Statistical properties of fatigue damage of Gaussian random loadings

Firstly, the fatigue damages associated with the random loadings were always deemed as high-cycle or very-high-cycle fatigue problems, and based on Chebyshev theorem, the number of rainflow cycles in a given time interval could be recognized as a constant by neglecting its randomness. Secondly, the randomness of fatigue damage induced by the distribution of rainflow cycles was analyzed. According to central limit theorem, the fatigue damage could be assumed to follow Gaussian distribution, and the statistical parameters: mean and variance, were derived from Dirlik's solution. Finally, the proposed method was used to a simulate Gaussian random loading and the measured random loading from an aircraft. Comparisons with observed results were carried out extensively. In the first example, the relative errors of the proposed method are 2.29%, 3.52% and 1.16% for the mean, standard deviation and variation coefficient of fatigue damage, respectively. In the second example, these relative errors are 11.70%, 173.32% and 18.20%, and the larger errors are attributable to non-stationary state of the measured loading to some extent.      

Storm-time atmospheric density modeling using neural networks and its application in orbit propagation

Upper atmospheric densities during geomagnetic storms are usually poorly estimated due to a lack of clear understanding of coupling mechanisms between the thermosphere and magnetosphere. Consequently, the orbit determination and propagation for low-Earth-orbit objects during geomagnetic storms have large uncertainties. Artificial neural networks are often used to identify nonlinear systems in the absence of rigorous theory. In the present study, an attempt has been made to model the storm-time atmospheric density using neural networks. Considering the debate over the representative of geomagnetic storm effect, i.e. the geomagnetic indices ap and Dst, three neural network models (NNM) are developed with ap, Dst and a combination of ap and Dst respectively. The density data used for training the NNMs are derived from the measurements of the satellites CHAMP and GRACE. The NNMs are evaluated by looking at: (a) the mean residuals and the standard deviations with respect to the density data that are not used in training process, and (b) the accuracy of reconstructing the orbits of selected objects during storms employing each model. This empirical modeling technique and the comparisons with the models NRLMSIS-00 and Jacchia-Bowman 2008 reveal (1) the capability of neural networks to model the relationship between solar and geomagnetic activities, and density variations; and (2) the merits and demerits of ap and Dst when it comes to characterizing density variations during storms.     

基于学科链的卫星系统工程方法与实践

目前,绝大多数的卫星系统都是按照分系统来设计的,这种方法的弊端在于分系统内部重复的功能模块对整星而言是冗余的。因此,为了摒除按照分系统设计的卫星系统缺点以提高系统可靠性,我们设计了一个全新的卫星系统,其基于学科功能链。按照学科功能链,我们将卫星系统划分为控制学科链、结构热学科链、电子学学科链、载荷学科链,显著提高了卫星系统的性能、可靠性和功能密度,同时有效降低了研制成本,缩短了研制周期。最终,基于学科链的卫星系统已成功应用于北斗导航全球系统的首发卫星上。本文阐述了基于学科链设计的核心思想和四个主要的学科链内涵。     

“仿生学”沟槽减阻仿真分析及机理研究

"仿生学"沟槽结构在航空发动机叶片减阻和燃滑油系统减阻等领域有潜在的应用前景。为获得该结构构型参数和雷诺数对减阻效果的影响规律,通过对鲨鱼及海豚表皮特征进行仿生设计了横向和纵向沟槽,利用数值模拟方法对不同沟槽构型在不同雷诺数下的减阻效果开展了对比研究和机理分析。结果表明:横向和纵向沟槽构型减阻率均随雷诺数增大而减小,并且雷诺数影响占主导地位。对于横向沟槽构型,沟槽间距较大的构型沿程阻力占主导,在相对高雷诺数下减阻效果较好;沟槽数量较多的构型局部阻力占主导,在相对低雷诺数下减阻效果较好;无间距构型在相对低雷诺数下减阻效果最好,减阻率约为4.14%。对于纵向沟槽构型,减阻率比横向沟槽的高约1个百分点,雷诺数对减阻效果影响不大。     

