带电粒子云的演变过程

根据带电粒子云从破碎点开始向空间扩散过程中粒子云密度和形状的变化规律,以几何形状和起主要作用的因素为特征,定义了球形、椭球形、绳形、螺旋线形、全方位弥漫直至球壳形6个演变阶段.论述了在各个阶段的主要特征和对演变过程起主要作用的因素.分析了在各个阶段电磁场对带电粒子的摄动影响,比较了带电粒子云与不带电粒子云在演化过程上的差异.在球形阶段起主要作用的是分离速度,带电碎片之间的排斥力加快了碎片扩散的速度.从椭球形阶段到球壳形阶段,带电粒子和不带电粒子的演化规律基本一致.带电粒子的演化过程加快或减慢取决于粒子带正电或带负电.将电场摄动力等效于改变地球引力的大小,罗列了阶段转换标志点时刻的计算公式.利用计算机仿真的方法,给出了各个阶段不带电碎片云和带电碎片云分布示意图,验证了演变过程阶段划分和电磁场摄动分析的合理性.     

基于解体事件的空间碎片轨道演化算法研究

针对航天器解体事件所生成的空间碎片的演化过程,进行了数学分析,确定了新生成的空间碎片的速度增量,在该增量作用下碎片轨道会发生变更,本文根据该增量得出了空间碎片在轨道变更后的轨道根数,分析了在大气阻力摄动作用下,空间碎片的数目和轨道分布的演化情况,给出了相关结果,结果表明此算法可行.     

一种高效的计算卫星轨道寿命的方法

关于在大气阻力作用下卫星生存寿命的估计 ,提出了一种高效的数值方法 ,称为微分 -积分法。它的实质是以轨道要素的平均变化率为基础的微分方程 ,而方程的右端包含定积分。与传统方法比较验证了此新方法的正确性 ,并且显示了它的极高效率。在诸如空间碎片减缓这种需要非常大量的计算卫星寿命的问题中 ,新方法的价值得到充分体现。     

SGP4/SDP4模型用于空间碎片轨道预测的精度分析

为保证航天任务的顺利完成 ,必须采用一定的模型 ,对可能威胁目标轨道的空间碎片进行跟踪预测。文中首先给出标称轨道的计算模型 ;接着介绍两行轨道根数 (TLE)和考虑了简化常规 /深空扰动的近似解析解模型 (SGP4/SDP4) ,并提供TLE使用的坐标系和惯性系之间的转换 ;然后以典型轨道为例 ,分析SGP4/SDP4与标称轨道的偏差。运算结果表明SGP4/SDP4运算速度快 ,满足一定精度 ,可以用于空间碎片的轨道预测和初步威胁评估。     

Satellite collision probability estimation using polynomial chaos expansions

This paper presents the application of polynomial chaos (PC) to estimating the probability of collision between two spacecraft. Common methods of quantifying this probability for conjunction assessment use either Monte Carlo analyses or include simplifying assumptions to improve tractability. A PC expansion, or PCE, provides a means for approximating the solution to a large set of stochastic ordinary differential equations, which includes orbit propagation. When compared to Monte Carlo methods, non-intrusive, i.e., sampling-based, PCE generation techniques may greatly reduce the number of orbit propagations required to approximate the possibly non-Gaussian, a posteriori probability density function. The presented PC-based method of computing collision probability requires no fundamental simplifying assumptions, and reduces the computation time compared to Monte Carlo. This paper considers two cases where the common conjunction assessment assumptions are no longer valid. The results indeed demonstrate a reduction in computation time when compared to Monte Carlo, and improved accuracy when compared to simplified techniques.     

An adaptive strategy for active debris removal

Many parameters influence the evolution of the near-Earth debris population, including launch, solar, explosion and mitigation activities, as well as other future uncertainties such as advances in space technology or changes in social and economic drivers that effect the utilisation of space activities. These factors lead to uncertainty in the long-term debris population. This uncertainty makes it difficult to identify potential remediation strategies, involving active debris removal (ADR), that will perform effectively in all possible future cases. Strategies that cannot perform effectively, because of this uncertainty, risk either not achieving their intended purpose, or becoming a hindrance to the efforts of spacecraft manufactures and operators to address the challenges posed by space debris.     

Identification of a debris cloud from the nuclear powered SNAPSHOT satellite with haystack radar measurements

Data from the Massachusetts Institute of Technology Lincoln Laboratory Long Range Imaging Radar (known as the Haystack radar) have been used in the past to examine families of objects from individual satellite breakups or families of orbiting objects that can be isolated in altitude and inclination. This is possible because, for some time after a breakup, the debris cloud of particles can remain grouped together in similar orbit planes. This cloud will be visible to the radar, in fixed staring mode, for a short time twice each day, as the orbit plane moves through the field of view. There should be a unique three-dimensional pattern in observation time, range, and range rate which can identify the cloud. Eventually, through slightly differing precession rates of the right ascension of ascending node of the debris cloud, the observation time becomes distributed so that event identification becomes much more difficult.     

