JUXTA: A new probe of X-ray emission from the Jupiter system

For the future Japanese exploration mission of the Jupiter’s magnetosphere (JMO: Jupiter Magnetospheric Orbiter), a unique instrument named JUXTA (Jupiter X-ray Telescope Array) is being developed. It aims at the first in-situ measurement of X-ray emission associated with Jupiter and its neighborhood. Recent observations with Earth-orbiting satellites have revealed various X-ray emission from the Jupiter system. X-ray sources include Jupiter’s aurorae, disk emission, inner radiation belts, the Galilean satellites and the Io plasma torus. X-ray imaging spectroscopy can be a new probe to reveal rotationally driven activities, particle acceleration and Jupiter–satellite binary system. JUXTA is composed of an ultra-light weight X-ray telescope based on micromachining technology and a radiation-hard semiconductor pixel detector. It covers 0.3–2 keV with the energy resolution of <100 eV at 0.6 keV. Because of proximity to Jupiter (∼30 Jovian radii at periapsis), the image resolution of <5 arcmin and the on-axis effective area of >3 cm² at 0.6 keV allow extremely high photon statistics and high resolution observations.     

Ionospheric TEC prediction using hybrid method based on ensemble empirical mode decomposition (EEMD) and long short-term memory (LSTM) deep learning model over India

Total electron data (TEC) from GPS nowadays can be used as a tool for understanding the space weather phenomena. The development of prediction model for TEC is quiet crucial and challenging due to the dynamic behavior of the ionosphere, since it depends on different factors such as seasonal, diurnal and spatial variations, solar geomagnetic conditions etc. In this paper, an attempt is made for predicting the GPS derived TEC values for different GNSS stations over India using a hybrid method based on Ensemble empirical mode decomposition (EEMD) and Long Short-Term Memory (LSTM) deep learning method. The daily TEC time series data from the IISc Bangalore (Latitude 13.021, Longitude 77.570), Lucknow (Latitude 26.912, Longitude 80.956) and Hyderabad (Latitude 17.417, Longitude 78.551) stations over India during the period 2008 to 2015 of solar cycle 23 and 24 is used for analysis. The assessment of model performance for testing predicted output compared with LSTM and EMD-LSTM models, and their comparison results show that the hybrid EEMD-LSTM model presents better than the other models.     

A numerical study of noontime bite-outs in F2-region electron density

Noontime bite-outs in ionospheric F₂-region electron density in the geomagnetic equatorial, low, and middle latitudes have been reproduced in this study using the Thermosphere Ionosphere Electrodynamic General Circulation Model (TIEGCM). The different driving mechanisms of F₂-region noontime bite-outs at different latitudes were further verified by modeling simulation. In the geomagnetic equator, the upward ExB plasma drifts are the main process to produce the noontime bite-outs in ionospheric electron density. In the geomagnetic low latitudes, both the electrical fields and poleward meridional winds play a crucial role in forming the noontime bite-outs. In contrast to the case at the geomagnetic equator, a weaker fountain effect might be an favorable condition for the noontime bite-outs to occur at low latitudes. For geomagnetic middle latitudes, an upward plasma flux and poleward meridional winds are the dominated drivers in producing the noontime bite-outs. Modeling results show that a large upward plasma flux and poleward meridional winds make the noontime bite-outs to occur and observable over middle latitudes.     

高纯氧化铝基板的制备要点与宇航应用验证实践

通过分析高纯氧化铝陶瓷基板的制备要点，梳理了制备关键工艺与基板特性指标之间的关系，梳理出星用高纯氧化铝陶瓷基板的验证需求，最终提出了高纯氧化铝基板的验证思路，即在将全部验证项目分为构件级和组件级两个大类的基础上，进一步建立起三级验证指标体系。就具体验证项目的设计与实践，进行了细致的分析讨论。得出结论，验证过程体现出的既基于已有标准框架和测试原理，又不拘泥于某一特定标准的原则与思路，不仅适合于构件级的批次稳定性与工艺适用性验证，同样也适用于组件级各验证项目和具体测试方法的确定。在确保构件级和组件级全面、准确验证的前提下，为确保较高的验证效率和较低的验证成本，需要结合标准、测试条件、应用工况三方面综合考虑和细化验证项目条件。     

航天复合材料研究进展

航天复合材料的性能与应用水平是衡量航天型号先进性与可靠性的重要标志,是支撑航天型号发展的关键材料,决定型号性能与成败.本文总结了近年来在热结构、防热、热透波、隔热以及结构复合材料领域的重要研究进展,提出极端环境服役新材料、可重复使用防隔热材料、第三代结构复合材料以及复合材料构件低成本快速制造等是航天复合材料未来发展的重...     

