Impact behavior and fractographic study of carbon nanotubes grafted carbon fiber-reinforced epoxy matrix multi-scale hybrid composites

Carbon nanotubes are the most promising reinforcement for high performance composites. Multiwall carbon nanotubes were directly grown onto the carbon fiber surface by catalytic thermal chemical vapor deposition technique. Multi-scale hybrid composites were fabricated using the carbon nanotubes grown fibers with epoxy matrix. Morphology of the grown carbon nanotubes was investigated using field emission scanning electron microscopy and transmission electron microscopy. The fabricated composites were subjected to impact tests which showed 48.7% and 42.2% higher energy absorption in Charpy and Izod impact tests respectively. Fractographic analysis of the impact tested specimens revealed the presence of carbon nanotubes both at the fiber surface and within the matrix which explained the reason for improved energy absorption capability of these composites. Carbon nanotubes presence at various cracks formed during loading provided a direct evidence of micro crack bridging. Thus the enhanced fracture strength of these composites is attributed to stronger fiber–matrix interfacial bonding and simultaneous matrix strengthening due to the grown carbon nanotubes.     

Fault handling in large water networks with online dictionary learning

Fault detection and isolation in water distribution networks is an active topic due to the nonlinearities of flow propagation and recent increases in data availability due to sensor deployment. Here, we propose an efficient two-step data driven alternative: first, we perform sensor placement taking the network topology into account; second, we use incoming sensor data to build a network model through online dictionary learning. Online learning is fast and allows tackling large networks as it processes small batches of signals at a time. This brings the benefit of continuous integration of new data into the existing network model, either in the beginning for training or in production when new data samples are gathered. The proposed algorithms show good performance in our simulations on both small and large-scale networks.     

Distributed wireless power transfer in sensor networks with multiple Mobile Chargers

We investigate the problem of efficient wireless power transfer in wireless sensor networks. In our approach, special mobile entities (called the Mobile Chargers) traverse the network and wirelessly replenish the energy of sensor nodes. In contrast to most current approaches, we envision methods that are distributed and use limited network information. We propose four new protocols for efficient charging, addressing key issues which we identify, most notably (i) what are good coordination procedures for the Mobile Chargers and (ii) what are good trajectories for the Mobile Chargers. Two of our protocols (DC, DCLK) perform distributed, limited network knowledge coordination and charging, while two others (CC, CCGK) perform centralized, global network knowledge coordination and charging. As detailed simulations demonstrate, one of our distributed protocols outperforms a known state of the art method, while its performance gets quite close to the performance of the powerful centralized global knowledge method.     

Preparation and temperature-resistance characteristics of novel dense SiAlCN ceramics

The compact green bodies, prepared via a novel solid-liquid mixing method of precursors, were successfully pyrolyzed to obtain the dense bulk SiAlCN ceramics at 1000 °C. It can be seen from their SEM that they have uniform and dense microstructure, indicating that this method can be used to prepare bulk ceramics. In order to verify that they can be used as sensor heads, their temperature-resistance characteristics and repeatability were tested. The results show that the conductive mechanism belongs to Arrhenius's Tailed-State and Extended-State in the temperature range of 500–650 °C and 650–930 °C, respectively. And it shows that SiAlCN ceramics can be used as the sensor heads for high-temperature sensors.     

纤维在沥青混合料中的应用研究

选用工程中常用的几种纤维,结合工程应用要求,试验分析了纤维的吸湿性、耐热性,并通过网篮析漏试验、动态剪切试验和沉锥试验,讨论了纤维对沥青的稳定和吸附作用,以及纤维对沥青混合料“加筋”效果和作用机理。研究表明有的纤维“吸附、稳定”性能好,而有的纤维“加筋、桥接”效果好,在应用纤维时,应根据纤维的主要特点以及沥青混合料的使用要求来选用。     

Improving Short-Circuit Current Capacity, Resistance, and Breaking Load of OPGW Constructions by Modifying Aluminium Alloy With AlB2

This article presents a method that can be applied to molten AA-6101 alloy to improve electrical properties of the aluminium part of the optical ground wire (OPGW) used in overhead transmission lines to protect phase conductors from lightning strike and to transmit signals and data. AA-6101 alloy in casting of the log as 6 m length and 178 mm diameter for extrusion has been inoculated by AlB₂ to decrease detrimental effects of Cr, Ti, V, and Zr on the conductivity of the material. After inoculation, improved billets were extruded as 9.5 mm diameter feedstock. Required wires drawn from the feedstock according to the construction types of OPGW to be tested were exposed to aging at 175°C, 6 h (T-8). Upon completion of the back-twist and performing-type stranding process, resistance, and short-circuit current capacity and breaking load of the OPGW 88/44 constructions with other metal combinations have been examined and tested to show improvement. Results are summarized in tables and graphically.     

一种多晶硅高温压力传感器

制作压力传感器时，在二氧化硅层上淀积多晶硅膜，既可利用优良的机械特性，又可保证压敏电阻与衬底间具有良好的绝缘性，由此可大大提高器件的温度特性。介绍了一种多晶硅压力传感器的原理和设计。实验结果表明，这类传感器具有灵敏度好，精度高等特点，电路工作范围为０－２５０℃，且具有良好的温度稳定性。     

一种高分辨力柔性触觉传感器

本文描述了一种基于全内反射原理，用透明橡胶材料作为波导板的柔性触觉传感器。该传感器除具有一般刚性波导板触觉传感器的高分辨力等特点外，还具有柔性好，力灵敏阈值低，不怕碰撞等特点，该传感器特别适合装在智能机器人手爪上，为机器人系统高效率地获取物体形状，位置和姿态信息，实现智能抓握物体，操作物体等功能提供了有效的手段。     

机器人手指尖六维力/力矩传感器的研制

提出一种机器人手指尖六维力／力矩传感器，并对其弹性体结构进行详细论述；分析应变量与测量量的对应关系；采用现代设计手段对弹性体进行模态分析，并介绍了传感器放大处理电路，给出实验结果。