基于复杂网络教学矿井通风网络研究

近年来复杂网络研究的兴起,发现越来越多的实际网络具有复杂网络特性,通过研究矿井通风网络的复杂网络特征,矿井通风网络的节点度分布反映了巷道间连接紧密程度;运用节点的聚类系数识别最简单角联结构;将社团结构应用于绘制矿井通风网络图,有利于提高通风网络图的自动绘制质量;并将其应用到教学矿井中。     

Modeling and experimental validation for truncated cone parts forming based on water jet incremental sheet metal forming

Dieless sheet metal forming technology has many advantages for prototypes and small batch productions, but it is limited by its accuracy. This paper introduces a water jet incremental sheet metal forming (WJISMF) technology for dieless sheet metal forming. It gave a comprehensive study on truncated cone parts forming based on WJISMF, including its forming theoretical model and experimental validation. Firstly, a theoretical model for truncated cone forming based on WJISMF was developed based on plane strain assumption and work-energy theorem. The theoretical model mainly revealed the relationships between the key process parameters (especially water jet pressure) and truncated cone parts forming angle, which was very useful to predict the forming angle in certain water jet pressure or to determine the water jet pressure for different cone angle parts. Then, to validate the theoretical model, truncated cone workpiece was manufactured on a built WJISMF machine. Experimental results show that theoretical model matched the experiment well.     

E-business technologies for xRM: Exploring the readiness of public broadcasters

This paper examines the possibilities of enhancing relationship management between public service broadcasters and their stakeholders by harnessing the potential of newest e-business technologies and concepts, such as: social media, digital and interactive TV, and mobile computing. In order to facilitate adoption of relationship management strategy, a framework for leveraging relationship management is proposed. Evaluation was performed within the e-business system of a public broadcaster. This empirical study explored the readiness and expected benefits of relationship management implementation. The research results have indicated that a public broadcaster could achieve a higher level of social responsibility, improve business sustainability, and empower communication and collaboration with all the stakeholders by using emerging technologies for relationship management activities.     

新型装配式框架结构工程技术创新

传统装配式建筑受梁、板、柱自身性能及连接节点强度限制,结构整体性和抗震性能较差。对装配式结构节点或局部区域连接、抗侧力体系、空间框架结构体系进行创新,使其结构整体性和抗震性能优于传统装配式结构。采取工厂化生产构件、装配式施工的方式,节约资源和材料,减少现场施工对场地的需求,减少建筑垃圾,实现绿色施工。     

83/44侧向进油大排量抽稠泵的研制与应用

塔河油田碳酸盐岩稠油油藏具有超深、超稠,以及高密度、高黏度、高含胶质沥青质、高含硫化氢、高矿化度的"两超五高"特点,50℃原油黏度在1500~(210×104)mPa·s之间,原油黏温拐点深度为2500~5000m,采用掺稀油降黏方式生产。常规抽稠泵受排量限制,难以满足稠油举升需求;电泵运行寿命短,成本高。为提高机采井运行寿命,降低采油成本,在常规液压反馈式抽稠泵基础上,研制CYB-83/44侧向进油大排量抽稠泵。该泵上泵筒长度10.2m,最大冲程8.7m,进油通道仅为0.2m,进油口直径达到51mm,配套8m冲程抽油机,最大理论排量可达179m3/d。根据柱塞外径尺寸,设计了两种管柱及杆柱组合方式,并分别在稠油井中进行了矿场试验。结果表明,油井地层产量增加,稀稠比下降,有效泵效提高,且与电泵相比,免修期增加,采油成本显著下降,可替代小排量电泵在超稠油区块推广应用。     

Pasting,thermal, gel texture,resistant starch and colour properties of unripe banana flour from 10 desert banana varieties cultivated in South Africa

