一维自组织映射聚类数的自适应确定

针对利用一维自组织映射进行彩色分割时聚类数目应该根据经验人为预先设定这一问题,基于误差平方和准则,提出了一种根据误差平方和的变化速率来自动地确定类数的方法。通过对两个实例的处理,验证了该方法的有效性。     

分布式虚拟环境中环境信息动态更新研究

环境信息动态更新是分布式虚拟环境的一个主要特点,如何使环境信息更新更活跃、更反应实际情况,一直是分布式虚拟环境研究的重点。在典型的分布式交互环境中,环境信息动态更新是基于协议数据单元(PDU),它不提供数据可靠性传输保证。如何保证分布式环境中各结点环境信息一致性,本文提出了一种信息校验和协议,它通过极少的信息传输就可保证各结点环境信息高度一致。文中定义了保证分布式环境信息动态一致性更新的协议数据单元,并在试验环境中证明了协议的可靠性。     

飞行器动力学环境预示技术应用研究

动力学环境试验技术已被广泛应用 ,但动力学环境预示技术还没有得到很好的重视和发展。讨论了几种动力学环境预示方法的特点 ,着重研究了统计能量分析 ( SEA)方法的原理及其应用 ,并以某型号发动机长尾喷管舱为例 ,具体给出其工程分析估计过程     

EMS型磁浮列车悬浮控制系统对爬坡能力的约束分析

分析EMS型磁浮列车的悬浮控制系统对爬坡能力的约束。首先基于系统开环传递函数和通用的悬浮控制器模型,通过将其单实极点配置为闭环非主导极点,将爬坡能力与控制系统的频带和阻尼等参数对应起来;然后以圆曲线型缓和曲线为例,分析得出坡道段的最大跟踪误差与行车速度的关系;最后结合允许误差,给出最小竖曲线与最大爬坡速度半径的关系。研究结果对实际工程具有一定的指导意义。     

Deterrence under nuclear asymmetry: THAAD and the prospects for missile defense on the Korean peninsula

The 2016 decision to deploy Terminal High Altitude Area Defense (THAAD) to South Korea has generated multitude of intensely politicized issues and has proved highly controversial. This has made it challenging to alleviate, let alone clarify, points of analytical and policy tensions. We instead disaggregate and revisit two fundamental questions. One is whether THAAD could really defend South Korea from North Korean missiles. We challenge the conventional “qualified optimism” by giving analytical primacy to three countermeasures available to defeat THAAD–use of decoys, tumbling and spiral motion, and outnumbering. These countermeasures are relatively inexpensive to create but exceedingly difficult to offset. Second, we assess the optimal way to ensure South Korean national security against North Korean missiles. By examining the balance of capability and issues of credibility/commitment, we show that the U.S. extended deterrence by punishment remains plentiful and sufficiently credible even without enhancing the current defense capability.     

线性模型的海基制导系统误差分离方法性能分析

利用传统制导工具系统误差线性回归模型,对Bayes估计、主成分分析以及正则化分析三种改进的分离方法进行了比较,分析了它们在工程应用上的优缺点,给出了实际应用时的限制因素;同时结合海基导弹特有的初始状态误差,设计了整体估计、分段估计以及迭代估计三种估计策略,给出了相应的分离步骤。仿真结果表明,文中给出的三种误差分离方法在不同的评价标准下具有不同的实际应用意义;而在弹道差评价标准以及方差评价标准下,分段估计和迭代估计策略下的误差分离结果要明显好于传统整体估计结果。     

视频监视前景图像估计的盲源提取方法

在视频图像运动检测的背景消减方法中,场景图像或帧可建模为前景图像和背景图像的叠加或线性混合。然而,实际中图像的背景和前景往往相关,常用的主成分分析和独立分量分析等方法难以实现准确提取。为此,将视频图像的前景提取建模为盲源提取问题,提出了一种基于均方交叉预测误差的盲源提取方法,可以从相关的源视频图像中提取期望的前景图像,并将该方法扩展应用于基于基本模型和特征背景模型的背景消减方案中。基于人工和实际视频的实验验证了盲源提取背景消减方法的可行性和有效性。     

