温度对核电站传热管阵列声透射特性的影响

为了研究温度分布对于管阵列结构中的声透射特性的影响，以核电站的实际工况为背景，构建了不同的温度场以及周期性变化的非均匀温度场，利用有限元方法进行数值模拟。结果表明：（1）温度分布会改变管阵列声透射频谱的“禁带”宽度以及中心频率位置。在同一介质中，温度变化对频率较高位置的影响大于频率较低的位置。（2）在同样为10℃的温度差下，当水的平均声速为1 653 m·s^-1、饱和水蒸气的平均声速为522.5 m·s^-1时，介质为水时的禁带宽度及中心频率位置变化较大，即声速大的介质的频谱对于温度的变化更敏感。（3）当温度差在10℃以内，在周期性变化的非均匀温度场和与均匀温度场中管阵列声透射特性在第一中心频率23 996.1 Hz之前，两频谱差别很小，在第一禁带之后会出现明显区别。该研究成果对完善核电站应用的声学检测提供了理论基础。     

基于人工神经网络的智能化架空线路应变快速解调方法北大核心

为了提高智能化光纤复合架空线路态势感知的实时性,将人工神经网络方法应用于光纤沿线应变解调,确定了神经网络的结构。编程实现了基于洛伦兹模型的最小二乘谱拟合方法和神经网络方法,采用不同信噪比和布里渊频移的布里渊谱训练神经网络,将它们应用于某光纤复合架空线路沿线光纤应变的测量,从不同角度比较了两种方法的计算结果。计算结果表明,神经网络方法能有效获得光纤沿线的布里渊频移进而获得应变,具有与谱拟合方法相似的准确性,但应变解调时间仅约为谱拟合方法的1/20000。研究结果为提高智能光纤复合架空线路态势感知的实时性提供了参考。     

纳米零价铁材料对放射性核素的 去除及机理研究进展

随着人类社会的发展，放射性铀矿的开采和使用越来越多，环境面临着越来越严重的放射性污染问题。从生物和环境的角度来看，有效地清除环境中的放射性核素是核能利用过程中最重要的问题之一。纳米零价铁（nanoscale zero valent iron, nZVI）具有较大的比表面积和较高的活性位点，能显著提高放射性污染物的修复效率。本综述的目的是展示nZVI基材料对放射性核素的高效去除能力和环境修复作用。简介了常用的nZVI基材料（表面改性或多孔材料支撑的nZVI材料）及其对放射性核素的去除效果和相互作用机制（如吸附和氧化还原）。最后，对nZVI材料的应用和挑战给出个人见解。本综述有助于为高效去除放射性核素的nZVI材料的设计指明方向，为放射性核素的高效处理处置提供新材料。     

深调峰工况下锅炉虚假水位预测

  [目的]  火电机组深调峰工况运行“虚假水位”现象严重影响机组安全运行，准确预测虚假水位出现时刻和幅度能够优化控制系统设计。  [方法]  研究思路为:将实际水位看作真实水位和虚假水位两部分的叠加，先根据能量平衡和物质平衡建立汽包水位模型计算出真实水位，再用实际水位减真实水位得到虚假水位，然后利用小波分析燃料量、汽包压力等信号与虚假水位信号在不同时间空间尺度下的相关性。  [结果]  通过对某600 MW机组深调峰负荷段运行数据进行分析，发现通过机理建模有效消除了给水流量和蒸汽流量对虚假水位信号波动的影响；在0.062 5 Hz至0.125 Hz频段，燃料量和汽包压力分别与虚假水位信号呈强相关性。  [结论]  可以辅助判断虚假水位的产生及其波动幅度。     

