Damage assessment of the target area of the island/reef under the attack of missile warhead

Under the background of vigorously developing facilities of island/reef in the world, the economic value and strategic significance of the island/reef have become increasingly important. Unfortunately, they may easily become the attacking target of missiles in the war time. Therefore, aiming at the damage quantification of the targets in the island/reef under the missile attacking, a macroscopic damage assessment model for the target area is proposed in this paper. The model focuses on the construction of the assessment model framework. Firstly, the analytic hierarchy process and the grey relational analysis are applied to measure the importance of each target in the region through four indicators of the target hazard, striking urgency, damage advantage and mission relevance, respectively. Secondly, based on the damage mechanism of shock wave and fragments to target, the corresponding damage model is established, and the damage grade of each target in the evaluated area is obtained according to the damage criteria and grading standard. Finally, the model obtains the overall damage grade of the target area by employing the fuzzy comprehensive evaluation method, with synthesizing the importance and the damage grade of each target. Through the verification of an example, it demonstrates the certain feasibility of the model and provides a certain basis and reference for the subsequent research.     

Maximizing deviation method for multiple attribute decision making under q-rung orthopair fuzzy environment

Because of the uncertainty and subjectivity of decision makers in the complex decision-making environment, the evaluation information of alternatives given by decision makers is often fuzzy and uncertain. As a generalization of intuitionistic fuzzy set (IFSs) and Pythagoras fuzzy set (PFSs), q-rung orthopair fuzzy set (q-ROFS) is more suitable for expressing fuzzy and uncertain information. But, in actual multiple attribute decision making (MADM) problems, the weights of DMs and attributes are always completely unknown or partly known, to date, the maximizing deviation method is a good tool to deal with such issues. Thus, combine the q-ROFS and conventional maximizing deviation method, we will study the maximizing deviation method under q-ROFSs and q-RIVOFSs in this paper. Firstly, we briefly introduce the basic concept of q-rung orthopair fuzzy sets (q-ROFSs) and q-rung interval-valued orthopair fuzzy sets (q-RIVOFSs). Then, combine the maximizing deviation method with q-rung orthopair fuzzy information, we establish two new decision making models. On this basis, the proposed models are applied to MADM problems with q-rung orthopair fuzzy information. Compared with existing methods, the effectiveness and superiority of the new model are analyzed. This method can effectively solve the MADM problem whose decision information is represented by q-rung orthopair fuzzy numbers (q-ROFNs) and whose attributes are incomplete.     

Energy‐efficient scheduling for sustainable manufacturing systems with renewable energy resources

Environmentally friendly energy resources open a new opportunity to tackle the problem of energy security and climate change arising from wide use of fossil fuels. This paper focuses on optimizing the allocation of the energy generated by the renewable energy system to minimize the total electricity cost for sustainable manufacturing systems under time‐of‐use tariff by clipping the peak demand. A rolling horizon approach is adopted to handle the uncertainty caused by the weather change. A nonlinear mathematical programming model is established for each decision epoch based on the predicted energy generation and the probability distribution of power demand in the manufacturing plant. The objective function of the model is shown to be convex, Lipchitz‐continuous, and subdifferentiable. A generalized benders decomposition method based on the primal‐dual subgradient descent algorithm is proposed to solve the model. A series of numerical experiments is conducted to show the effectiveness of the solution approach and the significant benefits of using the renewable energy resources.     

智能化作战指挥模式需求

智能装备已经走入军队、走向战场,创建智能化作战指挥模式是智能化时代作战指挥的必然发展趋势,智能化作战指挥模式需求分析可为智能作战问题研究提供有效的信息。智能化作战指挥模式的需求分析已经具备了一定的物质、理论和技术基础,同时,也具有了一定的构建思路、实践条件和实验平台。在此基础上,本文从军事需求、功能需求和技术需求以及构建要求四个不同角度进行需求分析,以找准创建需求,为后续工作进一步展开奠定基础。     

基于层次分析法的军校学员体能训练评估

针对目前军校学员军事体育训练评估难以量化考核的问题,提出了基于层次分析法的军校学员体能训练评估方法。首先,通过建立评估指标体系,构建评估指标判断矩阵;其次,进行归一化并计算指标组合权重,构建评估基本模型;最后,利用评估模型对学员体能训练进行综合评估。结果表明本文提出的方法能够对军校学员体能训练进行有效评估,相比于传统考核评估方法更能反映出学员体能的真实状况,突出学员体能特征,开展针对性训练。      