NF-6风洞喷液氮降温系统研制

通过降低试验气体温度来进一步提高NF 6增压连续式跨声速风洞的雷诺数,采用喷液氮降温的方式成功实现了降温运行。结果表明:风洞气流总温达到-20℃,有效提高了试验雷诺数。所叙述的NF 6风洞喷液氮降温系统的设计指标、总体方案、系统组成、系统调试等,为国内连续式降温风洞的建设积累了经验。      

求根传播算子方法及其在ARM抗诱偏中的应用

反辐射导弹（ARM）抗有源诱偏问题中,多源信号在空、频域的强相关性往往造成导引头对信源数目欠估计,从而导致传统超分辨算法的测向性能下降。针对这一问题,提出了一种求根的传播算子方法,该算法首先在信源数过估计情况下计算信号到达角,然后利用每个角度对应的信号功率来剔除虚假角度。求根传播算子方法不需要预先估计信号源数目,而且在信号高度相关的情况下具备很好的角度分辨性能,因此适用于解决ARM抗诱偏问题。仿真实验结果表明,求根传播算子方法在提高ARM抗诱偏能力方面的表现优于MUSIC算法。     

基于MHD模拟数据的正午午夜子午面磁层顶位形研究

通过分析太阳风-磁层-电离层系统的三维全球磁流体力学(MHD)模型的计算数据, 给出了正午-午夜子午面磁层顶位形的定量模型. 分析表明, 正午-午夜子午面磁层顶位形可以用文献[3]提出的基于卫星观测数据的、描述赤道面磁层顶位形的函数来描述. 与赤道面磁层顶不同, 正午-午夜子午面磁层顶位形更为复杂. 在忽略极尖区(cusp)的简化条件下, 磁层顶位形仍需利用两条曲线来拟合. 太阳风动压Dp与行星际磁场分量Bz是控制磁层顶位形的主要因素. 行星际磁场为北向时, 磁场增强, 日下点距离r0增大; 行星际磁场为南向时, 磁场增强, 磁层顶日下点距离r0减小. 整体而言, 行星际磁场分量Bz由南转北时, r0增大, 且Bz对r0的影响减弱. 太阳风动压Dp是控制磁层顶日下点的主要因素, Dp增大, r0减小. 磁层顶位形的另一个参数磁层顶磁尾张角α, 随着行星际磁场南向分量增强而增大, 即磁层顶张开程度更加显著, 更多的磁通量由向阳侧传输到夜侧; Dp增大, α略增大, 这意味着Dp对磁通量由日侧向夜侧的传输也有一定的贡献.      

高可靠小条件数压缩感知叶尖定时信号辨识

为增强基于任意角度压缩感知(CS)叶尖定时信号(BTT)重构的稳定性,采用小生境微种群遗传算法提出了基于小条件数的高稳定性传感器安装布置方法。研究发现:任意角度CS的恢复矩阵条件数越小,不同信噪比下同步和非同步振动信号重构误差越趋于稳定在较低范围,优化后发现条件数为1的排布方案下,相邻传感器角度间隔趋向于均布2m取K的形式。利用条件数为1的矩阵冗余特性,设计了高可靠性的传感器排布方案,数值试验和有限元仿真验证表明叶尖定时系统在失效一个传感器的情况下仍可稳定得到准确的重构结果。在信噪比为5 dB时,冗余排布相比参考排布的主倍频幅值重构误差降低4.4%以上,验证了采用最小条件数排布的任意角度CS信号辨识方法在噪声及传感器失效情况下仍可保证BTT测量结果的有效性和可靠性。      

坡面浅层明流流态界定方法之商榷

为了探求坡面薄层水流流态界定方法,从流体力学与泥沙运动学观点出发,对4种不同粗糙尺度床面(光滑玻璃、人工加糙粒径分别为0.075、0.245和0.380mm)、5种不同坡度下坡面薄层水流放水进行试验研究,并对薄层水流阻力规律与明渠水流阻力规律进行了比较分析.在此基础上提出了粘性底层厚度与水深之比作为新的无量纲临界判数,结果表明该判数能更好地反映坡面薄层水流流动型态.