基于高效数值方法的一种高超声速飞行器外形气动力/热综合优化设计研究

基于所发展的高效气动力/热快速预测方法,建立了适用于高超声速飞行器的综合考虑气动力与气动热特性的外形优化设计技术,并在一种高超声速飞行器外形设计中应用,通过优化设计改变了初始外形纵向静不稳定特性,优化后外形实现了纵向静稳定、大攻角自配平和非驻点表面最大热流下降的设计目标。所发展的方法为适应气动外形快速选型设计需求提供了有效的途径。     

基于左手材料的翼面隐身结构设计及优化

翼面隐身结构能同时满足飞行器机翼气动、结构和隐身的要求,但在空间有限的机翼中应用时,由于结构特点使其隐身效果受到限制。为了解决该问题,在传统隐身结构中加入左手材料(LHM)进行改进。首先选取一种典型的LHM,从隐身设计角度出发,利用其雷达散射截面(RCS)计算不同入射角度下的后向吸收率,对其电磁特性进行研究。然后根据LHM的电磁特性,将其应用于翼面隐身结构,在相同的RCS减缩效果下,应用LHM可有效降低隐身结构体积。最后,为了进一步提高隐身效果,提出一种夹芯型LHM翼面隐身结构,并对该隐身结构中的结构参数利用代理模型进行优化。研究结果表明,相较金属翼面段RCS降低了15dB以上,较相同结构的翼面隐身结构RCS降低了10dB以上。     

A strategic flight conflict avoidance approach based on a memetic algorithm

Conflict avoidance （CA） plays a crucial role in guaranteeing the airspace safety. The cur- rent approaches, mostly focusing on a short-term situation which eliminates conflicts via local adjust- ment, cannot provide a global solution. Recently, long-term conflict avoidance approaches, which are proposed to provide solutions via strategically planning traffic flow from a global view, have attracted more attentions. With consideration of the situation in China, there are thousands of flights per day and the air route network is large and complex, which makes the long-term problem to be a large-scale combinatorial optimization problem with complex constraints. To minimize the risk of premature convergence being faced by current approaches and obtain higher quality solutions, in this work, we present an effective strategic framework based on a memetic algorithm （MA）, which can markedly improve search capability via a combination of population-based global search and local improve- ments made by individuals. In addition, a specially designed local search operator and an adaptive local search frequency strategy are proposed to improve the solution quality. Furthermore, a fast genetic algorithm （GA） is presented as the global optimization method. Empirical studies using real traffic data of the Chinese air route network and daily flight plans show that our approach outper- formed the existing approaches including the GA .based approach and the cooperative coevolution based approach as well as some well-known memetic algorithm based approaches.     

Aeroelastic two-level optimization for preliminary design of wing structures considering robust constraints

An aeroelastic two-level optimization methodology for preliminary design of wing struc- tures is presented, in which the parameters for structural layout and sizes are taken as design vari- ables in the first-level optimization, and robust constraints in conjunction with conventional aeroelastic constraints are considered in the second-level optimization. A low-order panel method is used for aerodynamic analysis in the first-level optimization, and a high-order panel method is employed in the second-level optimization. It is concluded that the design of the abovementioned structural parameters of a wing can be improved using the present method with high efficiency. An improvement is seen in aeroelastic performance of the wing obtained with the present method when compared to the initial wing. Since these optimized structures are obtained after consideration of aerodynamic and structural uncertainties, they are well suited to encounter these uncertainties when they occur in reality.     

转子-支承耦合结构的模型修正研究

在转子-支承耦合结构的动力学分析过程中,结构模态参数计算结果与实验测试结果往往存在较大差异。针对此问题,应用优化算法对结构动力学模型进行修正,使计算模型能更准确地反映结构特性。建立由梁单元、盘单元、弹性支承单元组成的结构动力学有限元模型;选择优化目标函数、设计参数,并对各参数进行灵敏度分析。应用粒子群算法对选取的设计参数进行优化,得到最优模型。利用转子-滚动轴承实验器进行验证,结果表明,方法能够有效地实现转子-支承耦合结构的动力学模型修正,修正后模型更接近实际结构。     

基于模块度的复杂网络社团结构聚类新算法

针对传统的分裂聚类算法删除连边会影响节点划分的问题,结合K-means算法的思想并加以改进,提出了一种以邻居节点为聚类备选集,所有社团中心节点同时聚类的同步聚类算法。该算法根据节点中心度和最短路变化率确定社团中心节点集,然后以中心节点为社团中心,以邻居节点为聚类备选集合进行聚类,完成社团的划分。将算法应用到Zachary网络中并与GN算法、Top Leader算法进行比较,仿真结果表明该算法对网络有较好的划分。     

单天基平台测向的空间非合作目标跟踪

针对仅含角度测量信息的单个天基平台可观测性较弱的问题,提出了一种含脉冲机动检测的空间非合作目标跟踪算法,并设计了非合作目标实时跟踪数据处理流程.该算法利用抗差估计技术和UKF（Unscented Kalman Filter,无迹卡尔曼滤波）算法构造目标跟踪滤波器,并综合残差多项式拟合和新息分布特征等方法实现目标机动检测,在天基平台观测信息类型有限和观测几何较差的情况下,可以同时排除孤立野值和成片测量野值的影响,实现非合作机动目标的连续稳定跟踪.数值实验验证了算法的可行性和有效性,也表明了跟踪精度和可靠性与测量精度密切相关.     

用于雷达方位超分辨的约束迭代Tikhonov正则化算法

针对Tikhonov正则化算法噪声适应能力差和不便于引进额外的约束对解进行限制等缺点,利用迭代Tik-honov正则化算法对雷达方位超分辨进行研究,证明了迭代Tikhonov正则化反卷积公式的收敛性,分析了迭代Tik-honov正则化算法的频域性质,在存在噪声的情况下,提出相应的噪声抑制方法,得到约束迭代Tikhonov正则化算法。针对不同信噪比情况进行了计算机仿真实验,结果表明,与迭代Tikhonov正则化算法相比,约束迭代Tikhonov正则化算法具有较强的噪声适应能力,与常用的约束迭代方法（CID）算法相比,具有较快的收敛速度,初步验证了算法的有效性。     

激光陀螺四位置寻北仪提高精度方法

为消除激光陀螺零偏和常值漂移的影响,采用四位置方案来实现高精度寻北。本文简述了单轴激光陀螺四位置寻北方案,给出了陀螺敏感轴与机体系前向偏差角标定方法,研究了寻北仪在倾斜基座下数据补偿算法。本文研究了由于在四个位置上电机转动不到位所引起的误差补偿算法。通过对寻北仪系统测试,采用电机转动不到位补偿后数据标准差降低了0.02º,激光陀螺寻北仪系统达到了高精度快速寻北的要求。     

粗糙条件熵算法在故障诊断中应用分析

给出了一种基于条件熵的算法,并应用于弹载电子设备故障诊断中。结果表明,诊断结果准确可靠,且弥补了差别矩阵算法和差别函数算法的不足。