Study on the relationship between the particle size distribution and the effectiveness of the K‐powder fire extinguishing agent

The relationship between the particle size distribution and the extinguishing effectiveness of the new K‐powder fire extinguishing agent has been studied experimentally, to explore the reason of the great extinguishing efficiency exhibited by the new K‐powder fire extinguishing agent on Class B fire (liquid fuel fire). The results of the experiment showed that the extinguishing effectiveness increased along with the decrease of the particle size distribution. In addition, a sharp discontinuity appeared around the limiting size, about 40 μm. The powder with the particle size below 40 μm exhibited highly effective extinguishing with the minimum effective extinguishing concentration C_xr = 23 g·m^?3, while the powder with the particle size above 40 μm exhibited little fire extinguishing efficiency. Compared with other fire extinguishing agents produced by different substances, the new K‐powder fire extinguishing has the bigger limiting size. That means, in the same particle size distribution, the new K‐powder fire extinguishing agent contains more highly effective powder than others contain, and is more effective.     

The use of bio-diesel based additive as rheology improver and pour point depressant of Nigerian waxy crude

The chemical method has proved to be the most effective mitigating method of wax deposition in petroleum system as it deals with the root cause of wax formation. Most of the commercial chemicals in the industry are very expensive and toxic. This paper aims the use of biodiesel based additives for improving the rheological behavior and pour points of waxy crude from Nigeria field. The biodiesels derived additives gave better performance than the commercial chemical and the seed oils as greatly improvement in rheology and pour point values of the waxy crude were observed     

基于SVM的煤与瓦斯突出预测模型及应用

为有效预测矿井内煤与瓦斯突出的危险程度,对其影响因素做了分析与探讨,分别构建了基于粒子群优化算法以及遗传算法支持向量机的煤与瓦斯突出预测模型,并且通过实例对两种模型预测的准确性进行了验证。分别利用单项以及综合指标、BP神经网络以及PSO-SVM模型、GA-SVM模型,对寺河煤矿二号井的突出区域进行预测比较。结果表明,PSO-SVM的预测模型不仅可以在小样本数据中预测出煤与瓦斯突出程度的大小,而且综合预测结果更加精确,其在解决矿井内煤与瓦斯突出的小样本数据中显示出更加强大、通用的性能。     

Artificial bee colony based algorithm for maximum power point tracking (MPPT) for PV systems operating under partial shaded conditions

Artificial bee colony (ABC) algorithm has several characteristics that make it more attractive than other bio-inspired methods. Particularly, it is simple, it uses fewer control parameters and its convergence is independent of the initial conditions. In this paper, a novel artificial bee colony based maximum power point tracking algorithm (MPPT) is proposed. The developed algorithm, does not allow only overcoming the common drawback of the conventional MPPT methods, but it gives a simple and a robust MPPT scheme. A co-simulation methodology, combining Matlab/Simulink™ and Cadence/Pspice™, is used to verify the effectiveness of the proposed method and compare its performance, under dynamic weather conditions, with that of the Particle Swarm Optimization (PSO) based MPPT algorithm. Moreover, a laboratory setup has been realized and used to experimentally validate the proposed ABC-based MPPT algorithm. Simulation and experimental results have shown the satisfactory performance of the proposed approach.     

Study on maximum power point tracking of photovoltaic array in irregular shadow

Traditional maximum power point tracking (MPPT) methods can hardly find global maximum power point (MPP) because output characteristics curve of photovoltaic (PV) array may have multi local maximum power points in irregular shadow, and thus easily fall into the local maximum power point. To address this drawback, Considering that sliding mode variable structure (SMVS) control strategy have such advantages as simple structure, fast response and strong robustness, and P&O method have the advantages of simple principle and convenient implementation, so a new algorithm combining SMVS control method and P&O method is proposed, besides, PI controller is applied to reduce system chattering caused by switching sliding surface. It is applied to MPPT control of PV array in irregular shadow to solve the problem of multi-peak optimization in partial shadow. In order to verity the rationality of the proposed algorithm, the experimental circuit is built, which achieves MPPT control by means of the proposed algorithm and P&O method. The experimental results show that compared with the traditional P&O algorithm, the proposed algorithm can fast track the global MPP, tracking speed increases by 60% and the relative error decreased by 20%. Moreover, the system becomes more stable near the MPP, the fluctuations of output power is greatly reduced, and thus make full use of solar energy.     