综合改进奇异谱分解和奇异值分解的齿轮故障特征提取方法

针对齿轮故障特征微弱，在强背景噪声下难以有效提取的问题，提出了一种改进奇异谱分解（ISSD）结合奇异值分解（SVD）的齿轮故障特征提取方法。针对奇异谱分解（SSD）算法中模态参数需凭经验选取的缺陷，基于散布熵优化算法对SSD算法进行了改进，在得到既定的一组奇异谱分量的基础上，根据峭度值最大准则筛选出了最佳奇异谱分量并进行了SVD处理，采用奇异值能量标准谱自适应地确定了信号重构阶数以还原信号和提高降噪效果。最后对信号进行包络解调以提取齿轮故障特征，将所提方法运用到仿真信号和齿轮实测信号中，并同传统包络谱、SSD包络谱以及经验模态分解结合SVD(EMD-SVD)方法进行了对比分析，结果表明，所提方法的降噪和特征提取效果更佳，能够更加有效地实现齿轮故障的判别。     

Assignment of inter-die signals in a simplified wiring model for die-stacking SiP designs

Compared with traditional flow in IC designs, the assignment of the inter-die signals between different dies is an important stage in a die-stacking SiP design. In this paper, given a tolerant spacing rule between two inter-die signals, the crossing constraint between two inter-die signals can be firstly defined for the bonding wires in a die-stacking SiP design with a simplified wiring model [7]. Furthermore, based on the connection constraint on any inter-die signal, the capacity constraint on any assigned pad on dies and the crossing constraint between two inter-die signals, an integer linear programming-based (ILP-based) approach is proposed to assign all the inter-die signals to minimize the total wirelength in a die-stacking SiP design. Compared with Lin’s two-stage approach [4] for some tested examples without a tolerant spacing distance between two inter-die signals in an Euclidean wiring model, the experimental results show that our proposed ILP-based approach increases 4.5% of CPU time and reduces 6.2% of total wirelength to assign all the inter-die signals on the average. Besides that, compared with Yan’s iterative approach [6] for some tested examples without a tolerant spacing distance between two inter-die signals in an Euclidean wiring model, the experimental results show that our proposed ILP-based approach uses reasonable CPU time to reduce 5.3% of total wirelength to assign all the inter-die signals on the average. Compared with Lin’s modified two-stage approach and Yan’s modified iterative approach for some dense tested examples with a tolerant spacing distance between two inter-die signals in a simplified wiring model [7], the experimental results show that Lin’s modified two-stage approach only achieves 95.9% of the assignment ratio on the average, Yan’s modified iterative approach only achieves 96.6% of the assignment ratio on the average and our proposed ILP-based approach uses reasonable CPU time to achieve 100% of the assignment ratio.     

Improving scenario decomposition algorithms for robust nonlinear model predictive control

This paper deals with the efficient computation of solutions of robust nonlinear model predictive control problems that are formulated using multi-stage stochastic programming via the generation of a scenario tree. Such a formulation makes it possible to consider explicitly the concept of recourse, which is inherent to any receding horizon approach, but it results in large-scale optimization problems. One possibility to solve these problems in an efficient manner is to decompose the large-scale optimization problem into several subproblems that are iteratively modified and repeatedly solved until a solution to the original problem is achieved. In this paper we review the most common methods used for such decomposition and apply them to solve robust nonlinear model predictive control problems in a distributed fashion. We also propose a novel method to reduce the number of iterations of the coordination algorithm needed for the decomposition methods to converge. The performance of the different approaches is evaluated in extensive simulation studies of two nonlinear case studies.     

Microstructure evolution of Ti5Si3 in Cu-Ti-Si alloys

The Cu-Ti-Si alloys containing in-situ formed Ti_5Si_3 are prepared.In order to clarify the Ti_5Si_3 formation processes and its microstructure characteristics,the as-cast and deeply etched Cu-Ti-Si alloys with different compositions and cooling rates were investigated using scanning electron microscopy (SEM),transmission electron microscopy (TEM) and X-ray diffraction (XRD).It is found that the eutectic Ti_5Si_3 phases in Cu-Ti-Si alloys are rod-like with hexagonal cross section which tend to intertwine with each other to form a firm skeleton like a bird nest structure which can make the alloys keep their original shape even after etching off the Cu matrix.In addition,there is Cu in the center of many Ti_5Si_3 rods,resulting in a core-shell structure.With the increase of the cooling rate,Ti_5Si_3 distributes more uniformly,and the diameter of Ti_5Si_3 significantly decreases,with a minimum size of less than 100 nm,while the aspect ratio of Ti_5Si_3 increases.