Direct ink writing of 3D-Honeycombed CL-20 structures with low critical size

3D-Honeycombed CL-20 structures with low critical size of detonation have been fabricated successfully for intelligent weapon systems using a micro-flow direct ink writing (DIW) technology. The CL-20-based explosive ink for DIW technology was prepared by a two-component adhesive system with waterborne polyurethane (WPU) and ethyl cellulose (EC). Not only the preparation of the explosive ink but also the principle of DIW process have been investigated systematically. The explosive ink displayed strong shear-thinning behavior that permitted layer-by-layer deposition from a fine nozzle onto a substrate to produce complex shapes. The EC content was varied to alter the pore structure distribution and rheological behavior of ink samples after curing. The deposited explosive composite materials are of a honeycombed structure with high porosity, and the pore size distribution increases with the increase of EC content. No phase change was observed during the preparation process. Both WPU and EC show good compatibility with CL-20 particles. Apparently high activation energy was realized in the CL-20-based composite ink compared with that of the refined CL-20 due to the presence of non-energetic but stable WPU. The detonation performance of the composite materials can be precisely controlled by an adjustment in the content of binders. The 3D honeycombed CL-20 structures, which are fabricated by DIW technology, have a very small critical detonation size of less than 69 μm, as demonstrated by wedge shaped charge test. The ink can be used to create 3D structures with complex geometries not possible with traditional manufacturing techniques, which presents a bright future for the development of intelligent weapon systems.     

An approach for predicting digital material consumption in electronic warfare

Electronic warfare is a modern combat mode, in which predicting digital material consumption is a key for material requirements planning (MRP). In this paper, we introduce an insensitive loss function (ε) and propose a ε-SVR-based prediction approach. First, we quantify values of influencing factors of digital equipments in electronic warfare and a small-sample data on real consumption to form a real combat data set, and preprocess it to construct the sample space. Subsequently, we establish the ε-SVR-based prediction model based on “wartime influencing factors - material consumption” and perform model training. In case study, we give 8 historical battle events with battle damage data and predict 3 representative kinds of digital materials by using the proposed approach. The results illustrate its higher accuracy and more convenience compared with other current approaches. Taking data acquisition controller prediction as an example, our model has better prediction performance (RMSE = 0.575 7, MAPE (%) = 12.037 6 and R² = 0.996 0) compared with BP neural network model (RMSE = 1.272 9, MAPE (%) = 23.577 5 and R² = 0.980 3) and GM (1, 1) model (RMSE = 2.095 0, MAPE (%) = 24.188 0 and R² = 0.946 6). The fact shows that the approach can be used to support decision-making for MRP in electronic warfare.     

Optimal design of a novel cylindrical sandwich panel with double arrow auxetic core under air blast loading

The increasing threat of explosions on the battle field and the terrorist action requires the development of more effective blast resistance materials and structures. Curved structure can support the external loads effectively by virtue of their spatial curvature. In review of the excellent energy absorption property of auxetic structure, employing auxetic structure as core material in curved sandwich shows the potential to improve the protection performance. In this study, a novel cylindrical sandwich panel with double arrow auxetic (DAA) core was designed and the numerical model was built by ABAQUS. Due to the complexity of the structure, systematic parameter study and optimal design are conducted. Two cases of optimal design were considered, case1 focuses on reducing the deflection and mass of the structure, while case2 focuses on reducing the deflection and increasing the energy absorption per unit mass. Parameter study and optimal design were conducted based on Latin Hypercube Sampling (LHD) method, artificial neural networks (ANN) metamodel and the nondominated sorting genetic algorithm (NSGA-Ⅱ). The Pareto front was obtained and the cylindrical DAA structure performed much better than its equal solid panel in both blast resistance and energy absorption capacity. Optimization results can be used as a reference for different applications.