Unripe banana flour is a potential commercial ingredient in various food products for increased resistant starch and reduced gluten contents. In the present study, the pasting (rapid visco-analysis), gel texture (penetration test), thermal (differential scanning calorimetry), colour (tri-stimulus colour indices) and the resistant starch properties of unripe banana flour produced from different dessert banana varieties (n?=?10) cultivated in South Africa, were analysed and juxtaposed to wheat and maize flour. The functional properties varied significantly (p?≤?0.05) between banana varieties, and from wheat and maize flours, to various extents. Selected functional property ranges of unripe banana, wheat and maize flours, respectively included; flour colour index (63.16–76.42, 77.34 and 80.96), paste viscosity (405.5–556.6, 124.7 and 115.6 RVU), gelatinization temperature (64.67–71.21, 71.11 and 69.95?°C), gel firmness (7.24–11.44?×?10^??2 N, 3.49?×?10^??2 N and 6.56?×?10^??2 N) and resistant starch content (19.9–47.4, 2.8 and 2.2% w/w). Multivariate analysis (principle component analysis) showed that the unripe banana flours from different varieties were distinguished from each other based on the pasting temperature. The unripe banana flours were distinguished from both wheat and maize flour based on breakdown and peak paste viscosities. The breakdown viscosity was the most positively related measure to the resistant starch content with a linear regression R-squared value of 0.898, indicating a significant role played by granule structure in resistance to enzymatic hydrolysis. The present research demonstrates that selection of appropriate dessert banana variety is important when replacing staple flours (wheat and maize) with unripe dessert banana flour as a functional ingredient.     

Investigation of immiscible Sn–Zn coatings with two-layer microstructure as anode material for Li-ion battery

The exfoliation of Sn as a result of volume expansion led to the drastic capacity decay in lithium-ion batteries. In this article, the immiscible Sn–Zn coating was successfully prepared by electrodeposition and applied as the anode material in Li-ion batteries. The physical structure and electrochemical properties were characterized by X-ray diffraction, scanning electron microscope, electron probe microanalysis and charge–discharge test, respectively. The Sn–Zn deposit displayed unique two-layer morphology composed of a Zn flat bottom layer and a Sn dendritic upper layer. The novel Sn–Zn electrodes showed noticeable improvement in cyclability compared to pure Sn film. This improvement was assigned to the characteristic of the two-layer microstructure: the Zn interlayer enhanced the binding strength between Sn dendrites and copper foil; the abundant space among these individual Sn dendrites accommodated the volume expansion during lithiation process. The two-layer Sn–Zn coatings were anticipated as potential anode materials for Li-ion batteries.     

Characteristics and Rheological Properties of Polysaccharide Nanoparticles from Edible Mushrooms (Flammulina velutipes)

Nanotechnology has become relevant in the food‐related industries, and edible mushrooms can be a potential raw material for providing satisfied edible nanomaterial. In this study, by following 3 different pretreatments (hot water or cold alkali or hot alkali) insoluble polysaccharide nanoparticles were prepared from Flammulina velutipes by wet milling and high pressure homogenization and their properties were investigated. The resultant nanoparticles were characterized by SEM, GC‐MS (for its main compositions), FTIR, XRD, and TG. The 1 wt% nanoparticle dispersions presented non‐Newtonian, shear‐thinning fluids with the viscosity in an increasing order for the hot water < cold alkali < hot alkali. Moreover, the dynamical rheological results showed differences of storage (G′) and loss (G″) moduli of these particle dispersions. It was concluded that the Flammulina velutipes‐derived polysaccharides nanoparticles have great potential applications in the food industry, for example, as emulsifiers, reinforcement agents, and bioactive carriers.     

全断面锚索施工钻机辅助支架的研制

普通锚索钻机难以在巷道帮部和底板施工,极大地制约了锚索支护的使用范围.为此,鹤煤公司六矿研制了一种可以实现全断面锚索施工的辅助支架,井在现场得到了应用.实践表明,使用该支架节省工时且安装方便,移动及维护简单,实现了全断面锚索施工.     

Fault Prediction Based on the Kernel Function for Ribbon Wireless Sensor Networks

There exist several applications of wireless sensor networks in which the reliable operation can be crucial. Fault prediction is a critical problem in reliability theory for ribbon wireless sensor networks (RWSNs). Accurate fault prediction can effectively improve the availability of the WSNs system. In this paper, we evaluated the network performance for RWSNs, studied the basic theory of kernel functions, proposed a new failure prediction method based on kernel function, and selected the radial basis function as kernel function failure prediction models from two aspects of node hardware failures and network failures for fault prediction. Theoretical evidence and experimental results have shown that the proposed algorithmic prediction method has higher accuracy of 12 and 15% than that of GRNN and PNN respectively. Finally, we provided extensive numerical results to demonstrate the usage and efficiency of the proposed algorithms and complement our theoretical analysis.