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.     

云模型在雷达干扰资源多目标优化配置中的应用

鉴于干扰效果/效益评估在雷达干扰资源优化分配中的重要地位,提出了一种基于云模型和匈牙利算法的雷达干扰资源优化分配模型。利用一维云模型单条件单规则发生器和逆向云发生器构建了评估指标干扰效果推理器,利用基于风险态度因子的云模型映射函数定义了云模型之间距离的度量方法。提出了一种基于云模型与逼近理想解法的雷达干扰效益矩阵求解方法,最后运用匈牙利算法实现了干扰资源优化分配。将所建模型应用到干扰资源分配中,结果表明该模型能够较好的处理评估中的不确定性知识,是合理、可行的。     

基于MDFT框架的海上能源通道航线动态决策建模与仿真

针对常规海上航线决策没有考虑决策选择过程的问题,引入多选择决策场理论（ MDFT）,构建了海上能源通道航线动态决策模型。基于信息完备、信息不确定和特殊情况等三种情景想定,进行了海上能源通道航线规划决策及其实验仿真。结果表明,决策过程受时间压力和信息质量的制约,时间压力会制约决策质量,同时还可能引起“偏好逆转”现象,信息不确定也会导致确定性决策。该模型不仅综合考虑了海上能源通道航线选择时需关注的各类要素,且模型参数可动态调整,进而能合理模拟真实的海上状况和决策过程。     

信息化条件下空战威胁评估指标体系

目标威胁评估是空战决策研究的重要组成部分,评价指标是进行威胁评估的前提和基础。根据现代空战的特点,借鉴网络中心战思想,从空间态势、物理域、信息域、认知域4个角度,构建了信息化条件下空战目标威胁评估指标体系,并对指标体系进行了完备性、合理性、有效性检验。通过实例分析表明威胁评估指标能较好地反映信息化条件下空中目标的实际威胁,为空战决策研究提供参考。     

基于向量相似度的组合赋权方法

针对多属性决策中属性权重的确定问题,提出了一种基于向量相似度的主、客观权重的集成方法。用权向量的相似度作为不同赋权方法重要性的度量,意义明确,计算简单,可操作性强。最后结合算例验证了此方法的有效性和实用性。     

行政复议机关在行政诉讼中的被告地位研究

行政复议制度具有其独立的功能价值,而我国现行法律关于经复议后如何确定行政诉讼被告的规定,却存在着许多弊端,使得这种功能价值很难体现。实践中,行政权的依法行使需要司法权强有力的监督,因此,有必要将行政复议的结果尤其是行政复议维持决定纳入司法审查范围。从行政诉讼法关于被告问题的规定和行政复议法中复议机关的职责责任方面对现行法律规定的完善进行了探讨。     

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.     

考虑地磁场空间梯度的飞行器磁干扰建模与求解方法

首先,在研究飞行器背景磁干扰模型与小信号模型的基础上,分析了地磁梯度沿纬度与高度的变化规律,分析可知由于飞行器的机动,地磁梯度会对测量结果造成影响;然后,考虑地磁梯度因素,对原有小信号模型求解方法进行了改进：飞行器在四个航向上做小角度的机动飞行,将地磁场沿纬度与高度的梯度作为未知量,与飞行器磁干扰模型中的剩磁参数、感磁参数和涡磁参数一起求解;最后,利用实测试验数据进行了验证,结果表明：考虑地磁梯度的影响与不考虑地磁梯度的影响相比,求解的模型参数可以在细节上进一步提高飞行器背景磁干扰的补偿效果。     

微槽结构单点金刚石飞切加工的切削力建模

超精密单点金刚石飞刀切削技术是一种比较新颖的微槽类结构加工方式。在飞切过程中,切削力是切削过程中重要的物理量,对加工后的表面质量、刀具磨损等有着直接影响。提出了一种基于直角微切削理论的动态微槽类结构飞切的力学模型,基于微切削理论,得到了前、后刀面切削力的理论模型。根据飞切的几何运动特征,建立了飞切过程中剪切角的计算模型,并根据单圈飞切实验得到了飞切过程中剪切面的变化规律。为了验证模型的正确性,采用不同切削参数进行了多圈重叠飞切实验,对切削力进行了测量和分析。实验得到的切削力大小和变化规律与理论模型计算得到的基本一致,证明了该切削力模型的有效性。