探空火箭级间段的CAD系统

本文在CADKEY绘图软件包的支持下,开发了加筋圆柱结构CAD系统—Hcadx.此系统通过菜单引导用户的操作,可用经验公式或解析法作轴压稳定分析,用罚函数法优化参数,可以在不退出Hcadx的情况下启动CADKEY,自动绘制设计草图。此草图经过适当地编辑、修改、便可成为工程中能接受的工作图纸。     

基于SysML的车辆信息系统设计

针对目前车辆信息系统缺乏有效设计方法的现状,结合新时期车辆信息系统的特点,提出了一种基于SysML的车辆信息系统设计方法。该方法明确了车辆信息系统设计过程的阶段和产物,并通过标准建模语言SysML的运用,用模型来支持系统的设计和有效性验证。该方法在智能巡航系统的设计中得到了运用。实践结果表明,该方法不仅能够自顶向下完整地设计系统、利用可视化的语言准确清晰地描述系统,而且能够在系统设计层面对系统功能逻辑和数据流进行动态仿真和迭代验证。该方法能够较好地指导新时期车辆信息系统的设计过程,满足信息系统的设计要求。     

MF-CFI: A fused evaluation index for camouflage patterns based on human visual perception

The evaluation index of camouflage patterns is important in the field of military application. It is the goal that researchers have always pursued to make the computable evaluation indicators more in line with the human visual mechanism. In order to make the evaluation method more computationally intelligent, a Multi-Feature Camouflage Fused Index (MF-CFI) is proposed based on the comparison of grayscale, color and texture features between the target and the background. In order to verify the effectiveness of the proposed index, eye movement experiments are conducted to compare the proposed index with existing indexes including Universal Image Quality Index (UIQI), Camouflage Similarity Index (CSI) and Structural Similarity (SSIM). Twenty-four different simulated targets are designed in a grassland background, 28 observers participate in the experiment and record the eye movement data during the observation process. The results show that the highest Pearson correlation coefficient is observed between MF-CFI and the eye movement data, both in the designed digital camouflage patterns and large-spot camouflage patterns. Since MF-CFI is more in line with the detection law of camouflage targets in human visual perception, the proposed index can be used for the comparison and parameter optimization of camouflage design algorithms.     

多武器平台目标域协同射击控制模型研究

目标域协同射击控制模型是在单平台火控系统空域窗射击控制、射击门控制等基础上,针对多武器平台对点目标或面目标协同射击的需求,进行了目标域和射击效能的定义,提出了空间/时间复合三维射击门的概念,设计了三维射击门模型,分别建立了多武器平台对点目标射击控制模型和多武器平台对面目标射击控制模型,通过对多武器平台协同射击效能的计算分析,证明了目标域协同射击控制模型可显著提高多武器平台协同射击对目标的火力打击效能.     

Real-time prediction of projectile penetration to laminates by training machine learning models withfinite element solver as the trainer

Studies on ballistic penetration to laminates is complicated, but important for design effective protection of structures. Experimental means of study is expensive and can often be dangerous. Numerical simu-lation has been an excellent supplement, but the computation is time-consuming. Main aim of this thesis was to develop and test an effective tool for real-time prediction of projectile penetrations to laminates by training a neural network and a decision tree regression model. A large number of finite element models were developed;the residual velocities of projectiles fromfinite element simulations were used as the target data and processed to produce sufficient number of training samples. Study focused on steel 4340tpolyurea laminates with various configurations. Four different 3D shapes of the projectiles were modeled and used in the training. The trained neural network and decision tree model was tested using independently generated test samples using finite element models. The predicted projectile velocity values using the trained machine learning models are then compared with thefinite element simulation to verify the effectiveness of the models. Additionally, both models were trained using a published experimental data of projectile impacts to predict residual velocity of projectiles for the unseen samples. Performance of both the models was evaluated and compared. Models trained with Finite element simulation data samples were found capable to give more accurate predication, compared to the models trained with experimental data, becausefinite element modeling can generate much larger training set, and thus finite element solvers can serve as an excellent teacher. This study also showed that neural network model performs better with small experimental dataset compared to decision tree regression model.     

