发动机冷却燃料超临界压力下做功潜力㶲分析

在高马赫数飞行下,超燃冲压发动机的燃料冷却量大于燃料燃烧量。为了降低燃料的冷却量以及实现燃料冷却量和燃烧量的匹配,采用分析法对超燃冲压发动机壁面燃料冷却工质在超临界压力下进行做功潜力分析。发动机壁面冷却燃料的特性决定其热量大小。根据发动机壁面温度分布、热流密度分布计算热量,建立稳定流动燃料工质的平衡方程。结果表明:在壁面最高温度为1200 K时,传入壁面的热量为562.4 k W,其中理论热量为541.3 k W;冷却燃料工质流量增加,最大输出功减小;燃料工质出口温度增加,输出功减小;燃料工质出口压力增加,输出功基本不变。     

基于稀疏贝叶斯学习的扩展目标雷达关联成像*

雷达关联成像不依赖于雷达与目标的相对运动,是一种高分辨凝视成像方式。传统的关联成像方法未考虑复杂扩展目标的结构信息,在高分辨成像时的应用受到限制,为此提出一种自适应结构配对稀疏贝叶斯学习方法。该算法在稀疏贝叶斯学习的框架内针对扩展目标建立一种结构配对层次化高斯先验模型,然后采用变分贝叶斯期望-最大化算法交替进行目标重构和参数优化。该算法将某一信号分量的重构与周围信号分量联系起来,并能在迭代过程中自适应地调整表征各信号分量相关性的参数。实验结果表明,该方法针对扩展目标可以有效地进行高分辨成像。     

多核贝叶斯优化的模型决策树算法

构造模型决策树时超参数较多,参数组合复杂,利用网格搜索等调参方法将会消耗大量的时间,影响模型性能的提升。提出了一种多核贝叶斯优化的模型决策树算法,该算法为应对不同分类数据特性,采用三种高斯过程建模寻优,利用贝叶斯优化技术,选出最优的参数组合。实验结果表明,所提算法在参数寻优上要优于传统的模型决策树寻优方法,并且能够在迭代次数不多的情况下找到全局最优参数值,在一定程度上提升了算法的分类性能,节省了大量的调参时间。     

EUROPEAN DEFENCE FIRMS: THE INFORMATION BARRIER ON PRIVATE FINANCE*

After the fall of the Berlin Wall, European governments adopted a hands‐off policy towards the defence industrial base, in an attempt to increase the sector’s efficiency and reactivity. In this context, one topical issue is how to motivate defence firms to apply for private rather than public finance. Since banks have no prior experience with European defence firms, a problem of asymmetric information may block this transition. The problem is analysed within the framework of a game between defence firms and banks. It is shown that the Bayesian Equilibrium might correspond to a situation where low‐risk firms prefer the state‐financed scheme; yet, in a perfect information set‐up, the same firms would apply for bank credit. In order to facilitate the transition to private finance, the government might decide to subsidize investors who agree on financing defence firms; the state aid should be made available during a transitory learning period.     

The effect of deployment on first‐ and second‐term re‐enlistment in the US active duty force

Why should deployment affect re‐enlistment? In our model, members enter the military with naïve beliefs about deployment and use actual deployment experience to update their beliefs and revise their expected utility of re‐enlisting. Empirically, re‐enlistment is related to the type and number of deployments, consistent with the learning model. Non‐hostile deployment increases first‐term re‐enlistment but hostile deployment has little effect except for the Army, where the effect is positive. Both types increase second‐term re‐enlistment. Interestingly, first‐term members with dependants tend to respond to deployment like second‐term members. In addition, deployment acts directly to affect re‐enlistment, not indirectly through time to promotion.     

