内埋武器机弹分离相容性研究进展综述

为满足新型有人或无人作战飞机高隐身、高速和高机动性等要求，作战飞机普遍采用武器内埋挂载方式。当高速气流流过内埋武器舱的空腔时，将引发边界层分离、舱口附近会存在复杂的剪切流动、舱内会产生极为恶劣的噪声环境等非定常流动现象，这些复杂的非定常流动现象严重影响内埋武器机弹分离相容性（ASSC）。首先，给出内埋武器机弹分离相容性的重要研究意义；接着，重点介绍内埋武器机弹分离相容性的研究进展；最后，论述和总结了国内外采用4种方法（理论分析与建模、风洞试验、数值模拟和飞行试验）研究内埋武器机弹分离相容性及其流动控制方法的进展，指出内埋武器机弹分离相容研究存在的主要问题，并给出几点建议。     

Solar flares,CMEs and solar energetic particle events during solar cycle 24

We present here a study of Solar Energetic Particle Events (SEPs) associated with solar flares during 2010–2014 in solar cycle 24. We have selected the flare events (≥GOES M-class), which produced SEPs. The SEPs are classified into three categories i.e. weak (proton intensity?≤?1?pfu), minor (1?pfu?<?proton intensity?<?10?pfu) and major (proton intensity?≥?10?pfu). We used the GOES data for the SEP events which have intensity greater than one pfu and SOHO/ERNE data for the SEP event less than one pfu intensity. In addition to the flare and SEP properties, we have also discussed different properties of associated CMEs.     

Classification of solar wind structures and intense geomagnetic storm alarms with self-organizing maps

Intense geomagnetic storms (D_st < −100 nT) usually occur when a large interplanetary duskward-electric field (with Ey > 5 mV m⁻¹) lasts for more than 3 h. In this article, a self-organizing map (SOM) neural network is used to recognize different patterns in the temporal variation of hourly averaged Ey data and to predict intense storms. The input parameters of SOM are the hourly averaged Ey data over 3 h. The output layer of the SOM has a total of 400 neurons. The hourly Ey data are calculated from solar wind data, which are provided by NSSDC OMNIWeb and ACE spacecraft and contain information on 143 intense storms and a fair number of moderate storms, weak storms and quiet periods between September 3, 1966 and June 30, 2002. Our results show that SOM is able to classify solar wind structures and therefore to give timely intense storm alarms. In our SOM, 21 neurons out of 400 are identified to be closely associated with the intense storms and they successfully predict 134 intense storms out of the 143 ones selected. In particular, there are 14 neurons for which, if one or more of them are present, the occurrence probability of intense storms is about 90%. In addition, several of these 14 neurons can predict big magnetic storm (D_st  −180 nT). In summary, our method achieves high accuracy in predicting intense geomagnetic storms and could be applied in space environment prediction.     

CONTOUR DESIGN AND PRACTICE FOR A LOW RADAR CROSS SECTION VEHICLE

ＣＯＮＴＯＵＲＤＥＳＩＧＮＡＮＤＰＲＡＣＴＩＣＥＦＯＲＡＬＯＷＲＡＤＡＲＣＲＯＳＳＳＥＣＴＩＯＮＶＥＨＩＣＬＥＺｈａｎｇＺｈｏｎｇａｎ；ＷａｎｇＬｕｅ（ＲｅｓｅａｒｃｈＩｎｓｔｉｔｕｔｅｏｆＰｉｌｏｔｌｅｓｓＡｉｒｃｒａｆｔ，ＮａｎｊｉｎｇＵｎｉｖｅ...     

三维非线性撕裂模耦合和快速磁场重联

基于三维不可压缩电阻性ＭＨＤ方程，在长柱形位型下，数值研究了电阻撕裂模不稳定性所引起的磁场重联过程。研究结果表明，撕裂模的非线性相互作用和耦合，将产生许多模式的强裂解稳和导致快速的磁场重联。这一过程的进一步发展，导致具有螺旋形结构，不同模式的磁岛磁力线重叠，从而引起较大区域内的磁场各态经历和磁力线随机走向，形成撕裂模端动。     

Structure and development of quiet loops in the solar corona

X-ray emission from solar coronal loops changes on two different timescales: a) flare loops and transient active region brightenings show a rapid variability, b) quiet region loops are quasi-steady and change only slowly with time. This different time behavior has been analyzed on the basis of Yohkoh SXT observations and we report here on the results from our analysis, mainly focussing on quiet loop variability.     

彩色氦气泡在风洞试验中的应用

彩色氦气泡流动显示是一极好的新技术。在风洞中应用彩色氦气泡进行流动显示已于1984年3月在哈尔滨空气动力研究所实现了,获得了丰富多采的彩色迹线,摄制了清晰的彩色录象和彩色照片。不久之后,进行了轿车、面包车、高楼、船舵、鱼鳞波表面、细长体、圆柱体、降落伞和各种飞机模型的试验。 本文描述了彩色氦气泡流动显示技术,介绍了在风洞中进行流动显示的一般装置、基本原理和应用。     

EXPERIMENTAL STUDY OF TURBULENT WINGBODY JUNCTION AND WAKE FLOW

ＥＸＰＥＲＩＭＥＮＴＡＬ　ＳＴＵＤＹ　ＯＦ　ＴＵＲＢＵＬＥＮＴ　ＷＩＮＧＢＯＤＹ　ＪＵＮＣＴＩＯＮ　ＡＮＤ　ＷＡＫＥＦＬＯＷＫａｎｇＨｏｎｇｗｅｎ；ＦａｎＭｅｎｇ；ＷｅｉＺｈｏｎｇｌｅｉ（ＤｅｐａｒｔｍｅｎｔｏｆＭｅｃｈａｎｉｃｓ，ＰｅｋｉｎｇＵｎｉ...     

PROBLEMS OF WINDBLAST

ＰＲＯＢＬＥＭＳＯＦＷＩＮＤＢＬＡＳＴＺｈａｎｇＹｕｎｒａｎ；ＷｕＧｕｉｒｏｎｇ（ＩｎｓｔｉｔｕｔｅｏｆＳｐａｃｅＭｅｄｉｃｏ－Ｅｎｇｉｎｅｅｒｉｎｇ，Ｂｅｉｊｉｎｇ，Ｃｈｉｎａ，１０００９４）ＰＲＯＢＬＥＭＳＯＦＷＩＮＤＢＬＡＳＴ￥ＺｈａｎｇＹｕｎ...