Construction of trace element in coal of China Database Management System: based on WebGIS

The combination of geographic information system and mineral energy data management is helpful to promote the study of mineral energy and its ecological damage and environmental pollution caused by its development and utilization, which has important application value. The Trace Elements in Coal of China Database Management System (TECC) is established in this paper, applying the techniques of B/S three-layer structure, Oracle database, AJAX and WebGIS. TECC is the first database system which aims at managing the data of trace elements in coal in China. It includes data management and analysis module, document management module, trace elements in coal data maintenance module and authority management module. The data entry specification is put forward in the present study and the spatial data is included in TECC system. The system achieves the functions of data query, analysis, management, maintenance and map browsing, thematic map drawing as well as satellite video display, which lay the foundation for the analysis of large data of trace elements in coal. It is a practical platform for the acquisition, management, exchange and sharing of trace element research and geochemical research data of coal

Energy Efficiency Optimization Design of a Forward-Swept Axial Flow Fan for Heat Pump

As one of the key components of the heat pump system, compared to that of a conventional axial fan, the blade tip area of a forward-swept axial fan is much larger than its blade root, which is the main noise source of the fan and also has an important influence on the fan efficiency. Enhancement of the aerodynamic performance and efficiency of a forward-swept axial fan was addressed by utilizing the Bezier function to parameterize the forward-swept curve on blade tops. In order to quickly select an agent model suitable for the project, an ES model was established by integration of the radial basis function model and the Kriging model. When NSGA-II was combined, multi-objective optimization was carried out with the flow rate and total pressure efficiency as optimization goals. Analysis of optimization results revealed that the optimized axial flow fan’s flow rate and total pressure efficiency were improved to some degree. At the design working point, the fan’s flow rate increased by 1.78 m³/min, while the total pressure efficiency increased by 3.0%. These results lay solid foundation for energy saving of the heat pump system

Secured green communication scheme for interference alignment based networks

In this paper, a new security and green communication scheme is proposed to the Interference-Alignment (IA) based networks. To achieve a secured communication, full-duplex receivers are utilized to transmit artificial noise (AN). Both the signals and the ANs are used to harvest energy to realize green communication. For these reasons, the feasible conditions of this scheme are analyzed first. Secondly, the average transmission rate, the secrecy performance and the harvested energy are investigated. Thirdly, an optimization scheme of simultaneous wireless information and power transfer (SWIPT) is given to optimize the information transmission and the energy harvesting efficiency. Meanwhile, an improved IA iteration algorithm is designed to eliminate both the AN and the interference. Furthermore, relay cooperation is considered and its system performance is analyzed. The simulations show that the target average transmission rate is not affected by AN, while the secrecy performance can be greatly improved. The energy harvesting efficiency is also better than the traditional schemes. As expected, the average transmission rate further is improved with the relay cooperation

Mapping of Trace Elements in Coal and Ash Research Based on a Bibliometric Analysis Method Spanning 1971–2017

Coal is the most important fossil energy used in China. The environmental impact of trace elements released in coal combustion has become one of the hottest issues in recent years. Based on a software named CiteSpace, and social network analysis (SNA), a bibliometric analysis of research into trace elements in coal and ash field during 1971–2017 is presented with the information of authors, countries, institutions, journals, hot issues and research trends in the present study. The study results indicate that: (1) Shifeng Dai, Robert B Finkelman, Guijian Liu and James C Hower have a large number of publications with great influence. (2) China (29.8%) and USA (22.2%) have high productivity in total publications. China and the USA correlate closely in the cooperative web system. (3) China University of Mining and Technology and Chinese Academy of Sciences take the leading position in the quantity of publications among all research institutions. (4) Energy and fuels, engineering and environmental science are three disciplines with the most studies in this field. (5) International Journal of Coal Geology, Fuel, Energy and Fuels and Fuel Processing Technology are the top four journals with the most publications in this field. (6) The enrichment origin and modes of occurrence of trace elements are the mainstream research related to trace elements in coal and ash. The environmental problems caused by coal combustion have promoted the development of trace elements in coal research, and human health is getting more and more popular in recent years. The study findings provide a better understanding of features of trace elements in coal and ash research, which could be taken as a reference for future studies in this field