高落差粉尘扩散规律和分布特征

高溜井放矿过程中会形成强大的冲击气流引起粉尘扩散，造成严重的井下环境污染，对其进行有效治理一直是井下通风除尘的工作重心，本工作利用相似实验和数值模拟相结合的方式探究溜井放矿过程中粉尘的扩散规律和分布特征。通过改变放矿质量、矿石粒径、溜井密闭程度、含水率等因素测试不同条件下气流大小和粉尘浓度分布，并利用CFD-DPM耦合方法模拟卸矿过程中的气?固两相流，研究气流和粉尘浓度时空分布特征。结果表明，最大粉尘浓度和风速随放矿质量增加而上升，随颗粒粒径和溜井密闭程度增大而降低，且含水率越大，粉尘浓度越小，风速无明显变化，在放矿过程中矿石颗粒之间碰撞占主导作用，颗粒流呈横向分布。     

基于深度学习的人体姿态估计方法综述

基于深度学习的人体姿态估计方法旨在通过构建合适的神经网络，直接从二维的图像特征中回归出人体姿态信息。主要按照2D人体姿态估计到3D人体姿态估计的顺序，并从单人检测与多人检测、稀疏的关节点检测与密集的模型构建等方面，对近年来基于深度学习的人体姿态估计方法进行系统介绍，从而初步了解如何通过深度学习的方法得到人体姿态的各个要素，包括肢体部件的相对朝向和比例尺度、骨骼关节点的位置坐标和连接关系，甚至更为复杂的人体蒙皮模型信息。最后,对当前研究面临的挑战以及未来的热点动向进行概述，清晰地呈现出该领域的发展脉络。     

氧化石墨烯改性碳纤维复合材料抗冲击行为研究

使用单层纳米氧化石墨烯（NGO）粒子对环氧树脂进行改性处理，采用真空辅助树脂传递模塑成型工艺制备了[±45/0/90]_2S铺层角度下的纯树脂及单层NGO改性碳纤维复合材料（CFRP）层合板。通过落锤冲击试验、超声C扫描检测、冲击后压缩试验等对纯树脂及单层NGO改性CFRP进行实验研究。结果表明，纯树脂及单层NGO改性CFRP在损伤阻抗及损伤容限实验中均存在拐点现象，且拐点出现在相同深度位置，其中纯树脂CFRP拐点位置为0.51 mm，单层NGO改性CFRP拐点位置为0.43 mm；相对于纯树脂CFRP，单层NGO改性CFRP可以显著提高复合材料的抗冲击性能及冲击后的压缩性能；通过对冲击后凹坑深度及凹坑面积进行数据模拟，可以用拟合公式实现对复合材料的损伤预测。     

A facile pathway to prepare molybdenum boride powder from molybdenum and boron carbide

Molybdenum boride is an ideal hard and wear-resistant material. In this study, a new method is proposed for preparing molybdenum boride, by which Mo first reacts with B₄C to generate the mixture of molybdenum boride and C, and then the product is decarburized by molten Ca to generate CaC₂. Pure molybdenum boride could be obtained after acid leaching to remove the by-product CaC₂. According to the experimental and thermodynamic calculation results, it is concluded that the single-phase MoB could be successfully prepared, while Mo₂B, Mo₂B₅, and MoB₄ could not be synthesized by this method. Moreover, it was found that the particle size of finally prepared MoB is determined by particle size of raw Mo powder. The residual carbon content of the product could be decreased to 0.10 wt% after first reaction at 1673 K for 6 hours and then decarburization reaction at 1673 K for 6 hours.     

析湿工况下翅片管式换热器表面粉尘沉积过程的数值模型

空调器采用翅片管式换热器作为蒸发器，在制冷工况下换热器表面发生析湿及粉尘沉积，导致性能衰减。建立湿翅片表面粉尘颗粒物沉积过程的数学模型，模拟冷凝水捕集颗粒物以及湿积灰层黏附颗粒物的过程。被冷凝水捕集的颗粒物数量等于运动轨迹与水表面轮廓会出现相交的入射颗粒物的数量；后续的入射颗粒物与湿积灰层碰撞时，部分入射颗粒物会发生沉积且部分被碰撞的已沉积湿颗粒物会发生移除，这两部分的颗粒物数量相减即为被湿积灰层黏附的颗粒物数量。模拟与实验结果的对比表明，预测的湿积灰层形状与实验照片的吻合度较好，预测的单位面积颗粒物沉积质量与91%的实验数据之间的误差在±20%之间，平均误差为11.8%。