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1.
太阳质子通量模型研究   总被引:1,自引:1,他引:0       下载免费PDF全文
太阳质子事件对航天活动构成重要威胁, 预测一定时期内太阳质子通量对航天器抗辐射加固设计有重要的指导意义. 在第20至23太阳活动周的太阳质子事件数据统计分析的基础上, 建立了一个针对 E>10 MeV和 E>30 MeV太阳质子通量的新模型. 新模型与目前航天工程中常用的JPL模型相比较, 引入了太阳活动性对质子事件发生概率的影响因素, 能够评估不同太阳活动水平下的质子通量, 其结果更符合质子事件的分布特征.   相似文献   

2.
太阳质子事件中短期预报模型研究   总被引:2,自引:0,他引:2       下载免费PDF全文
太阳质子事件通量的预测对航天器抗辐射加固设计和航天员出舱活动具有非常重要的意义.针对一年以下的航天任务,利用经验统计方法,确认太阳活跃年和太阳平静年期间,1——365天不同时间段内 > 10MeV,> 30MeV和 > 60MeV的太阳质子事件积分通量符合对数正态分布,且通量对数的标准偏差σ和期望值μ随任务期时间的变化满足对数函数形式.以此为基础,构建太阳质子通量的中短期预报模型.该模型能够针对太阳活跃年和太阳平静年,给出一定置信度下1——365天不同时间内 > 10MeV,> 30MeV和 > 60MeV的质子事件通量分布,从而为执行中短期航天任务提供太阳质子事件通量的预测,以规避不必要的风险.   相似文献   

3.
通过分析几十个典型太阳质子事件表明,具有以下特征的质子事件其后1-3天内一般有强烈地磁扰动发生:1.质子耀班级别和亮度较大(3B以上);2.质子通量在上升阶段增加很快,而在下降阶段相对来说衰减也很快(尤其是在峰值附近);3.电子通量远远大于质子通量并且和质子通量有相似的变化规律.在此基础上,利用神经网络预报太阳质子事件发生后3天内地磁扰动的趋势.  相似文献   

4.
在耀斑伴随日冕物质抛射(CME)事件编目数据的基础上,进行太阳质子事件(SPE)匹配,构建研究数据集.利用Apriori算法挖掘SPE与耀斑级别、耀斑发生日面位置以及CME角宽度和速度的关联关系.结果表明:X级耀斑、全晕CME、高速(>1000km·-1) CME和日面西半球耀斑是最可能伴随质子事件的4种特征,其诱发质子事件概率依次为0.366,0.355,0.30,0.155.角宽度低于120°或速度低于400km·-1的CME产生质子事件的概率为0.高速CME产生质子事件的概率是低速(400~1000km·-1) CME的8.6倍,X级耀斑产生质子事件的概率是M级耀斑的6.2倍,日面西部耀斑产生质子事件的概率是日面东部耀斑概率的3.9倍,全晕CME产生太阳质子事件的概率是非全晕(120°~360°) CME的3.8倍.对太阳质子事件样本进行过采样处理,利用随机森林等5种典型有监督学习算法,构建了基于第23太阳活动周耀斑和CME特征的质子事件预测模型.结果表明,该预报模型的质子事件预测准确率、精确率和召回率均控制在91%以上.   相似文献   

5.
质子事件的爆发与太阳软X射线辐射有着很强的相关性,利用GOES卫星的1~8 (A)波段和0.5~4 (A)波段的软X射线数据,选取一些特征参量验证该相关性并应用到质子事件短期预报中.在当前质子事件传输物理机制不完全明确的情况下,在现有的预报质子事件有无的模型基础上,利用BP神经网络,根据软X射线通量水平等预测事件质子峰值通量水平,再对训练后的网络进行检验,检验预测所得结果与实际探测值误差小于一个量级,具备一定实用意义.   相似文献   

6.
第23至24周太阳质子事件的统计特征   总被引:2,自引:2,他引:0       下载免费PDF全文
第23至24太阳活动周(1997-2016年)期间太阳质子事件的强度统计分析表明,1997-2016年期间总共发生了128个太阳质子事件,其中峰值通量范围为10~99pfu,100~999pfu,1000~2999pfu及>3000pfu的事件分别占55.15%,27.94%,9.56%,7.35%.太阳质子事件的不对称性分析表明,不同强度太阳质子事件东西不对称性的程度不相同,其中1000~2999pfu事件的不对称性最强,而3000pfu以上事件的不对称性最弱.第23周期间,太阳质子事件主要发生在太阳活动周两个峰值之间和最大峰值之后的时段,而第24周太阳质子事件主要发生在太阳活动周最大峰值之前.   相似文献   

