天线波束对飞机射频隐身性能的影响分析

射频隐身是新一代军用飞机必须具备的重要能力。从隐身飞机的实际使用环境出发,针对以往只考虑个体对抗特性,采用Schleher截获因子评价飞机射频隐身性能的不足,提出了基于整体对抗特性,采用联合截获概率评估射频隐身性能的新方法,为射频隐身研究提供了新思路。通过对隐身飞机的射频使用环境建模,计算了天线波束的空、地覆盖区大小,结合联合截获概率的定义和计算方法,仿真了不同情况下天线波束宽度对联合截获概率的影响。根据仿真结果,分析了天线波束对飞机射频隐身性能的影响,其结论可为隐身飞机天线设计时的折中考虑提供基础和参考依据。     

声自导鱼雷一次转角射击参数的优化

为了提高声自导鱼雷一次转角射击的发现概率,建立了一次转角射击的解析模型,并将射击参数的优化归结为一个带约束的优化问题。使用了一种改进的粒子群算法解决了上述问题,优化了自导扇面相遇点系数和出管直航距离两个射击参数。实验结果表明,使用优化后的射击参数显著提高了鱼雷的发现概率。     

舰载弹炮结合近程反导武器系统火力分配模型研究

为最大程度发挥弹炮结合武器系统的作战效能,引入优化设计方法求取最大毁伤概率,建立了基于毁伤概率的火力分配模型。该模型将弹炮结合武器系统导弹和火炮的火力分配转化为导弹火力分配。根据导弹杀伤纵深和发射间隔确定导弹发射数量。根据导弹在杀伤区内毁伤概率特性,确定导弹发射时机。     

反潜巡逻机双机协同鱼雷攻潜作战仿真研究

反潜巡逻机双机协同鱼雷攻潜,是航空反潜作战的重要样式之一。根据巡逻机的技战术性能,首先研究了巡逻机双机协同鱼雷攻击方法中的投雷数量、投雷阵位和投雷时间间隔等问题;然后,结合反潜作战过程,给出投雷参数解算方法;最后,以命中概率为双机协同鱼雷攻潜作战效能的评估指标进行仿真计算,并对仿真结果进行了分析,为作战运用提供参考依据。     

舰炮拦截靶弹试验的安全性分析

为充分考核末端反导舰炮武器系统的反导能力,结合末端反导舰炮武器系统拦截靶弹需求对威胁概率进行了分析,提出了相关计算模型,并给出了相应的计算结果。其思路及算法不仅直接适用于末端反导舰炮拦截靶弹的安全分析,对其它武器装备试验及训练的安全分析也具有一定的参考价值。     

System reliability based on diffusion models for fatigue crack growth

Diffusion processes are commonly used to describe the dynamics of complex systems arising in a wide range of application fields. In this paper we propose, on the basis of diffusion processes, two models concerned with the stochastic behavior of fatigue cracks in a system. They are then used to get the distribution of the failure time, the first time the crack size of at least one of the cracks exceeds a given value. Several properties of our proposed models are presented, and the unknown parameters are estimated by the method of maximum likelihood. From these an estimate of failure time distribution is obtained. In this part, contrary to common practice, we do not assume availability of failure data. © 2004 Wiley Periodicals, Inc. Naval Research Logistics, 2005     

超视距反舰导弹打击水面舰艇编队计算模型

对水面舰艇编队采用超视距反舰导弹进行饱和攻击时,需要计算所需导弹数量。文章通过交战模型原型和损伤积累目标毁伤规律的分析,逐步建立超视距导弹对水面舰艇编队攻击作战的概率计算模型,以确定发射导弹数目与目标毁伤程度之间的关系。     

舰艇编队对空防御队形优化配置模型

分析了海上机动编队中防空舰的位置配置对舰艇编队拦截目标效果的影响,通过舰艇对来袭目标拦截概率的推导,建立了被掩护舰的生存概率模型,从而提供了一种解算编队防御队形最佳配置的方法。     

Scheduling recurrent construction

A problem we call recurrent construction involves manufacturing large, complex, expensive products such as airplanes, houses, and ships. Customers order configurations of these products well in advance of due dates for delivery. Early delivery may not be permitted. How should the manufacturer determine when to purchase and release materials before fabrication, assembly, and delivery? Major material expenses, significant penalties for deliveries beyond due dates, and long product makespans in recurrent construction motivate choosing a release timetable that maximizes the net present value of cash flows. Our heuristic first projects an initial schedule that dispatches worker teams to tasks for the backlogged products, and then solves a series of maximal closure problems to find material release times that maximize NPV. This method compares favorably with other well‐known work release heuristics in solution quality for large problems over a wide range of operating conditions, including order strength, cost structure, utilization level, batch policy, and uncertainty level. Computation times exhibit near linear growth in problem size. © 2004 Wiley Periodicals, Inc. Naval Research Logistics, 2004     

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