数字自相关检测技术在电子侦察接收机中的应用

现代雷达通常采用脉冲压缩、超低副瓣天线等相关技术来降低雷达信号的被截获概率,这给电子侦察接收机的信号检测带来了困难。文中提出在数字信道化接收机基础上,采用子信道内数字自相关检测技术对来波信号进行相关运算,获得较大的处理增益,提高系统接收灵敏度,并且算法运算量较小,适合实际工程应用。     

大电流矩形镉镍蓄电池组的FMEA分析

对大电流矩形镉镍电池进行了详细的失效模式与影响分析（ＦＭＥＡ），提出了相应的预防措施，对一南类电池的可靠性和维修性设计具有一定的帮助。     

空间站大面积柔性太阳电池阵的动力学问题

讨论了空间站大面积柔性太阳电池阵的动力学问题。针对该种太阳电池阵的结构特点，指出了动力学分析的复杂性。对国外所开展的几个有关动力学问题的工作作了简单的介绍。最后，利用解析法和有限元法分别对一个大面积柔性太阳电池阵的动态特性进行了分析和计算，并给出了初步的数值结果。     

A new two-scale model for large eddy simulation of wall-bounded flows

A new hybrid approach to model high Reynolds number wall-bounded turbulent flows is developed based on coupling a two-level simulation (TLS) approach (Kemenov and Menon, 2006 [1], 2007 [2] in the inner region with conventional large eddy simulation (LES) away from the wall. This new approach is significantly different from previous near-wall approaches for LES. In this hybrid TLS–LES approach, a very fine small-scale (SS) mesh is embedded inside the coarse LES mesh. The SS equations capture fine-scale temporal and spatial variations in all three Cartesian directions for all three velocity components near the wall. The TLS–LES equations are derived using a new scale separation operator that allows a smooth transition between the two regions, with the equations in the transition region obtained by blending the TLS large-scale and LES equations. New terms in the hybrid region are identified. The TLS–LES approach is used to study the near-wall features in canonical turbulent channel flows for a range of Reynolds number using relatively coarse large-scale (LS) grids. Results show that the TLS–LES approach is able to capture the effect of both the LS and SS features in the wall region consistently for the range of simulated Reynolds number.     

LES of the Sandia flame series D-F using the Eulerian stochastic field method coupled with tabulated chemistry

In this paper, the Eulerian Stochastic Field (ESF) model in the Transported Probability Density Function (TPDF) class model is combined with the Flamelet Generated Manifolds (FGM) model. This method solves the joint probability density function transport equation by ESF method that considers the interaction mechanism between flame and turbulence with high precision. At the same time, by making use of the advantage of the FGM model, this model is able to incorporate the detailed chemical reaction mechanism (GRI 3.0) with acceptable computational cost. The new model has been implemented in the open source CFD suite-OpenFOAM. Validation of the model has been carried out by simulating the Sandia flame series (three turbulent piloted methane jet flames) issued by the National Laboratory of the United States. The accuracy and advancement of the ESF/FGM turbulent combustion model are verified by comparing the LES results of the new model with the rich experimental data as well as the RANS results. The results demonstrate that the model has a strong ability in capturing combustion phenomena such as extinction and re-ignition in turbulent flame, which is essential in the accurate prediction of the combustion process in real combustion devices, for example, aircraft engines.     

Decentralized formation pose estimation for spacecraft swarms

For spacecraft swarms, the multi-agent localization algorithm must scale well with the number of spacecraft and adapt to time-varying communication and relative sensing networks. In this paper, we present a decentralized, scalable algorithm for swarm localization, called the Decentralized Pose Estimation (DPE) algorithm. The DPE considers both communication and relative sensing graphs and defines an observable local formation. Each spacecraft jointly localizes its local subset of spacecraft using direct and communicated measurements. Since the algorithm is local, the algorithm complexity does not grow with the number of spacecraft in the swarm. As part of the DPE, we present the Swarm Reference Frame Estimation (SRFE) algorithm, a distributed consensus algorithm to co-estimate a common Local-Vertical, Local-Horizontal (LVLH) frame. The DPE combined with the SRFE provides a scalable, fully-decentralized navigation solution that can be used for swarm control and motion planning. Numerical simulations and experiments using Caltech’s robotic spacecraft simulators are presented to validate the effectiveness and scalability of the DPE algorithm.     

Physical model for acoustic resonance in annular cavity structure

A physical model for acoustic resonance in the annular cavity structure is developed to represent the typical characteristic when acoustic resonance occurs. Firstly, the measurement of sound pressure in the casing and rotor blades vibration is operated in a multistage high pressure compressor. The sharp peak frequency and discrete multi-tone occur in the frequency spectrum of sound pressure in the compressor, and the vibration of the first stage of rotor blades synchronously presents the high amplitude. The frequencies associated with rotor blades vibration can be calculated with rotating sound source theory. It is also confirmed that acoustic resonance occurs in the multistage compressor. With acoustic similarity principle, an annular cavity model is established to simulate the typical characteristics of acoustic resonance in the compressor based on Large Eddy Simulation (LES) and Lighthill acoustic analogy. The coupling relationship between cavity acoustic mode and disc vibration mode shape is expounded when acoustic resonance occurs in the model. And acoustic resonance will be locked in the certain flow rate range. All these characteristics match well with those occur in the multistage high pressure compressor.     

模糊控制方法及其在飞控中的应用

对于较大的飞行包线，飞机对象的参数变化剧烈，采用常规控制方法往往不能保证在较大飞行包线范围内均取得良好的控制效果，基于此，提出了一种新型的自组织模糊控制方法，该对系统内部参数的剧烈变化具有很强的适应性，然后对飞机飞行控制系统的控制律设计进行了研究。用所提出的模糊控制方法设计了部分控制律，最后以某型国产飞机对象，采用飞机六自由度非线性仿真模型，在一个较大的飞行包线范围内，进行了飞行仿真，取得了良好的     

A high-fidelity design methodology using LES-based simulation and POD-based emulation: A case study of swirl injectors

Engineering design is undergoing a paradigm shift from design for performance to design for affordability, operability, and durability, seeking multi-objective optimization. To facilitate this transformation, significantly extended design freedom and knowledge must be available in the early design stages. This paper presents a high-fidelity framework for design and optimization of the liquid swirl injectors that are widely used in aerospace propulsion and power-generation systems. The framework assembles a set of techniques, including Design Of Experiment (DOE), high-fidelity Large Eddy Simulations (LES), machine learning, Proper Orthogonal Decomposition (POD)-based Kriging surrogate modeling (emulation), inverse problem optimization, and uncertainty quantification. LES-based simulations can reveal detailed spatiotemporal evolution of flow structures and flame dynamics in a high-fidelity manner, and identify important injector design parameters according to their effects on propellant mixing, flame stabilization, and thermal protection. For a given a space of design parameters, DOE determines the number of design points to perform LES-based simulations. POD-based emulations, trained by the LES database, can effectively explore the design space and deduce an optimal group of design parameters in a turn-around time that is reduced by three orders of magnitude. The accuracy of the emulated results is validated, and the uncertainty of prediction is quantified. The proposed design methodology is expected to profoundly extend the knowledge base and reduce the cost for initial design stages.