论欧洲安全稳定的基石:《欧洲常规武装力量条约》及其《修改协议》

本文简要地论述了被西方称之为是“欧洲安全基石”的《欧洲常规武装力量条约》及其《修改协议》的内容、产生的背景,以及它们对欧洲安全产生的有利影响及存在的缺陷。     

国外核现场放射性污染处理与研究

介绍了目前国外在核现场处理方面的技术途径以及采用的放射性去污和治理方法,分析了这些方法的优点和效果,并提出了适合中国国情的治理技术。     

流动注射分析法测定成烟产物中的Zn^2＋

采用流动注射分析技术建立了Zn^2＋的FIA分析方法．谊分析方法可行、简便。其数据可靠,具有较好的选择性和重现性．样品测定频率大于30个／h;在1．0～5．0mg／L范围内呈良好的线性关系,γ=0．9999;回收率大于98%．实现了烟幕剂成烟产物中Zn^2＋的快速定量测定．     

适于卫星闪电监测系统的地面站数目配置初探

闪电监测载荷搭载在不同卫星平台时,地面站对它的观测时间都会发生相应的改变,文中对其进行了计算,并对不同轨道高度下所需的地面站个数作了简要分析。     

流体网络在线性能评估与故障诊断方法

在流体网络机理建模的基础上,研究了各种性能退化因素对流体网络特性的影响,通过对网络当前特征参数与理想状态的偏差分析,给出了量化的流体网络性能评价指标,然后以该指标为依据,结合网络的拓扑结构和动态数据,实现了在线性能评估、故障诊断和故障定位。将该方法应用于实际工程案例,并通过仿真结果和实际情况的对比,证明了该方法的实用性和诊断评估结果的准确性。     

基于锥形量热法的油池火相似性及点火特性模拟实验

针对油料池火灾相似性及点火特性研究需要,构建了一种基于耗氧原理的油池火锥形量热法模拟实验系统,引入火灾尺度相似性概念,研究了实验室尺度油池火与真实尺度油池火的相似性关系,探讨了实验室尺度油池火预测真实尺度油池火的可行性,基于实验室尺度锥形量热法研究了油池火点火特性,得到了辐射强度、辐射距离对油料点燃时间的影响规律以及点燃时间与锥照射强度之间的拟合公式。     

The (s,Q) inventory model with Erlang lead time and deterministic demand

We develop a simple, approximately optimal solution to a model with Erlang lead time and deterministic demand. The method is robust to misspecification of the lead time and has good accuracy. We compare our approximate solution to the optimal for the case where we have prior information on the lead‐time distribution, and another where we have no information, except for computer‐generated sample data. It turns out that our solution is as easy as the EOQ's, with an accuracy rate of 99.41% when prior information on the lead‐time distribution is available and 97.54–99.09% when only computer‐generated sample information is available. Apart from supplying the inventory practitioner with an easy heuristic, we gain insights into the efficacy of stochastic lead time models and how these could be used to find the cost and a near‐optimal policy for the general model, where both demand rate and lead time are stochastic. © 2004 Wiley Periodicals, Inc. Naval Research Logistics, 2004     

误差配准在两种纯距离定位算法的应用比较

组网雷达系统中,由于观测信息量的增加,对目标存在多种定位算法。很多情形下,误差配准公式是基于某一定位算法推导而来,误差配准的结果也相应的用来提高此定位算法的定位精度。定位算法的复杂程度不同导致基于此算法推导误差配准公式难度不一致,不同定位算法的定位精度也不尽相同。因此,对两种多距离定位算法的定位精度、误差配准推导难易程度进行了理论分析和仿真计算,给出了定位精度的解析表达式和仿真结果。利用表达式简单的定位算法推导基于最小二乘的误差配准公式,并将误差配准结果反馈给定位精度高的定位算法,以最大程度提高误差配准结果的应用效果,减轻计算复杂度,提高信息的利用度。     

Blast resistance evaluation of urban utility tunnel reinforced with BFRP bars

To improve corrosion-resistance of shallow-buried concrete urban utility tunnels(UUTs),basalt fiber reinforced polymer(BFRP)bars are applied to reinforce UUTs.As the UUT must have excellent survival capability under accidental explosions,a shallow-buried BFRP bars reinforced UUT(BBRU)was designed and constructed.Repetitive blast experiments were carried out on this BBRU.Dynamic responses,damage evolutions and failure styles of the BBRU under repetitive explosions were revealed.The tunnel roof is the most vulnerable component and longitudinal cracks develop along the tunnel.When the scaled distance is larger than 1.10 m/kg1/3,no cracks are observed in the experiments.When the BBRU is severely damaged,there are five cracks forming and developing along the roof.The roof is simplified as a clamped-supported one-way slab,proved by the observation that the maximum strain of the transverse bar is much larger than that of the longitudinal bar.Dynamic responses of the roof slab are predicted by dynamic Euler beam theory,which can consistently predict the roof displacement under large-scaled-distance explosion.Compared with the UUT reinforced with steel bars,the BBRU has advantages in blast resistance with smaller deflections and more evenly-distributed cracks when the scaled distance is smaller than 1.260 m/kg1/3 and the steel bars enter plastic state.Longer elastic defamation of the BFRP bars endows the UUT more excellent blast resistance under small-scaled-distance explosions.     

针对KMC局部最优问题的飞蛾捕焰优化方法

针对传统飞蛾捕焰(MFO)算法求解复杂函数时后期收敛速度慢与求解精度较低等问题,提出了一种基于快速收敛的飞蛾捕焰(RMFO)算法.采用最大最小距离积的方法来初始化飞蛾群,能够提高算法全局收敛速度并且优化解的质量,同时构造出MFO算法的适应度函数作为寻优函数.将RMFO算法和有K均值聚类算法(KMC)进行交叉迭代,构建基于RMFO优化的KMC算法,求解聚类中心时能够改善聚类性能,可以解决现有KMC算法选取初始聚类中心不确定陷入结果局部最优的问题.实验结果表明,通过用UCI国际通用测试数据库的Iris、Wine和Glass 3种数据集,对RMFO算法和优化KMC算法进行性能测试,提出的RMFO算法更加精准,收敛速度快,不易陷入局部最优解,同时,优化KMC算法的聚类性能更好.