锚栓用量对纯锚固岩棉保温系统抗风压性能的影响

采用ETAG 004:2013《外墙外保温薄抹灰系统欧洲技术认证指南》中规定的静态泡沫块法,测试在单位面积上使用不同数量锚栓的岩棉板外保温系统的抗风压性能。通过试验可以得出:在混凝土墙体上单纯采用敲击式锚栓锚固岩棉板外保温系统时,拉伸强度可达12.9 k Pa;单位面积增加锚栓的使用量可以提高系统的抗拉承载力,但在不同条件下增加相同数量锚栓对系统抗风载能力提高的程度不同;在普通混凝土墙中,单纯锚固岩棉板保温系统破坏时,单个锚栓承载力平均值的最大值约为其拉拔承载力的50.3%。     

Interlayer Engineering of Molybdenum Trioxide toward High‐Capacity and Stable Sodium Ion Half/Full Batteries

Orthorhombic molybdenum trioxide (MoO₃) is one of the most promising anode materials for sodium‐ion batteries because of its rich chemistry associated with multiple valence states and intriguing layered structure. However, MoO₃ still suffers from the low rate capability and poor cycle induced by pulverization during de/sodiation. An ingenious two‐step synthesis strategy to fine tune the layer structure of MoO₃ targeting stable and fast sodium ionic diffusion channels is reported here. By integrating partially reduction and organic molecule intercalation methodologies, the interlayer spacing of MoO₃ is remarkably enlarged to 10.40 Å and the layer structural integration are reinforced by dimercapto groups of bismuththiol molecules. Comprehensive characterizations and density functional theory calculations prove that the intercalated bismuththiol (DMcT) molecules substantially enhanced electronic conductivity and effectively shield the electrostatic interaction between Na⁺ and the MoO₃ host by conjugated double bond, resulting in improved Na⁺ insertion/extraction kinetics. Benefiting from these features, the newly devised layered MoO₃ electrode achieves excellent long‐term cycling stability and outstanding rate performance. These achievements are of vital significance for the preparation of sodium‐ion battery anode materials with high‐rate capability and long cycling life using intercalation chemistry.     

Performance investigation on a novel 3D wave flow channel design for PEMFC

Flow field structure can largely determine the output performance of Polymer electrolyte membrane fuel cell. Excellent channel configuration accelerates electrochemical reactions in the catalytic layer, effectively avoiding flooding on the cathode side. In present study, a three-dimensional, multi-phase model of PEMFC with a 3D wave flow channel is established. CFD method is applied to optimize the geometry constructions of three-dimensional wave flow channels. The results reveal that 3D wave flow channel is overall better than straight channel in promoting reactant gases transport, removing liquid water accumulated in microporous layer and avoiding thermal stress concentration in the membrane. Moreover, results show the optimal flow channel minimum depth and wave length of the 3D wave flow channel are 0.45 mm and 2 mm, respectively. Due to the periodic geometric characteristics of the wave channel, the convective mass transfer is introduced, improving gas flow rate in through-plane direction. Furthermore, when the cell output voltage is 0.4 V, the current density in the novel channel is 23.8% higher than that of conventional channel.     

酸碱理论及其在有机反应中的应用研究

酸碱反应无论是在无机化学还是有机化学中,都占有极高的地位,文章以综述的形式讨论酸碱理论及其在一些重要的有机反应中应用研究。     

汽车空调的操作和应用分析

2013年国内汽车产销量超过2000万台,汽车正在快速进入中国的千家万户,但大部分车主还缺乏对汽车空调知识的了解,夏天又是空调故障多发期,如果车主了解相关汽车空调知识,在实际应用中会达到事倍功半的效果,因此介绍了一般车型的空调结构、工作原理以及特殊气候下的调节。     

Distributed learning consensus control based on neural networks for heterogeneous nonlinear multiagent systems

This paper considers a novel distributed iterative learning consensus control algorithm based on neural networks for the control of heterogeneous nonlinear multiagent systems. The system's unknown nonlinear function is approximated by suitable neural networks; the approximation error is countered by a robust term in the control. Two types of control algorithms, both of which utilize distributed learning laws, are provided to achieve consensus. In the provided control algorithms, the desired reference is considered to be an unknown factor and then estimated using the associated learning laws. The consensus convergence is proven by the composite energy function method. A numerical simulation is ultimately presented to demonstrate the efficacy of the proposed control schemes.     

深度学习识别光网络单元故障的设计与应用

为解决依赖装维上门鉴别光网络单元故障带来的不便,可以从机器视觉入手实现自动化故障识别。近年,ImageNet挑战赛的成功推动了物体识别技术的跨越式发展,特别是基于卷积的深度学习技术在视觉识别方面已经达到人类水平,为光网络单元故障的自动识别提供了技术基础。文章对识别光网络单元的工作状态进行了研究,将设备工作状态分为7个场景,提出了利用手机APP采集图片识别故障的解决方案并投入了实际生产;重点阐述了深度学习模块的设计与实现,提出一种通过算法整合的方式综合运用物体检测和图像分类算法,分3阶段逐步求精,解决了图片过滤,光网络单元型号和状态识别等问题,实现了基于计算机视觉自动识别光网络单元故障。从数据上看产品的端到端准确率超过84%,识别速度达到10 FPS,月均提供服务超过1万人次,在减少用户等待的同时节约了人力资源。     

基于关键水平的水下采油树预防性维修决策方法

为解决电液复合水下采油树在运行过程中工作环境恶劣且复杂、系统要求可靠性高、维修难度大且费用高的问题,建立基于伽马退化过程的水下采油树组件可靠度退化模型和考虑维修花费、停产损失在内的维修成本模型,建立水下采油树系统预防性维修优化目标体系,基于多目标粒子群优化算法对维修策略进行优化。建立的模型可有效描述水下采油树系统的工作特性,最优解能够满足在低维修成本的前提下系统高可靠性的工作要求。     

某进口固体废物“铁精粉”的鉴别方法探析

为了确保不进口污染环境的固体废物，针对某冒充铁精粉的进口固体废物，通过外观、成分、物相分析进行了系统的鉴别。确定样品主要为经研磨加工的氧化铁皮，属于禁止进口的固体废物——轧钢产生的氧化皮。