Waypoint analysis for command and control

Command and Control (C2) in a military setting can be epitomized in battles‐of‐old when commanders would seek high ground to gain superior spatial‐temporal information; from this vantage point, decisions were made and relayed to units in the field. Although the fundamentals remain, technology has changed the practice of C2; for example, enemy units may be observed remotely, with instruments of varying positional accuracy. A basic problem in C2 is the ability to track an enemy object in the battlespace and to forecast its future position; the (extended) Kalman filter provides a straightforward solution. The problem changes fundamentally if one assumes that the moving object is headed for an (unknown) location, or waypoint. This article is concerned with the new problem of estimation of such a waypoint, for which we use Bayesian statistical prediction. The computational burden is greater than an ad hoc regression‐based estimate, which we also develop, but the Bayesian approach has a big advantage in that it yields both a predictor and a measure of its variability. © 2004 Wiley Periodicals, Inc. Naval Research Logistics, 2004     

装备研制中的Bayesian网及其应用

针对装备研制过程中产生的大量试验和调试数据,提出采用Bayesian网挖掘各组成单元间的依赖关系,并对Bayesian网学习中基于信息论的方法进行了改进,使确定网络拓扑结构的过程更加客观.学习得到Bayesian网后,分析了其在失效源判定和发现设计缺陷等方面的应用.     

Effects of nano-sized aluminum on detonation characteristics and metal acceleration for RDX-based aluminized explosive

Nano-sized aluminum(Nano-Al)powders hold promise in enhancing the total energy of explosives and the metal acceleration ability at the same time.However,the near-detonation zone effects of reaction between Nano-Al with detonation products remain unclear.In this study,the overall reaction process of 170 nm Al with RDX explosive and its effect on detonation characteristics,detonation reaction zone,and the metal acceleration ability were comprehensively investigated through a variety of experiments such as the detonation velocity test,detonation pressure test,explosive/window interface velocity test and confined plate push test using high-resolution laser interferometry.Lithium fluoride(LiF),which has an inert behavior during the explosion,was used as a control to compare the contribution of the reaction of aluminum.A thermochemical approach that took into account the reactivity of aluminum and ensuing detonation products was adopted to calculate the additional energy release by afterburn.Combining the numerical simulations based on the calculated afterburn energy and experimental results,the param-eters in the detonation equation of state describing the Nano-Al reaction characteristics were calibrated.This study found that when the 170 nm Al content is from 0％to 15％,every 5％increase of aluminum resulted in about a 1.3％decrease in detonation velocity.Manganin pressure gauge measurement showed no significant enhancement in detonation pressure.The detonation reaction time and reaction zone length of RDX/Al/wax/80/15/5 explosive is 64 ns and 0.47 mm,which is respectively 14％and 8％higher than that of RDX/wax/95/5 explosive(57 ns and 0.39 mm).Explosive/window interface velocity curves show that 170 nm Al mainly reacted with the RDX detonation products after the detonation front.For the recording time of about 10 μs throughout the plate push test duration,the maximum plate velocity and plate acceleration time accelerated by RDX/Al/wax/80/15/5 explosive is 12％and 2.9 μs higher than that of RDX/LiF/wax/80/15/5,respectively,indicating that the aluminum reaction energy significantly increased the metal acceleration time and ability of the explosive.Numerical simulations with JWLM explosive equation of state show that when the detonation products expanded to 2 times the initial volume,over 80％of the aluminum had reacted,implying very high reactivity.These results are significant in attaining a clear understanding of the reaction mechanism of Nano-Al in the development of aluminized explosives.     

一种网络设备告警事件纵向关联方法的设计与实现

现有的网络事件关联系统主要存在以下不足:各被管设备感知的大量告警事件全部传送到管理端处理,会带来很多传输与事件管理问题;现有的网络事件关联方法很不成熟,一般只涉及底层协议告警事件的关联.在分析网络告警与故障关系的基础上,提出了一种在设备这一级驻留代理,采用贝叶斯网络推理技术完成包括应用层告警事件在内的本地告警事件纵向关联方法.并在描述协议栈各层协议实体模型的基础上,给出了利用AdventNet API和ebayes进行系统具体实现的方法.     

和谐本位社会中公共政策的价值冲突及其均衡

以利益原则为基础的功利主义倾向是当前政府实践决策的主要选择,这种决策模式不能解决建构和谐社会中公共政策的价值冲突问题。如何更好地坚持和谐本位原则,寻求公共政策价值冲突的均衡,构造和谐的公共政策价值结构,是建构和谐社会的一个重要课题。试图通过寻求公共政策价值冲突的均衡,探求建构和谐社会中公共政策价值冲突的解决办法。