On the effect of considering more realistic particle shape and mass parameters in MMOD risk assessments

One of the primary mission risks tracked in the development of all spacecraft is that due to micro-meteoroids and orbital debris (MMOD). Both types of particles, especially those larger than 0.1 mm in diameter, contain sufficient kinetic energy due to their combined mass and velocities to cause serious damage to crew members and spacecraft. The process used to assess MMOD risk consists of three elements: environment, damage prediction, and damage tolerance. Orbital debris risk assessments for the Orion vehicle, as well as the Shuttle, Space Station and other satellites use ballistic limit equations (BLEs) that have been developed using high speed impact test data and results from numerical simulations that have used spherical projectiles. However, spheres are not expected to be a common shape for orbital debris; rather, orbital debris fragments might be better represented by other regular or irregular solids. In this paper we examine the general construction of NASA’s current orbital debris (OD) model, explore the potential variations in orbital debris mass and shape that are possible when using particle characteristic length to define particle size (instead of assuming spherical particles), and, considering specifically the Orion vehicle, perform an orbital debris risk sensitivity study taking into account variations in particle mass and shape as noted above. While the results of the work performed for this study are preliminary, they do show that continuing to use aluminum spheres in spacecraft risk assessments could result in an over-design of its MMOD protection systems. In such a case, the spacecraft could be heavier than needed, could cost more than needed, and could cost more to put into orbit than needed. The results obtained in this study also show the need to incorporate effects of mass and shape in mission risk assessment prior to first flight of any spacecraft as well as the need to continue to develop/refine BLEs so that they more accurately reflect the shape and material density variations inherent to the actual debris environment.     

Impact effects from small size meteoroids and space debris

When the impact risk from meteoroids and orbital debris is assessed the main concern is usually structural damage. With their high impact velocities of typically 10–20 km/s millimeter or centimeter sized objects can puncture pressure vessels and other walls or lead to destruction of complete subsystems or even whole spacecraft. Fortunately chances of collisions with such larger objects are small (at least at present). However, particles in the size range 1–100 μm are far more abundant than larger objects and every orbiting spacecraft will encounter them with certainty. Every solar cell (8 cm² area) of the Hubble Space Telescope encountered on average 12 impacts during its 8.25 years of space exposure. Most were from micron sized particles.     

航天器微流星体及空间碎片环境与风险分析

微流星体及空间碎片的高速撞击威胁着长寿命、大尺寸航天器的安全运行 ,导致其严重的损伤和灾难性的失效。文章对低地球轨道微流星体及空间碎片环境进行了分析 ,给出了微流星体及空间碎片对航天器威胁方向的确定方法 ,得到了空间碎片撞击航天器相对撞击角的概率分布以及地球对微流星体遮挡的影响。编制了风险分析软件 ,以采用单防护屏防护结构的柱状低地球轨道航天器为例进行风险分析。     

Faster algorithm of debris cloud orbital character from spacecraft collision breakup

Space debris is polluting the space environment. Collision fragment is its important source. NASA standard breakup model, including size distributions, area-to-mass distributions, and delta velocity distributions, is a statistic experimental model used widely. The general algorithm based on the model is introduced. But this algorithm is difficult when debris quantity is more than hundreds or thousands. So a new faster algorithm for calculating debris cloud orbital lifetime and character from spacecraft collision breakup is presented first. For validating the faster algorithm, USA 193 satellite breakup event is simulated and compared with general algorithm. Contrast result indicates that calculation speed and efficiency of faster algorithm is very good. When debris size is in 0.01–0.05 m, the faster algorithm is almost a hundred times faster than general algorithm. And at the same time, its calculation precision is held well. The difference between corresponding orbital debris ratios from two algorithms is less than 1% generally.     

Ariane 5 GTO debris mitigation using natural perturbations

GTO objects can potentially collide with operative satellites in LEO and GEO protected regions. Internationally accepted debris mitigation guidelines require that these objects exit these protected regions within 25?years, e.g. by re-entering and burning up in Earth’s atmosphere. In this paper, an inventory of the GTO debris generated from Ariane 5 launches in the period 2012–2017 is provided, and it is expected that none of these objects will re-enter within 25?years. For future launches, natural perturbations can be exploited to increase compliance with mitigation guidelines without the use of extra propellant or complex de-orbiting systems, which is attractive from an economic point of view. The lifetime of GTO objects is very sensitive to initial conditions and some environmental and body-related parameters, mainly due to the effect of solar gravity on the perigee altitude. As a consequence, the lifetime of a specific GTO object cannot be predicted accurately, but its probability of re-entering in less than 25?years can be estimated with proper accuracy by following a statistical approach. By propagating the orbits of over 800,000 simulated Ariane 5 GTO objects, it was found that the launch time leading to the highest probability of compliance with debris mitigation guidelines for GEO launches from Kourou corresponds to about 2 PM local time, regardless of the date of launch, which leads to compliance rates ranging from 60 to 100%. Current practice is to launch at around 5–9?PM, so a change in procedures would be required in order to reach a higher degree of compliance with debris mitigation guidelines, which was predicted to be on average below 20% for the objects generated in the period 2012–2017.     

