Optimizing the spatial pattern of networks for monitoring radioactive releases

This study presents a method to optimize the sampling design of environmental monitoring networks in a multi-objective setting. We optimize the permanent network of radiation monitoring stations in the Netherlands and parts of Germany as an example. The optimization method proposed combines minimization of prediction error under routine conditions with maximizing calamity detection capability in emergency cases. To calculate calamity detection capability, an atmospheric dispersion model was used to simulate potentially harmful radioactive releases. For each candidate monitoring network, we determined if the releases were detected within one, two and three hours. Four types of accidents were simulated: small and large nuclear power plant accidents, deliberate radioactive releases using explosive devices, and accidents involving the transport of radioactive materials. Spatial simulated annealing (SSA) was used to search for the optimal monitoring design. SSA was implemented by iteratively moving stations around and accepting all designs that improved a weighted sum of average spatial prediction error and calamity detection capability. Designs that worsened the multi-objective criterion were accepted with a certain probability, which decreased to zero as iterations proceeded. Results were promising and the method should prove useful for assessing the efficacy of environmental monitoring networks designed to monitor both routine and emergency conditions in other applications as well.     

Optimal observer design to minimize the effect of system parameter variations

The sensitivity of an observer to variations in the parameters of the system being observed is considered. An equation is developed for the error in the observer output caused by variations in the system parameters. An analogue computer design procedure is utilized to minimize a quadratic performance index. An example is provided to illustrate this procedure.     

铁道罐车纵向冲击实验数据分析研究

考虑铁道罐车以及罐内装载的物体作为一个复杂系统,在运行时轮轨与轨道的相互作用下,研究车辆的安全问题,特别是罐车纵向加速度引起的问题显得相当复杂。为了分析罐车出现问题时的纵向加速度特性及故障原因,对正常信号和含故障的纵向加速度信号求互谱密度函数,找出共有纵向冲击频率,将该频率从含故障信号中滤除,反复数次,削弱故障信号中的正常运行的主要成分,最后通过加速度功率谱密度将纵向故障冲击频率从故障信号提取出来。     

杆式应变天平的优化设计

采用序列二次规划法,对一台实际的杆式六分量应变天平元件进行优化设计。在天平总体尺寸和输出应变基本相同的情况下,截面惯性矩提高4%～13%,提高了天平强度和刚度。     

微结构气体传感器的优化设计

利用SiO2相对于SiNx有更低的热导率,作为膜式微气体传感器的热绝缘和电绝缘层,而单晶Si适合通过各向异性腐蚀形成倒杯状结构来支撑SiO2膜。将膜式微气体传感器中的加热器和信号电极设计在一个平面上,以减小工艺复杂度,获得较高的加热效率。利用有限元分析工具ANSYS分析比较加热器和信号电极在不同宽度与间距时的温度分布。当设定加热器宽度为50μm,信号电极宽度50μm,加热器和信号电极间距为25μm,微气体传感器将获得更低的功耗和比较均匀的中心温度分布,有利于传感器整体性能的提高。     

Scheduling parallel jobs to minimize the makespan

We consider the NP-hard problem of scheduling parallel jobs with release dates on identical parallel machines to minimize the makespan. A parallel job requires simultaneously a prespecified, job-dependent number of machines when being processed. We prove that the makespan of any nonpreemptive list-schedule is within a factor of 2 of the optimal preemptive makespan. This gives the best-known approximation algorithms for both the preemptive and the nonpreemptive variant of the problem. We also show that no list-scheduling algorithm can achieve a better performance guarantee than 2 for the nonpreemptive problem, no matter which priority list is chosen. List-scheduling also works in the online setting where jobs arrive over time and the length of a job becomes known only when it completes; it therefore yields a deterministic online algorithm with competitive ratio 2 as well. In addition, we consider a different online model in which jobs arrive one by one and need to be scheduled before the next job becomes known. We show that no list-scheduling algorithm has a constant competitive ratio. Still, we present the first online algorithm for scheduling parallel jobs with a constant competitive ratio in this context. We also prove a new information-theoretic lower bound of 2.25 for the competitive ratio of any deterministic online algorithm for this model. Moreover, we show that 6/5 is a lower bound for the competitive ratio of any deterministic online algorithm of the preemptive version of the model jobs arriving over time.     

