循环加荷条件下饱和砂土液化细观数值模拟

利用离散单元法中的二维颗粒流方法(particle flow code in 2-dimension,PFC2D),通过对双轴数值试样施加循环等幅应变且控制加荷过程中试样体积(面积)不变的方法,模拟了循环加荷条件下饱和砂土的液化特性。在得到试样液化宏观力学响应的同时,分析了液化过程中内部平均接触数的变化规律。进一步研究了应变幅值、围压对数值试样液化特性的影响,并与室内试验规律进行了对比。结果表明,数值模拟能够定性地反映饱和砂土振动液化的一般规律,数值模拟得到的应变幅值、围压对试样抗液化强度的影响规律符合实际砂土室内试验规律。     

神东网络现状及解决思路

神东煤炭公司信息网络发展至今已经形成规模,在整个神华集团广域网中神东也是重要节点之一,肩负着周边各兄弟公司的广域网接入以及旗下众多煤矿和分公司业务数据的传输。由于神东网络属于自然发展型网络,在网络规模建设初期,问题容易规避,在形成规模以后,各种潜在的问题都可能导致网络故障从而影响整体网络的正常运行。分别从神东煤炭集团公司局域网、宽带网、井下工业以太网3个方面分别进行详细阐述。     

基于滑模变结构的感应电动机直接转矩控制

针对感应电动机常规直接转矩控制中存在磁链、转矩脉动大,低速控制不精确等问题,在建立α-β坐标系感应电动机数学模型的基础上,提出了一种基于滑模变结构的新型直接转矩控制方法。该方法利用转速滑模变结构控制器代替常规直接转矩控制中的PI控制器,可有效减小常规直接转矩控制中的磁链和转矩脉动,增强了系统的稳定性。仿真结果证明了该方法的正确性。     

A balanced solution of a fuzzy soft set based decision making problem in medical science

The purpose of this paper is two folded. Firstly, the concept of mean potentiality approach (MPA) has been developed and an algorithm based on this new approach has been proposed to get a balanced solution of a fuzzy soft set based decision making problem. Secondly, a parameter reduction procedure based on relational algebra with the help of the balanced algorithm of mean potentiality approach has been used to reduce the choice parameter set in the parlance of fuzzy soft set theory and it is justified to the problems of diagnosis of a disease from the myriad of symptoms from medical science. Moreover the feasibility of this proposed method is demonstrated by comparing with Analytical Hierarchy Process (AHP), Naive Bayes classification method and Feng's method.     

On the sizing of a solar thermal electricity plant for multiple objectives using evolutionary optimization

Design, implementation and operation of solar thermal electricity plants are no more an academic task, rather they have become a necessity. In this paper, we work with power industries to formulate a multi-objective optimization model and attempt to solve the resulting problem using classical as well as evolutionary optimization techniques. On a set of four objectives having complex trade-offs, our proposed procedure first finds a set of trade-off solutions showing the entire range of optimal solutions. Thereafter, the evolutionary optimization procedure is combined with a multiple criterion decision making (MCDM) approach to focus on preferred regions of the trade-off frontier. Obtained solutions are compared with a classical generating method. Eventually, a decision-maker is involved in the process and a single preferred solution is obtained in a systematic manner. Starting with generating a wide spectrum of trade-off solutions to have a global understanding of feasible solutions, then concentrating on specific preferred regions for having a more detailed understanding of preferred solutions, and then zeroing on a single preferred solution with the help of a decision-maker demonstrates the use of multi-objective optimization and decision making methodologies in practice. As a by-product, useful properties among decision variables that are common to the obtained solutions are gathered as vital knowledge for the problem. The procedures used in this paper are ready to be used to other similar real-world problem solving tasks.     

Web模式的仿真想定编辑与管理系统设计

基于虚拟战场对战场态势信息的需求,构建了Web模式的仿真想定编辑与管理系统,该系统包括仿真想定的输入,管理,编辑,标绘,输出等功能模块。在地理信息系统（Geographic Information System,GIS）和军标库等的支持下,用户可以根据具体的仿真需求,通过对仿真想定进行可视化编辑,简单灵活地实现对战场初始态势信息的输入。同时系统加强对已有的仿真想定的统一管理,建立仿真想定库,便于用户获取已有的仿真想定,大大提高其重用率,减少了不必要的重复劳动。     

浅谈软件开发过程中的方法问题

先进的制造模式要求信息集成和功能集成贯穿于产品生命周期的每一阶段,功能的集成需要软件系统的支持,从而推动先进制造模式的实现。软件开发过程是建造软件解决方案的关键要素。本文详细讨论了两类主要的过程开发方法,即面向对象方法和结构化方法。     

基于柔性互联技术的含高渗透率新能源配电网多目标优化运行

智能软开关（SOP）可控制潮流、提供无功补偿,进而改善配电网电压、降低网损。因此,针对可再生能源大规模接入配电网后电能质量下降问题,采用K-means算法构建风-光典型场景,同时建立了基于SOP、可投切电容器的含高渗透率分布式电源的主动配电网优化运行模型。该模型以电压偏差、系统网损最小以及系统运行成本最低为目标,综合考虑了能源利用率及系统运行稳定性。最后利用基于参考点的非支配排序方法的多目标优化算法（NSGA-III）进行求解,输出Pareto最优解集,并采用改进的IEEE 33节点系统对所建立模型的有效性进行了验证。     

密集观测场景下的敏捷成像卫星任务规划方法

针对密集观测场景下敏捷成像卫星任务规划问题求解空间大、输入任务序列较长的特点,综合考虑时间窗口约束、任务转移时卫星姿态调整时间、存储约束和电量约束,对敏捷成像卫星任务规划问题进行建模. 提出融合IndRNN和Pointer Networks的算法模型（Ind-PN）对敏捷成像卫星任务规划问题进行求解,使用多层的IndRNN结构作为算法模型的解码器. 基于Pointer Networks机制对输入任务序列进行选择,使用Mask向量考虑敏捷成像卫星任务规划问题中的各类约束. 基于Actor Critic强化学习算法对算法模型进行训练,以获得最大的观测收益率. 实验结果表明,对于密集观测场景下的任务规划,Ind-PN算法的收敛速度更快,可以获得更高的观测收益率.