Upscaled DEM-CFD model for vibrated fluidized bed based on particle-scale similarities

Simulation based on discrete element method (DEM) coupled with computational fluid dynamics (CFD), coupled DEM-CFD, is a powerful tool for investigating the details of dense particle–fluid interaction problems such as in fluidized beds and pneumatic conveyers. The addition of a mechanical vibration to a system can drastically alter the particle and fluid flows; however, their detailed mechanisms are not well understood. In this study, a DEM-CFD model based on a non-inertial frame of reference is developed to achieve a better understanding of the influence of vibration in a vibrated fluidized bed. Because the high computational cost of DEM-CFD calculations is still a major problem, an upscaled coarse-graining model is also employed. To realize similar behaviors with enlarged model particles, non-dimensional parameters at the particle scale were deduced from the governing equations. The suitability and limitations of the proposed model were examined for a density segregation problem of a binary system. To reduce the computational costs, we show that the ratio between the bed width and model particle size can be reduced to a minimum value of 100; to obtain similar segregation behaviors, the ratio between the bed height and model particle size is considered unchanged.     

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.     

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。     

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。     

煤矿破碎机人员安全探测系统的研制

文中给出了煤矿人员安全探测系统设计的性能要求，详细介绍系统的硬件设计和软件设计。对利用热释电传感器实现人员定位与移动相对位置匹配算法设计进行深入细致的讨论．从防止漏报警、提高系统可靠性和降低系统功耗三个方面探讨了设计中涉及到的关键技术及其具体解决方法、与其他报警和定位系统相比，系统具有结构简单、成本低、功耗小、定位准确的特点。     

钢管内径光电检测装置

介绍了一种检测细长钢管内径的光电检测装置。该装置利用线阵ＣＣＤ作传感器，采用８０３１单片机作为主控制。