木星辐射环境不确定性对总剂量风险的影响
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摘要
以木星探测任务为背景,针对木星辐射带粒子能量高、通量大的强辐射特点,基于器件总剂量辐照试验数据、木星辐射带模型、太阳质子通量模型,将器件失效点剂量不确定性与辐射环境不确定性应用到总剂量设计中,可定量评估特定任务一定屏蔽下的器件失效概率、辐射设计余量(RDM)的置信度及影响因素,可实现木星任务中器件指标、屏蔽厚度和失效概率之间的权衡和优化。首先,根据商业器件TL084辐照试验数据,发现其失效概率分布符合威布尔分布。对于10个木星半径的赤道面轨道,辐射带质子通量比太阳质子大3个数量级,随着屏蔽厚度的增加和任务期的减小,TL084器件所受剂量和失效概率减小。当屏蔽厚度为10 mm铝时,器件平均寿命小于2星期。另外,定义并考察了器件的失效速率,失效速率随屏蔽厚度的减小和在轨时间的增加而增加。对于传统的RDM为2的设计方法,1 mm铝屏蔽下对应的置信度为89%。
In a Jupiter exploration mission,the Jovian radiation belt has a strong radiation characteristic with high energy and large flux. Based on the data from the radiation test on device,the Jovian radiation belt model and solar proton model,we introduce a method to evaluate the failure possibility and the confidence level of the RDM( radiation design margin) caused by the total ionizing dose after shielding layers,which includes the radiation environment variability in the Jovian mission. Using this method,we can approach a balance among the device ability,shielding thickness,and failure probability. We find that the Weibull distribution fits the failure possibility of the TL084 experimental data well. For a mission in an equatorial orbit with an altitude of 10 radii of Jupiter,the proton flux of the radiation belt is 3 orders of magnitude larger than solar proton. When the shielding thickness increases and the duration of mission decreases,the failure probability of the TL084 caused by the total dose decreases. The mean lifetime of the TL084 is shorter than 2 weeks after a 10 mm aluminum shielding. In addition,we calculate the failure rate of the TL084. When the shielding layer is thinned and the orbiting period increases,the device fails faster. When the RDM is set as 2,the confidence level after1 mm aluminum shielding is about 89%.
In a Jupiter exploration mission,the Jovian radiation belt has a strong radiation characteristic with high energy and large flux. Based on the data from the radiation test on device,the Jovian radiation belt model and solar proton model,we introduce a method to evaluate the failure possibility and the confidence level of the RDM( radiation design margin) caused by the total ionizing dose after shielding layers,which includes the radiation environment variability in the Jovian mission. Using this method,we can approach a balance among the device ability,shielding thickness,and failure probability. We find that the Weibull distribution fits the failure possibility of the TL084 experimental data well. For a mission in an equatorial orbit with an altitude of 10 radii of Jupiter,the proton flux of the radiation belt is 3 orders of magnitude larger than solar proton. When the shielding thickness increases and the duration of mission decreases,the failure probability of the TL084 caused by the total dose decreases. The mean lifetime of the TL084 is shorter than 2 weeks after a 10 mm aluminum shielding. In addition,we calculate the failure rate of the TL084. When the shielding layer is thinned and the orbiting period increases,the device fails faster. When the RDM is set as 2,the confidence level after1 mm aluminum shielding is about 89%.
引文
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[24]李婷婷,师立勤,刘四清.太阳质子通量模型研究[J].空间科学学报,2010,30(3):205-210.[Li Ting-ting,Shi Li-qin,Liu Siq-ing. Research on the solar proton fluence model[J].Chin. J. Space Sci.,2010,30(3):205-210.]
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[2] Fieseler P D,Ardalan S M,Frederickson A R. The radiation effects on Galileo spacecraft systems at Jupiter[J]. IEEE Trans.Nucl. Sci.,2002,49(6):2739-2758.
[3] Bolton,S,Levin S,Bagenal F. Juno’s first glimpse of Jupiter’s complexity[J]. Geophys. Res. Lett.,2017,44:7663-7667,doi:10. 1002/2017GL074118.
[4] Grasset O,Dougherty M K,Coustenis A. JUpiter ICy moons Explorer(JUICE):An ESA mission to orbit Ganymede and to characterise the Jupiter system[J]. Planetary and Space Science,2013,78:1-21,doi:10. 1016/j. pss. 2012. 12. 002.
[5]任远,崔平远,栾恩杰.基于退火遗传算法的小推力轨道优化问题研究[J].宇航学报,2007,28(1):162-166.[Ren Yuan, Cui Ping-yuan, Luan En-jie. Low-thrust trajectory optimization based on annealing-genetic algorithm[J]. Journal of Astronautics,2007,28(1):162-166.]
