3D打印裂隙岩体动态力学性能及能量耗散规律初探

地下岩体结构经常遭受到地震、爆炸、冲击振动等产生的动力扰动，利用3D打印技术的优势研究冲击荷载下岩体动态力学性能对实现3D打印技术在工程领域的应用具有重要意义。采用φ50 mm的变截面霍普金森压杆(SHPB)装置，对含预制裂隙的3D打印岩体试样进行动态单轴压缩试验。研究结果表明：试样的动态抗压强度随着预制裂隙倾角的增大呈现出先减小后增大的趋势，当预制裂隙倾角为30°时试样强度最小，当预制裂隙倾角为90°时试样强度最大。与3D打印岩体试样的静态单轴压缩强度对比发现，3D打印砂性材料具有明显的率效应，当应变率为139.65 s^-1时，3D打印岩体试样的动态抗压强度是静态抗压强度的4.34倍。预制裂隙缺陷在一定程度上加剧了试样的能量耗散和破碎过程，并且30°倾角预制裂隙对试样能量耗散和破碎结果的影响程度最大。同时，3D打印岩体试样的能量耗散过程与破碎块度表现出明显的自相关性，所用的3D打印砂性材料的宏观破碎结果与能量耗散之间的关系与天然岩石材料有一定相似性，为今后3D打印材料模拟天然岩体应用于动态力学试验的可行性奠定了基础。     

Understanding enhancing mechanism of Pr6O11 and Pr(OH)3 in methanol electrooxidation

The presence of oxygen vacancies and hydroxyl groups are both favorable for the methanol electrooxidation on Pt-based catalysts.Understanding and differentiating the enhancing mechanism between oxygen vacancies and hydroxyl groups for high activity of Pt catalysts in methanol oxidation reaction(MOR)is essential but still challenging.Herein,we developed two kinds of co-catalyst for Pt/CNTs,Pr₆O₁₁is rich in oxygen vacancies but contains substantially no hydroxyl groups,while Pr(OH)₃ possesses abundant hydroxyl groups without oxygen vacancies.After a seque nce of designed experiments,it can be found that both oxygen vacancies and hydroxyl groups can improve the performance of Pt/CNTs electrocatalysts,but the enhancing mechanism and improving degree of oxygen vacancies and hydroxyl groups for the MOR are different.Since the oxygen vacancies are more conducive to increasing the intrinsic activity of the Pt catalyst,and the hydroxyl groups play a decisive role in dehydrogenation and deproto nation of methanol,the co-catalysts with both oxygen vacancies and hydroxyl groups mixed with Pt/CNTs have higher catalytic performance.Therefore,hydroxyl-rich Pr₆O₁₁·xH₂O was prepared and used as MOR electrocatalyst after mixed with Pt/CNTs.Benefiting from the synergistic effect of oxygen vacancies and hydroxyl groups,the Pr₆O₁₁·xH₂O/Pt/CNTs shows a high peak current density of 741 mA/mg,which is three times higher than that of Pt/CNTs.These new discoveries serve as a promising strategy for the rational design of MOR catalysts with low cost and high activity.     

基于随机搜索树法的机械臂视觉伺服研究

在当今的工业应用中,机械臂完成某一特定作业任务的基础是进行轨迹规划。针对单纯基于图像的视觉伺服(the image-based visual servoing,IBVS),不能直接对相机或机械臂的运行轨迹进行控制,容易造成跟踪目标脱离视野、机械臂与工作空间障碍物相碰撞的问题,本文提出了三维随机搜索树算法(the three-dimensional Rapidly-exploring Random Trees algorithm,3D-RRT)实现机械臂的轨迹规划,将轨迹规划与视觉伺服相融合,使机械臂在跟踪移动过程中,满足图像视野范围限制和空间障碍物约束问题。在MATLAB平台建立算法仿真实验,结果表明三维随机搜索树算法(3D-RRT)可以较好解决基于图像的视觉伺服(IBVS)中存在的问题。     

