小涵道比涡扇发动机动态特性数值计算

研究了涡扇发动机动态数学模型以及数值模拟方法,对于进口条件变化、发动机加速、发动机减速、发动机加力等情况下动态工作过程,改进的发动机动态性能数值模拟程序具备了数值仿真的能力,并对小涵道比涡扇发动机动态特性进行了数值计算分析,结果表明:对于飞行条件快速变化的情况,当发动机推力增大到一定程度后,会有逐渐减小的趋势,而缓慢变化时,就没有这种振荡现象;对于燃油质量流量增大、减小情况,变化的快慢对应耗油率的峰值是不同的;同样,随着加力温升的变化速度不同,发动机推力和耗油率达到的峰值也不同.      

吸气式脉冲爆震发动机反压传播规律研究

以汽油为燃料,空气为氧化剂,在内径为60mm的吸气式脉冲爆震发动机上进行了反压传播规律实验研究.测量了10 ～30Hz频率范围内进气道内的反传压力.实验结果表明,进气道内的反压峰值随着工作频率的增加而增加,两者基本呈线性关系.随着工作频率的增加,压力波动的时间占每个工作循环时间的比例增加.压力脉动比在20Hz时达到最大.建立了数值模型,采用小能量点火及温度梯度自适应方法,计算得到了反压的形成及传播特性.计算结果印证了反压是由于回传爆震引起的.将计算结果与实验结果进行了比较,结果表明两者符合地较好.     

三维疲劳裂纹扩展仿真的双重边界元法

运用双重边界元方法求解三维疲劳裂纹前沿的应力应变场,基于Forman理论、最小应变能密度法和Elber模型,采用增量步裂纹扩展分析方法,并根据裂纹几何形状的改变,对裂纹面进行网格重划分和迭代计算,模拟了三维裂纹的扩展和预测裂纹扩展寿命.获得了裂纹前沿各点的扩展长度、扩展方向和应力强度因子等特征量.扭力轴表面裂纹扩展的应用实例表明该方法正确合理.     

基于三维原子磁强计的核磁共振陀螺仪实验优化

核磁共振陀螺仪内嵌三维原子磁强计是实现核磁共振陀螺仪小型化的一种有效途径,故介绍了一种基于三维原子磁强计的核磁共振陀螺仪.对影响三维原子磁强计性能的重要参数进行了优化,得到了较优的x轴、yy轴和z轴磁强计信号标度因子,进而实现了更灵敏的三维原子磁强计.在三维磁场闭环锁定6000 s后,测得核磁共振陀螺仪的角度随机游走和...     

梯度硅铝管壳回流焊接快速冷却热力仿真研究

针对某航天电子管壳焊接组件冷却过程中的热力耦合影响问题,建立了焊接组件的有限元热分析模型,研究了在快速冷却过程中梯度材料分布对低温共烧陶瓷(low temperature co-fired ceramic, LTCC)基板、梯度管壳的残余应力和变形的影响。以不超过基板断裂强度为前提条件,以降低管壳整体的残余应力与变形为优化目标,采用了多因素变换优选法,确定了管壳材料的最优梯度分布方案,即合金管壳自上而下的梯度分布为Al-35Si、Al-42Si、Al-50Si、Al-60Si、Al-70Si。其中,Al-35Si厚度为2.5mm, Al-42Si与Al-60Si的厚度均为1.6mm, Al-50Si厚度为0.8mm, Al-70Si厚度为2mm。在该方案下,LTCC基板冷却至室温时的最大变形量为4.86μm,最大第一主应力为6.761MPa,远小于LTCC材料的断裂强度320MPa;管壳冷却至室温时的最大变形量为18.291μm,最大残余应力值为20.46MPa,远小于管壳材料的屈服强度100MPa。管壳各层之间的应力集中现象不明显,管壳的整体焊接质量得到提升。     

基于Kinect三维重建的地下井室可视化方法研究

针对现有地下井室病害探测与维护方法的不足,提出了一种基于Kinect三维重建的地下井室可视化方法,以实现其三维可视化探测与维护.还提出了一种基于多项式曲面拟合的Kinect深度测量误差修正方法,利用联合双边滤波算法对深度图像数据进行预处理;结合SIFT特征匹配和改进的RANSAC算法获取相邻点云间的初始位姿,并利用基于...     

Satellite lithium-ion battery remaining useful life estimation with an iterative updated RVM fused with the KF algorithm

Lithium-ion batteries have become the third-generation space batteries and are widely utilized in a series of spacecraft. Remaining Useful Life (RUL) estimation is essential to a spacecraft as the battery is a critical part and determines the lifetime and reliability. The Relevance Vector Machine (RVM) is a data-driven algorithm used to estimate a battery’s RUL due to its sparse feature and uncertainty management capability. Especially, some of the regressive cases indicate that the RVM can obtain a better short-term prediction performance rather than long-term prediction. As a nonlinear kernel learning algorithm, the coefficient matrix and relevance vectors are fixed once the RVM training is conducted. Moreover, the RVM can be simply influenced by the noise with the training data. Thus, this work proposes an iterative updated approach to improve the long-term prediction performance for a battery’s RUL prediction. Firstly, when a new estimator is output by the RVM, the Kalman filter is applied to optimize this estimator with a physical degradation model. Then, this optimized estimator is added into the training set as an on-line sample, the RVM model is re-trained, and the coefficient matrix and relevance vectors can be dynamically adjusted to make next iterative prediction. Experimental results with a commercial battery test data set and a satellite battery data set both indicate that the proposed method can achieve a better performance for RUL estimation.     

面向空间应用的双核容错微处理器的研究与实现

介绍了用双核微处理器实现的容错微处理器系统SPARC—V8FIS。该系统由两个同构微处理器与支持容错操作的容错管理模块组成。微处理器是基于SPRARCV8规范的32-bit微处理器。容错管理模块提供了错误检测、诊断、从“软故障”中故障恢复，以及当发生“硬故障”时，将系统配置成单一处理器继续执行的机制，以适应空间复杂环境应用。SPARC—V8FIS用较少的硬件实现了所有容错操作，以很低的性能损失达到了很高的系统可靠性。     

磁流变机床误差分析和加工工艺优化

首先通过实验分析不同工艺参数下对去除函数稳定性的影响,并进行了仿真分析,确定了机床的敏感方向;其次,对磁流变机床运动轴误差进行了测量,分析这些误差引起法线方向误差的大小;最后,实验验证采用较大的压深和补偿法线方向误差可以有效提高机床的加工精度.     

Design and simulation of an innovative cylinder fabricated by selective laser melting

Additive Manufacturing (AM) processing has attracted wide attention due to its advantages, e.g., rapid prototyping and free design. In aeronautic and astronautic engineering, it is especially attractive to apply AM processing, especially Selective Laser Melting (SLM), into primary structures that always occupy most of the whole mass of aircraft or spacecraft. In this paper, an innovative lattice sandwich structure that is suitable to be manufactured with SLM is adopted to design the typical cylinder under axial compression. Firstly, the mechanical properties of pyramidal lattice are investigated, and the bearing capacity of the lattice sandwich cylinder is given analytically for each failure mode. Secondly, a composite cylinder is re-designed in the form of lattice sandwich structure, which sizes are ultimately obtained through optimization. Finally, finite element model of the innovative cylinder is established and several kinds of imperfection are introduced to simulate the defects caused by SLM. Numerical result shows that the lattice sandwich design can obviously enhance the bearing capacity of cylindrical shell even though the original one is designed with composite material. In other words, SLM has great potential in improving the primary structure of spacecraft in the future.