Stress and deformation analysis on deep surrounding rock at different time stages and its application

Based on the characteristics of the deep circular tunnel, the surrounding rock was divided into three regions: the cracked region, the plastic region and the viscoelastic region. The process of rock stress deformation and change was divided into three stages after the roadway excavation. By using the elastic–plastic mechanics theory, the analytical solutions of the surrounding stress and displacement at different stages and the radii of cracked and plastic regions were formulated. We additionally explained the surrounding rock stress and displacement which appeared in practical project. Simultaneously, based on the problem which emerged from a mine in Xuzhou during the excavating process of rock roadway’s transport, we got the theoretical solutions for the stress and displacement in the process of rock roadway’s excavation and considered that the broken area of rock roadway was largely loosing circle. The results indicate that according to the rheological characteristics of surrounding rock, in the primeval excavation of rock roadway, we should increase the length of anchor bolt and cooperate it with anchor nets cable-U steel supporting frame. In addition, when the deformation rate of the surrounding rock is descending after the 15 days’ excavation, we should use the “three anchor” supporting method (anchor bolt spray, anchor note and anchor rope) and set aside about 20 cm as the reserved deformation layer.     

A ctivation measurement of neutron distribution in intermediate energy heavy ion target area

The distribution of neutrons produced by the reaction of 50MeV/u ^12C-ion on a thick Cu target are studied.The neutrons are measured with threshold activation detectors.Al.F,C,Al and In activation samples were used to measure neutrons with energy greater than 7,11,20,50MeV and thermal neutrons,respectively,The fluence rate,energy and angular distributions of neutrons,total neutron yield of 12C-ion and the emission rate in the forward direction of neutrons over 11 and 20MeV were obtained.     

基于多种交易方式的省间省内现货市场双层出清模型

新能源比例不断提升,省间消纳需求不断增加,构建满足全局资源优化运行的省间市场是促进市场效率提升的关键。文中基于多种块交易及小时交易的时间耦合关系,建立了省间省内两级现货市场出清模型。首先,构建了包含普通小时交易、灵活小时交易、常规块交易、可移动式块交易和扩展链接式块交易多种交易方式的混合整数线性规划模型。其次,为解决省间市场主体较多、块交易时间耦合复杂带来的出清难度大的问题,提出了基于省内出清结果的参与省间市场主体的筛选机制,进一步实现基于各省筛选出主体的省间市场出清,通过融合省间、省内出清结果形成最终中标结果。最后,通过多区域互联的IEEE RTS-96系统算例验证该模型的合理性及其作用效果。结果表明,相较于各省单独出清,省间省内两级市场出清提升了整体社会福利。所提方法在提高求解效率的同时,尽量逼近省间整体出清的全局最优解,实现了社会福利最大化。     

基于模糊数学的低致敏营养餐包感官评价研究

以低致敏蛋白、微囊化油脂以及复合糖元为主要原料制备开发低致敏营养餐包。从粉体的颗粒特性、冲调特性和主客观感官特性等对餐包开展评价研究,利用模糊数学法对餐包冲调后的色泽、气味及滋味、组织状态进行感官评价;通过餐粉的均匀度、溶解稳定性、湿润性进行基本特性评定。结果表明：餐包粉体粒度分布与餐包冲调特性具有相关性,细粉颗粒（0~30 μm、0~50 μm、0~100 μm）与餐包冲调特性呈负相关性,与粗粉颗粒（200~500 μm）呈正相关性,即随细粉粉体颗粒体积不断增加,湿润时间不断增加,冲调特性逐渐变差;随粗粉粉体颗粒体积不断增加,湿润时间不断减少,则冲调特性不断加强。粉体粒径与餐包感官评分呈正向线性相关性,一定范围内,随粒径不断增大,感官评分不断加强,产品品质质量较好。该评价体系为完善低致敏营养包的加工工艺提供了理论依据。     

微机控制的感应电动机特性测试系统

采用单片机作为下位机,PC机作为上位机,联合组成了感应电动机特性的微机测试系统。单片机对被测电量波形进行同步采样,对被测电机的运行状态进行控制。PC机控制单片机的运行,对测量数据进行快速处理,打印试验报告,绘制图形曲线,实现了测试过程的自动化。     

串补装置中快速暂态过程的建模与时域求解

为了对间隙放电在串补平台设备上造成的快速暂态过电压进行评估,以部分单元等效电路(partial element equivalent circuit,PEEC)为基础,提出了含有集中元件支路的考虑全部段间电磁耦合的复杂多导体系统建模方法.此外还对含有非线性元件的复杂多导体系统状态方程的时域求解方法进行了深入研究.典型算例下与EMTP计算结果的对比表明,该文采用的方法计算结果准确,此外与传统方法相比对于紧密耦合的复杂多导体系统(如串补装置)电磁暂态过程的仿真具有更好的适用性.     

最少拍数字控制改善磁致伸缩微小位移机构动态特性

本文介绍一种新的适用于快速动态过程的磁致伸缩微小位移机构及其计算机数字控制实验系统;求出磁致伸缩微小位移机构系统的传递函数,并对利用计算机数字校正来进一步改善机构系统的动态特性进行了分析和实验。结果表明,该机构系统不仅适用于镜面车削时作精密微量进刀,而且还可以应用在误差动态补偿系统中作执行机构。     

基于概念格的多层属性约简方法

属性约简是粗糙集理论中的核心问题之一,概念格是进行知识表示和数据分析的一种有效工具。文中利用概念格作为约简工具,给出基于概念格的多层属性约简算法,提出相融可辨概念、相融等价概念、亏n级等概念,研究内涵亏值对分类能力变化产生的影响,给出概念格中形式背景约简的判定定理。文中算法能完备地求出所有可约简的最大属性集合,从而为概念格中属性约简提供一种有效方法。最后,通过实例分析和实验对比说明该约简算法的可行性与有效性。     

A general stochastic clustering method for automatic cluster discovery

Finding clusters in data is a challenging problem. Given a dataset, we usually do not know the number of natural clusters hidden in the dataset. The problem is exacerbated when there is little or no additional information except the data itself. This paper proposes a general stochastic clustering method that is a simplification of nature-inspired ant-based clustering approach. It begins with a basic solution and then performs stochastic search to incrementally improve the solution until the underlying clusters emerge, resulting in automatic cluster discovery in datasets. This method differs from several recent methods in that it does not require users to input the number of clusters and it makes no explicit assumption about the underlying distribution of a dataset. Our experimental results show that the proposed method performs better than several existing methods in terms of clustering accuracy and efficiency in majority of the datasets used in this study. Our theoretical analysis shows that the proposed method has linear time and space complexities, and our empirical study shows that it can accurately and efficiently discover clusters in large datasets in which many existing methods fail to run.