Reaction degree of composition B explosive with multi-layered compound structure protection subjected to detonation loading

The explosive reaction degree and protection from explosions are concerns in the military field.In this work,the reaction degree of the composition B explosive was investigated experimentally.Multi-layered compound structures were used as barriers to weaken the blast loads.A comprehensive experiment using a high-speed camera and image processing techniques,side witness plates,and bottom witness plates was presented.Using the experimental fragment velocities,fragment piercing patterns,and damage characteristics,the reaction degree of the explosive impeded by different multi-layered com-pound structures could be precisely differentiated.Reaction parameters of the explosive obstructed by compound structures were obtained by theoretical analysis and numerical simulations.Unlike the common method in which the explosive reaction degree is only distinguished based on the initial pressure amplitude transmitted into the explosive,a following shock wave reflected from the side steel casing was also considered.Different detonation growth paths in the explosive formed.Therefore,all these shock wave propagation characteristics must be considered to analyze the explosive response impeded by compound structures.     

Multi-scale traffic vehicle detection based on faster R-CNN with NAS optimization and feature enrichment

It well known that vehicle detection is an important component of the field of object detection. However, the environment of vehicle detection is particularly sophisticated in practical processes. It is compara-tively difficult to detect vehicles of various scales in traffic scene images, because the vehicles partially obscured by green belts, roadblocks or other vehicles, as well as influence of some low illumination weather. In this paper, we present a model based on Faster R-CNN with NAS optimization and feature enrichment to realize the effective detection of multi-scale vehicle targets in traffic scenes. First, we proposed a Retinex-based image adaptive correction algorithm (RIAC) to enhance the traffic images in the dataset to reduce the influence of shadow and illumination, and improve the image quality. Second, in order to improve the feature expression of the backbone network, we conducted Neural Architecture Search (NAS) on the backbone network used for feature extraction of Faster R-CNN to generate the optimal cross-layer connection to extract multi-layer features more effectively. Third, we used the object Feature Enrichment that combines the multi-layer feature information and the context information of the last layer after cross-layer connection to enrich the information of vehicle targets, and improve the robustness of the model for challenging targets such as small scale and severe occlusion. In the imple-mentation of the model, K-means clustering algorithm was used to select the suitable anchor size for our dataset to improve the convergence speed of the model. Our model has been trained and tested on the UN-DETRAC dataset, and the obtained results indicate that our method has art-of-state detection performance.     

A novel DOA estimation algorithm using directional antennas in cylindrical conformal arrays

In this paper, a novel direction of arrival (DOA) estimation algorithm using directional antennas in cy-lindrical conformal arrays (CCAs) is proposed. To eliminate the shadow effect, we divide the CCAs into several subarrays to obtain the complete output vector. Considering the anisotropic radiation pattern of a CCA, which cannot be separated from the manifold matrix, an improved interpolation method is investigated to transform the directional subarray into omnidirectional virtual nested arrays without non-orthogonal perturbation on the noise vector. Then, the cross-correlation matrix (CCM) of the sub-arrays is used to generate the consecutive co-arrays without redundant elements and eliminate the noise vector. Finally, the full-rank equivalent covariance matrix is constructed using the output of co-arrays, and the unitary estimation of the signal parameters via rotational invariance techniques (ESPRIT) is performed on the equivalent covariance matrix to estimate the DOAs with low computational complexity. Numerical simulations verify the superior performance of the proposed algorithm, especially under a low signal-to-noise ratio (SNR) environment.     

中法战争中的晚清外交

本文阐述了晚清法越问题的历史渊源,对中法战争中清政府的内外处境和应对措施,以及与之有关的外交政策进行了客观中肯的评述。     

论赤壁之战敌对双方战争指导的优劣得失

发生在建安十三年(公元208年)的赤壁之战以其深远独特的影响、丰富多样的作战形式在三国乃至整个中国军事史上占据着不可替代的地位。它是一场典型的以弱胜强、以少胜多的战争,是一场囊括了野战、攻城、追击、遭遇、火攻、退却、水战等多种作战形式的战争,是中国历史上第一次在长江流域进行的大规模江河作战,同时又是中国历史上第一次企图通过江河作战而谋求实现统一而最终失败的战争。无论从大战略的高度来看,还是从军事战略的角度来分析,赤壁之战都是一场具有多种典型价值的战争。今天,我们分析战争敌对双方曹军与孙刘联军战争指导的优劣得失,仍能获得历史的经验与有益的启示。     

紧跟中国特色军事变革走向加速培养复合型军事指挥人才

中国特色军事变革的走向,决定着我军人才队伍建设的方向.复合型军事指挥人才培养,是我军面对的一个崭新课题.要科学解析复合型军事指挥人才内涵特征和主导地位;加速构建复合型军事指挥人才培养的主体格局;积极推动复合型军事指挥人才培养良性发展.     

激光平行光幕的爆炸成型弹丸形貌测试技术

针对目前爆炸成型弹丸形貌测试普遍使用的脉冲X光摄影法成本昂贵、结构复杂、测试困难的缺点,提出了激光平行光幕形貌测试系统。该系统中,由启动网靶、停止网靶和计时仪组成的区截测速装置测试EFP的速度,激光平行光幕和示波器测试EFP弹丸通过光幕时直径随时间的变化过程。然后将上述测试结果用Matlab软件进行仿真,得出EFP弹丸的形貌。测试与仿真表明:激光平行光幕形貌测试系统可以测试EFP弹丸的速度与形貌,而且成本低廉、可靠性高,可以在大威力战斗部试验中使用。     

基于ISIGHT的微型飞行器布局优化设计研究

微型飞行器具有飞行雷诺数低、易受外界环境干扰等特点,并存在多目标优化问题,因此其气动布局优化设计难度较大。针对微型飞行器的特点及优化设计要求,采用N-S方程与遗传算法相结合的方法对微型飞行器的多目标优化设计,基于ISIGHT软件来实现该方法的具体流程,克服了计算量大、无法实现自主迭代的缺点。并对微型飞行器的展弦比、尾翼安装角、尾翼的高度和根弦长进行优化,优化目标为飞行器的静稳定性和升阻特性,优化后的构型具有良好的气动性能,结果表明该方法明显提高了计算的精度和优化设计的水平,在工程上有一定的应用价值。     

美军武装直升机电子战设备的现状与发展趋势

介绍了武装直升机在现代战场上面临的种种威胁,重点介绍了美军武装直升机目前装备的电子战设备和尚处于研制中的新一代综合性电子战设备,分析了美军武装直升机电子战设备的发展趋势。     

YFRIO 实时I/O语言与YFSIM 仿真语言的同步关系

本文介绍ＹＦＲＩＯ语言和ＹＦＳＩＭ语言的同步关系,阐述了两者同步的硬件、软件机制,以及如何进行程序设计。