线性拟合法建立航空发动机状态变量模型

针对非线性拟合法建立航空发动机状态变量模型过程中的初值问题,提出了一种能够避免该问题的线性拟合法,即在离散域情况下,利用已知的状态序列来构建系统矩阵与模型响应之间呈线性关系的目标函数,从而使非线性最小二乘问题转化为线性最小二乘问题.应用该方法建立某型涡扇发动机的小偏差状态变量模型,并与非线性拟合法进行了对比研究,结果表...     

空间拦截防御的射击诸元快速解算算法

针对空间平台发射非制导毁伤单元对近程高速非合作目标进行拦截防御的射击诸元快速解算问题,建立了命中方程,并基于命中方程的一阶解,给出了2种解析算法确定发射时刻、发射速度矢量与提前点坐标之间的函数关系.提出了计算命中时刻、发射速度矢量与发射时刻间函数关系的二分数值方法.最后通过仿真分析了算法的方法误差及适用范围.     

关于某个四阶非对称微分方程边值问题的唯一性

本文处理如下形式的四阶非对称微分方程边值问题的唯一性。 对于对称情形,传统的处理方法是利用Thichmarsh,E.C.的函数论方法与亏指标理论。而当方程为非对称时,上述方法会有些困难。但若通过构造某个特殊的与(?)λ有关的内积,并利用内插不等式及Opial不等式,则非对称情形能被容易地处理且得到许多唯一性的结果。     

S_2流面正命题适用于纯物质流体的变分原理族及其对偶变分原理族

本文建立了适用于纯物质流体轴流式S_2流面正命题的变分原理族及其对偶变分原理族。证明了其中的两条狭义变分原理在均转子焓均熵条件下在亚声速区内分别为极大值原理和极小值原理。在变分原理的构造中,采用吉布斯关系作为约束,从而使这些变分原理适用于纯物质流体。     

关于对偶理论中互补松弛定理的使用方法探讨

对于对偶理论中互补松弛定理在各种情况下的使用方法进行了说明，能够使学生更好地掌握该定理的含义和应用方法     

转子/静子干涉气动声学反问题研究

探讨了通过测量空间有限点声压来反演静叶表面压力分布的转子/静子干涉气动声学反问题。具体从线化欧拉方程出发,将空间有限点的声压与静叶表面的非定常压力分布关联成第一类Fredholm积分方程的形式。鉴于问题的不适定,本文采用奇异值分解与Tikhonov正则化解法相结合的最小二乘方法进行求解,并采用离散Picard条件进行可解性分析,而最优正则化参数的选取则采用广义互校核方法。计算结果表明,在信噪比不是很低的情况下,反演是可行的。      

Hybrid partition- and network-level scheduling design for distributed integrated modular avionics systems

Distributed Integrated Modular Avionics (DIMA) develops from Integrated Modular Avionics (IMA) and realizes distributed integration of multiple sub-function areas. Time-triggered network provides effective support for time synchronization and information coordination in DIMA systems. However, inconsistency between processing resources and communication network destroys the time determinism benefiting from partitions and time-triggered mechanism. To ensure such time determinism and achieve guaranteed real-time performance, system design should collectively provide a global communication scheme for messages in network domain and a corresponding execution scheme for partitions in processing domain. This paper firstly establishes a general DIMA model which coordinates partitioned processing and time-triggered communication, and then proposes a hybrid scheduling algorithm using Mixed Integer Programming to produce feasible system schemes. Furthermore, incrementally integrating new functions causes upgrades or reconfigurations of DIMA systems and will generate integration cost. To control such cost, this paper further develops an optimization algorithm based on Maximum Satisfiability Problem and guarantees that the scheduling design for upgraded DIMA systems inherit their original schemes as much as possible. Finally, two typical cases, including a simple fully connected DIMA system case and an industrial DIMA system case, are constructed to illustrate our DIMA model and validate the effectiveness of our hybrid scheduling algorithms.     

采用二维贝叶斯方法求解旋转盘腔导热反问题

为了研究压气机旋转盘腔换热特性,实现准确求解转盘表面传热系数,引入二维贝叶斯方法,此方法采用先验分布优化测温误差,并且更加符合转盘的二维特性。通过加入噪声的模拟数据验证方法的可行性,结果表明无测温误差时方法的平均误差是3.2%,有测温误差时方法的平均误差是10.6%,并分析了误差来源。通过与已有实验结果对比,发现方法更适用于计算转盘迎风面与背风面传热差异较大时的表面传热系数,平均相对误差为9.6%,满足实际工程精度的要求。通过改变盘面温度测点数量,发现测点增加会提升计算精度,并采用统计抽样理论分析原因,发现在可接受误差为10%时,所需要的测点数量比较合理。     

Two-phase framework for near-optimal multi-target Lambert rendezvous

This paper proposes a two-phase framework to obtain a near-optimal solution of multi-target Lambert rendezvous problem. The objective of the problem is to determine the minimum-cost rendezvous sequence and trajectories to visit a given set of targets within a maximum mission duration. The first phase solves a series of single-target rendezvous problems for all departure-arrival object pairs to generate the elementary solutions, which provides candidate rendezvous trajectories. The second phase formulates a variant of traveling salesman problem (TSP) using the elementary solutions prepared in the first phase and determines the final rendezvous sequence and trajectories of the multi-target rendezvous problem. The validity of the proposed optimization framework is demonstrated through an asteroid exploration case study.     

Uncertain multiobjective redundancy allocation problem of repairable systems based on artificial bee colony algorithm

Based on the uncertainty theory, this paper is devoted to the redundancy allocation problem in repairable parallel-series systems with uncertain factors, where the failure rate, repair rate and other relative coefficients involved are considered as uncertain variables. The availability of the system and the corresponding designing cost are considered as two optimization objectives. A crisp multiobjective optimization formulation is presented on the basis of uncertainty theory to solve this resultant problem. For solving this problem efficiently, a new multiobjective artificial bee colony algorithm is proposed to search the Pareto efficient set, which introduces rank value and crowding distance in the greedy selection strategy, applies fast non-dominated sort procedure in the exploitation search and inserts tournament selection in the onlooker bee phase. It shows that the proposed algorithm outperforms NSGA-II greatly and can solve multiobjective redundancy allocation problem efficiently. Finally, a numerical example is provided to illustrate this approach.