An active debris removal parametric study for LEO environment remediation

Recent analyses on the instability of the orbital debris population in the low Earth orbit (LEO) region and the collision between Iridium 33 and Cosmos 2251 have reignited interest in using active debris removal (ADR) to remediate the environment. There are, however, monumental technical, resource, operational, legal, and political challenges in making economically viable ADR a reality. Before a consensus on the need for ADR can be reached, a careful analysis of its effectiveness must be conducted. The goal is to demonstrate the need and feasibility of using ADR to better preserve the future environment and to explore different operational options to maximize the benefit-to-cost ratio. This paper describes a new sensitivity study on using ADR to stabilize the future LEO debris environment. The NASA long-term orbital debris evolutionary model, LEGEND, is used to quantify the effects of several key parameters, including target selection criteria/constraints and the starting epoch of ADR implementation. Additional analyses on potential ADR targets among the existing satellites and the benefits of collision avoidance maneuvers are also included.     

近距离空间交会动力学

首先研究两个飞行器在近距离相对运动的动力学方程,包括简易（线性化）和精确模型;其次推导出一个工程实用在轨道平面内保持点轨迹椭圆方程;最后讨论保持点的动力学特性和轨道摄动对保持点的影响。     

Uncertainty-aware Cube algorithm for medium-term collision risk assessment

The number of Earth orbiting objects is constantly growing, and some orbital regions are becoming risky environments for space assets of interest, which are increasingly threatened by accidental collisions with other objects, especially in Low-Earth Orbit (LEO). Collision risk assessment is performed by various methods, both covariance and non-covariance based. The Cube algorithm is a non-covariance-based method used to estimate the collision rates between space objects, whose concept consists in dividing the space in cubes of fixed dimension and, at each time instant, checking if two or more objects share the same cube. Up to now its application has been limited to the long-term scenarios of orbital debris evolutionary models, where considering the uncertainties is not necessary and impractical. Within operative contexts, instead, medium-term collision risk analysis may be an important task, in which the propagation-related uncertainties play a prominent role, but the timescale poses challenges for the application of standard covariance-based conjunction analysis techniques. In this framework, this paper presents an approach for the evaluation of the medium-term collision frequency for objects in LEO, called Uncertainty-aware Cube method. It is a modified version of the Cube, able to take the possible errors in the space objects’ position into account for the detection of the conjunctions. As an object’s orbit is propagated, the along-track position error grows more and more, and each object could potentially be in a different position with respect to the one determined by numerical propagation and, thus, in a different cube. Considering the uncertainties, at each time instant the algorithm associates more than one cube to each object and checks if they share at least one cube. If so, a conjunction is detected and a degree of confidence is evaluated. The performance of the method is assessed in different LEO scenarios and compared to the original Cube method.     

空间飞行器碎片防护结构的简化设计

给出一种基于实验和理论分析的航天器碎片防护结构简化设计方法 ,该方法可用于进行大型空间飞行器碎片防护结构的方案选择和初步结构设计。利用空间碎片的工程环境模型和防护结构几何经验公式 ,采用“设计碎片”的概念 ,对防护结构进行几何结构设计和质量估算 ,并采用改进的防护性能验证算法进行空间碎片的风险评估。通过对惠式防护结构的计算 ,得到的计算结果基本符合实际要求。     

Spacecraft Design-for-Demise implementation strategy & decision-making methodology for low earth orbit missions

Space missions designed to completely ablate upon an uncontrolled Earth atmosphere reentry are likely to be simpler and cheaper than those designed to execute controlled reentry. This is because mission risk (unavailability) stemming from controlled reentry subsystem failure(s) is essentially eliminated. NASA has not customarily implemented Design-for-Demise meticulously. NASA has rather approached Design-for-Demise in an ad hoc manner that fails to entrench Design-for-Demise as a mission design driver. Thus, enormous demisability challenges at later formulation stages of missions aspired to be demisable are evident due to these perpetuated oversights in entrenching Design-for-Demise practices. The investigators hence propose a strategy for a consistent integration of Design-for-Demise practices in all phases of a space mission lifecycle. Secondly, an all-inclusive risk-informed, decision-making methodology referred to as Analytic Deliberative Process is proposed. This criterion facilitates in making a choice between an uncontrolled reentry demisable or controlled reentry. The authors finally conceive and synthesize Objectives Hierarchy, Attributes, and Quantitative Performance Measures of the Analytical Deliberative Process for a Design-for-Demise risk-informed decision-making process.