轮式车载防空导弹行进间发射动力学仿真分析

利用谐波叠加法生成三维随机路面图,建立三维随机路面模型和8×8轮式车载防空导弹多体动力学模型。根据对比试验法设计平整路面静止状态、D级路面10 km/h和20 km/h 3种工况,对影响导弹出筒时刻状态的因素进行了分析。对行进间发射进行了不同时刻导弹弹射实验仿真,去除实验结果的偶然性,得出影响行进间发射导弹出状态的两个主要因素:在导弹弹射时刻车体的振动状态和导弹与导弹箱之间的接触碰撞。     

基于Vague集的装备采购项目组织结构评价方法

在装备采购项目组织评价中引入Vague集理论，在列举现有项目组织结构类型的基础上，构建项目组织结构评价指标体系，建立各项目组织结构和理想组织结构的Vague集，计算各项目组织结构和理想组织结构的相似度量，完成对装备采购项目组织结构的评价，为装备采购项目组织设计奠定基础。     

基于混合遗传算法的拦截弹道优化方法

传统的遗传算法中,交叉和变异样本的选择直接影响算法的收敛.通常根据工程实际需求调整交叉和变异样本的选择概率来提高遗传算法运行的有效性和防止早熟现象的发生.将传统的单纯形搜索算法与遗传算法相结合,提出了一种混合遗传算法,并在算法中增加了加速循环操作,提高遗传算法在求解优化问题特别是工程应用中的有效性,以便优化拦截弹道.数学仿真结果表明该方法能够有效地解决迎面拦截弹道问题.     

Nonperiodic preventive maintenance for repairable systems

As a complex system with multiple components usually deteriorates with age, preventive maintenance (PM) is often performed to keep the system functioning in a good state to prolong its effective age. In this study, a nonhomogeneous Poisson process with a power law failure intensity is used to describe the deterioration of a repairable system, and the optimal nonperiodic PM schedule can be determined to minimize the expected total cost per unit time. However, since the determination of such optimal PM policies may involve numerous uncertainties, which typically make the analyses difficult to perform because of the scarcity of data, a Bayesian decision model, which utilizes all available information effectively, is also proposed for determining the optimal PM strategies. A numerical example with a real failure data set is used to illustrate the effectiveness of the proposed approach. The results show that the optimal schedules derived by Bayesian approach are relatively more conservative than that for non‐Bayesian approach because of the uncertainty of the intensity function, and if the intensity function are updated using the collected data set, which indicates more severe deterioration than the prior belief, replacing the entire system instead of frequent PM activities before serious deterioration is suggested. © 2010 Wiley Periodicals, Inc. Naval Research Logistics, 2010     

基于DSP的旋转弹用微小型导航系统设计

在无陀螺捷联惯导系统中,针对旋转弹体积小、功耗大、采样频率高、姿态变化快、解算周期短等问题。为满足旋转弹对其导航计算机的严格要求,提出了一种基于DSP的旋转弹用微小型导航系统设计,首先叙述了系统的总体方案设计,接着重点介绍了系统各模块的软硬件设计。本设计在硬件上节省了系统的体积和功耗,软件设计上节省了解算周期。     

一种低精度捷联式惯导系统初始对准方法

捷联式惯导系统的对准,是指在系统进入工作前建立姿态矩阵的初始值。针对低精度捷联式惯导的初始对准,提出了基于捷联式惯导系统和双天线GPS测向系统组合的初始对准方案,并着重推导了失准角和陀螺常值漂移的计算过程,最后利用最小二乘法进行了实验验证,结果表明方法可行。     

工控机简易飞机模拟座舱设计与实现

基于工控机的简易飞机模拟座舱是针对现在综合模拟座舱造价高而飞行员和空地勤人员必须熟悉航电设备的要求而设计的一种模拟设备.首先介绍了简易模拟座舱的硬件、软件组成、功能、工作原理和实现过程,同时重点介绍了操纵杆和方向舵的传递模型.     

A multi‐stage stochastic programming approach for network capacity expansion with multiple sources of capacity

In networks, there are often more than one sources of capacity. The capacities can be permanently or temporarily owned by the decision maker. Depending on the nature of sources, we identify the permanent capacity, spot market capacity, and contract capacity. We use a scenario tree to model the uncertainty, and build a multi‐stage stochastic integer program that can incorporate multiple sources and multiple types of capacities in a general network. We propose two solution methodologies for the problem. Firstly, we design an asymptotically convergent approximation algorithm. Secondly, we design a cutting plane algorithm based on Benders decomposition to find tight bounds for the problem. The numerical experiments show superb performance of the proposed algorithms compared with commercial software. © 2016 Wiley Periodicals, Inc. Naval Research Logistics 63: 600–614, 2017     

体育教学中如何培养学生的意志品质

意志品质是人们为达到既定目的而在行动所表现出来的自觉克服困难的心理过程。意志品质具体表现在鉴定的目的性;顽强性和果断性;勇敢创新精神。在体育教学中能否体现出意志品质的培养和有目的的是学生克服各种各样的困难完成意志行动,这对提高教学质量有很大的促进和发展作用。     

Integrating decisions with advance supply information in an assemble-to-order system

We study a periodic-review assemble-to-order (ATO) system with multiple components and multiple products, in which the inventory replenishment for each component follows an independent base-stock policy and stochastic product demands are satisfied according to a First-Come-First-Served rule. We assume that the replenishment for various component suffers from lead time uncertainty. However, the decision maker has the so-called advance supply information (ASI) associated with the lead times and thus can take advantage of the information for system optimization. We propose a multistage stochastic integer program that incorporates ASI to address the joint optimization of inventory replenishment and component allocation. The optimal base-stock policy for the inventory replenishment is determined using the sample average approximation algorithm. Also, we provide a modified order-based component allocation (MOBCA) heuristic for the component allocation. We additionally consider a special case of the variable lead times where the resulting two-stage stochastic programming model can be characterized as a single-scenario case of the proposed multistage model. We carry out extensive computational studies to quantify the benefits of integrating ASI into joint optimization and to explore the possibility of employing the two-stage model as a relatively efficient approximation scheme for the multistage model.