Nitro-tetrazole based high performing explosives: Recent overview of synthesis and energetic properties

Heterocyclic skeleton (Azoles) and different energetic groups containing high performing explosives are highly emerged in recent years to meet the challenging requirements of energetic materials in both military and civilian applications with improved performance. For this purpose tetrazole (Azole) is identified as an attractive heterocyclic backbone with energetic functional groups nitro (-NO₂), nitrato (-ONO₂), nitrimino (-NNO₂), and nitramino (–NH–NO₂) to replace the traditionally used high performing explosives. The tetrazole based compounds having these energetic functional groups demonstrated advanced energetic performance (detonation velocity and pressure), densities, and heat of formation (HOF) and became a potential replacement of traditional energetic compounds such as RDX. This review presents a summary of the recently reported nitro-tetrazole energetic compounds containing poly-nitro, di/mono-nitro, nitrato/nitramino/nitrimino, bridged/bis/di tetrazole and nitro functional groups, describing their preparation methods, advance energetic properties, and further applications as high-performing explosives, especially those reported in the last decade. This review aims to provide a fresh concept for designing nitro-tetrazole based high performing explosives together with major challenges and perspectives.     

Study on energy release characteristics of reactive material casings under explosive loading

Reactive Materials (RMs), a new material with structural and energy release characteristics under shock-induced chemical reactions, are promising in extensive applications in national defense and military fields. They can increase the lethality of warheads due to their dual functionality. This paper focuses on the energy release characteristics of RM casings prepared by alloy melting and casting process under explosive loading. Explosion experiments of RM and conventional 2A12 aluminum alloy casings were conducted in free field to capture the explosive fireballs, temperature distribution, peak overpressure of the air shock wave and the fracture morphology of fragments of reactive material (RM) warhead casings by using high-speed camera, infrared thermal imager temperature and peak overpressure testing and scanning electron microscope. Results showed that an increase of both the fireball temperature and air shock wave were observed in all RM casings compared to conventional 2A12 aluminum ally casings. The RM casings can improve the peak overpressure of the air shock wave under explosion loading, though the results are different with different charge ratios. According to the energy release characteristics of the RM, increasing the thickness of RM casings will increase the peak overpressure of the near-field air shock wave, while reducing the thickness will increase the peak overpressure of the far-field air shock wave.     

改进的接触算法及其在光滑粒子流体动力学中的应用

采用以黎曼解描述粒子间相互作用的接触算法,模拟一维情况下包含间断的流场。在弱间断的条件下,采用弱波近似的黎曼解来描述粒子间的相互作用;在强间断的条件下,则引入非迭代黎曼解来描述粒子间的相互作用。并引入Taylor展开思想,提高了接触算法在自由边界的计算精度。该算法无需引入人为粘性,程序结构简洁。数值计算表明,改进后的接触算法能很好地描述强间断,并有效改善了原始接触算法在自由面的计算缺陷。     

基于生物视觉原理的图像结构信息变化检测方法

为克服多时相遥感图像变化检测中照度差异和配准误差的影响,采用边缘结构信息进行变化检测。利用多方向Gabor函数从图像梯度强度图中提取边缘结构信息,称之为边缘标记(Edge Tag,ET),通过比较多时相遥感图像中ET的互相关系数实现变化检测。为减小差异较小的边缘对检测结果的影响,在相关系数的计算中引入抑制因子。仿真图像和真实图像的实验结果表明,该方法能克服图像照度差异和配准误差对变化检测的影响,取得了较好的检测效果。     

利用混合编程改善SMP机群上并行矩阵乘法的性能

针对SMP机群,探讨了分别利用单机优化、OpenMP与MPI从指令级、共享存储级与分布主存级三个层次上改善矩阵并行乘Fox算法性能的方法。并通过调用数学函数库与混合编程的方式,在深腾6800上进行了实验,取得了相当满意的数值效果。