Simulation of reflectometry Bragg backscattering spectral responses in the absence of a cutoff layer

Experimental reflectometry signals obtained in the absence of a cutoff layer, with the possibility of interferometric operation excluded, show a coherent and recurrent frequency spectrum signature similar to an Alfvén cascade signature. A possible explanation resides in the modulation of a resonant Bragg backscattering response by an Alfvén mode structure located at the center of the plasma whose frequency of oscillation modulates the backscattered signal in a conformable way. This situation is modeled and simulated using an O-mode full-wave Maxwell finite-difference time-domain code and the resulting signatures are discussed.     

Machine learning application to predict the electron temperature on the J-TEXT tokamak

The reliability of diagnostic systems in tokamak plasma is of great significance for physics researches or fusion reactor. When some diagnostics fail to detect information about the plasma status, such as electron temperature, they can also be obtained by another method: fitted by other diagnostic signals through machine learning. The paper herein is based on a machine learning method to predict electron temperature, in case the diagnostic systems fail to detect plasma temperature. The fully-connected neural network, utilizing back propagation with two hidden layers, is utilized to estimate plasma electron temperature approximately on the J-TEXT. The input parameters consist of soft x-ray emission intensity, electron density, plasma current, loop voltage, and toroidal magnetic field, while the targets are signals of electron temperature from electron cyclotron emission and x-ray imaging crystal spectrometer. Therefore, the temperature profile is reconstructed by other diagnostic signals, and the average errors are within 5%. In addition, generalized regression neural network can also achieve this function to estimate the temperature profile with similar accuracy. Predicting electron temperature by neural network reveals that machine learning can be used as backup means for plasma information so as to enhance the reliability of diagnostics.     

中国抗中子辐照钢的抗辐照设计与验证

聚变堆等未来先进核能系统要求材料在强流高能中子辐照下长期保持良好的结构稳定性和机械性能。为适应未来先进核能技术发展的需要，中国科学院核能安全技术研究所•凤麟团队牵头研发了具有我国自主知识产权的中国抗中子辐照钢--CLAM钢。CLAM钢的设计考虑了未来核能清洁性的要求，以及苛刻服役环境中材料抗辐照、耐高温、耐腐蚀等性能要求。通过中子学计算分析设计了低活化成分范围，基于选择性纳米相析出进行了抗辐照、耐高温性能优化设计。针对材料的抗辐照性能，利用国内外中子、离子、电子及等离子体辐照设施开展了系列辐照考验研究，通过多角度表征辐照前后材料的微观结构和宏观性能，综合评估了材料的辐照性能，并与国际上同类材料在相近或相同条件下的辐照性能进行了对比分析，结果表明CLAM钢具有良好的抗辐照性能。     

武汉电大系统现代远程教育改革与发展研究

武汉电大系统现代远程教育在新一轮改革大潮中面临难得的发展机遇和严峻的挑战。在终身教育思想指导下,以”两型社会”建设为契机,以服务社会为宗旨,以非学历教育为突破口,探索远程教育与社区教育相结合的途径,深化改革,科学发展,努力成为武汉市构建终身教育体系框架和建设学习型城市的重要骨干力量。     

X-ray flares in early GRB afterglows

The Swift X-ray Telescope (XRT) has discovered that flares are quite common in early X-ray afterglows of gamma-ray bursts (GRBs), being observed in roughly 50% of afterglows with prompt follow-up observations. The flares range in fluence from a few per cent to approximately 100% of the fluence of the prompt emission (the GRB). Repetitive flares are seen, with more than four successive flares detected by the XRT in some afterglows. The rise and fall times of the flares are typically considerably smaller than the time since the burst. These characteristics suggest that the flares are related to the prompt emission mechanism, but at lower photon energies. We conclude that the most likely cause of these flares is late-time activity of the GRB central engine.     

结合几何的MCNP计算结果可视化分析系统的研究与实现

蒙特卡罗粒子输运程序MCNP在分析复杂例题的模拟计算结果数据时,具有分析过程不直观、效率低等问题。FDS团队结合科学计算可视化技术、GPU(图形处理器)可视化编程技术,以及本团队自动建模系统MCAM的反向转换引擎,自主研发了集数据分类提取、图形化管理以及结合几何的三维数据可视化分析功能于一体的MCNP计算结果可视化分析系统。以国际热核实验堆ITER为代表的大量测试结果表明,该系统显著提高了数据的利用率和分析效率。     

SST-1 Refurbishment Progress: an Update

Refurbishment of steady state tokamak (SST-1) primarily focused at addressing the issues and bottle-necks involving various subsystems of SST-1 as observed during earlier commis- sioning attempts, have progressed significantly. Under the refurbishment spectrum, all joints in the superconducting magnet system have been re-fabricated as low DC leak tight joint resistances, all toroidal field (TF) magnets have been equipped with 5 K radiation shields on the inner side and successfully tested for their rated parameters in cold under nominal currents, all vessel sectors and modules have been baked and tested under representative conditions, supporting helium and ni- trogen cryogenic facilities have been made > 99% reliable in various envisaged operating scenarios of SST-1. The reassemblies of the critical subsystems of the SST-1 machine shell have progressed aggressively and are nearing completion. Auxiliaries such as the baking facility for the vacuum vessel and first wall components, current leads assembly distributions, synchronized timing sys- tem, reliable data acquisition and plasma control systems as well as essential diagnostics have also been readied towards the first plasma. A detailed engineering validation of the assembled SST-1 machine shell including field error measurements has been planned prior to first plasma attempts.     

聚变驱动乏燃料焚烧堆氦冷包层中子学设计与分析

采用VisualBUS程序和HENDL数据库,对聚变驱动乏燃料焚烧堆氦冷包层开展了中子学设计与分析工作,设计目标是在满足Keff小于0.95,功率密度小于100 MW·m-3和氚自持的前提下,获得至少1 GWe的能量输出和最大增殖、嬗变能力,且系统能够连续稳定运行.文中通过对包层中的乏燃料成分和是否装载贫铀开展优化分析并给出了优化方案,该方案能够很好地满足设计目标.     

基于CAD技术的特征线中子输运计算程序开发

特征线方法(Method of Characteristics,MOC)能否应用于复杂几何关键在于能否将特征线方法与有效的几何处理方法结合起来。本文在菱形差分特征线理论基础上,基于FDS团队自主研发的核与辐射输运计算自动建模软件MCAM的几何处理引擎,研发了基于CAD技术的特征线中子输运计算程序,并利用相关基准例题对程序进行了数值验证,其结果与参考值吻合良好,表明本文方法和程序的可行性、正确性与可靠性。