导管螺旋桨敞水性能的预报和比较

借助于计算流体力学软件,对导管螺旋桨的敞水性能进行了数值模拟,得到了在不同网格模型和湍流模型下导管螺旋桨的正车敞水性能曲线,通过与试验图谱的对比分析,发现Wilcoxk-ω模型更适合于导管螺旋桨的敞水性能计算,并且采用结构化网格和非结构化网格相结合的计算方法能够满足导管螺旋桨敞水性能预报的工程精度要求。同时,当网格中存在少量高度倾斜的网格单元时,在不影响计算收敛的情况下,仍能将计算误差控制在10%以内。此外,如果要获得更为精确的计算结果,应提高网格质量,尽量使用结构化网格,并将近壁面网格加密,合理控制壁面附近的Y+值。虽然网格数量的增加并不总是意味着计算误差的减少,但合理控制网格细密度能够获得更为可信的计算结果。     

具有全局收敛性的盲均衡算法

为了解决传统的自适应均衡技术需发送训练序列的问题,采用盲均衡技术,利用接收信号本身的特征使均衡器收敛。提出了一种新的盲均衡算法(C&D算法),该算法将CRIMNO算法和判决引导(Decision Directed,DD)算法相结合,利用信号序列间的互不相关特性,从而使其具有全局收敛性能。实验结果表明:与CRIMNO算法相比,在相同的信噪比下,该算法具有收敛快速、运算量少和残留误差小的特点。     

基于马尔可夫过程的坦克火力随机对抗模型

根据小规模坦克火力对抗中所具有的马尔可夫性特点,将该过程视为离散状态、离散时间的马尔可夫随机过程(马尔可夫链),由此建立了坦克与反坦克武器系统之间一对一对抗的随机格斗模型,并给出双方获胜概率和平均对抗回合数的计算公式。最后通过实例验证了模型的有效性。该模型克服了轮流对抗不符合战场实际的缺点,为分队指挥员在射击策略的选择和分队火力运用上的快速决策提供了较为精确的量化依据。     

Information security: Designing a stochastic‐network for throughput and reliability

Todas information and communication network requires a design that is secure to tampering. Traditional performance measures of reliability and throughput must be supplemented with measures of security. Recognition of an adversary who can inflict damage leads toward a game‐theoretic model. Through such a formulation, guidelines for network designs and improvements are derived. We opt for a design that is most robust to withstand both natural degradation and adversarial attacks. Extensive computational experience with such a model suggests that a Nash‐equilibrium design exists that can withstand the worst possible damage. Most important, the equilibrium is value‐free in that it is stable irrespective of the unit costs associated with reliability vs. capacity improvement and how one wishes to trade between throughput and reliability. This finding helps to pinpoint the most critical components in network design. From a policy standpoint, the model also allows the monetary value of information‐security to be imputed. © 2009 Wiley Periodicals, Inc. Naval Research Logistics, 2009     

Fire truck relocation during major incidents

The effectiveness of a fire department is largely determined by its ability to respond to incidents in a timely manner. To do so, fire departments typically have fire stations spread evenly across the region, and dispatch the closest truck(s) whenever a new incident occurs. However, large gaps in coverage may arise in the case of a major incident that requires many nearby fire trucks over a long period of time, substantially increasing response times for emergencies that occur subsequently. We propose a heuristic for relocating idle trucks during a major incident in order to retain good coverage. This is done by solving a mathematical program that takes into account the location of the available fire trucks and the historic spatial distribution of incidents. This heuristic allows the user to balance the coverage and the number of truck movements. Using extensive simulation experiments we test the heuristic for the operations of the Fire Department of Amsterdam‐Amstelland, and compare it against three other benchmark strategies in a simulation fitted using 10 years of historical data. We demonstrate substantial improvement over the current relocation policy, and show that not relocating during major incidents may lead to a significant decrease in performance.     

Interdiction models for delaying adversarial attacks against critical information technology infrastructure

Information technology (IT) infrastructure relies on a globalized supply chain that is vulnerable to numerous risks from adversarial attacks. It is important to protect IT infrastructure from these dynamic, persistent risks by delaying adversarial exploits. In this paper, we propose max‐min interdiction models for critical infrastructure protection that prioritizes cost‐effective security mitigations to maximally delay adversarial attacks. We consider attacks originating from multiple adversaries, each of which aims to find a “critical path” through the attack surface to complete the corresponding attack as soon as possible. Decision‐makers can deploy mitigations to delay attack exploits, however, mitigation effectiveness is sometimes uncertain. We propose a stochastic model variant to address this uncertainty by incorporating random delay times. The proposed models can be reformulated as a nested max‐max problem using dualization. We propose a Lagrangian heuristic approach that decomposes the max‐max problem into a number of smaller subproblems, and updates upper and lower bounds to the original problem via subgradient optimization. We evaluate the perfect information solution value as an alternative method for updating the upper bound. Computational results demonstrate that the Lagrangian heuristic identifies near‐optimal solutions efficiently, which outperforms a general purpose mixed‐integer programming solver on medium and large instances.     

The politics of multinational military operations

Today, few countries fight alone; most fight as allies or partners in multilateral campaigns. The end of the Cold War opened a window of opportunity for multinational military operations (MMOs). These have seen varying degrees of participation, enthusiasm, and success. This special forum is devoted to the politics of multilateral warfare including their formation, maintenance, and durability. The introduction sketches past research and derives some key questions of continuing relevance. The contributions shed light on the domestic and international politics of MMOs, focusing on the implementation of national restrictions and their repercussions for MMOs, party politics of military intervention, the conditions under which states decide to defect from military operations, and the role of junior partners in MMOs. In sum, this forum offers a fresh look at the politics of MMOs, including conceptual contributions to the study of national restrictions, domestic constraints, and coalition warfare.     

National restrictions in multinational military operations: A conceptual framework

Recent scholarship in security studies has started to explore the causes and consequences of various forms of national restrictions in multinational military operations (MMOs). This article makes a conceptual contribution to this literature by developing a theoretical framework of national restrictions in MMOs that distinguishes between structural, procedural, and operational restrictions. I argue that these types of restrictions are governed by different causal mechanisms. Structural restrictions are relatively stable over time and effect deployment decisions irrespective of other factors. Procedural restrictions, on the other hand, can constitute veto points against deployment only in combination with distinct political preferences. Finally, operational restrictions directly affect the rules of engagement of troop contributing countries. The article illustrates the three types of restrictions and their interaction with empirical examples from a range of countries and sketches their impact on MMO deployment decisions and mandates.