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.     

Performance evaluation and optimization design of photoelectric pyrometer detection optical system

The measurement and control of high temperature play very important roles in national defense, military, scientific experiments, industrial and agricultural production. Photoelectric pyrometer is one of the important radiation thermometers for non-contact temperature measurement. It has an important application in the field of high temperature measurement, and its performance directly affects the accuracy of temperature measurement. By improving the design of the detection optical system of the photoelectric pyrometer, the imaging performance of the photoelectric pyrometer can be improved effectively, and the temperature measurement accuracy can be improved. In this paper, the temperature measurement principle of photoelectric pyrometer, the working principle of the detection optical system and the composition of the system are introduced. The optical components that affect the imaging of the optical system of the photoelectric pyrometer are analyzed. The optical pyrometer detection optical system is simulated by ZEMAX software, based on the analysis results, the Modulation Transfer Function (MTF) and the spot Diagram are used as the main evaluation criteria to optimize the design of the objective lens of the photoelectric pyrometer detection optical system. The imaging performance of the photoelectric pyrometer detection optical system and the accuracy of temperature measurement of the photoelectric pyrometer are improved by optimization design of the detection optical system.     

Effect of nano powder (Al2O3-CaO) addition on the mechanical properties of the polymer blend matrix composite

This work describes the preparation and study of the properties of composite nanoparticles prepared by the sol-gel method which consists of two materials (Al₂O₃-CaO), and study the effect of these nanoparticles on the mechanical behavior of a polymer blend (EP 4% + 96% UPE). The powder was evaluated by X-ray diffraction analysis, scanning electron microscopy analysis (SEM), particle size analysis, and energy dispersive X-ray analysis (EDX). The mechanical behavior of the composite material was assessed by tensile test, bending test and hardness test. The evaluation results of the composite nanoparticles showed good distribution of the chemical composition between aluminum oxide and calcium oxide, smoothness in particles' size at calcination in high and low temperatures, formation of different shapes of nanoparticles and different (kappa and gamma) phases of the Al₂O₃ particles. The results of mechanical behavior tests showed marked improvement in the mechanical properties of the resulted composite material, especially at 1.5%, compared with polymer blend material without nano powder addition. The tensile properties improved about (24 and 14.9) % and bending resistance about (23.5 and 16.8) % and hardness by (25 and 22) % when adding particles of size (63.8 and 68.6) respectively. Therefore, this reflects the efficiency of the proposed method to manufacture the nanocomposite powder and the possibility of using this powder as a strengthening material for the composite materials and using these composite materials in bio applications, especially in the fabrication of artificial limbs.     

导弹结构热防护一体化设计与优化

针对导弹面临的严酷气动热力环境,基于传统波纹夹芯结构,为导弹设计了一种兼具承载和热防护功能的一体化结构。建立热-结构耦合计算模型,对一体化结构进行结构承载与热防护性能分析,结果表明:一体化结构在高温下具有较好的承载能力;增加一体化结构隔热层与内壁厚度有助于提高导弹的热防护效率。以一体化结构热防护效率最高和质量最小为目标,采用第二代非支配排序遗传算法实现了多目标优化,并认识到:一体化结构热防护效率与质量相互影响,设计时需要需综合考虑。     

滑翔飞行器多目标弹道优化的进化-配点混合求解策略

针对高超声速滑翔飞行器弹道多目标优化问题,综合考虑计算效率和精度,结合分解进化算法与配点法提出一种混合求解策略。根据滑翔飞行器动力学模型和弹道设计中需要考虑的约束条件,建立飞行器多目标弹道优化模型。利用控制量离散化方法将多目标弹道优化问题转化为带约束的多目标参数优化问题,并采用罚函数法处理约束条件,随后利用分解多目标进化算法进行求解。为了提高弹道优化的精度,将椭球聚合法与配点法相结合,以多目标进化算法得到的Pareto解作为初始解进行迭代求解。通过典型的复杂约束多目标弹道优化的算例表明,所提出的混合求解策略能够获得满足复杂约束要求的Pareto最优解集,实现有效的多目标弹道优化。     

Application of Markov renewal theory and semi-Markov decision processes in maintenance modeling and optimization of multi-unit systems

In this paper, a condition-based maintenance model for a multi-unit production system is proposed and analyzed using Markov renewal theory. The units of the system are subject to gradual deterioration, and the gradual deterioration process of each unit is described by a three-state continuous time homogeneous Markov chain with two working states and a failure state. The production rate of the system is influenced by the deterioration process and the demand is constant. The states of the units are observable through regular inspections and the decision to perform maintenance depends on the number of units in each state. The objective is to obtain the steady-state characteristics and the formula for the long-run average cost for the controlled system. The optimal policy is obtained using a dynamic programming algorithm. The result is validated using a semi-Markov decision process formulation and the policy iteration algorithm. Moreover, an analytical expression is obtained for the calculation of the mean time to initiate maintenance using the first passage time theory.     

利用最小二乘支持向量机求解潜艇内外磁场映射模型

为提高潜艇磁隐身能力,应对潜艇固定磁场进行实时监测,提出利用最小二乘支持向量机的潜艇内外磁场映射方法。结合内外映射法和最小二乘支持向量机原理,通过交叉验证优化模型参数,建立由内到外的潜艇磁场映射模型。以潜艇外部垂向固定磁场变化量为分析对象,仿真和实验结果均与标准值吻合良好。与径向基神经网络算法相比,该方法的泛化能力和推算精度有明显提高,且更符合工程实际,对闭环消磁技术的研究具有指导意义。     

OFDM系统中深度神经网络指导的IQ不平衡补偿算法

正交频分复用(Orthogonal Frequency Division Multiplexing,OFDM)是现代移动通信中一项重要的物理层通信技术,并且OFDM系统要求子载波间严格正交。然而,在实际系统中,振荡器和滤波器等器件的非理想特性会导致同相正交(In-phase and Quadrature-phase,IQ)不平衡,从而破坏子载波的正交性,严重影响OFDM系统的性能。通过研究IQ不平衡对OFDM系统的影响,提出了一种并联深度神经网络架构下的IQ不平衡补偿算法。该算法利用了深度神经网络不依赖于模型的特点,直接从接收到的频域信号恢复原输入信号的二进制序列,并利用干扰信号来自镜像子载波的先验知识来初始化模型驱动的神经网络,加快其网络优化的收敛速度。仿真结果表明,该算法能有效地补偿IQ不平衡失真,并且在幅度和相位失真的补偿上,其性能都优于传统的基于导频的最小二乘补偿算法,证明了深度学习方法解决物理层问题的优越性。     

创新人才军民融合培养体系及其构建

创新人才军民融合培养构成人才强国战略、创新驱动发展战略和军民融合发展战略的交汇点。创新人才是战略资源,军民融合为创新人才培养提供了一条全新路径。作为一项系统工程,创新人才军民融合培养包括创新人才军民融合培养主体系统、创新人才军民融合培养客体系统、创新人才军民融合培养方案系统、创新人才军民融合培养资源系统、创新人才军民融合培养制度系统、创新人才军民融合培养考评系统,在系统构建过程中需加大统筹协调、投入保障、政策倾斜、法治保障、合理使用力度,注重体系推进。