系统可靠性预计方法综述

系统可靠性预计是进行可靠性设计的基础，其主要价值在于为设计决策提供依据。本文阐明了系统可靠性预计的概念，分析了系统可靠性预计的基本过程，综述了系统可靠性的预计方法，介绍和评论了各自的优缺点和适用范围，并对预计方法的发展前景做了初步展望。     

"公寓"型LRU可靠性指标的预计法探讨

探讨了“公寓”型LRU可靠性预计的方法，“公寓”型LRU的电子元器件不属于同一系统，因此不能按“串联”型预计，如何预计则应进一步研究，本文提出了预计的3种方法。     

用于省内公路干线网规划研究的启发式模型

本文阐述了一种将运量在运输线路上的配置和投资在项目上的分配相结合的启发式方法的模型。文章对这种方法的原理与应用进行了研究探讨。     

一种尾流消散动态预测的改进算法

尾流间隔是增大跑道容量的主要限制因素之一，为了在保持安全水平的前提下有效地增大跑道容量，可以对尾流消散进行动态预测，并据此缩减尾流间隔。研究了一种尾涡消散动态预测算法，该算法考虑了真实大气的大气分层、湍流、侧风、迎面风、风切变以及地效影响，并用一阶后向差分对该算法进行了离散化改进；在改进算法的基础上，时进近阶段尾流的消散在Matlab中进行了仿真计算；计算结果复现了尾涡的下沉现象和侧风对尾涡传输的线性累积效应。     

A Structured Mesh Euler and Interactive Boundary Layer Method for Wing/Body Configurations

To compute transonic flows over a complex 3D aircraft configuration, a viscous/inviscid interaction method is developed by coupling an integral boundary-layer solver with an Eluer solver in a ＂semi-inverse＂ manner. For the turbulent boundary-layer, an integral method using Green＇s lag equation is coupled with the outer inviscid flow. A blowing velocity approach is used to simulate the displacement effects of the boundary layer. To predict the aerodynamic drag, it is developed a numerical technique called far-field method that is based on the momentum theorem, in which the total drag is divided into three component drags, i.e. viscous, induced and wave-formed. Consequently, it can provide more physical insight into the drag sources than the often-used surface integral technique. The drag decomposition can be achieved with help of the second law of thermodynamics, which implies that entropy increases and total pressure decreases only across shock wave along a streamline of an inviscid non-isentropic flow. This method has been applied to the DLR-F4 wing/body configuration showing results in good agreement with the wind tunnel data.     

区域运输规划模型系统

提出一种区域运输规划模型系统,以求从定量的角度,预测一个区域内的货物运输量,继而确定这些运输量对该区域内存在的多种运输方式的偏好结构,最后仿真这些运量在相应的各种运输网络上的分布情况,同时仿真模型还对运输网线路经过新建或扩建后所形成的新的运量分布进行模拟。根据运量分布情况,就可提出初步的规划建设方案。     

Numerical analysis and optimization of boundary layer suction on airfoils

Numerical approach of hybrid laminar flow control(HLFC) is investigated for the suction hole with a width between 0.5 mm and 7 mm. The accuracy of Menter and Langtry’s transition model applied for simulating the flow with boundary layer suction is validated. The experiment data are compared with the computational results. The solutions show that this transition model can predict the transition position with suction control accurately. A well designed laminar airfoil is selected in the present research. For suction control with a single hole, the physical mechanism of suction control, including the impact of suction coefficient and the width and position of the suction hole on control results, is analyzed. The single hole simulation results indicate that it is favorable for transition delay and drag reduction to increase the suction coefficient and set the hole position closer to the trailing edge properly. The modified radial basis function(RBF) neural network and the modified differential evolution algorithm are used to optimize the design for suction control with three holes. The design variables are suction coefficient, hole width, hole position and hole spacing. The optimization target is to obtain the minimum drag coefficient. After optimization,the transition delay can be up to 17% and the aerodynamic drag coefficient can decrease by 12.1%.     

大型齿轮在多因素耦合影响下齿形误差测量的灰色动态预报

提出了一种旁置式的大型齿轮测量装置,分析了影响该装置测量精度的主要误差来源及其特性,给出了一种处理多因素耦合影响的灰色动态预报方法.首先,基于测量装置特性,对影响齿形误差测量精度的误差源进行分析和标定,计算出各误差源的灵敏度系数;然后对测得的有限误差数据进行再抽样及灰色生成,分别计算出在每次测量中各影响因素对测量结果的作用大小,之后按照误差合成方法生成误差源耦合作用结果;最后,通过在测量结果中去除耦合作用进而提高大型齿轮齿形误差测量精度.与测量精度为0.5μm的三坐标测量机进行对比测量,结果表明所提出测量装置能满足3级精度以上的大型齿轮齿形误差检测需求.     

火箭返回制导动力着陆段的自适应启动方法

针对重复使用火箭垂直返回着陆问题,提出了一种燃料最优的动力着陆段自适应启动方法。首先,将燃料最优启动点对应的动力着陆轨迹的推力剖面和攻角剖面描述为解析的形式,该解析形式中攻角剖面由状态量唯一确定,推力剖面仅含一个待定参数。随后,通过预测具有上述解析剖面形式的轨迹判断是否启动动力着陆。计算中引入松弛终端位置约束的策略求解推力剖面待定参数,由终端位置约束判断是否满足燃料最优启动条件。上述策略将燃料最优启动条件的判断问题简化为单一变量求解问题,实现了该问题的快速求解。仿真结果表明,该方法得到的启动点与数值优化方法得到的燃料最优启动点接近,且求解过程稳定、计算效率高。     

一种高超声速滑翔飞行器轨迹智能预测方法

针对高超声速滑翔飞行器(Hypersonic glide vehicle, HGV)机动性强、轨迹预测困难的问题,选取气动加速度作为预测参数,提出了一种基于集合经验模态分解和注意力长短时记忆网络的HGV轨迹智能预测方法。首先,以HGV六自由度运动方程为基础,分析了其机动特性和气动力变化规律,建立了动力学跟踪模型,对气动加速度进行实时估计;其次,利用集合经验模态分解对估计的气动加速度进行分解和重构,减弱噪声影响,避免对预测模型的干扰;最后,利用去噪后的气动加速度数据对注意力长短时记忆网络进行训练,进而预测未来气动加速度数据并重构HGV未来轨迹,实现轨迹的在线预测。实验仿真表明,该方法能有效预测HGV机动轨迹,预测精度高、稳定性好。