样品温度对在线pH计测量的影响

在线分析仪表的种类繁多，在工业中的应用日趋广泛。作为其中的一类分析仪表，无论按被测介质的相态来划分，还是按照测量原理来划分，在线pH计通常都被划分为简单的一类分析仪表，掌握pH计的维护一般都会作为在线分析仪表从业者技能的最低要求。然而，pH计的测量原理实际上非常复杂，运行过程中也会出现种种问题需要解决。这其中样品温度的变化导致的测量误差会经常发生。本文就着重对于样品温度对于在线pH计的影响情况进行了探讨并给出了解决方法。     

Dynamic hierarchical collaborative caching scheme in ultra-dense networks

Pushing popular contents to the edge of the network can meet the growing demand for data traffic, reduce latency and relieve the pressure of the backhaul. However, considering the limited storage space of the base stations, it is impossible to cache all the contents, especially in ultra-dense network ( UDN). Furthermore, the uneven distribution of mobile users results in load imbalance among small base stations (SBSs) in both time and space, which also affects the caching strategy. To overcome these shortcoming, the impact of the changing load imbalance in UDN was investigated, and then a dynamic hierarchical collaborative caching (DHCC) scheme was proposed to optimize latency and caching hit rate. The storage of the SBS is logically divided into the independent caching layer and the collaborative caching layer. The independent caching layer caches the most popular contents for local users爷interest, and the collaborative caching layer caches contents as much as possible for the benefit of content diversity in the region. Different SBSs have respective storage space layer division ratios, according to their real-time traffic load. For SBSs with heavy load, the independent caching layers are allocated with more space. Otherwise, the collaborative caching layers could store more contents with larger space. The simulation results show that, DHCC improved both transmission latency and hit rate compared with existing caching schemes.     

基于1D CNN与XGBoost的恶意代码纹理检测

恶意代码数量已经呈现爆炸式增长,对于恶意代码的检测防护显得尤为重要.近几年,基于深度学习的恶意代码检测方法开始出现,基于此,提出一种新的检测方法,将恶意代码二进制文件转化为十进制数组,并利用一维卷积神经网络(1 Dimention Convolutional Neural Networks,1D CNN)对数组进行分类和识别.针对代码家族之间数量不平衡的现象,该算法选择在分类预测上表现良好的XGBoost,并对Vision Research Lab中的25个不同恶意软件家族的9458个恶意软件样本进行了实验.实验结果表明,所提的方法分类预测精度达到了97％.     

基于MFD的多路网子区协调交通控制策略

为了缓解大规模路网的交通拥堵，提出了一种基于宏观基本图的多路网子区协调控制策略。首先，将实际路网划分为城市道路网络的核心区域和相邻区域，并以此以获得不同区域的宏观基本图特征。假设在路网核心区域采用控制策略，进而得到核心区域的预期溢出车辆数；计算出当相邻区域可增加的车辆数量接近核心区域的溢出车辆数量时路网核心区域的绿灯压缩时间。之后对核心区域采取应用了压缩绿色时间的控制策略，使得促进核心区域和邻近区域的交通状况趋于一致，改善整个路网的交通性能。通过实际道路网络建立了仿真路网，并利用仿真工具SUMO对上述区域控制策略的效果进行评估。仿真结果表明，基于MFD的多路网子区协调交通控制策略的实施可以提高整个路网的运行指标。     

一种改进的特征匹配算法在碎片云测量建模中的应用

为满足超高速撞击典型Whipple防护构型的损伤评估需求,利用图像处理技术对碎片云序列阴影图像进行深入研究。使用超高速序列激光阴影成像仪得到三组不同实验条件下碎片云发展过程的高清阴影图像,分别对每组最具代表性的2帧进行图像处理分析;根据碎片云图像特点以及碎片运动特性,提出了一种改进的碎片二次特征匹配算法,该方法包含碎片粗定位、特征定义及初匹配和精确匹配三步策略;通过运用改进的匹配算法,对选取的相邻两帧图片完成碎片高效匹配,并提取匹配碎片的运动参数,进而分析碎片的速度分布和飞行角度分布,获取二次碎片云相关运动特性;得到三组实验各自的轨迹模拟图。根据得到的轨迹分析结果分别对三组实验的后板损伤进行估计,并通过与防护构型的实际损伤结果进行比较,验证了该方法的有效性。