each time step. In this paper we consider six numerical examples, namely, the problem of two-dimensional membrane vibrations, the wave propagation in a two-dimensional irregular domain, the wave propagation in an L-shaped geometry and wave vibration problems in the three-dimensional irregular domain, etc. Numerical validations of the robustness and the accuracy of the proposed method have proven that the meshless numerical model is a highly accurate and efficient tool for solving multi-dimensional wave equations with irregular geometries and even with non-smooth boundaries.     

Order statistics-based parametric classification for multi-dimensional distributions

Traditionally, in the field of Pattern Recognition (PR), the moments of the class-conditional densities of the respective classes have been used to perform classification. However, the use of phenomena that utilized the properties of the Order Statistics (OS) were not reported. Recently, in [10], [8], we proposed a new paradigm named CMOS, Classification by the Moments of Order Statistics, which specifically used these quantifiers. It is fascinating that CMOS is essentially “anti”-Bayesian in its nature because the classification is performed in a counter-intuitive manner, i.e., by comparing the testing sample to a few samples distant from the mean, as opposed to the Bayesian approach in which the task is based on the central points of the distributions. In our initial works, we proposed the foundational theory of CMOS for the uni-dimensional Uniform and some other distributions. These results were extended for various symmetric and asymmetric uni-dimensional distributions within the exponential family in [8]. In this paper, we generalize these results for multi-dimensional distributions. The multi-dimensional generalization is particularly non-trivial because there is no well-established method for achieving the ordering of multi-dimensional data specified in terms of its uni-dimensional components. The strategy is analogous to a Naïve-Bayes' approach, although it really is of an anti-Naïve-Bayes' paradigm. We provide here the analytical and experimental results for the 2-dimensional Uniform, Doubly Exponential and Gaussian distributions, and also clearly specify the way by which one should extend the results for higher dimensions. The analogous results for the other distributions in the exponential family, which were discussed in [10], [8] are alluded to, but omitted to avoid repetition.     

多维力传感器动态特性研究中的一种新方法

为了将动态补偿与动态解耦这两种改善多维力传感器动态特性的重要方法有机结合起来,同时为了避免在较大耦合时不变性动态解耦造成的信号失真,提出了传感器并行补偿解耦方法。该方法综合了补偿和解耦两方法的优点,既能动态跟踪输入信号,提高了动态响应品质,又能去除耦合信号,并行处理效果明显。     

网络访问行为关联规则提取的研究与设计

首先介绍了用户网络访问行为分析系统的框架,然后针对系统需要解决的提取用户访问模式信息中的多维多值关联规则的问题,对传统的关联规则挖掘方法进行了扩充和改进.改进后的方法能够结合系统设计的属性参数及概念划分要求,提取有价值的关联规则,有效反映用户的访问行为模式.     

审计数据多维关联规则挖掘算法

现代信息技术在审计中的广泛应用导致审计数据量的快速增长,能否对这些审计数据作出正确的分析将直接影响到能否对可能出现的问题进行及时预测和调整.提出一个基于多维关联规则分析审计数据的挖掘算法,通过找出可能出现问题的频繁因素组合来发现这些问题发生的规律,并将此规律作为现实中预防举措的依据.     

基于编码频繁模式树的序列模式挖掘算法

提出了同时适用于一维和多维序列数据的统一存储结构——编码频繁模式树(CFP-tree),并通过渐进的前缀序列搜索方式来发现频繁序列模式,避免了在挖掘过程中递归地产生大量的中间子序列。实验证明,该算法在大规模数据的处理上比现有序列模式挖掘算法有更好的性能。