Stochastic quasigradient algorithm to minimize the quantile function

A stochastic quasigradient algorithm to minimize the quantile function on the basis of order statistic was proposed, and its convergence with the probability one was proved. An example was considered.     

Automatic concept model generation for optimisation and robust design of passenger cars

A fully automated method of structural optimisation for the body in white structure is presented. The body in white is a technical term for the car body without windows and closures. The iterations in the optimisation loop comprise the following steps: fully parameterised design creation, automated meshing and model assembly, parallel computation and evaluation. For this purpose several free and commercially available software applications were combined, including: SFE concept, Hypermesh, Perl, Matlab, and Radioss. The optimisation was conducted using Genetic Algorithms (GA), which are ideally suited to solve problems with solution spaces that are too large to be exhaustively searched. The viability of the method is demonstrated for a vehicle component model of a front bumper system utilizing both material and geometry related properties as design variables.     

Scheduling of network tasks to minimize the consumed energy

In this paper, we consider the problem of scheduling network tasks that have to be performed in a given computer network. Each network task consists of the transmission of data files between two nodes of the network and has to be performed in an a priori known time window in such a way that the energy consumed by the network equipment during the transmission of all the considered tasks is minimized. The entire mathematical model of this scheduling problem is proposed. Some results of computational experiments are also presented to show energy savings achieved through implementation of the proposed model in the interdata center network.     

强抗干扰遥控汽车编解码器的设计与应用

为提高遥控汽车的抗干扰能力,优化其控制功能,设计了一款具有16位随机地址码学习能力的多功能遥控汽车编解码器(MT-5/MR-5)。通过建立良好的通信协议、引入随机地址码学习功能和优化电路结构,极大地提高了遥控汽车的抗干扰和精确控制能力。最后介绍了该对编解码器在电路中的应用,具有进一步推广应用价值。     

基于AT89C52单片机的自动存取柜的设计与实现

本文介绍了基于AT89C52单片机的自动存取柜的软硬件设计方法。通过外接8255芯片、微型打印机及字符点阵式LCD、反射式红外传感器,键盘专用芯片74C922,限位开关及继电器阵列实现了人机交互能力强、简洁可靠的设计目的。     

雷达装备测试性设计优化技术

针对雷达装备测试性优化设计的实际技术需求,对雷达测试性优化设计过程进行了分析。以雷达装备各阶段数据为基础,综合考虑测试效能、测试代价、可靠性约束等要素,研究了基于测试代价和测试效能的测试性优化方法,并给出了基于最小测试代价的雷达系统测试性优化模型。针对模型多目标优化求解问题,给出了一种基于改进的粒子群优化算法。该算法引入混沌理论,使初始种群呈现多样性,避免了传统粒子群算法的早熟现象,同时提高了搜索的精度和速度。通过对案例的仿真与验证表明,利用这种改进的粒子群算法对基于最小测试代价的测试性优化模型进行求解时,能够在满足模型目标函数的约束条件下,获得全局最优解。     

Optimal design of a horizontal circular tank with ellipsoidal heads

A horizontal circular tank, supported at both ends, is loaded by internal or external pressure. In the design process of such structures the proper choice of basic dimensions to ensure minimal mass may cause a problem. In this paper the optimal radii, lengths and wall thicknesses of a series of tanks of given capacity have been defined. The results of numerical analysis are presented in the form of diagrams.     

Stochastic quasigradient algorithm to minimize the function of integral quantile

Proposed was a stochastic quasigradient algorithm to minimize the integral quantile function (CVaR criterion) with the use of the order statistics. Convergence of the algorithm with the probability one was proved, and an example was considered.     

基于LONWORKS油库智能管理控制系统设计

介绍了油库智能管理控制系统的软件结构及油情检测子系统、发油子系统、MIS系统、远程查询子系统的功能,最后给出了本文的结论。