第21,22周峰年太阳射电爆发中毫秒级精细结构的分析

本文对第21周的2840MHz及22周峰年的2545MHz，2645MHz和2840MHz波段上所观测到的285个快速事件进行分析，发现两个峰年的快速事件具有多种多样的快速活动（快速精细结构）．它们与耀斑的对应关系也做了统计分析．     

Towards a scientific understanding of the risk from extreme space weather

Like all natural hazards, space weather exhibits occasional extreme events over timescales of decades to centuries. Historical events provoked much interest, and sometimes alarm, because bright aurora becomes visible at mid-latitudes. However, they had little economic impact because the major technologies of those eras were not sensitive to space weather. This is no longer true. The widespread adoption of advanced technological infrastructures over the past 40 years has created significant sensitivity. So these events now have the potential to disrupt those infrastructures – and thus have profound economic and societal impact. However, like all extreme hazards, such events are rare, so we have limited data on which to build our understanding of the events. This limitation is uniquely serious for space weather since it is a global phenomenon. Many other natural hazards (e.g. flash floods) are highly localised, so statistically significant datasets can be assembled by combining data from independent instances of the hazard recorded over a few decades. Such datasets are the foundation on which reliable risk assessment methodologies are built. But we have a single instance of space weather so we would have to make observations for many centuries in order to build a statistically significant dataset. We show that it is not practicable to assess the risk from extreme events using simple statistical methods. Instead we must exploit our knowledge of solar-terrestrial physics to find other ways to assess these risks. We discuss three alternative approaches: (a) use of proxy data, (b) studies of other solar systems, and (c) use of physics-based modelling. We note that the proxy data approach is already well-established as a technique for assessing the long-term risk from radiation storms, but does not yet provide any means to assess the risk from severe geomagnetic storms. This latter risk is more suited to the other approaches, but significant research is needed to make progress. We need to develop and expand techniques to monitoring key space weather features in other solar systems (stellar flares, radio emissions from planetary aurorae). And to make progress in modelling severe space weather, we need to focus on the physics that controls severe geomagnetic storms, e.g. how can dayside and tail reconnection be modulated to expand the region of open flux to envelop mid-latitudes?     

A new inversion method of plasma density distribution of plasmasphere in the geomagnetic equatorial plane from IMAGE data

The plasma density distribution of plasmasphere in the geomagnetic equatorial plane can help us study the magnetosphere like plasmasphere, ionosphere and their kinetics. In this paper, we introduce a new inversion method, GE-ART, to calculate the plasma density distribution in the geomagnetic equatorial plane from the Extreme Ultraviolet (EUV) data of IMAGE satellite under the assumption that the plasma density is constant along each geomagnetic field line. The new GE-ART algorithm was derived from the traditional Algebraic Reconstruction Techniques (ART) in Computed Tomography (CT) which was different from the several existing methods. In this new method, each value of the EUV image data was back-projected evenly to the geomagnetic field lines intersected by this EUV sight. A 3-D inversion matrix was produced by the contributions of all the voxels contained in the plasmasphere covered by the EUV sensor. That is, we considered that each value of the EUV image data was relative to the plasma densities of all the voxels passed through by the corresponding EUV radiation, which is the biggest difference to all the existing inversion methods. Finally, the GE-ART algorithm was evaluated by the real EUV data from the IMAGE satellite.     

特大展弦比机翼的特性与设计

大展弦比机翼有明显的升/阻(L/D)优势。但随着机翼展弦比的增大,在机翼结构重量控制条件下,机翼成柔性机翼,飞行中机翼的弹性变形量随速压(1/2ρV2)增大而增大,出现了严重的气动/结构耦合的问题。本文阐述了耦合问题的成因和解决途径,为特大展弦比机翼飞机(长航时无人机)的设计提供参考。     

Modeling M(3000)F2 based on extreme learning machine

This paper presents an novel extreme learning machine (ELM)-based prediction model for the ionospheric propagation factor M(3000)F2 at Darwin station (12.4°S, 131.5°E; −44.5°dip) in Australia. The proposed ELM model is trained with hourly daily values of M(3000)F2 from the period 1998–2014 except 2001 and 2009. The hourly daily values of 2001 (high solar activity) and 2009 (low solar activity) are used for validating the prediction accuracy. The proposed ELM for modeling M(3000)F2 can achieve faster training process and similar testing accuracy compared with backward propagation neural network (BPNN). In addition, the performance of the ELM is verified by comparing the predicted values of M(3000)F2 with observed values and the international reference ionosphere (IRI −2016) model predicted values. Based on the error differences (the root mean square error (RMSE) and the M(3000)F2 percentage improvement values M(3000)F2_IMP(%)), the result demonstrates the effectiveness of the ELM model compared with the IRI-2016 model at hourly, daily, monthly, and yearly in high (2001) and low (2009) solar activity years. The ELM also shows good agreement with observations compared with the IRI during disturbed magnetic activity.     

极端太阳风条件下的磁层顶位形

基于极端太阳风条件下的三维MHD数值模拟数据, 构建了一种极端太阳风条件下的三维非对称磁层顶位形模型. 所提出的模型考虑了行星际南向磁场(IMF) B_z日下点距离侵蚀的饱和效应, 太阳风动压B_d对磁层顶张角影响的饱和效应, 赤道面、昼夜子午面磁层顶的不对称性以及极尖区的内凹结构和内凹中心的移动, 并利用Levenberg-Marquart多参量非线性拟合方法拟合了模型参数. 数值模拟研究表明, 在极端太阳风条件下, 随B_d增大, 磁层顶日下点距离减小, 磁层顶磁尾张角几乎不变; 随南向(IMF)B_z增大, 磁层顶日下点距离略有减小, 磁层顶磁尾张角减小, 极尖区内凹中心向低纬移动. 通过对2010年8月1日太阳风暴事件验证发现, 本文所建立的模型能够描述极端太阳风条件下的三维磁层顶位形.      

Solar proton events recorded in the stratosphere during cosmic ray balloon observations in 1957–2008

Long-term balloon observations have been performed by the Lebedev Physical Institute since 1957 up to the present time. The observations are taken several times a week at the polar and mid latitudes and allow us to study dynamics of galactic and solar cosmic ray as well as secondary particle fluxes in the atmosphere and in the near-Earth space. Solar energetic particles (120) – mostly protons – (SEP) events with >100 MeV proton intensity above 1 cm⁻² s⁻¹ s⁻¹ were recorded during 1958–2006. Before the advent of the SEP monitoring on spacecraft these results constituted the only homogeneous series of >100 MeV SEP events. The SEP intensities and energy spectra inferred from the Lebedev Physical Institute observations are consistent with the results taken in the adjacent energy intervals by the spacecraft and neutron monitors. Joint consideration of the SEP events series recorded by balloons and by neutron monitors during solar cycles 20–23 makes it possible to restore the probable number of events in solar cycle 19, which was not properly covered by observations. Some correlation was found between duration of SEP event production in a solar cycle and sunspot cycle characteristics.     

应用BP神经网络针对高通量质子事件的通量数值预报

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.      

基于极限学习机的修正当前统计模型跟踪算法

针对当前统计(Current Statistical,CS)模型由于先验知识的缺乏和其结构特点导致的跟踪精度降低的问题,通过使用极限学习机(Extreme Learning Machine,ELM)并根据目标历史状态信息,实时估计并修正CS模型的加速度估计值,提出了基于ELM的修正CS模型跟踪算法.ELM的训练结果表明...