汉江大跨越输电模型塔试验研究

为了深入探索模型塔动力特性,以汉江大跨越塔为原型,按照动力相似理论制作了模型塔.试验采用施加突卸荷载的方法使模型产生自由振动,获取模型动力参数.结果表明,模型前两阶固有频率满足相似要求,模型设计合理.为更好地研究模型塔动力特性,在模型塔动力测试基础上,建立了模型塔有限元模型,对测试结果与模态分析结果进行了比较,提出了模...     

车辆典型部件结构的有限元模型修正方法

以车身结构中简化的典型结构形式为研究对象,利用有限元软件中的焊点模拟单元,建立典型结构的有限元模型并进行模态分析。在参数灵敏度分析的基础上,结合模态试验测得的数据,利用广义简约梯度算法,对结构的有限元模型进行修正和模型验证,深入探讨了车辆典型部件结构的有限元模型修正方法。通过模型修正,有限元模型的精度得到了明显的提高,为进一步研究车辆结构部件的振动特性奠定了基础。     

基于最小最大决策的三站时差定位布阵优化

提出了一种基于最小最大决策的三站时差定位布阵优化方法,以提高系统对目标区域的整体定位精度。应用基于最小最大决策的最优化理论,建立布阵优化问题的数学模型。该模型以三站坐标为决策变量,以目标区域的最大水平定位误差最小为目标函数,然后运用基于最小最大决策的最优化算法,求解模型的最优解,并将此最优解作为三站时差定位系统的最优布阵。仿真结果与理论计算一致,验证了这种布阵优化结果的最优性。     

考虑压缩性影响的超空泡流动数值计算

为了研究水下航行体航速接近水中声速时水的可压缩性对超空泡外形的影响,采用理想可压缩流体定常流动以及Riabouchinsky空化封闭模型,基于势流理论和有限体积方法,对绕圆盘空化器的超空泡流动进行了数值计算.计算时考虑到水的压缩性,水的状态方程采用Tait幂次率.提出了一种新的超空泡外形迭代方法并分析了流体压缩性对超空...     

基于不同分裂的修正局部Crank-Nicolson方法对一维热传导方程的应用

本文采用不同分裂的修正局部Crank-Nicolson方法讨论了一维热传导方程的初边值问题。该方法不仅具有原来计算量少,无条件稳定的优点,而且推广了该方法对复杂的数学物理方程应用的可能性。理论上分析了无条件稳定性、相容性及收敛性,最后进行数值试验,验证了它的可行性。     

以优质的信息服务打造武警高校名牌图书馆

武警院校图书馆要以提供优质的信息服务为着眼点,不断创新服务理念、服务方法和服务手段,并通过各项措施保障优质信息服务,达到创建武警高校名牌图书馆的目的。     

网络中心战战场精确时间的同步技术

本文阐述网络中心战战场的时间同步技术、精确时间体系结构、双向比对远距离时间同步技术。对各种时间获取技术进行了比较,对GPS定时原理作了较为详细的说明。     

Deterministic and stochastic scheduling with teamwork tasks

We study a class of new scheduling problems which involve types of teamwork tasks. Each teamwork task consists of several components, and requires a team of processors to complete, with each team member to process a particular component of the task. Once the processor completes its work on the task, it will be available immediately to work on the next task regardless of whether the other components of the last task have been completed or not. Thus, the processors in a team neither have to start, nor have to finish, at the same time as they process a task. A task is completed only when all of its components have been processed. The problem is to find an optimal schedule to process all tasks, under a given objective measure. We consider both deterministic and stochastic models. For the deterministic model, we find that the optimal schedule exhibits the pattern that all processors must adopt the same sequence to process the tasks, even under a general objective function GC = F(f₁(C₁), f₂(C₂), … , f_n(C_n)), where f_i(C_i) is a general, nondecreasing function of the completion time C_i of task i. We show that the optimal sequence to minimize the maximum cost MC = max f_i(C_i) can be derived by a simple rule if there exists an order f₁(t) ≤ … ≤ f_n(t) for all t between the functions {f_i(t)}. We further show that the optimal sequence to minimize the total cost TC = ∑ f_i(C_i) can be constructed by a dynamic programming algorithm. For the stochastic model, we study three optimization criteria: (A) almost sure minimization; (B) stochastic ordering; and (C) expected cost minimization. For criterion (A), we show that the results for the corresponding deterministic model can be easily generalized. However, stochastic problems with criteria (B) and (C) become quite difficult. Conditions under which the optimal solutions can be found for these two criteria are derived. © 2004 Wiley Periodicals, Inc. Naval Research Logistics, 2004     

Flow‐shop batch scheduling with identical processing‐time jobs

In many practical situations of production scheduling, it is either necessary or recommended to group a large number of jobs into a relatively small number of batches. A decision needs to be made regarding both the batching (i.e., determining the number and the size of the batches) and the sequencing (of batches and of jobs within batches). A setup cost is incurred whenever a batch begins processing on a given machine. This paper focuses on batch scheduling of identical processing‐time jobs, and machine‐ and sequence‐independent setup times on an m‐machine flow‐shop. The objective is to find an allocation to batches and their schedule in order to minimize flow‐time. We introduce a surprising and nonintuitive solution for the problem. © 2004 Wiley Periodicals, Inc. Naval Research Logistics, 2004     

Bounding the optimal burn‐in time for a system with two types of failure

Burn‐in is a widely used method to improve the quality of products or systems after they have been produced. In this paper, we consider the problem of determining bounds to the optimal burn‐in time and optimal replacement policy maximizing the steady state availability of a repairable system. It is assumed that two types of system failures may occur: One is Type I failure (minor failure), which can be removed by a minimal repair, and the other is Type II failure (catastrophic failure), which can be removed only by a complete repair. Assuming that the underlying lifetime distribution of the system has a bathtub‐shaped failure rate function, upper and lower bounds for the optimal burn‐in time are provided. Furthermore, some other applications of optimal burn‐in are also considered. © 2004 Wiley Periodicals, Inc. Naval Research Logistics, 2004