粉体含能材料生产与储运中的静电安全及防护

分析了静电产生的原因,阐述了粉体含能材料生产中的静电起电现象、静电的危害、静电安全性评估标准以及建立在此标准基础上的静电放电危险的评价办法,提出了粉体含能材料在生产、运输中所需要采取的静电防护措施。     

一种直升机避障电力线检测方法

电力线是一类形状细长、特征稀疏、随着视角的变化容易混淆在大量背景信息中的特殊障碍物，常规电力线检测识别算法得到的目标框对电力线所在位置的估计不够准确。为此，提出了一种相对角度估计方法，基于常规电力线目标检测与识别算法，并结合电力线相对角度估计，从而提高电力线的检测识别过程中所在位置的精度。相比电力线绝对角度回归的方法，提出的相对角度估计方法容易训练易收敛，计算量小，适用于实时性要求较高的应用场合。     

Automated prediction system of household energy consumption in cities using web crawler and optimized artificial intelligence

The supply of electrical energy is critical to convenient and comfortable living. However, people consume a large amount of energy, contributing to an energy crisis and global warming, and damaging some ecological cycles. Residential electricity consumption has greater elasticity than industrial and business consumption; it therefore has high energy-saving potential. This work establishes an automated platform, which provides information about residential electricity consumption in each city in Taiwan. Machine learning was used to forecast future residential electricity demand. A nature-inspired optimization method was applied to enhance the accuracy of the best machine learner, yielding an even better hybrid ensemble model. Performance measures indicate that the resulting model is accurate and provides effective information for reference. An automatic web-based system based on the model was combined with a web crawler and scheduled to run automatically to provide information on monthly residential electricity consumption in each county and city. By providing energy consumption information across the country, power providers and government can discuss policy and set different goals for energy use. The results of this study can facilitate the early implementation of energy-saving and carbon emission-reducing in cities and aid utility companies in establishing energy conservation guidelines.     

Stable power supply of an independent power source for a remote island using a Hybrid Energy Storage System composed of electric and hydrogen energy storage systems

We propose a self-sustaining power supply system consisting of a “Hybrid Energy Storage System (HESS)” and renewable energy sources to ensure a stable supply of high-quality power in remote islands. The configuration of the self-sustaining power supply system that can utilize renewable energy sources effectively on remote islands where the installation area is limited is investigated. It is found that it is important to select renewable energy sources whose output power curve is close to the load curve to improve the efficiency of the system. The operation methods that can increase the cost-effectiveness of the self-sustaining power supply system are also investigated. It is clarified that it is important for increasing the cost effectiveness of the self-sustaining power supply system to operate the HESS with a smaller capacity of its components by setting upper limits on the output power of the renewable energy sources and cutting the infrequent generated power.     

IRS辅助的SWIPT系统中基于能效优先的波束成形设计与优化

以智能反射面(intelligent reflecting surface,IRS)辅助的无线携能通信(simultaneous wireless information and power transfer,SWIPT)系统为背景,研究了该系统中基于能效优先的多天线发送端有源波束成形与IRS无源波束成形联合设计与优化方法。以最大化接收端的最小能效为优化目标,构造在发送端功率、接收端能量阈值、IRS相移等多约束下的非线性优化问题,用交替方向乘子法(alternating direction method of multipliers,ADMM)求解。采用Dinkelbach算法转化目标函数,通过奇异值分解(singular value decomposition,SVD)和半定松弛(semi-definite relaxation,SDR)得到发送端有源波束成形向量。采用SDR得到IRS相移矩阵与反射波束成形向量。结果表明,该系统显著降低了系统能量收集(energy harvesting,EH)接收端的能量阈值。当系统总电路功耗为?15 dBm时,所提方案的用户能效为300 KB/J。当IRS反射阵源数与发送天线数均为最大值时,系统可达最大能效。     

Application of artificial neural network method to predict the breakage properties of PGE bearing chromite ore

In the present investigation, systematic grinding experiments were conducted in a laboratory ball mill to determine the breakage properties of low-grade PGE bearing chromite ore. The population balance modeling technique was used to study the breakage parameters such as primary breakage distribution (B_{i, j}) and the specific rates of breakage (S_i). The breakage and selection function values were determined for six feed sizes. The results stated that the breakage follows the first-order grinding kinetics for all the feed sizes. It was observed that the coarser feed sizes exhibit higher selection function values than the finer feed size. Further, an artificial neural network was used to predict breakage characteristics of low-grade PGE bearing chromite ore. The predicted results obtained from the neural network modeling were close to the experimental results with a correlation of determination R² = 0.99 for both product size and selection function.     

