HTPB复合固体推进剂率相关损伤机理分析与验证

固体发动机在点火过程中常由于结构完整性问题而出现爆炸或性能曲线异常等问题，结合发动机在点火状态下推进剂的受载情况，亟待探索固体推进剂的率相关损伤机理。本研究从某HTPB复合固体推进剂在宽温和宽应变率下单向定速拉伸试验的力学响应特征入手，针对应力-应变曲线呈现的“双峰”、“脱湿”点前后移位等现象阐释了推进剂的率相关界面损伤特性。然后，基于建立的推进剂细观有限元模型对推进剂的率相关损伤过程进行了仿真计算，通过提取有限元分析结果的损伤界面分析了推进剂的界面损伤机理。最后，通过高速摄像试验的结果对损伤机理进行了验证。结果表明，推进剂的界面损伤过程具有很强的率相关性，“双峰”和“脱湿”点前后移位均与推进剂在不同应变率下拉伸时内部的损伤演化过程有关。通过对比推进剂在不同应变率下拉伸时断裂前的形貌，高应变率下AP颗粒析出数量较多，在一定程度上印证了本研究对推进剂损伤机理的阐释。     

The adaptive Gaussian mixtures unscented Kalman filter for attitude determination using light curves

The Adaptive Gaussian Mixtures Unscented Kalman Filter (AGMUKF) is introduced to estimate the attitude of a Resident Space Object using light curves. This filter models the state probability density function as a Gaussian Mixture. This enables to capture the non-linearities of the light-curve measurement model. A non-linearity index is used to refine the mixture when necessary, and individual Gaussian kernels are merged back together when their relative distance is below a certain threshold. A conventional attitude Unscented Kalman Filter (UKF) is used to propagate and update each kernel. The AGMUKF efficiently maintains the mixture population as low as possible, while still being able to represent non-symmetric, multimodal, arbitrarily complex distributions. Therefore, it is presented as a promising alternative to Particle-Filter-based implementations, the current state of the art used in sequential attitude estimation from light curves. The non-linearity index has been used to show that the measurement model is the main contributor to the system non-linearity. Results have demonstrated the superiority of the AGMUKF w.r.t. the UKF for attitude determination, and that it can converge for high initial state uncertainty cases, successfully capturing the non-Gaussian probability distribution of the state.