A Novel Convolutional Neural Network Architecture for SAR Target Recognition

Among many improved convolutional neural network (CNN) architectures in the optical image classification, only a few were applied in synthetic aperture radar (SAR) automatic target recognition (ATR). One main reason is that direct transfer of these advanced architectures for the optical images to the SAR images easily yields overfitting due to its limited data set and less features relative to the optical images. Thus, based on the characteristics of the SAR image, we proposed a novel deep convolutional neural network architecture named umbrella. Its framework consists of two alternate CNN-layer blocks. One block is a fusion of six 3-layer paths, which is used to extract diverse level features from different convolution layers. The other block is composed of convolution layers and pooling layers are mainly utilized to reduce dimensions and extract hierarchical feature information. The combination of the two blocks could extract rich features from different spatial scale and simultaneously alleviate overfitting. The performance of the umbrella model was validated by the Moving and Stationary Target Acquisition and Recognition (MSTAR) benchmark data set. This architecture could achieve higher than 99% accuracy for the classification of 10-class targets and higher than 96% accuracy for the classification of 8 variants of the T72 tank, even in the case of diverse positions located by targets. The accuracy of our umbrella is superior to the current networks applied in the classification of MSTAR. The result shows that the umbrella architecture possesses a very robust generalization capability and will be potential for SAR-ART

Research on Multi-Optimal Project of Outlet Guide Vanes of Nuclear Grade Axial Flow Fan Based on Sensitivity Analysis

Nuclear grade axial flow fans are widely used in nuclear power plants for ventilation and heat dissipation and have the advantages of high efficiency and high flow rates. A nuclear grade axial flow fan with OGVs (outlet guide vanes) can recover the kinetic energy of the dynamic impeller outlet winding to increase the ventilator pressure, thus improving the ventilator efficiency; therefore, the OGVs play an essential role in the performance of the axial flow fan. Based on accurate numerical simulations, an MRGP approximation model was developed to analyse the factors affecting the OGVs duct and optimise the guide vane structure, combined with the Sobol method for sensitivity analysis. The experiments and numerical simulations show that the total pressure of the optimised model increases by 154 Pa, and the noise decreases by 4.1 dB. The multi-objective optimisation method using the parametric approach and combining it with the MRGP model is highly reliable. It provides a key design direction for optimising nuclear grade axial flow fans

Improvement of Electrical Properties of Silver Nanowires Transparent Conductive by Metal Oxide Nanoparticles Modification

At present, silver nanowire transparent conductive films (AgNWs-TCFs) still have problems such as high resistance of AgNWs network nodes, uneven distribution of resistance and poor electrical performance stability, which restrict their commercial application. Different from chemical modification, in this paper, a method of modifying AgNWs-TCFs with metal oxide nanoparticles (MONPs) is proposed, that is, ZnO, SnO2, Al2O3 and TiO2 etc., four transparent metal oxides are used as targets respectively in a magnetron sputtering process, modifying the silver nanowire network wire–wire junctions and silver nanowire in AgNWs-TCFs using active MONPs generated by magnetron sputtering. A series of AgNWs@MONPs for the AgNWs@ZnO-TCFs, AgNWs@SnO2-TCFs, AgNWs@Al2O3-TCFs and AgNWs@TiO2-TCFs were obtained. A significant decrease in the resistance of AgNWs-TCFs through the modification of MONPs was shown. Respectively, the reduction of resistance was 75.6%, 70.4%, 53.2% and 59.8% for AgNWs@ZnO-TCFs, AgNWs@SnO2-TCFs, AgNWs@Al2O3-TCFs and AgNWs@TiO2-TCFs. Correspondingly, its non-uniformity of resistance distribution was 12.5% (18.2% before), 10.0% (17.1% before), 10.1% (24.3% before) and 10.6% (13.4% before), respectively, which markedly improved the uniformity of electrical property. Respectively, their failure voltages reach 16, 16, 15 and 16 (V), so accordingly, the electrical stability is considerably enhanced. In addition, the uniformity of temperature distribution was also significantly optimized with its temperature non-uniformity of 10.4%, 8.7%, 10.3% and 9.6%, respectively. Contrast that with AgNWs@MONPs, and the failure voltages and temperature non-uniformity of AgNWs-TCFs are 12 V and 40.6%

Luminous Self-Assembled Fibers of Azopyridines and Quantum Dots Enabled by Synergy of Halogen Bond and Alkyl Chain Interactions

Herein, a simple approach for the fabrication of luminous self-assembled fibers based on halogen-bonded azopyridine complexes and oleic acid-modified quantum dots (QDs) is reported. The QDs uniformly align on the edge of the self-assembled fibers through the formation of van der Waals force between the alkyl chain of oleic acid on the QD surface and the alkyl chain of the halogen-bonded complexes, 15Br or 15I. Furthermore, the intermolecular interaction mechanism was elucidated by using Fourier-transform infrared spectroscopy (FTIR), Raman spectroscopy, and density functional theory (DFT) calculations. This approach results in retention of the fluorescence properties of the QDs in the fibers. In addition, the bromine-bonded fibers can be assembled into tailored directional fibers upon evaporation of the solvent (tetrahydrofuran) when using capillaries via the capillary force. Interestingly, the mesogenic properties of the halogen-bonded complexes are preserved in the easily prepared halogen-bonded fluorescent fibers; this provides new insight into the design of functional self-assembly materials