坦克直瞄/间瞄射击一体化火控技术

直瞄射击方式是目前坦克采用的主要射击方式。直瞄射击方式受战场通视度及瞄准装置视距的影响,最大射击距离一般在5 km左右。间瞄射击方式不需要直接瞄准目标,不受战场通视度的影响,最大射击距离主要取决于火炮及弹药的性能,一般在10 km以上。未来坦克应具备直瞄射击与间瞄射击一体化能力。通过直瞄/间瞄射击火控技术的对比与分析,提出坦克直瞄/间瞄射击一体化火控方案。一体化火控具有新的技术特色,具有更强的综合作战能力,是未来坦克火控技术发展的一种趋势。     

Budget allocation,national security,military intelligence,and human capital: a dynamic model

This study develops a dynamic model that integrates military intelligence into the defense capability of the country and the optimal allocation of its government budget. We assert that the effectiveness of the country’s military intelligence is contingent on the quality of its human capital, which, in turn, implies a long-term positive relationship between the government’s various civilian expenditures and its capacity to achieve a cost-effective intelligence and, hence, military capability. This relationship is developed within a multiple-period arms race model between two rivals. Using this model and stylized data for the Israeli–Syrian arms race, we show that an appropriate budget shift from defense to civilian expenditures during the initial periods of the planning horizon will gradually (over a decade, say) increase the quality of human capital in the country and, thus, the effectiveness of its intelligence, which, in turn, will increase the country’s future security and welfare.     

装备技术体系结构演化和超网络建模

装备技术体系结构演化模型是把握装备技术发展规律和制定发展战略的基础。文章系统梳理装备技术发展的体系特征,深入分析了其体系演化动力、要素和过程,将演化实体与关系抽象为超网络的节点和边,可以给前沿技术探测和装备技术体系评估提供新思路。     

简谐外磁场环境下J-C模型的热力学纠缠

以简谐外磁场环境下的J-C模型为研究对象,从系统的哈密顿矩阵出发,通过计算模拟得出热力学纠缠度解析表达式。计算结果表明,对应于不同的外磁场强度,系统热力学纠缠度呈周期性余弦变化,但随环境温度升高快速衰减;在相同环境温度下,系统热力学纠缠度关于磁场强度左右不对称变化。     

水顶油顺序输送油水混合模型研究

顺序输送是利用一条管道输送多种油品,因其可最大限度发挥管道输送潜能而被广泛应用。按照前后行液体不同可分为水顶油、油顶水和不同油品间顺序输送等,其中水顶油顺序输送主要用于管道撤收前的排空作业。对水顶油顺序输送油水混合过程进行了分析,建立了油水混合模型,利用CFD对其进行数值求解,并将仿真结果与前期理论分析进行了对比,两者吻合较好。所得结论可为机动管线水顶油排空作业提供科学指导。     

改进遗传算法求解电力网攻击无人机分队任务分配

遗传算法因其出色的寻优能力,自提出后就被广泛用于工程技术上的最优化问题求解。根据电力网攻击无人机分队任务分配的实际需要,提出基于遗传算法思想的解决方案,并在原算法基础上,采用种群分组进化的策略进行改进。详细介绍算法的基本原理和仿真步骤,再举出实际算例进行仿真,实验结果证明算法的改进取得了良好效果。     

A learning tabu search for a truck allocation problem with linear and nonlinear cost components

The two‐level problem studied in this article consists of optimizing the refueling costs of a fleet of locomotives over a railway network. The goal consists of determining: (1) the number of refueling trucks contracted for each yard (truck assignment problem denoted TAP) and (2) the refueling plan of each locomotive (fuel distribution problem denoted FDP). As the FDP can be solved efficiently with existing methods, the focus is put on the TAP only. In a first version of the problem (denoted (P1)), various linear costs (e.g., fuel, fixed cost associated with each refueling, weekly operating costs of trucks) have to be minimized while satisfying a set of constraints (e.g., limited capacities of the locomotives and the trucks). In contrast with the existing literature on this problem, two types of nonlinear cost components will also be considered, based on the following ideas: (1) if several trucks from the same fuel supplier are contracted for the same yard, the supplier is likely to propose discounted prices for that yard (Problem (P2)); (2) if a train stops too often on its route, a penalty is incurred, which represents the dissatisfaction of the clients (Problem (P3)). Even if exact methods based on a mixed integer linear program formulation are available for (P1), they are not appropriate anymore to tackle (P2) and (P3). Various methods are proposed for the TAP: a descent local search, a tabu search, and a learning tabu search (LTS). The latter is a new type of local search algorithm. It involves a learning process relying on a trail system, and it can be applied to any combinatorial optimization problem. Results are reported and discussed for a large set of instances (for (P1), (P2), and (P3)), and show the good performance of LTS. © 2014 Wiley Periodicals, Inc. 62:32–45, 2015     

Model parameter estimation and residual life prediction for a partially observable failing system

We consider a partially observable degrading system subject to condition monitoring and random failure. The system's condition is categorized into one of three states: a healthy state, a warning state, and a failure state. Only the failure state is observable. While the system is operational, vector data that is stochastically related to the system state is obtained through condition monitoring at regular sampling epochs. The state process evolution follows a hidden semi‐Markov model (HSMM) and Erlang distribution is used for modeling the system's sojourn time in each of its operational states. The Expectation‐maximization (EM) algorithm is applied to estimate the state and observation parameters of the HSMM. Explicit formulas for several important quantities for the system residual life estimation such as the conditional reliability function and the mean residual life are derived in terms of the posterior probability that the system is in the warning state. Numerical examples are presented to demonstrate the applicability of the estimation procedure and failure prediction method. A comparison results with hidden Markov modeling are provided to illustrate the effectiveness of the proposed model. © 2015 Wiley Periodicals, Inc. Naval Research Logistics 62: 190–205, 2015     

电传动装甲车辆电源系统建模与仿真

电源系统是电传动装甲车辆的核心,对其进行建模与仿真研究具有重要意义。电源系统的非线性特性导致了建模困难、模型精度低以及模型实用性差等难题,针对不同的部件特性采取不同的方法建立其仿真模型,完成了基于模糊控制的系统多目标优化功率分配策略研究。并在此基础上进行了部件和系统两个层次的仿真试验,证明所建模型能够较好地反映电传动车辆电源系统的工作特性。     

高超声速飞行器新息滤波交互式多模型跟踪算法

研究临近空间高超声速飞行器在运动特点,针对强杂波环境下高速、高机动目标跟踪问题,提出用新息滤波减小观测噪声以修正模型概率更新过程的算法。Monte-Carlo仿真结果表明:该算法可以有效减小量测噪声对系统滤波的影响,提高滤波精度,在临近空间强杂波环境下具有较好的跟踪精度,具有一定工程实用价值。