7.
质子事件上升时间及峰值强度的统计研究   总被引:1,自引:0,他引:1  
在耀斑已基本确定为质子耀斑的情况下, 为了对即将到达地球的太阳质子作出半定量的粗略预报(警报), 即估计从观测到光学耀斑开始, 需经多长时间质子通量将到达峰值;峰值强度有多大。为此, 我们收集了1967年5月—1972年12月约五年半期间国外发表的比较系统的质子事件资料, 以及相应的太阳耀斑和太阳射电资料。   相似文献   

8.
对第21~24太阳周不同等级的太阳X射线耀斑事件、太阳质子事件、地磁暴事件及高能电子增强事件的爆发频次特征进行统计,结果表明:太阳周耀斑爆发的总数量与该太阳周的黑子数峰值呈正比,耀斑总数、X级耀斑事件数与峰值的相关系数分别为0.974,0.997;太阳质子事件主要发生在峰年前后1~2年,约占总发生次数的80%,峰值通量大于10pfu (1 pfu=1 cm-2·sr-1·s-1)的质子事件中,84%伴有耀斑爆发,并且主要伴随M或X级耀斑,少量伴随C级耀斑,峰值通量大于1000pfu的质子事件中,98%伴随M或X级耀斑,并且以X级耀斑为主;第21,22,23和24太阳周发生地磁暴最频繁的时间分别在1982,1991,2003年和2015年,分别滞后黑子数峰值时间3年、2年、2年和1年;72%的高能电子增强事件发生在太阳周下降期,24%的高能电子增强事件发生在太阳周上升期.   相似文献   

9.
采用GOSE-10卫星4~9 MeV(P2),9~15 MeV(P3),15~40 MeV(P4),40~80 MeV(P5)能段上的质子通量数据,结合质子能谱,对太阳质子事件发生前各能谱参数的变化特征进行分析,详细介绍利用能谱参数的变化特征及能量E>10 MeV的质子通量数据对太阳质子事件进行预报的新方法,并运用这种方法对2002-2006年期间太阳质子事件进行了预报.预报结果显示,预报提前量最多达到100 h以上,对质子事件的报准率达97.5%,预报方法具备一定的有效性和实用性.   相似文献   

10.
为了预测民航运行的安全水平,针对评价结果数据序列样本少、不确定性大的特点,选择灰色区间预测方法,建立了民航安全评价的区间预测模型.给出了民航安全指数计算结果,分析了民航运行的安全水平现状,展示了这一安全评价体系的功能和使用方式.通过实例验证了民航安全评价的灰色区间预测模型的正确性,给出了下一年度民航综合安全指数的预测区间.结果表明:灰色区间预测方法是可行的.   相似文献   

11.
Since 1988 high sensitivity dosimeter-radiometer “Liulin” has been installed on board the MIR space station. Device measured absorbed dose rate and flux of penetrating particles. Results of measurements showed that after powerful solar proton events (SPE) September–October, 1989 and March, 1991 additional quasistable radiation belts were formed in the near earth space within the interval L=1.8−3.0. These “new” belts were observed as an additional maximums in flux (and sometimes dose) channels when crossing the SAA region. “New” belts were quasi stable and existed at least several months, decaying slightly after SPE. Dose to flux ratio analysis showed that major components of these belts were energetic electrons and protons arising in connection with preceding SPEs.  相似文献   

12.
The support vector machine (SVM) combined with K-nearest neighbors (KNN), called the SVM-KNN method, is new classing algorithm that take the advantages of the SVM and KNN. This method is applied to the forecasting models for solar flares and proton events. For the solar flare forecasting model, the sunspot area, the sunspot magnetic class, and the McIntosh class of sunspot group and 10 cm solar radio flux are chosen as inputs; for the solar proton event forecasting model, the inputs include the longitude of active regions, the flux of soft X-ray, and those for the solar flare forecasting model. Detailed tests are implemented for both of the proposed forecasting models, in which the SVM-KNN and the SVM methods are compared. The testing results demonstrate that the SVM-KNN method provide a higher forecasting accuracy in contrast to the SVM. It also gives an increased rate of ‘Low’ prediction at the same time. The ‘Low’ prediction means occurrence of solar flares or proton events with predictions of non-occurrence. This method show promise for forecasting models of solar flare and proton events.  相似文献   

13.
Using data from dosimetry-radiometry system "Liulin" on board of "Mir"-space station the particle flux and doserate during September-October, 1989 has been studied. The orbit of the station was 379 km perigee, 410 km apogee and 51.6 degrees inclination. Special attention has been paid to the flux and doserate changes inside the station after intensive solar proton events (SPE) on 29 of September, 1989. The comparison between the doses before and after the solar flares shows increase of the calculated mean dose per day by factor of 10 to 200. During the SPE on the 29 of September the additional dose was 310 mrad. The results of the experiment are compared with the data for the solar proton fluxes obtained on the GOES-7 satellite.  相似文献   

