北京自由电子激光Wiggler中电子轨迹偏离的改进

提出了一种从实验上确定用于北京自由电子激光（ＢＦＥＬ）装置的Ｗｉｇｇｌｅｒ中ＮｄＦｅＢ矩形磁块的轨迹敏感系数β的方法．用β值来表征磁单块在Ｗｉｇｇｌｅｒ中对电子轨迹的贡献，并用此β值对磁块进行挑选，优化组合，可达到改进Ｗｉｇｇｌｅｒ对电子轨迹偏离的目的．     

TESTING DIFFERENT CONJUGATE GRADIENT METHODS FOR LARGE—SCALE UNCONSTRAINED OPTIMIZATION

In this PaPer we test different conjugate gradient (CG) methods for solving large-scale unconstrained optimization problems.The methods are divided in two groups:the first group includes five basic CG methods and the second five hybrid CG methods.A collection of medium-scale and large-scale test problems are drawn from a standard code of test problems.CUTE.The conjugate gradient methods are ranked according to the numerical results.Some remarks are given.     

金属Bi的卸载熔化实验研究

在火炮上利用金属铋(Bi)直接撞击单晶LiF窗口, 开展了金属Bi反向碰撞的冲击加载-卸载实验研究, 实验采用激光位移干涉测试系统, 获得了金属Bi在11—16 GPa压力范围内完整的卸载粒子速度剖面. 实验结果结合特征线方法计算表明, 金属Bi经冲击加载进入体心立方相, 并在11—16 GPa冲击压力作用下发生了卸载熔化, 界面粒子速度剖面的卸载拐点, 对应着金属Bi经冲击加载后发生的卸载熔化, 而这一结论同Cox的理论计算及一维流体力学程序计算结果基本一致. 本文报道的金属Bi卸载波剖面解读技术, 对于认识冲击加载下其他相似材料相变具有实用价值.     

基于束流位置探测器的束团长度测量

分析了驱动电子束团的频域特性,研究了基于该特性进行长度测量的理论基础;使用三维模拟软件对束流位置探测器(BPM)进行建模,用模拟的方法对传输阻抗进行了数值计算;对不同长度的束团进行了测量和计算,并且分析了束团位置在真空管道中偏移对束团长度测量的影响。由测量结果可见,电子束团长度在10~100 ps(3~30 mm)时,测量误差均小于2%,满足中国工程物理研究院高平均功率自由电子激光太赫兹实验测量的使用要求。     

色散补偿光子晶体光纤结构参数对其色散的影响

光子晶体光纤由于其灵活可调的色散特性用作色散补偿具有极大的应用潜力. 设计了一种色散补偿光子晶体光纤, 并运用频域有限差分法模拟了其色散特性,从理论上分析了其结构参数孔间距Λ和空气占空比d/Λ对该光子晶体光纤的色散系数的影响, 并且实际制备出了3种不同结构参数的光子晶体光纤. 通过对其色散曲线对比分析表明: 当光子晶体光纤孔间距在1 μm附近时, 其色散系数随着孔间距Λ和占空比d/Λ的增大而增加, 但对于孔间距Λ的变化比占空比d/Λ更为敏感, 并且随着孔间距Λ的增加,其对色散系数的影响能力逐渐减小. 设计并制备的光子晶体光纤在1550 nm处的色散系数为-241.5 ps·nm^-1·km^-1, 相对色散斜率为0.0018, 具有较好的色散补偿能力. 关键词： 色散 色散补偿 光子晶体光纤 结构参数     

用光电离技术探测钐原子的奇宇称束缚激发态的光谱

采用光电离探测方法,对钐原子奇宇称束缚激发态进行了系统研究.通过设计三条不同的激发路径, 采用共振激发方式,先将钐原子分三步从基态激发到不同的束缚激发态,然后采用光电离手段对其进行探测. 通过对第三步激发光的波长进行大范围的扫描,在同一能域内获得了三组不同的光谱. 通过比对三条路径所得到的三组光谱,不仅精确确定了大量奇宇称束缚激发态的能级位置, 而且还获得了相应跃迁的相对强度的信息.最后,通过运用三条不同的激发路径的选择定则, 还确定了上述能级的总角动量. 关键词： 钐原子 束缚激发态 奇宇称 光电离探测     

考虑材料熔化潜热的高温高压本构

本文在修正的SCG模型基础上，提出了一种考虑了熔化潜热的高温高压本构.该本构所给出的铝的剪切模量的变化分为三个阶段：加工硬化，温度软化和熔化，并在完全熔化点处变为零.并且在前两个阶段，计算的结果与修正的SCG模型所给出的剪切模量的差别不超过4%，这一差别是在动高压实验误差范围之内的，在熔化区所给出的剪切模量与现有的实验数据相符合. 关键词： 剪切模量 熔化潜热 修正的SCG模型 动高压实验     

