Symplectic adaptive algorithm for solving nonlinear two-point boundary value problems in Astrodynamics

In this paper, from a Hamiltonian point of view, the nonlinear optimal control problems are transformed into nonlinear two-point boundary value problems, and a symplectic adaptive algorithm based on the dual variational principle is proposed for solving the nonlinear two-point boundary value problem. The state and the costate variables within a time interval are approximated by using the Lagrange polynomial and the costate variables at two ends of the time interval are taken as independent variables. Then, based on the dual variational principle, the nonlinear two-point boundary value problems are replaced by a system of nonlinear equations which can preserve the symplectic structure of the nonlinear optimal control problem. Furthermore, the computational efficiency of the proposed symplectic algorithm is improved by using the adaptive multi-level iteration idea. The performance of the proposed algorithm is tested by the problems of Astrodynamics, such as the optimal orbital rendezvous problem and the optimal orbit transfer between halo orbits.     

Automated Prediction of CMEs Using Machine Learning of CME – Flare Associations

Machine-learning algorithms are applied to explore the relation between significant flares and their associated CMEs. The NGDC flares catalogue and the SOHO/LASCO CME catalogue are processed to associate X and M-class flares with CMEs based on timing information. Automated systems are created to process and associate years of flare and CME data, which are later arranged in numerical-training vectors and fed to machine-learning algorithms to extract the embedded knowledge and provide learning rules that can be used for the automated prediction of CMEs. Properties representing the intensity, flare duration, and duration of decline and duration of growth are extracted from all the associated (A) and not-associated (NA) flares and converted to a numerical format that is suitable for machine-learning use. The machine-learning algorithms Cascade Correlation Neural Networks (CCNN) and Support Vector Machines (SVM) are used and compared in our work. The machine-learning systems predict, from the input of a flare’s properties, if the flare is likely to initiate a CME. Intensive experiments using Jack-knife techniques are carried out and the relationships between flare properties and CMEs are investigated using the results. The predictive performance of SVM and CCNN is analysed and recommendations for enhancing the performance are provided.     

Effectiveness of fast electron retention in the magnetic cavern during disturbance of the magnetic field azimuthal symmetry

The loss rate of fast electrons (with an energy much higher than the energy of the plasma electron thermal motion), when they leave a magnetic cavern during a disturbance of the magnetic field azimuthal symmetry, is studied. The cases of point and volume sources of fast particles have been considered. The plasma density in the cavern is supposed to be low, so that collisions of fast electrons with plasma particles can be neglected. The effect of the electric field on particle motion is neglected because it is assumed that the electric charge particles outgoing from the cavern is compensated by the counter current of plasma conductivity electrons. The dependence of the loss value on the harmonic number and the amplitude of the cavern boundary radius disturbance has been obtained.     

空间视角下城乡物流网络的内涵、构成要素与研究框架

地理学视角的物流网络研究已成为物流科学领域的热点方向。从地理学的空间视角出发,在明确城乡物流网络理论来源和相关概念的基础上,对城乡物流网络的内涵、构成及研究框架进行梳理。基于研究,首先给出了城乡物流网络的定义,认为城乡物流网络的本质是旧的城市物流网络和乡村物流网络在空间上的延伸、衔接和提效。其次,从空间视角将城乡物流网络分解为节点、连线和域面3要素,指出网络各要素均出现了功能强化和更新,如节点的管理、衔接和经济社会功能强化;连线的联结功能和平衡功能出现,域面的协同组织、动态调整功能突出。最后,遵循地理学“格局-过程-机理-决策”的科学逻辑,提出“数据采集与融合、要素映射与解析、时空比较与分析、机理探究与优化”4个模块的城乡物流网络分析框架,为深刻揭示城乡物流网络结构及其演化机理提供基础。进一步指出未来应探讨城乡物流节点、连线、域面及网络的地区类型、区域适宜性及要素间相互作用机制,提炼适应不同区域、能有效提升要素流通效应的多尺度空间组织模式,加强对城乡要素流通系统的科学认知,科学支撑城乡地域融合发展实践。     

Twisted Flux Tube Emergence Evidenced in Longitudinal Magnetograms: Magnetic Tongues

Bipolar active regions (ARs) are thought to be formed by twisted flux tubes, as the presence of such twist is theoretically required for a cohesive rise through the whole convective zone. We use longitudinal magnetograms to demonstrate that a clear signature of a global magnetic twist is present, particularly, during the emergence phase when the AR is forming in a much weaker pre-existing magnetic field environment. The twist is characterised by the presence of elongated polarities, called “magnetic tongues”, which originate from the azimuthal magnetic field component. The tongues first extend in size before retracting when the maximum magnetic flux is reached. This implies an apparent rotation of the magnetic bipole. Using a simple half-torus model of an emerging twisted flux tube having a uniform twist profile, we derive how the direction of the polarity inversion line and the elongation of the tongues depend on the global twist in the flux rope. Using a sample of 40 ARs, we verify that the helicity sign, determined from the magnetic polarity distribution pattern, is consistent with the sign derived from the photospheric helicity flux computed from magnetogram time series, as well as from other proxies such as sheared coronal loops, sigmoids, flare ribbons and/or the associated magnetic cloud observed in situ at 1 AU. The evolution of the tongues observed in emerging ARs is also closely similar to the evolution found in recent MHD numerical simulations. We also found that the elongation of the tongue formed by the leading magnetic polarity is significantly larger than that of the following polarity. This newly discovered asymmetry is consistent with an asymmetric Ω-loop emergence, trailing the solar rotation, which was proposed earlier to explain other asymmetries in bipolar ARs.     

Uncertainties in modelling future hydrological change over West Africa

The aim of this paper is to evaluate current knowledge and uncertainties associated with the impact of increasing greenhouse gas and aerosol concentrations on the West African monsoon. For this purpose, coupled and time-slice simulations are used. A global measure of the monsoon changes is defined in order to avoid regional biases and to try and obtain significant results. The position and width of the monsoon in latitude are the main focuses. There is almost no agreement between the Coupled General Circulation models from the Coupled models Inter-Comparison project—Phase II in regard to the impact of climate change on the monsoon. Moreover, very simple discriminations between the models seem inappropriate to get a better signal. The role of the different forcings in time-slice simulations is then investigated. The sea surface temperature (SST) and particularly the pattern of the SST are shown to be the most important forcing. This accounts for the diversity of the results either from the coupled or the forced simulations with different SST changes. With a fixed SST, but of a smaller magnitude in AMJ, there are still uncertainties, coming first from the Atmospheric General Circulation models and the way they balance greenhouse gas and global SST increase. Finally the uncertainty due to the Land Surface models (LSMs) is not negligible. The greenhouse gas and the LSMs are shown to have more impact in August, when the monsoon is at its highest latitude on the continent.     

Prediction of Water Temperature as Affected by a Pre‐Constructed Reservoir Project Based on MIKE11

Reservoir construction can lead to much more water stored in front of the dam and significantly increase heat storage capacity of the reservoir waters, thus resulting in different distribution pattern of water temperature in reservoir area compared to river. Especially for large reservoir, the obvious stratification of water temperature will appear in the reservoir with deeper water levels. Meanwhile, the low water temperature will be observed in the downstream river due to the operation of the reservoir. The vertical numerical simulation model for reservoir from MIKE 11 was used to predict the changes of water temperature of Wuxikou Reservoir to check the effects of the reservoir construction on water temperature. The water temperature prediction model was developed to simulate the water temperature of the reservoir and the discharged outflow water. The predicted results can contribute to assessing the feasibility of the pre‐constructed project based on the environmental influence of water temperature.