Numerical simulation of the natural fragmentation of explosively loaded thick walled cylinders

The ability to predict the natural fragmentation of an explosively loaded metal casing would represent a significant achievement. Physically-based material models permit the use of small scale laboratory tests to characterise and validate their parameters. The model can then be directly employed to understand and design the system of interest and identify the experiments required for validation of the predictions across a wide area of the performance space. This is fundamentally different to the use of phenomenologically based material algorithms which require a much wider range of characterisation and validation tests to be able to predict a reduced area of the performance space. Eulerians numerical simulation methods are used to describe the fragmentation of thick walled EN24 steel cylinders filled with PBXN-109 explosive. The methodology to characterise the constitutive response of the material using the physically based Armstrong–Zerilli constitutive model and the Goldthorpe path dependent fracture model is described, and the results are presented. The ability of an Eulerian hydrocode to describe the fragmentation process and reproduce the experimentally observed fragment mass and velocity distributions is presented and discussed. Finally the suitability of the current experimental analysis methodology for simulation validation is addressed.     

Neural network modeling to evaluate the dynamic flow stress of high strength armor steels under high strain rate compression

An artificial neural network (ANN) constitutive model is developed for high strength armor steel tempered at 500 °C, 600 °C and 650 °C based on high strain rate data generated from split Hopkinson pressure bar (SHPB) experiments. A new neural network configuration consisting of both training and validation is effectively employed to predict flow stress. Tempering temperature, strain rate and strain are considered as inputs, whereas flow stress is taken as output of the neural network. A comparative study on Johnson–Cook (J–C) model and neural network model is performed. It was observed that the developed neural network model could predict flow stress under various strain rates and tempering temperatures. The experimental stress–strain data obtained from high strain rate compression tests using SHPB, over a range of tempering temperatures (500–650 °C), strains (0.05–0.2) and strain rates (1000–5500/s) are employed to formulate J–C model to predict the high strain rate deformation behavior of high strength armor steels. The J-C model and the back-propagation ANN model were developed to predict the high strain rate deformation behavior of high strength armor steel and their predictability is evaluated in terms of correlation coefficient (R) and average absolute relative error (AARE). R and AARE for the J–C model are found to be 0.7461 and 27.624%, respectively, while R and AARE for the ANN model are 0.9995 and 2.58%, respectively. It was observed that the predictions by ANN model are in consistence with the experimental data for all tempering temperatures.     

基于最大保障时间的战时装备维修任务调度模型

战时维修机构承担的维修任务比较繁重,合理、科学地安排维修任务可以有效地提高作战部队的战斗力.对此,分析了战时维修任务调度的特点,建立了基于最大保障时间的维修任务静态、动态调度模型,并提出了相应的模型求解方法.利用本方法在满足作战单元最大保障时间前提下,可使得装备维修效益最大,并可以实现实时动态维修任务调度,有效地解决了一种战时维修任务调度问题.     

低空水平轰炸中安全退曳距离及安全高度的估算

根据终点弹道学理论、毁伤理论和爆炸理论,在分析炸弹的爆炸规律、破片的飞行规律及破片对战斗机毁伤作用的基础上,提出了低空水平轰炸过程中安全退曳距离及安全高度的估算方法.给出了仿真实例,并对相应的仿真结果进行分析,其结果可为飞机武器系统安全投弹提供参考依据.最后,为确保战斗机的低空投弹安全提出了一些建议.     

基于传感器网络数据融合的目标定位方法

针对传感器网络测试系统在战场及终点效应中的应用,探讨了基于多种传感器网络的目标定位方法,提出了采用最优加权融合估计算法将各种传感器的定位信息进行融合处理,并将融合结果与各种传感器计算结果进行比较,结果证明了经融合处理可以大大提高定位精度.     

科学管理、精益管理与精确作战工程保障研究

设计是作战行动筹划的重要步骤,精确工程保障需要对工程保障行动进行精密的设计和精确管理与控制。科学管理采用科学实验的方法,通过劳动方法标准化和差别计件工资制度,有效提高了工作效率,其基本原理经过百余年的实际检验,被证明是一个成熟有效的管理方法。借鉴科学管理理论,需要对工程保障行动进行动作研究,进而研究工程保障行动的作业标准,以期提高其保障效率。精益管理是在科学管理在新的历史时期的发展与改进,它使用了准时制、零库存、均衡生产、持续改进等先进的管理理念和六西格玛管理、成组技术等先进技术,为基于信息系统体系作战的工程保障能力生成提供了有益的借鉴,可加深我们对精确工程保障的理解,促进精确工程保障研究的可操作性。     

分布式储能技术的探索与实践

文章阐述了分布式储能技术的重要意义,介绍了分布式储能技术在经济社会可持续发展重要领域——能源互联网发展中的重要地位,并对分布式储能的技术形态与载体进行了分析,最后以信息网络重要组成部分——数据中心为应用场景,对分布式储能技术的实践进行了探讨。     

基于概率图模型的海上多目标跟踪

针对海上复杂环境中多运动目标跟踪问题,提出了一种融合概率图模型和粒子滤波的跟踪方法.该方法采用二元马尔可夫随机场构建多目标模型,利用势函数表示其联合概率分布,最后用变差分法和粒子滤波推理后验概率密度.通过二阶回归模型准确构建状态转移方程,以及Mean-Shift迭代加速粒子采样,提高了算法精确度和运行效率.实验表明:该方法能很好地实现海上复杂环境中的多目标实时跟踪.     

新形势下警卫部队训练工作探讨

部队战斗力的生成和提高主要依靠平时的军事训练来实现。根据公安警卫部队当前任务实际,着眼新形势下的警卫任务执勤需要,就警卫部队训练对象的层级划分和具体训练目标、训练科目和内容、训练管理体制的建立与完善等问题进行探讨。     

基于网关的LVC互操作研究

仿真体系结构解决了各自领域内仿真资源的互操作问题,而体系结构间的互操作是解决多种仿真资源互操作的有效方法.由于通信协议、中间件和对象模型的不同,体系结构间不能直接进行信息交互.对象模型间的相同点是异构仿真系统间互操作的基础.建立异构系统对象模型与通用数据交换模型的映射关系,通过模型转换实现各异构系统间的数据交互,最后通过"点对点"和通用网关间的时延比较,总结了通用网关的性能特点.