不连续不可逆二维映象的动力学特性

总结两个保守映象不可逆地分段连续链接(称为类耗散系统)以及一个保守映象与一个耗散映象不可逆地分段连续链接(称为半耗散系统)情况下得到的五项共同动力学特征：不连续边界象集构成的随机网成为唯一的混沌轨道；由于某些相点具有两个逆象而导致的相空间塌缩(类耗散)；由于系统的不连续不可逆性质而出现的胖分形禁区网；在具有吸引子共存时占据不连续边界象集随机网和胖分形禁区网区域的点滴状吸引域以及由此导致的吸引子不可预言性；即使在传统强耗散存在的情况下点滴状吸引域仍由类耗散机制主宰.以一个累积-触发电路为例，说明这五项系统动 关键词： 随机网 禁区网 点滴状吸引域     

Assessment and Prediction of Water Resources Vulnerability Based on a NRS-RF Model: A Case Study of the Song-Liao River Basin,China

The vulnerability of water resources is an important criterion for evaluating the carrying capacity of water resources systems under the influence of climate change and human activities. Moreover, assessment and prediction of river basins’ water resources vulnerability are important means to assess the water resources security state of river basins and identify possible problems in future water resources systems. Based on the constructed indicator system of water resources vulnerability assessment in Song-Liao River Basin, this paper uses the neighborhood rough set (abbreviated as NRS) method to reduce the dimensionality of the original indicator system to remove redundant attributes. Then, assessment indicators’ standard values after dimensionality reduction are taken as the evaluation sample, and the random forest regression (abbreviated as RF) model is used to assess the water resources vulnerability of the river basin. Finally, based on data under three different future climate and socio-economic scenarios, scenario predictions are made on the vulnerability of future water resources. The results show that the overall water resources vulnerability of the Song-Liao River Basin has not improved significantly in the past 18 years, and the overall vulnerability of the Song-Liao River Basin is in the level V of moderate to high vulnerability. In the future scenario 1, the overall water resources vulnerability of the river basin will improve, and it is expected to achieve an improvement to the level III of moderate to low vulnerability. At the same time, the natural vulnerability and vulnerability of carrying capacity will increase significantly in the future, and the man-made vulnerability will increase slowly, which will deteriorate to the level V of moderate to high vulnerability under Scenario 3. Therefore, taking active measures can significantly reduce the vulnerability of nature and carrying capacity, but man-made vulnerability will become a bottleneck restricting the fragility of the overall water resources of the river basin in the future.     

A Fast Approach to Removing Muscle Artifacts for EEG with Signal Serialization Based Ensemble Empirical Mode Decomposition

An electroencephalogram (EEG) is an electrophysiological signal reflecting the functional state of the brain. As the control signal of the brain–computer interface (BCI), EEG may build a bridge between humans and computers to improve the life quality for patients with movement disorders. The collected EEG signals are extremely susceptible to the contamination of electromyography (EMG) artifacts, affecting their original characteristics. Therefore, EEG denoising is an essential preprocessing step in any BCI system. Previous studies have confirmed that the combination of ensemble empirical mode decomposition (EEMD) and canonical correlation analysis (CCA) can effectively suppress EMG artifacts. However, the time-consuming iterative process of EEMD may limit the application of the EEMD-CCA method in real-time monitoring of BCI. Compared with the existing EEMD, the recently proposed signal serialization based EEMD (sEEMD) is a good choice to provide effective signal analysis and fast mode decomposition. In this study, an EMG denoising method based on sEEMD and CCA is discussed. All of the analyses are carried out on semi-simulated data. The results show that, in terms of frequency and amplitude, the intrinsic mode functions (IMFs) decomposed by sEEMD are consistent with the IMFs obtained by EEMD. There is no significant difference in the ability to separate EMG artifacts from EEG signals between the sEEMD-CCA method and the EEMD-CCA method (p > 0.05). Even in the case of heavy contamination (signal-to-noise ratio is less than 2 dB), the relative root mean squared error is about 0.3, and the average correlation coefficient remains above 0.9. The running speed of the sEEMD-CCA method to remove EMG artifacts is significantly improved in comparison with that of EEMD-CCA method (p < 0.05). The running time of the sEEMD-CCA method for three lengths of semi-simulated data is shortened by more than 50%. This indicates that sEEMD-CCA is a promising tool for EMG artifact removal in real-time BCI systems.