Recent progress of machine learning in flow modeling and active flow control

In terms of multiple temporal and spatial scales, massive data from experiments, flow field measurements, and high-fidelity numerical simulations have greatly promoted the rapid development of fluid mechanics. Machine Learning(ML) provides a wealth of analysis methods to extract potential information from a large amount of data for in-depth understanding of the underlying flow mechanism or for further applications. Furthermore, machine learning algorithms can enhance flow information and automat...     

Ionospheric climate index as a driving parameter for the NeQuick model

Ionospheric delay is one of the significant error sources for global navigation satellite system (GNSS) positioning. GNSSs broadcast the coefficients of the ionospheric model to correct ionospheric delay for single-frequency users. A modified three-dimensional model (NeQuick G) based on the NeQuick climatological model is adopted for Galileo users. The NeQuick G model uses the effective ionization level (Az) instead of the sunspot number as the driving parameter. In this study, we introduce the ionospheric climate index (ICI) as a new driving parameter for the NeQuick model. In comparison, the ICI-driven NeQuick model has a better performance than the Az-driven NeQuick G model at both low and high latitudes. In addition, only one GNSS station at low latitudes is required to calculate the ICI, which would save maintenance costs and improve the efficiency of updating the broadcast coefficients. This model has potential application value for future upgrades of Galileo’s ionospheric broadcast model.     

Analysis of NASA’s DSN Venus Express radio occultation data for year 2014

The Venus Express Radio Science Experiment (VeRa) was part of the scientific payload of the Venus Express (VEX) spacecraft and was targeted at the investigation of Venus’ atmosphere, surface, and gravity field as well as the interplanetary medium. This paper describes the methods and the required calibrations applied to VEX-VeRa raw radio occultation data used to retrieve vertical profiles of Venus’ ionosphere and neutral atmosphere. In this work we perform an independent analysis of a set of 25 VEX, single-frequency (X-band), occultations carried out in 2014, recorded in open-loop at the NASA Deep Space Network. Our temperature, pressure and electron density vertical profiles are in agreement with previous studies available in the literature. Furthermore, our analysis shows that Venus’ ionosphere is more influenced by the day/night condition than the latitude variations, while the neutral atmosphere experiences the opposite. Our scientific interpretation of these results is based on two major responsible effects: Venus’ high thermal inertia and the zonal winds. Their presence within Venus’ neutral atmosphere determine why in these regions a latitude dependence is predominant on the day/night condition. On the contrary, at higher altitudes the two aforementioned effects are less important or null, and Venus’ ionosphere shows higher electron density peaks in the probed day-time occultations, regardless of the latitude.     

Investigation of the planar midlatitude ionospheric trend under different levels of solar activity

A better understanding of the ionosphere through accurate mathematical models is no doubt a crucial element. This study focuses on the challenging problem of building a model representing the complex structure of the midlatitude ionosphere. Previous studies have shown that a regional planar model is suitable in representing the total electron content (TEC) trend in the midlatitude ionosphere in both hemispheres. In this study, the planar trend model for 12 non-overlapping northern hemisphere regions in three groups of geographically near 4 regions is further investigated under different levels of solar activity; low, moderate and high. To that end, the coefficients of the model are estimated in the least squares sense using total electron content values from global ionospheric maps (GIMs) for the years 2009, 2012 and 2014. Subsequently, these coefficients are used to reconstruct estimated TEC maps which are then compared with actual GIM-TEC by investigating their difference in normalized $L_2$ norm squared sense. The regional planar trend model provides a particularly successful representation in the years 2012 and 2014 for which the solar activity level is the dominant factor determining the TEC trend. Under low solar activity conditions of 2009, other factors such as ocean currents, temperature variations and meteorological phenomena are suspected to have a considerable effect in some regions depending on their geographic location and on seasonal trends in those regions. As an example, studies show that under the influence of the Pacific Decadal Oscillation (PDO) and Siberian High (SH), a significant cooling trend between 2004 and 2018 in autumn is observed in Eurasia, which, in conjunction with the low solar activity levels, may be related to the deviations from the actual GIM-TEC in 2009 in these regions. As solar radiation increases, however, such bottom-side forcings are masked in 2012 and 2014 and these deviations are no longer observed.