大型飞机高速气动力关键问题解决的技术手段及途径

大型飞机采用超临界机翼,并具有尺度大、飞行雷诺数高等特点,其研制中必须解决好高升阻比机翼、翼身组合体设计,推进系统/机体一体化设计,抖振特性、静气动弹性特性预测及超临界机翼流动控制等高速气动力问题。要解决这些关键气动力问题,必须进行一系列相关的大型高速风洞试验,以及解决相应的试验技术问题。     

2.4m跨声速风洞带TPS测力试验数据精度要求分析

成功建立带TPS风洞测力试验技术的一个关键问题是确保试验数据具有足够的精度,必须精细地分配误差。为获得满足工程需要的高精度测力试验数据,给出一种基于计算机符号运算的子程序,完成不确定度计算过程中公式自动推导、计算。最后通过对TPS风洞试验数据精度的敏度分析,给出了某运输机在2.4m跨声速风洞TPS试验中各环节的误差分配要求。     

GRACE gravity field modeling with an investigation on correlation between nuisance parameters and gravity field coefficients

The GRACE (Gravity Recovery And Climate Experiment) monthly gravity models have been independently produced and published by several research institutions, such as Center for Space Research (CSR), GeoForschungsZentrum (GFZ), Jet Propulsion Laboratory (JPL), Centre National d’Etudes Spatiales (CNES) and Delft Institute of Earth Observation and Space Systems (DEOS). According to their processing standards, above institutions use the traditional variational approach except that the DEOS exploits the acceleration approach. The background force models employed are rather similar. The produced gravity field models generally agree with one another in the spatial pattern. However, there are some discrepancies in the gravity signal amplitude between solutions produced by different institutions. In particular, 10%–30% signal amplitude differences in some river basins can be observed. In this paper, we implemented a variant of the traditional variational approach and computed two sets of monthly gravity field solutions using the data from January 2005 to December 2006. The input data are K-band range-rates (KBRR) and kinematic orbits of GRACE satellites. The main difference in the production of our two types of models is how to deal with nuisance parameters. This type of parameters is necessary to absorb low-frequency errors in the data, which are mainly the aliasing and instrument errors. One way is to remove the nuisance parameters before estimating the geopotential coefficients, called NPARB approach in the paper. The other way is to estimate the nuisance parameters and geopotential coefficients simultaneously, called NPESS approach. These two types of solutions mainly differ in geopotential coefficients from degree 2 to 5. This can be explained by the fact that the nuisance parameters and the gravity field coefficients are highly correlated, particularly at low degrees. We compare these solutions with the official and published ones by means of spectral analysis. It is found that our solutions are, in general, consistent with others in the spatial pattern. The water storage variations of the Amazon, Chari and Ganges river basins have also been computed. The variations computed with the NPARB approach are closer to those produced by JPL and DEOS solutions, while the variations produced with the NPESS approach are in good agreement with those produced by the CSR and GFZ solutions. A simulation study is implemented with considering realistic noise and low-frequency error. The two approaches are used to recover the true model. The NPESS solution appears closer to the true one. Therefore we are inclined to estimate the nuisance parameters simultaneously with the geopential coefficients.     

A review of topology optimization for additive manufacturing: Status and challenges

Topology optimization was developed as an advanced structural design methodology to generate innovative lightweight and high-performance configurations that are difficult to obtain with conventional ideas. Additive manufacturing is an advanced manufacturing technique building as-designed structures via layer-by-layer joining material, providing an alternative pattern for complex components. The integration of topology optimization and additive manufacturing can make the most of their advantages and potentials, and has wide application prospects in modern manufacturing. This article reviews the main content and applications of the research on the integration of topology optimization and additive manufacturing in recent years, including multi-scale or hierarchical structural optimization design and topology optimization considering additive manufacturing constraints. Meanwhile, some challenges of structural design approaches for additive manufacturing are discussed, such as the performance characterization and scale effects of additively manufactured lattice structures, the anisotropy and fatigue performance of additively manufactured material, and additively manufactured functionally graded material issues, etc. It is shown that in the research of topology optimization for additive manufacturing, the integration of material, structure, process and performance is important to pursue high-performance, multi-functional and lightweight production. This article provides a reference for further related research and aerospace applications.     

航天器总装多余物控制方法探讨

带有多余的航天产品存在重大的质量事故隐患。文章对航天器总装中的多余物进行了分类,从而分析多余物产生的机理有4大来源:总装工艺过程、零组件及人员带入、贮存过程、有害气体。介绍了多余物的危害,提出了系统控制多余物的思路和多余物常用检查及排除的方法。     

液氧甲烷重复使用辅助动力系统方案与进展

航班化航天运输系统的应用需求日趋迫切,基于液氧/甲烷(LOX/LCH₄)发动机的可重复使用运载火箭成为国内外研究热点。面向某型运载火箭对一级返回辅助动力系统的需求,提出了基于电动泵的主辅一体化液氧甲烷系统方案和独立挤压式液氧甲烷系统方案,开展了方案比选和应用优势分析,并介绍了液氧甲烷轨姿控发动机和低温表面张力贮箱的研究基础,以及国内首款液氧甲烷轨姿控推进系统集成演示试验情况。液氧甲烷辅助动力系统可以实现全箭推进剂的统一和无毒化,助力运载火箭走向高效及完全可重复使用。选择切实可行的“分步走”策略,优先开展挤压式液氧甲烷辅助动力系统的工程化研制与飞行应用,逐步实现基于电动泵的主辅一体化液氧甲烷辅助动力系统在重复使用运载火箭和低温上面级等领域应用。     

基于神经网络的无迹滤波改进算法

介绍了采用无迹变换(UT)描述随机变量通过非线性系统后的均值及方差的方法,提出可以将神经模糊推理系统(ANFIS)用于确定无迹变换中的参数,使其对随机变量均值的描述达到二次以上精度,并给出了改进的无迹滤波器(UKF)结构和神经网络训练方法;仿真结果表明,该算法适用于系统含有未知输入或系统噪声为非高斯的情况,并可解决一些典型的非线性估计问题,改进算法的性能优于传统无迹滤波器。     

一种提高导航卫星星座自主定轨精度的方法研究

针对近地导航卫星仅利用星间测距进行自主定轨时,因无法消除星座整体旋转误差而导致长期自主定轨精度不高的问题,提出了利用拉格朗日导航卫星星座与近地导航卫星星座联合仅利用星间测距进行自主定轨的方法。建立了拉格朗日轨道导航卫星星座和近地导航卫星星座联合仅利用星间测距进行自主定轨的动力学模型和观测模型。利用扩展Kalman滤波（EKF）算法和星间测距信息实现了拉格朗日轨道导航星座与近地导航星座的长期自主定轨。以4颗拉格朗日卫星组成的导航星座与12颗GPS卫星组成的近地导航星座作为仿真对象进行了仿真分析,仿真结果表明本文仅利用星间测距的联合自主定轨方法可以有效提高导航卫星星座的长期自主定轨精度。
     

运载火箭交叉输送系统关键影响因素辨识与分析

为深入了解交叉输送系统特性,辨识关键影响因素及其影响规律,通过系统建模与仿真分析开展交叉输送系统关键影响因素研究.推导了交叉输送系统关键组件数学模型,基于AMESim软件构建了系统仿真模型.研究表明,贮箱气枕压差和输送管路流阻是两大关键影响因素.为保证推进剂按额定流量交叉输送,必须对各子级箱压进行精确调节.由于助推上游...     

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。