Systematic analysis and multi-objective optimization of an integrated power and freshwater production cycle

This study represents the results of the analysis and optimization of an integrated system for cogenerating electricity and freshwater. This setup consists of a Solid Oxide Fuel cell (SOFC) for producing electricity. Unburned fuel of the SOFC is burned in the afterburner to increase the temperature of the SOFC's outlet gasses and operate a Gas turbine (GT) to produce additional power and operate the air compressor. At the bottom of this cycle, a combined setup of a Multi-Effect Desalination (MED) and Reverse Osmosis (RO) is considered to produce freshwater from the unused heat capacity of the GT's exhaust gasses. Also, a Stirling engine is used in the fuel supply line to increase the fuel's temperature. Using LNG and the Stirling engine will replace the fuel compressor with a pump which increases the system performance and eliminates the need for the expansion valve. To study the system performance a mathematical model is developed in Engineering Equation Solver (EES) program. Then, the system's simulated data from the EES has been sent to MATLAB to promote the best operating condition based on the optimization criteria. An energetic, exergetic, economic, and environmental analysis has been performed and a Non-dominated Sorting Genetic Algorithm (NSGA-II) is used to achieve the goal. The two-objective optimization is performed to maximize the exergetic efficiency of the proposed system while minimizing the system's total cost of production. This cost is a weighted distribution of the Levelized Cost of Electricity (LCOE) and Levelized Cost of freshwater (LCOW). The results showed that the exergetic and energetic efficiencies of the system can reach 73.5% and 69.06% at the optimum point. The total electricity production of the system is 99 MW. The production cost is 11.71 Cents/kWh, of which 1.04 Cents/kWh is emission-related and environmental taxes. The freshwater production rate is 42.44 kg/s which costs 4.38 USD/m³.     

多堆厂址始发事件分析探讨

多堆厂址一级概率安全评价（PSA）研究中，机组数目的增加使得建模工作量剧增，给整个核电厂的风险评估带来困难。结合已有基础，本文研究了多堆厂址始发事件分析的筛选方法，提出利用堆芯损伤频率（CDF）上下限值评估方法，分析厂址内不同机组数对厂址CDF的影响。结果表明，双机组厂址适合优先进行具体分析。针对双机组核电站，对多堆厂址内各始发事件进行筛选。结果表明，丧失厂外电、丧失热阱等事件适合建模分析，并对其他筛选结果给出后续分析建议，为多堆厂址一级PSA后续事故序列建模工作提供了重要基础。     

Oil Demand and Stocks

Current data of world oil demand. This includes international bunkers and refinery fuel. Updated on a monthly basis. Current data of oil demand from counties such as Canada, the United States of America, Japan, OECD Europe, Belgium, France, Germany, Italy, Netherlands, Spain, Sweden, the United Kingdom, Australia, Mexico, Republic of Korea, and Turkey. Updated on a monthly basis. Current data for crude oil and refined product stocks in Canada, Chile, Mexico, the United States (Western Hemisphere), France, Germany, Italy, Netherlands, Spain, the United Kingdom and Other Europe (Europe), Japan, Republic of Korea, Other Pacific (Asia‐Pacific), and Total OECD (Table 12.1) Current data for refined product stocks in the OECD Western Hemisphere, OECD Europe, OECD Asia‐Pacific and Total OECD. Products include gasoline, diesel and gasoil, and heavy fuel oil. Updated on a monthly basis (Table 12.2).     

Bioinspired Triboelectric Soft Robot Driven by Mechanical Energy

A sustainable power source is a key technical challenge for practical applications of electrically responsive soft robots, especially the required voltage is over several thousand volts. Here, a practicable new technology, triboelectric soft robot (TESR) system with the primary characteristics of power source from mechanical energy, is developed. At its heart is TESR with bioinspired architectures made of soft-deformable body and two triboelectric adhesion feet, which is driven and accurately controlled through triboelectric effect, while reaching maximum crawling speeds of 14.9 mm s⁻¹ on the acrylic surface. The characteristics of the TESR, including displacement and force, are tested and simulated under the power of a rotary freestanding triboelectric nanogenerator (RF-TENG). Crawling of TESR is successfully realized on different materials surfaces and different angle slopes under the driven of RF-TENG. Furthermore, a real-time visual monitoring platform, in which TESR carries a micro camera to transmit images in a long narrow tunnel, is also achieved successfully, indicating that it can be used for fast diagnosis in an area inaccessible to human beings in the future. This study offers a new insight into the sustainable power source technologies suitable for electrically responsive soft robots and contributes to expanding the applicability of TENGs.