基于Gabor谱方法的跳频信号参数盲估计

提出了一种基于Gabor谱的未知跳频信号参数盲估计方法。该方法利用Gabor谱能量集中、时频分辨率高、交叉项干扰小的特点,在未知任何先验参数的情况下,能够准确估计出跳频信号的跳频频率、跳变时刻和跳频信号驻留时间等参数。通过计算机仿真得到了较为准确的估计结果,验证了该算法的有效性。     

Synergistic effect of hybrid Himalayan Nettle/Bauhinia-vahlii fibers on physico-mechanical and sliding wear properties of epoxy composites

The cellulosic bast fibers are recognized as a justifiable and biodegradable substitute for producing moderate strength polymer composite materials because of their characteristics of renewability, eco-friendliness, and higher specific strength. Hence the aim of this research work is to fabricate Himalayan bast fibers (Nettle fiber (NF)/bauhinia vahlii fiber (BF)) based mono/hybrid epoxy composites at varying weight percentage of 2–6 wt% and evaluate the physical (void fraction and water absorption), mechanical (tensile strength, flexural strength, hardness) and sliding wear properties of as-fabricated composites. The 6 wt% NBF reinforced composites exhibited higher mechanical properties as compared to NF and BF composites with tensile strength of 34.04 MPa, flexural strength of 42.45 MPa, and hardness of 37.01 H_v respectively. The influence of various control factors (sliding velocity, NF/BF/NBF contents, normal load and sliding distance) on specific sliding wear rate of composites was evaluated by Taguchi (three factors at three levels) experimental design and the percentage contribution of these selected parameters on sliding wear performance was examined by Analysis of variance (ANOVA). The sliding wear property of as-developed composites was found to be greatly influenced by sliding velocity and the wear resistance was observed to be improved with the NF/BF/NBF contents. The wear mechanism of the as-fabricated composites has been elucidated by scanning electron microscopy analysis. The research outcomes demonstrated that the hybridization of Bauhinia vahlii fiber with Nettle fiber led to improve the mechanical and wear properties of epoxy composites.     

Study on dynamic response of multi-degree-of-freedom explosion vessel system under impact load

In order to study the dynamic response and calculate the axial dynamic coefficient of the monolayer cylindrical explosion vessel, the wall of vessel is simplified as a multi-degree-of-freedom (MDoF) undamped elastic foundation beam. Decoupling the coupled motion equation and using Duhamel's integrals, the solutions in generalized coordinates of the equations under exponentially decaying loads, square wave loads and triangular wave loads are calculated. These solutions are consistent in form with the solutions of single-degree-of-freedom (SDoF) undamped forced vibration simplified model. Based on the model, equivalent MDoF design method (also called MDoF dynamic coefficient method) of cylindrical explosion vessel is proposed. The traditional method can only predict the dynamic coefficient of torus portion around the explosion center, but this method can predict that of the vessel wall at any axial n dividing point position. It is verified that the prediction accuracy of this model is greatly improved compared with the SDoF model by comparing the results of this model with SDoF model and numerical simulation in different working conditions. However, the prediction accuracy decreases as the scaled distance decreases and approaches the end of the vessel, which is related to the accuracy of the empirical formula of the implosion load, the simplification of the explosion load direction, the boundary conditions, and the loading time difference.     

Knowledge-oriented modeling for influencing factors of battle damage in military industrial logistics: An integrated method

Modeling influencing factors of battle damage is one of essential works in implementing military industrial logistics simulation to explore battle damage laws knowledge. However, one of key challenges in designing the simulation system could be how to reasonably determine simulation model input and build a bridge to link battle damage model and battle damage laws knowledge. In this paper, we propose a novel knowledge-oriented modeling method for influencing factors of battle damage in military industrial logistics, integrating conceptual analysis, conceptual modeling, quantitative modeling and simulation implementation. We conceptualize influencing factors of battle damage by using the principle of hierarchical decomposition, thus classifying the related battle damage knowledge logically. Then, we construct the conceptual model of influencing factors of battle damage by using Entity-Relationship approach, thus describing their interactions reasonably. Subsequently, we extract the important influencing factors by using social network analysis, thus evaluating their importance quantitatively and further clarifying the elements of simulation. Finally, we develop an agent-based military industry logistics simulation system by taking the modeling results on influencing factors of battle damage as simulation model input, and obtain simulation model output, i.e., new battle damage laws knowledge, thus verifying feasibility and effectiveness of the proposed method. The results show that this method can be used to support human decision-making and action.     

