Effect of projectile parameters on opening behavior of PELE penetrating RC target

When a penetrator with enhanced lateral effect (PELE) impacts on a reinforced concrete (RC) target, the target is damaged with a large opening. An understanding of how PELE projectile parameters affect the opening dimension, is essential for effective design of the PELE projectile. In this study, under the condition that the impact velocity and target parameters (strength and thickness) were fixed values, the important influence factors of the PELE (jacket wall thickness B, jacket material strength Y1, filling material strength Y2 and angle of monolithic jacketθ) were determined by a dimensional analysis. Tests and simulations of the PELE penetrating the RC target were conducted to analyze the influence of these factors on opening diameter ((D), an equivalent diameter under relative kinetic energy). Based on the test and simulation results, it is found that the influence of these factors B, Y1 andθon the deformation mode of the jacket shows a similar trend:as values of the three factors decrease, the jacket deforms from small bending deformation to large one, and then to curling deformation. This causes the opening diameter to first increase with the decrease of these three factors, and then decreases. It is well known that the bending resistance of the jacket is related to these factors B, Y1 andθ. Therefore, a plastic limit bending moment (M0) of the jacket was quoted to characterize the influence of these factors on the bending deformation of the jacket and the opening diameter of the target. The influence factor Y2 causes (D) to first increase with the increase of Y2, and then decreases. A formula was developed to predict the opening diameter, whose influence parameters were considered in a dimensionless way. It has been shown that the dimensionless opening diameter (D)/d1 is dependent on two dimensionless parameters Q = (d31fc/M0) and G = (fc/Y2), where d1 and fc are the outer diameter of the projectile and the compressive strength of the target, respectively.     

Thermal and combustion behavior of Al-MnO2 nanothermite with poly(vinylidene fluoride -co- hexafluoropropylene) energetic binder

Fluoropolymers get increasing attention in energetic materials application due to the high fluorine content. To explore the effect of poly(vinylidene fluoride-co-hexafluoropropylene) (P(VDF-HFP)) on Al/MnO2 nanothermite, the samples with different contents are prepared and characterized by SEM, TG-DSC, XRD, and their ignition and combustion behavior are tested and recorded. The results show that P(VDF-HFP) as an energetic binder can combine the nanothermite components together, even exist in the gaps. The integrity of energetic materials has been improved. Thermal analysis shows that the addition of P(VDF-HFP) greatly changes the thermal reaction processes, and the exothermic peaks appear early, but the utilization of fuel and oxidizer is not efficient from the XRD results. Furthermore, the appropriate addition of P(VDF-HFP) can directly reduce the ignition energy threshold and increase the combustion time, which is necessary for the potential ignition charge application. The possible reasons for above phenomena are discussed and analyzed. This research provides a reference for improvement of thermite-based ignition charge formulation.     

面向车辆通过性的地理因子分析与应用

全地形环境感知系统是研究车辆自主能力的重要部分,也是车辆安全行驶的绝对基础,而车辆的可通行区域分析则是环境感知系统中不可缺少的一步。本文分析了全地形环境下可能对装备车辆的地面通行性产生影响的众多地理环境因素,并结合多类型的地理环境因素,对包含地面坡度、植被、水系和建筑物等因素在内的,能够反映地面可通行性的车辆可通行区域以及装备车辆的可行驶区域进行规划。依托 ArcGIS平台和C++编程语言,对ArcGIS进行了二次开发,建立了一套针对全地形复杂环境下的路面可通行区域分析模型。该模型可以根据装备车辆的不同参数实现地理因子影响系数的设定,满足不同条件下车辆的可通行区域规划。     

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%.     

Performance analysis of the cultural and creative industry: a network‐based approach

The cultural and creative industries (CCIs) in Taiwan have gradually contributed to the national economy under the impetus of government policies. We employ a two‐stage data envelopment analysis model with an additive efficiency decomposition approach to measure the profitability and marketability of 22 Taiwanese cultural and creative companies. Furthermore, we employ the network‐based ranking approach to identify benchmark inputs/outputs, and the strengths and weakness of each company. Our empirical results show that the profitability of the cultural and creative companies is better than their marketability. Companies in the industries of publishing, creative life, popular music, and cultural content averagely perform better than those in the other three types of CCIs in terms of profitability. Companies in the creative life industry are on average more efficient than those in the other five types of CCIs in terms of marketability. The profitability/marketability matrix of cultural and creative companies is also presented.     

某轮式装甲车辆悬架系统改进及其仿真

某轮式装甲车辆悬架系统缓和、衰减冲击效果不佳,影响车辆战术性能发挥。提出了简单有效的改进方案,并应用AMESim软件对悬架原系统与改进系统进行了建模仿真。通过仿真结果分析,验证了改进方案的可行性。为装备的技术改造提供了一个简单有效的可选方案。     

提取时间对硝基油漆稀料燃烧产物鉴定的影响

油漆稀料是一种常见的助燃剂,提取时间对其燃烧产物的鉴定会有一定的影响。选取了纯毛织品作为实验载体,以硝基油漆稀料为研究对象,对燃烧残留物及燃烧烟尘进行了系统的GC-MS分析,找出了纯样和加载油漆稀料后燃烧产物主要成分的变化规律,对样品中目标化合物的相对峰面积随燃烧产物提取时间的变化曲线进行了非线性数学分析,初步找出了样品燃烧产物的相对峰面积随硝基油漆稀料燃烧产物提取时间变化的规律,为合理选择物证的提取时间提出了建议。