Ballistic response of armour plates using Generative Adversarial Networks

It is important to understand how ballistic materials respond to impact from projectiles such that informed decisions can be made in the design process of protective armour systems. Ballistic testing is a standards-based process where materials are tested to determine whether they meet protection, safety and performance criteria. For the V₅₀ ballistic test, projectiles are fired at different velocities to determine a key design parameter known as the ballistic limit velocity (BLV), the velocity above which projectiles perforate the target. These tests, however, are destructive by nature and as such there can be considerable associated costs, especially when studying complex armour materials and systems. This study proposes a unique solution to the problem using a recent class of machine learning system known as the Generative Adversarial Network (GAN). The GAN can be used to generate new ballistic samples as opposed to performing additional destructive experiments. A GAN network architecture is tested and trained on three different ballistic data sets, and their performance is compared. The trained networks were able to successfully produce ballistic curves with an overall RMSE of between 10 and 20 % and predicted the V₅₀ BLV in each case with an error of less than 5 %. The results demonstrate that it is possible to train generative networks on a limited number of ballistic samples and use the trained network to generate many new samples representative of the data that it was trained on. The paper spotlights the benefits that generative networks can bring to ballistic applications and provides an alternative to expensive testing during the early stages of the design process.     

基于BP人工神经网络的GPS/SINS组合导航算法

基于扩展Kalman滤波的GPS/SINS组合导航算法,需要对原始的非线性连续系统模型进行线性化和离散化处理,要求系统噪声和测量噪声为零均值的高斯白噪声,且易于出现滤波器发散。BP人工神经网络无需对所求解的问题建模,能够很好地逼近系统非线性特性,获得较高精度的导航定位信息;还具有计算过程稳定,不涉及矩阵求逆,不需要迭代逼近,以及容易实现并行处理等优点。设计适用于GPS/SINS组合导航系统的BP网络模型,并在标准的BP算法基础上,采用共轭梯度法改进网络训练速度及精度。最后,通过仿真算例说明BP网络方法用于GPS/SINS组合导航计算的可行性。     

ZCS半桥式DC/DC变流器状态空间法建模及Matlab仿真分析

分析了一种ZCS半桥式DC DC变流器时域工作特性.通过研究其工作各阶段的特性建立了其状态空间模型,采用Matlab语言进行编程仿真,得到其输出电压时域仿真波,与实测吻合,证明了所建状态空间模型的正确性,得到变流器工作的一些有用结论,有助于指导下一步变流器的传导干扰分析和抑制.     

基于DTRC的形式自动证明平台及其应用

动态项重写计算(DTRC)是项重写系统(TRS)的元计算模型,具有层次化结构和动态重写等特征,可应用于归纳定理的形式自动证明以及项重写系统弱终止性的形式自动证明等方面.文中介绍了一个基于DTRC的形式自动证明平台及其在TRS弱终止性自动证明上的应用.     

基于MAS的武器装备供应管理支持系统设计

对武器装备供应管理系统结构和功能进行了分析,给出系统的一般构成模式和运行要求,阐明了其所需的决策支持;以系统一般模式为背景,探讨了利用多Agent系统理论构建装备供应管理支持系统的思路,提出支持系统的组成框架,并说明了其主要特点;最后,对支持系统的信息监控过程做了具体研究,给出了相应程序。     

AMESim与MATLAB/Simulink联合仿真技术及应用

分析了AMESim与MATLAB/Simulink的特点,对两者的联合仿真技术进行了研究,解决了联合仿真的接口问题.并把该技术应用于主动悬架系统,取得了良好效果.     

Optimal inventory control policy for periodic‐review inventory systems with inventory‐level‐dependent demand

We consider a setting in which inventory plays both promotional and service roles; that is, higher inventories not only improve service levels but also stimulate demand by serving as a promotional tool (e.g., as the result of advertising effect by the enhanced product visibility). Specifically, we study the periodic‐review inventory systems in which the demand in each period is uncertain but increases with the inventory level. We investigate the multiperiod model with normal and expediting orders in each period, that is, any shortage will be met through emergency replenishment. Such a model takes the lost sales model as a special case. For the cases without and with fixed order costs, the optimal inventory replenishment policy is shown to be of the base‐stock type and of the (s,S) type, respectively. © 2012 Wiley Periodicals, Inc. Naval Research Logistics, 2012     

WSEIAC模型的中远程空空导弹武器系统效能分析

依据中远程空空导弹武器平台系统的战术指标,建立了中远程空空导弹武器平台系统的效能评价体系.对ADC扩展模型中的人为因素K进行了修正,在能力矩阵C中增加对载机生存能力和信息支持能力的体现.在此基础上给出了修正扩展模型下的系统效能,计算了在原始ADC模型下的系统效能,并对两种模型下的效能差异进行了比较.     

军用飞机综合效能/费用评估方法

军用飞机的效能与费用是两个相互制约的因素,对两者进行科学合理的综合评估,对于军用飞机的发展和使用有着很重要的意义。在分析综合效能/费用的基本评估指标基础上,提出了在军用飞机全寿命周期综合效能/费用评估指标,重点对作战使用阶段的最佳效能/费用进行评估分析,最后给出结论。     

The effect of al particle size on thermal decomposition,mechanical strength and sensitivity of Al/ZrH2/PTFE composite

To study the thermal decomposition of Al/ZrH2/PTFE with different Al particle size as well as mechanical strength and impact sensitivity under medium and low strain rates, molding-vacuum sintering was adopted to prepare four groups of power materials and cylindrical specimens with different Al particle size. The active decomposition temperature of ZrH2 was obtained by TG-DSC, and the quasi-static me-chanics/reaction characteristics as well as the impact sensitivity of the specimen were studied respec-tively by quasi-static compression and drop-hammer test. The results show that the yield strength of the material decreased with the increase of the Al particle size, while the compressive strength, failure strain and toughness increased first and then decreased, which reached the maximum values of 116.61 MPa, 191％, and 119.9 MJ/m respectively when the Al particle size is 12—14μm because of particle size grading. The specimens with the highest strength and toughness formed circumferential open cracks and reacted partly when pressed. Those with developmental cracks formed inside did not react. It is considered that fracture of specimens first triggered initial reaction between Al and PTFE to release an amount of heat. Then ZrH2 was activated and decomposed, and participated in subsequent reaction to generate ZrC. The impact sensitivity of the specimens decreased with the increase of Al particle size.