On the probabilistic-deterministic transition involved in a fragmentation process of brittle materials

Dynamic loadings produce high stress waves leading to the fragmentation of brittle materials such as ceramics, concrete, glass and rocks. The main mechanism used to explain the change of the number of fragments with stress rate is a shielding phenomenon. However, under quasi-static loading conditions, a weakest link hypothesis may be applicable. Therefore, depending on the local strain or stress rate, different fragmentation regimes are observed. One regime corresponds to single fragmentation for which a probabilistic approach is needed. Conversely, the multiple fragmentation regime may be described by a deterministic approach. The transition between the two fragmentation regimes is discussed for high performance concrete, glass and SiC ceramics.     

基于模糊解耦的火电单元机组负荷控制

讨论了火电单元机组负荷控制问题．根据火电单元机组工况多变的特点,提出一种基于模糊解耦的火电单元机组负荷控制方案,以提高控制系统适应负荷变化的能力．针对300MW仿真机的实测表明,与传统的PID定值控制相比,该方法改善了负荷控制性能,是一种具有实用价值的火电机组负荷控制方法．     

直流电磁继电器测试系统的设计

本文介绍了一种智能小型直流电磁继电器测试系统的软硬件设计。系统能根据继电器型号自动构建测试电路或控制合适的线性受控电源,只用单插座就能完成多规格继电器参数的自动测试;继电器动作时间性能参数的测试采用软件定时器为主、硬件电路为辅的方法。     

Mining atomic Chinese abbreviations with a probabilistic single character recovery model

An HMM-based single character recovery (SCR) model is proposed in this paper to extract a large set of atomic abbreviations and their full forms from a text corpus. By an “atomic abbreviation,” it refers to an abbreviated word consisting of a single Chinese character. This task is important since Chinese abbreviations cannot be enumerated exhaustively but the abbreviation process for compound words seems to be compositional. One can often decode an abbreviated word character by character to its full form. With a large atomic abbreviation dictionary, one may be able to handle multiple character abbreviation problems more easily based on the compositional property of abbreviations.     

中国中阶煤和高阶煤的储层特性及提高单井产量主要对策

中国山西河东地区中阶煤储层的含气量比较低、含气饱和度低，而储层渗透性好，储层能量比较大；山西沁水盆地南部高阶煤储层的含气饱和度比较低，渗透率小，储层能量低。文章针对这些特点，进行了精细的地质对比研究，提出了提高气产量的对策。认为最大限度地降低储层的废弃压力可提高采收率；应通过改善钻井液、采用欠平衡钻井和羽状水平井钻井技术，最大限度地降低钻井工程对煤层气储层造成的伤害；同时还要利用合理的固井程序和水泥浆、套管射孔完井技术和压裂技术；通过排水降压提高有效压差及注入CO₂来达到加快煤层气解吸和提高解吸量的目的。实践表明，该技术对提高单井气产量意义重大。     

康普顿散射对X射线透射谱的影响

采用一定组分的材料对X射线进行辐射屏蔽,可以吸收大部分的低能光子,减少X射线对电子系统的辐射损伤。但通过研究发现,由于康普顿散射的影响,在一定条件下,透射谱中的低能光子数不但没有减少反而大于入射谱,这对于电子元器件的辐射防护是不利的。通过改变入射源光子能谱、探测器位置、屏蔽材料类型以及屏蔽材料厚度等参量,采用蒙特卡罗方法计算并分析了散射光子对X射线透射谱的影响,得到了康普顿散射光子对X射线透射谱的影响规律,并提出了降低散射光子影响的几种措施。     

Metaheuristics for the single machine weighted quadratic tardiness scheduling problem

This paper considers the single machine scheduling problem with weighted quadratic tardiness costs. Three metaheuristics are presented, namely iterated local search, variable greedy and steady-state genetic algorithm procedures. These address a gap in the existing literature, which includes branch-and-bound algorithms (which can provide optimal solutions for small problems only) and dispatching rules (which are efficient and capable of providing adequate solutions for even quite large instances). A simple local search procedure which incorporates problem specific information is also proposed.The computational results show that the proposed metaheuristics clearly outperform the best of the existing procedures. Also, they provide an optimal solution for all (or nearly all, in the case of the variable greedy heuristic) the smaller size problems. The metaheuristics are quite close in what regards solution quality. Nevertheless, the iterated local search method provides the best solution, though at the expense of additional computational time. The exact opposite is true for the variable greedy procedure, while the genetic algorithm is a good all-around performer.     

激光测高技术的发展趋势

激光测高技术作为一种的先进测量手段,已广泛应用于地形地貌测绘、地球科学研究、航天工程、城市规划、森林资源调查等诸多方面。虽然激光测高技术已相对成熟,但随着激光技术的发展和应用需求的拓展,激光测高技术仍有很大的发展空间。通过对国外近期研制或正在研究的几个具体激光测高设备的介绍和分析,总结了激光测高技术的一些典型技术特点和发展趋势,介绍了多光束发射和接收、单光子探测、多回波测量和多功能集成等技术在激光测高仪的应用。这对开展新型激光测高技术的研究具有一定参考价值。     

极限学习机类不平衡数据学习算法研究

尽管极限学习机因具有快速、简单、易实现及普适的逼近能力等特点被广泛应用于分类、回归及特征学习问题,但是,极限学习机同其他标准分类方法一样将最大化各类总分类性能作为算法的优化目标,因此,在实际应用中遇到数据样本分布不平衡时,算法对大类样本具有性能偏向性。针对极限学习机类不平衡学习问题的研究起步晚,算法少的问题,在介绍了极限学习机类不平衡数据学习研究现状,极限学习机类不平衡数据学习的典型算法-加权极限学习机及其改进算法的基础上,提出一种不需要对原始不平衡样本进行处理的Adaboost提升的加权极限学习机,通过在15个UCI不平衡数据集进行分析实验,实验结果表明提出的算法具有更好的分类性能。     

SIMO信道中信噪比估计算法分析与仿真

针对单输入多输出(SIMO)信道信噪比估计问题,在建立同一信号模型的基础上,研究期望最大化估计、二阶矩四阶矩估计、四阶联合估计和六阶矩估计等4种算法。从天线数、调制方式及噪声功率等方面进行仿真,将结果与Cramer-Rao下界进行对比。结合仿真结果分析各种算法的实现复杂度。