[6]潘迅,泮斌峰,唐硕.求解中途飞越燃料最优转移轨道的同伦方法[J].宇航学报,2017,38(4):393-400.[Pan Xun,Pan Bing-feng,Tang Shuo. Homotopy method for fuel-optimal trajectory design in flyby mission[J]. Journal of Astronautics,2017,38(4):393-400.]
[7] Kayali S,Mcalpine W,Becker H,et al. Juno radiation design and implementation[C]. IEEE Aerospace Conference,Big Sky,MT,USA,Mar 3-9,2012.
[8] Sorla-Santacruz M,Garrett H B,Evans R W,et al. The GIRE2model and its application to the Europa mission[C]. IEEE Aerospace Conference,Big Sky,MT,USA,Mar 2-9,2016.
[9]王建昭,田岱,张庆祥,等.木星环绕探测任务中的内带电风险评估[J].深空探测学报,2017,4(6):564-570.[Wang Jian-zhao,Tian Dai,Zhang Qing-xiang,et al. Internal charging evaluation in Jupiter exploration mission[J]. Journal of Deep Space Exploration,2017,4(6):564-570.]
[10] Poivey C,Radiation hardness assurance for space systems[C],IEEE Nuclear and Space Radiation Effects Conference,Phoenix,AZ,USA,July 15-19,2002.
[11] Ladbury R, Gorelick J L, Mc Clure S S. Statistical model selection for TID hardness assurance[J]. IEEE Trans. Nucl.Sci.,2009,56(6):3354-3360.
[12] Ladbury R,Gorelick J L. Statistical methods for large flight lots and ultra-high reliability applications[J]. IEEE Trans. Nucl.Sci.,2005,52(6):2630-2637.
[13] Xapsos M A,Stauffer C,Phan A,et al. Inclusion of radiation environment variability in total dose hardness assurance methodology[J]. IEEE Trans. Nucl. Sci.,2017,64(1):325-331.
[14] Jun I,Garrett H B,Swimm R,et al. Statistics of the variations of high-energy electron population between 7 and 28 jovian radii as measured by the Galileo spacecraft[J]. Icarus,2005,178:386-394.
[15]贾志宏,向宏文,蔡震波,等.商用ADSP-21060L总剂量辐照试验与分析[J].宇航学报,2007,28(3),249-253.[Jia Zhi-hong,Xiang Hong-wen, Cai Zhen-bo, et al. Test and analysis for total ionizing dose of COTS ADSP-21060L[J].Journal of Astronautics,2007,28(3),249-253.]
[16] QJ 10004—2008,宇航用半导体器件总剂量辐照试验方法[S].
[17] Garrett H B,Levin S M,Bolton S J et al. A revised model of Jupiter’s inner electron belts:Updating the Divine radiation model[J]. Geophys. Res. Lett., 2005, 32, article no.L04104. DOI:10. 1029/2004GL021986.
[18] Sorla-Santacruz M,Garrett H B,Evans R W et al. An empirical model of the high-energy electron environment at Jupiter[J]. J.Geophys. Res:Space Phy.,2016,121:9732-9743.
[19] Sicard-Piet A,Bourdarie S,Krupp N,JOSE:a new Jovian specification environment model[J]. IEEE Trans. Nucl. Sci.,2011,58(3):923-931.
[20] SPENVIS.[Online]. Available:https://www. spenvis. oma.be/intro. php
[21] King J H. Solar protonfluences for 1977-1983 space missions[J]. J. Spacec. Roc.,1974,11(6):401-409.
[22] Feynman J,Spitale G,Wang J. Interplanetary proton fluence model:JPL 1991[J]. J. Geophys. Res.,1993,98:13281-13295.
[23] Xapsos M A,Barth J L,Stassinopoulos E G,et al. Probability model for cumulative solar proton event fluences[J]. IEEE Trans. Nucl. Sci.,1999,47(3):22-26.
[24]李婷婷,师立勤,刘四清.太阳质子通量模型研究[J].空间科学学报,2010,30(3):205-210.[Li Ting-ting,Shi Li-qin,Liu Siq-ing. Research on the solar proton fluence model[J].Chin. J. Space Sci.,2010,30(3):205-210.]
[25] Seltzer S M. Updated calculations for routine-shielding radiation dose estimates:SHIELDOSE-2[R]. Nat. Inst. Standards Technol.,Gaithersburg,MD,USA,Dec. 1994.
[26] Guenther C F. A method to quantitatively justify and relate shielding requirements and design margins to hardware requirements[C]. IEEE 9th Digital Avionics Systems Conference,Virginia,USA,Oct. 15-18,1990.