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碎片云演化分析新进展: 完全基于概率表征方法

舒鹏 杨震 罗亚中

舒鹏, 杨震, 罗亚中. 碎片云演化分析新进展: 完全基于概率表征方法. 力学进展, 2021, 51(4): 910-914 doi: 10.6052/1000-0992-21-002
引用本文: 舒鹏, 杨震, 罗亚中. 碎片云演化分析新进展: 完全基于概率表征方法. 力学进展, 2021, 51(4): 910-914 doi: 10.6052/1000-0992-21-002
Shu P, Yang Z, Luo Y Z. Progress in the analysis of debris cloud evolution: Fully based on probabilistic methods. Advances in Mechanics, 2021, 51(4): 910-914 doi: 10.6052/1000-0992-21-002
Citation: Shu P, Yang Z, Luo Y Z. Progress in the analysis of debris cloud evolution: Fully based on probabilistic methods. Advances in Mechanics, 2021, 51(4): 910-914 doi: 10.6052/1000-0992-21-002

碎片云演化分析新进展: 完全基于概率表征方法

doi: 10.6052/1000-0992-21-002
基金项目: 国家自然科学基金资助项目 (11972044)
详细信息
    作者简介:

    罗亚中, 国防科技大学空天科学学院教授, 博士生导师. 主要从事航天动力学与控制研究. 被表彰为中国载人航天工程突出贡献者, 获教育部青年科学奖、省自然科学一等奖2项

    通讯作者:

    luoyz@nudt.edu.cn

  • 中图分类号: V41

Progress in the analysis of debris cloud evolution: Fully based on probabilistic methods

More Information
  • 摘要: 从碎片云的不确定性特征出发, 可以构建完全基于概率表征的碎片云演化分析方法. 用于对解体、演化和碰撞过程进行解析分析, 避免了数值方法计算效率低和结果鲁棒性差的问题.

     

  • 图  1  (a)分别通过采样法(颜色图)和解析法(等高线)得到的解体碎片半长轴与偏心率分布; (b)不同采样数量得到的概率密度(实线)与解析法(虚线)比较, 采样方法需要大量样本才能捕获小概率事件; (c)解体碎片云对空间目标的年碰撞率变化; (d) (e) (f) 碎片云在选定位置的速度分布 (Frey & Colombo 2021)

    Baidu
  • [1] Frey S, Colombo C. 2021. Transformation of satellite breakup distribution for probabilistic orbital collision hazard analysis. Journal of Guidance, Control, and Dynamics, 44: 88-105. doi: 10.2514/1.G004939
    [2] Heard W B. 1976. Dispersion of ensembles of non-interacting particles. Astrophysics and Space Science, 43: 63-82. doi: 10.1007/BF00640556
    [3] Jones B A, Doostan A, Born G H. 2013. Nonlinear propagation of orbit uncertainty using non-intrusive polynomial chaos. Journal of Guidance, Control, and Dynamics, 36: 430-444. doi: 10.2514/1.57599
    [4] Letizia F. 2018. Extension of the density approach for debris cloud propagation. Journal of Guidance, Control, and Dynamics, 41: 2651-2657. doi: 10.2514/1.G003675
    [5] Letizia F, Colombo C, Lewis H G. 2015. Analytical model for the propagation of small-debris-object clouds after fragmentations. Journal of Guidance, Control, and Dynamics, 38: 1478-1491. doi: 10.2514/1.G000695
    [6] Letizia F, Colombo C, Lewis H G. 2016. Collision probability due to space debris clouds through a continuum approach. Journal of Guidance, Control, and Dynamics, 39: 2240-2249. doi: 10.2514/1.G001382
    [7] Liou J-C. 2008. A statistical analysis of the future debris environment. Acta Astronautica, 62: 264-271. doi: 10.1016/j.actaastro.2006.12.030
    [8] Liou J-C, Hall D T, Krisko P H, et al. 2004. LEGEND – a three-dimensional LEO-to-GEO debris evolutionary model. Advances in Space Research, 34: 981-986. doi: 10.1016/j.asr.2003.02.027
    [9] Liou J-C, Johnson N L. 2006. Risks in space from orbiting debris. Science, 311: 340-341. doi: 10.1126/science.1121337
    [10] Luo Y, Yang Z. 2017. A review of uncertainty propagation in orbital mechanics. Progress in Aerospace Sciences, 89: 23-39. doi: 10.1016/j.paerosci.2016.12.002
    [11] Mcinnes C R. 1993. An analytical model for the catastrophic production of orbital debris. ESA Journal, 17: 293-305.
    [12] Walker R, Martin C E, Stokes P H, et al. 2001. Analysis of the effectiveness of space debris mitigation measures using the delta model. Advances in Space Research, 28: 1437-1445. doi: 10.1016/S0273-1177(01)00445-8
    [13] Wittig A, Di Lizia P, Armellin R, et al. 2015. Propagation of large uncertainty sets in orbital dynamics by automatic domain splitting. Celestial Mechanics and Dynamical Astronomy, 122: 239-261. doi: 10.1007/s10569-015-9618-3
    [14] Yang Z, Luo Y-Z, Zhang J, et al. 2016. Uncertainty quantification for short rendezvous missions using a nonlinear covariance propagation method. Journal of Guidance Control and Dynamics, 39: 2170-2178. doi: 10.2514/1.G001712
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出版历程
  • 收稿日期:  2021-01-15
  • 录用日期:  2021-06-15
  • 网络出版日期:  2021-06-30
  • 刊出日期:  2021-11-26

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