Generalized F-discrepancy-based point selection strategy for dependent random variables in uncertainty quantification of nonlinear structures

In the performance evaluation of structures under disastrous actions, for example, earthquakes, it is important to take into account the randomness of structural parameters. Generally, these random parameters are treated either as independent or perfectly dependent, but practically they are partly dependent. This article aims at developing a point selection strategy for uncertainty quantification of nonlinear structures involving probabilistically dependent random parameters characterized by copula function. For this purpose, the point selection strategy for structures involving independent basic variables is first revisited. As an improvement, a generalized F-discrepancy diminishing oriented iterative screening algorithm is proposed. Then, combining with the conditional sampling method, a conditional point set rearrangement method and a conditional iterative screening-rearrangement method are proposed for probabilistically dependent variables. These new point selection strategies are readily incorporated into the probability density evolution method for uncertainty quantification of nonlinear structures involving dependent random parameters, which is characterized by copula function. The proposed methods are illustrated by two examples including a shear frame with hysteretic restoring forces and a reinforced concrete frame structure with the damage constitutive model of concrete, where the material parameters are probabilistically dependent. The results demonstrate the effectiveness of the proposed method. Problems to be studied are discussed.     

A review on spindle thermal error compensation in machine tools

Thermal error caused by the thermal deformation is one of the most significant factors influencing the accuracy of the machine tool. Among all the heat sources which lead to the thermal distortions, the spindle is the main one. This paper presents an overview of the research about the compensation of the spindle thermal error. Thermal error compensation is considered as a more convenient, effective and cost-efficient way to reduce the thermal error compared with other thermal error control and reduction methods. Based on the analytical calculation, numerical analysis and experimental tests of the spindle thermal error, the thermal error models are established and then applied for implementing the thermal error compensation. Different kinds of methods adopted in testing, modeling and compensating are listed and discussed. In addition, because the thermal key points are vital to the temperature testing, thermal error modeling, and even influence the effectiveness of compensation, various approaches of selecting thermal key points are introduced as well. This paper aims to give a basic introduction of the whole process of the spindle thermal error compensation and presents a summary of methods applied on different topics of it.     

Estimation of a preference map of new consumers for spatial load forecasting simulation methods using a spatial analysis of points

The paper presents a spatial analysis of points especially suited to estimate a preference map for new consumers, which is then used as an analytical tool in spatial electric load forecasting. This approach is an exploratory spatial data analysis used to discover useful point patterns in the spatial location of distribution transformers to calculate a preference value for each area, rating it with respect to a hypothetical load change that may occur. We consider the locations of distribution transformers occupied land. Random points are generated in the study area where the new loads are expected; these points are referred to as unoccupied land. The method uses a generalized additive model (GAM) to estimate the probability of unoccupied land becoming occupied land. We test the approach with data from a real distribution system in a mid-size city in Brazil; the result is a preference map that shows the areas where new consumers are most likely to be allocated. The main advantage of this method is the ability work with a small-scale resolution, which enables the use of a resolution suitable for spatial load forecasting method chosen. We test the calculated probabilities in a spatial load forecasting simulation, yielding results with lower spatial error when compared with the heuristic technique.     

基于列表的迭代分枝定界MIMO检测算法

提出了基于列表的迭代分枝定界算法,利用搜索到的候选列表计算比特软信息,降低了MAP计算复杂度,同时进一步提出了改进的列表分枝定界算法,每次迭代利用更新的先验信息重新计算候选列表,提高了列表质量。仿真结果表明列表分枝定界算法通过在MIMO信道检测和信道解码之间传递外信息,取得了逼近信道容量的性能,而修正的考虑先验信息的列表分枝定界算法在性能损失可忽略的情况下,减小了候选列表的大小。     

Solving method of generalized nonlinear dynamic least squares for data processing in building of digital mine

Data are very important to build the digital mine. Data come from many sources, have different types and temporal states. Relations between one class of data and the other one, or between data and unknown parameters are more nonlinear. The unknown parameters are non-random or random, among which the random parameters often dynamically vary with time. Therefore it is not accurate and reliable to process the data in building the digital mine with the classical least squares method or the method of the common nonlinear least squares. So a generalized nonlinear dynamic least squares method to process data in building the digital mine is put forward. In the meantime, the corresponding mathematical model is also given. The generalized nonlinear least squares problem is more complex than the common nonlinear least squares problem and its solution is more difficultly obtained because the dimensions of data and parameters in the former are bigger. So a new solution model and the method are put forward to solve the generalized nonlinear dynamic least squares problem. In fact, the problem can be converted to two sub-problems, each of which has a single variable. That is to say, a complex problem can be separated and then solved. So the dimension of unknown parameters can be reduced to its half, which simplifies the original high dimensional equations. The method lessens the calculating load and opens up a new way to process the data in building the digital mine, which have more sources, different types and more temporal states.     

三维数字摄影图中注记点高程值的自动检查

针对三维数字摄影图中注记点高程值出现的某些问题，进行了探索、研究，编写了对三维数字摄影图中注记点高程值进行自动检查与提取的程序，该程序的应用使三维数字摄影图中注记点高程值的数据质量有了保证。     

危机矿山问题的对策研究

危机矿山问题 ,是一个涉及矿产资源勘查与开发政策、矿业发展战略、国家资源安全和社会经济可持续发展的重要问题。本研究提出“实施资源接替勘查工程 ,加大矿业治理整顿力度 ,加大科技攻关力度”的三项建议 ;认为开展资源、矿业、矿山开发程度与发展潜力的调查与评价 ;编制我国资源矿产总体规划 ;通过国家适当政策扶持 ,发展科学发展观指导下的矿产资源的开发利用机制 ,是解决危机矿山问题最基本的工作基础和前提     

箱变坐标系与多元储量计算积分法要点简介

本文简要介绍了作为多元储量计算积分法算法依据的箱变坐标系、变值函数等新型数学方法和二元线性类单元层的基本算法，并对其它多元类算法作了简要提示。本法算法精确、用法简便，适用于一般矿产的各类储量计算和矿山设计、生产与科研及矿业管理中的各类有关问题，更可作为一种基本数学工具广泛用于解决其它行业和领域中的各类有关问题。     

最少圆弧逼近曲线的算法和Matlab的实现

讨论了三点圆弧最大误差逼近曲线的算法,理论上使圆弧逼近的段数达到最少。基于Matlab进行了程序的编制求解节点,用等弦长等弧长的圆弧替代理论圆弧,搜索节点的初始值,保证了程序的可靠快速运行。圆弧连接光顺性较好,数控程序段数少、效率高。