Optimal design of a novel cylindrical sandwich panel with double arrow auxetic core under air blast loading

The increasing threat of explosions on the battle field and the terrorist action requires the development of more effective blast resistance materials and structures. Curved structure can support the external loads effectively by virtue of their spatial curvature. In review of the excellent energy absorption property of auxetic structure, employing auxetic structure as core material in curved sandwich shows the potential to improve the protection performance. In this study, a novel cylindrical sandwich panel with double arrow auxetic (DAA) core was designed and the numerical model was built by ABAQUS. Due to the complexity of the structure, systematic parameter study and optimal design are conducted. Two cases of optimal design were considered, case1 focuses on reducing the deflection and mass of the structure, while case2 focuses on reducing the deflection and increasing the energy absorption per unit mass. Parameter study and optimal design were conducted based on Latin Hypercube Sampling (LHD) method, artificial neural networks (ANN) metamodel and the nondominated sorting genetic algorithm (NSGA-Ⅱ). The Pareto front was obtained and the cylindrical DAA structure performed much better than its equal solid panel in both blast resistance and energy absorption capacity. Optimization results can be used as a reference for different applications.     

Fulfillment by Amazon versus fulfillment by seller: An interpretable risk-adjusted fulfillment model

With dual-channel choices, E-retailers fulfill their demands by either the inventory stored in third-party distribution centers, or by in-house inventory. In this article, using data from a wedding gown E-retailer in China, we analyze the differences between two fulfillment choices—fulfillment by Amazon (FBA) and fulfillment by seller (FBS). In particular, we want to understand the impact of FBA that will bring to sales and profit, compared to FBS, and how the impact is related to product features such as sizes and colors. We develop a risk-adjusted fulfillment model to address this problem, where the E-retailer's risk attitude to FBA is incorporated. We denote the profit gaps between FBA and FBS as the rewards for this E-retailer fulfilling products using FBA, our goal is to maximize the E-retailer's total rewards using predictive analytics. We adopt the generalized linear model to predict the expected rewards, while controlling for the variability of the reward distribution. We apply our model on a set of real data, and develop an explicit decision rule that can be easily implemented in practice. The numerical experiments show that our interpretable decision rule can improve the E-retailer's total rewards by more than 35%.     

基于效用分析的武器装备发展方案决策

武器装备发展方案效用决策分析的目的就是以一定的方法和途径,根据决策者对武器装备发展所涉及的各项决策准则的偏好及其对各决策备选方案可能出现风险程度的态度,诱导出决策者对于各项准则的效用函数,从而以诱导的形式综合出各决策备选方案的综合效用,以获得决策者认为是最满意的决策方案.     

基于自校正卡尔曼滤波器的信息融合算法

设计了一种新的基于ARMA模型自校正卡尔曼滤波器及其信息融合的方法,从而避免了经典卡尔曼滤波器需要精确知道系统的模型参数和噪声统计特性的缺点.仿真结果表明,在未知部分模型参数和噪声统计特性的情况下,自校正卡尔曼滤波器的滤波性能非常接近稳态最优卡尔曼滤波器;基于自校正卡尔曼滤波器的信息融合滤波性能接近基于稳态最优卡尔曼滤波器的信息融合滤波性能.     

基于人工势场的军事态势分析模型

在基于Agent建模仿真方法的战争复杂性研究过程中,为了解决高层指挥控制Agent对军事态势自主分析判断能力的问题,引入了高等物理学中电势场的基本原理来对战场军事态势分析进行建模--并取名为人工势场.介绍了人工势场模型构建的基本原理,结合工程实践详细讨论了该模型在理论和工程实现上的一些基本问题,最后给出了基于该模型的几个简单的分析测试实例.仿真实验证明该模型用于高层指挥控制Agent的实时军事态势分析是可行的.     

灰色关联投影法的威胁排序算法

威胁评估与排序是作战系统和C4I系统必须具备的重要功能.结合多指标决策理论和灰色系统理论,提出了基于多指标决策灰色关联投影法的威胁排序算法.首先通过建立灰色关联判断矩阵将威胁排序转化为多指标决策问题;其次为缩小极端值的影响提出了基于信息熵的威胁指标权重算法;最后从矢量投影角度应用灰色关联投影值进行威胁排序;并分别研究了分辨系数和指标权重对威胁排序的影响.通过现代防空作战实例验证了算法的有效性和工程实用性.