Optimization of entry-vehicle shapes during conceptual design

During the conceptual design of a re-entry vehicle, the vehicle shape and geometry can be varied and its impact on performance can be evaluated. In this study, the shape optimization of two classes of vehicles has been studied: a capsule and a winged vehicle. Their aerodynamic characteristics were analyzed using local-inclination methods, automatically selected per vehicle segment. Entry trajectories down to Mach 3 were calculated assuming trimmed conditions. For the winged vehicle, which has both a body flap and elevons, a guidance algorithm to track a reference heat-rate was used. Multi-objective particle swarm optimization was used to optimize the shape using objectives related to mass, volume and range. The optimizations show a large variation in vehicle performance over the explored parameter space. Areas of very strong non-linearity are observed in the direct neighborhood of the two-dimensional Pareto fronts. This indicates the need for robust exploration of the influence of vehicle shapes on system performance during engineering trade-offs, which are performed during conceptual design. A number of important aspects of the influence of vehicle behavior on the Pareto fronts are observed and discussed. There is a nearly complete convergence to narrow-wing solutions for the winged vehicle. Also, it is found that imposing pitch-stability for the winged vehicle at all angles of attack results in vehicle shapes which require upward control surface deflections during the majority of the entry.     

核磁共振法测定四氧化二氮中相当水含量测量不确定度评定

讨论了自行建立的核磁共振法测定四氧化二氮中相当水含量测量不确定度的影响因素,并对各不确定度分量和测量结果的不确定度进行了评定。     

空天机复合循环推进技术新概念研究——液化空气循环在其中的应用

研究了空天机复合循环推进技术中的一个新概念——以液化空气循环为基础的SERJ组合发动机性能。计算了空气液化后分离为液氧和液氮后组合发动机在不同高度、不同飞行马赫数下的性能曲线,并考虑了液化空气量对组合发动机性能的影响。对计算结果的分析表明,液化空气循环虽然使组合发动机推力下降,但能使比冲有较大幅度的上升;液化空气量过大与过小均不利于进一步提高比冲性能,而是存在一个最佳值。     

掩星大气探测系统误差源分析

根据掩星大气探测反演原理,研究了影响系统产品精度的误差源,并对多普勒观测误差、天线相位中心变化误差、多路径误差、卫星质心变化误差、导航卫星钟飘、卫星姿态变化误差和精密定轨速度误差进行分析,根据工程实现可行性提出了系统误差分配建议,为掩星大气探测系统设计提供参考.     

大气重力波与电子密度扰动的耦合

本文从相互耦合的大气流体方程和双流体等离子体方程出发, 导出了赤道F区大气重力波和电子密度扰动的耦合色散关系, 据此对两者的共振相互作用作了进一步的理论分析。结果表明, 大气重力波可以通过共振耦合将部分能量转换给带电粒子, 为赤道扩展F提供初始电子密度扰动;在这过程中, 等离子体不稳定性对共振条件和共振耦合有着重要的影响。     

大气对遥感卫星图像品质的影响分析

影响遥感卫星图像品质的因素很多,其中包括成像条件中的大气辐射.文章根据遥感成像理论分析了大气辐射对遥感卫星图像品质的影响,计算了大气背景及大气对图像层次和图像对比度的影响.最后,结合遥感相机的特点,给出了减少大气影响、提高图像品质的建议.     

Deriving remote sensing reflectance from turbid Case II waters using green-shortwave infrared bands based model

The objectives of this study are to validate the applicability of a shortwave infrared atmospheric correction model (SWIR-based model) in deriving remote sensing reflectance in turbid Case II waters, and to improve that model using a proposed green-shortwave infrared model (GSWIR-based model). In a GSWIR-based model, the aerosol type is determined by a SWIR-based model and the reflectance due to aerosol scattering is calculated using spectral slope technology. In this study, field measurements collected from three independent cruises from two different Case II waters were used to compare models. The results indicate that both SWIR- and GSWIR-based models can be used to derive the remote sensing reflectance at visible wavelengths in turbid Case II waters, but GSWIR-based models are superior to SWIR-based models. Using the GSWIR-based model decreases uncertainty in remote sensing reflectance retrievals in turbid Case II waters by 2.6–12.1%. In addition, GSWIR-based model’s sensitivity to user-supplied parameters was determined using the numerical method, which indicated that the GSWIR-based model is more sensitive to the uncertainty of spectral slope technology than to that of aerosol type retrieval methodology. Due to much lower noise tolerance of GSWIR-based model in the blue and near-infrared regions, the GSWIR-based model performs poorly in determining remote sensing reflectance at these wavelengths, which is consistent with the GSWIR-based model’s accuracy evaluation results.     

Advanced ensemble modeling method for space object state prediction accounting for uncertainty in atmospheric density

For objects in the low Earth orbit region, uncertainty in atmospheric density estimation is an important source of orbit prediction error, which is critical for space traffic management activities such as the satellite conjunction analysis. This paper investigates the evolution of orbit error distribution in the presence of atmospheric density uncertainties, which are modeled using probabilistic machine learning techniques. The recently proposed “HASDM-ML,” “CHAMP-ML,” and “MSIS-UQ” machine learning models for density estimation (Licata and Mehta, 2022b; Licata et al., 2022b) are used in this work. The investigation is convoluted because of the spatial and temporal correlation of the atmospheric density values. We develop several Monte Carlo methods, each capturing a different spatiotemporal density correlation, to study the effects of density uncertainty on orbit uncertainty propagation. However, Monte Carlo analysis is computationally expensive, so a faster method based on the Kalman filtering technique for orbit uncertainty propagation is also explored. It is difficult to translate the uncertainty in atmospheric density to the uncertainty in orbital states under a standard extended Kalman filter or unscented Kalman filter framework. This work uses the so-called “consider covariance sigma point (CCSP)” filter that can account for the density uncertainties during orbit propagation. As a test-bed for validation purposes, a comparison between CCSP and Monte Carlo methods of orbit uncertainty propagation is carried out. Finally, using the HASDM-ML, CHAMP-ML, and MSIS-UQ density models, we propose an ensemble approach for orbit uncertainty quantification for four different space weather conditions.     

Deorbiting spacecraft with passively stabilised attitude using a simplified quasi-rhombic-pyramid sail

This paper studies deorbiting using an analogue to the quasi-rhombic-pyramid concept for planar motion. The focus is on maintaining a stable (meaning oscillatory) attitude close to the direction of the velocity of the spacecraft relative to the atmosphere. The study consists of a massive computation of deorbit times chosen in a region of the phase space where atmospheric drag plays a leading role. Here, no damping effects are considered. Thus, any passive stabilisation observed is either due to solar radiation pressure or atmospheric drag. The results show that such stable deorbiting is feasible up to a threshold that depends upon the physical parameters of the sail. This threshold is around 500 km of altitude. Stable deorbiting is also shown to reduce the unpredictability that appears due to tumbling.