Analysis of some critical aspects in hot machining of Ti-5553 superalloy: Experimental and FE analysis

In this study, a newly developed titanium superalloy, i.e., the Ti-5553 alloy has used for hot machining. This material replaced Ti-grade-5 alloy in the application of aerospace, automobile, and biomedical sector. However, similar to Ti-grade-5 alloy, the Ti-5553 alloy has a low thermal conductivity which makes it difficult-to-cut material categories hence, high tool wear, cutting force and bad surface finish. Hot machining of Ti-5553 has been studied at different machining condition (room and hot) using Deform-2D finite element analysis. The result from the simulation test was compared with the experimental value and reduction of cutting and thrust forces was observed. The experiment was carried out with the same input parameters as simulation, and good coherence between them observed. Additionally, cutting zone temperature, effective stress, etc. for both room and elevated the temperature are also discussed.     

信息中心网络缓存节点位置选择算法

信息中心网络（Information-Centric Networking, ICN）“泛在缓存”的特性,引发数据副本率过高、缓存空间不能充分利用等问题。为了解决上述问题,分别从用户、服务提供商和网络运营商的角度出发,以最小化网络流量与网络费用开销为优化目标建立两个单目标优化模型,并将二者结合为帕累托模型;基于帕累托求解方法中数学规划法的思想,详细描述缓存节点位置选择算法。仿真结果表明：在流量性价比方面,所提缓存节点选择算法优于ICN的默认缓存机制;在网络费用开销方面,所提算法更适用于只有少数内容较为流行的网络中,而在所有内容都流行的情况下,ICN中默认的“遍地缓存”机制更为适宜。     

高超声速飞行器低可探测性滑翔弹道优化方法

为进一步提高高超声速飞行器的突防性能,提出高超声速飞行器低可探测性滑翔弹道优化方法。考虑飞行器180°×360°方向的雷达散射截面,针对原数据尖峰多、收敛难的难题,运用高斯滤波法对其进行预处理,既不改变原数据趋势又加以平滑,提高优化问题收敛性能。为使计算所用雷达散射截面数据具备较强的保真性,采用三次样条插值方法调用离散数据计算实时雷达散射截面。完成了高超声速飞行器低可探测性滑翔弹道优化问题的建模,以探测概率为目标函数,运用hp自适应Radau伪谱法优化求解,采用逐步计算策略进一步提高优化效率和收敛性能。与传统最短飞行时间弹道对比表明,该方法有效降低了飞行器被雷达发现的概率。     

未确知条件下多枚导弹打击不规则面目标的毁伤效果评估

在信息缺乏的情况下,如何提高对多枚导弹打击不规则面目标毁伤效果评估的可信度是导弹作战运用研究的重难点。通过蒙特卡罗方法建立给定参数下的面目标毁伤效果评估模型;采用信度分布函数对该问题的未确知性进行评估,评估结果显示毁伤效果未确知性较高;基于信度熵,分析导弹各个属性的未确知性对毁伤效果未确知性的影响;通过针对性减小影响大的属性的未确知性,迭代减小毁伤效果的未确知性。仿真实验结果表明面目标有效毁伤率的未确知范围得到显著减小。该研究能够有效指导毁伤效果评估工作,减小其中的不确定性。     

稀薄气体动理论中介观尺度数值模拟的加速方法

针对滑移流、早期过渡流区域采用离散速度法(discrete velocity method, DVM)求解Boltzmann方程收敛速度极慢、计算资源消耗大的难题,提出全流场耦合介观/宏观方程加速方法。在介观层面基于有限差分的DVM求解Boltzmann方程,在宏观层面基于有限体积的压力耦合方程组半隐式方法求解矩方程,充分利用纳维-斯托克斯-傅里叶/R26矩方程在低克努森数下的快速收敛特性,对介观方程进行加速。基于高阶Hermite多项式重构分布函数,完成宏观方程与介观方程之间的数据传输。仿真结果表明:全流场耦合介观/宏观方程的加速方法在滑移流、早期过渡流区域具有显著加速性能,最大降低了95.28%的计算时长;但对中、大克努森数流域,加速性能大幅度下降。