14.
The present study examines the effects of orbit progression on the exposures within a Space Station Freedom module in a 51.6-degree inclined orbit at 450 km. The storm evolution is modeled after the November 1960 event, and the solar proton flux evolution is taken from the August 1972 solar proton event. The effects of a strong magnetic shock, such as was observed during the October 1989 event, is also modeled. The statistics on hourly average storm fields for the last forty years reveal that the largest geomagnetic storms approach a Dst value of -500 nanotesla at the storm peak. Similarly, one of the largest satellite-measured proton flux (> 10 MeV) for space exposures is the event of August 1972. The effects of orbit progression (advance of the line of nodes) is examined for the above conditions to study the variation of exposures under differing times of occurrence of the solar proton peak intensity, attainment of geomagnetic storm maximum, and the location of the line of nodes of the last geomagnetically protected orbit. The impact of the inherent inhomogeneity of the space station module is examined as a limiting factor on exposure with regard to the need of additional parasitic shielding.  相似文献   

15.
We have developed an operational code, SOLPENCO, that can be used for space weather prediction schemes of solar energetic particle (SEP) events. SOLPENCO provides proton differential flux and cumulated fluence profiles from the onset of the event up to the arrival of the associated traveling interplanetary shock at the observer’s position (either 1.0 or 0.4 AU). SOLPENCO considers a variety of interplanetary scenarios where the SEP events develop. These scenarios include solar longitudes of the parent solar event ranging from E75 to W90, transit speeds of the associated shock ranging from 400 to 1700 km s−1, proton energies ranging from 0.125 to 64 MeV, and interplanetary conditions for the energetic particle transport characterized by specific mean free paths. We compare the results of SOLPENCO with flux measurements of a set of SEP events observed at 1 AU that fulfill the following four conditions: (1) the association between the interplanetary shock observed at 1 AU and the parent solar event is well established; (2) the heliolongitude of the active region site is within 30° of the Sun–Earth line; (3) the event shows a significant proton flux increase at energies below 96 MeV; (4) the pre-event intensity background is low. The results are discussed in terms of the transit velocity of the shock and the proton energy. We draw conclusions about both the use of SOLPENCO as a prediction tool and the required improvements to make it useful for space weather purposes.  相似文献   

16.
太阳耀斑与太阳质子事件的发生通常与太阳活动区存在非常密切的关系, 对这种关系的深入分析有助于太阳耀斑和太阳质子事件预报模型的建立. 本文利用主成分分析(Principal Component Analysis, PCA)方法对1997-2010年太阳质子事件所在活动区的主要参量进行分析, 选取的参量包括黑子磁分类、 McIntosh分类、太阳黑子群面积、10.7 cm射电流量、耀斑指数、质子耀斑位置和软X射线耀斑强度. 结果得到81个太阳活动主成分得分值排序(得分值代表每个事件的强弱), 与太阳质子事件峰值流量、太阳黑子年均值以及10.7 cm射电流量年均值的对比显示相似度非常高, 表明主成分得分值一定程度上可以反映太阳活动的强弱规律.   相似文献   

17.
为了更加准确地判断X级耀斑是否引发质子事件,对X级质子耀斑和非质子耀斑的耀斑积分通量、源区、CME速度、CME角宽度、背景太阳风速度及背景X射线通量的分布进行了统计研究.发现非质子耀斑和质子耀斑的积分通量、经度、CME速度和CME角宽度具有明显不同的分布.非质子耀斑大多集中在东部,耀斑积分通量小于0.3J·m-2,CME速度小于1300km·s-1的区域内;质子耀斑大多集中在中部或西部,耀斑积分通量大于0.3J·m-2,CME速度大于1300km·s-1的区域内.质子耀斑伴随的CME角宽度主要集中在360°,非质子耀斑的CME角宽度分布则相对分散.两类耀斑的背景太阳风速度和背景X射线通量分布差别不大.利用两类耀斑各个参量分布上的差异,有望提高X级耀斑预报的准确率.   相似文献   

18.
A new event-oriented solar proton prediction model has been developed and implemented at the USAF Space Environment forecast facility. This new model generates predicted solar proton time-intensity profiles for a number of user adjustable energy ranges and is also capable of making predictions for the heavy ion flux. The computer program is designed so a forecaster can select inputs based on the data available in near real-time at the forecast center as the solar flare is occurring. The predicted event amplitude is based on the electromagnetic emission parameters of the solar flare (either microwave or soft X-ray emission) and the solar flare position on the sun. The model also has an update capability where the forecaster can normalize the prediction to actual spacecraft observations of spectral slope and particle flux as the event is occurring in order to more accurately predict the future time-intensity profile of the solar particle flux. Besides containing improvements in the accuracy of the predicted energetic particle event onset time and magnitude, the new model converts the predicted solar particle flux into an expected radiation dose that might be experienced by an astronaut during EVA activities or inside the space shuttle.  相似文献   

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