Fractal characterization for the mining crack evolution process of overlying strata based on microseismic monitoring technology

In order to study the evolution laws during the development process of the coal face overburden rock mining-induced fissure,we studied the process of evolution of overburden rock mining-induced fissures and dynamically quantitatively described its fractal laws,based on the high-precision microseismic monitoring method and the nonlinear Fractal Geometry Theory.The results show that:the overburden rock mining-induced fissure fractal dimension experiences two periodic change processes with the coal face advance,namely a Small→ Big→ Small process,which tends to be stable;the functional relationship between the extraction step distance and the overburden rock mining-induced fissure fractal dimension is a cubic curve.The results suggest that the fractal dimension reflects the evolution characteristics of the overburden rock mining-induced fissure,which can be used as an evaluation index of the stability of the overburden rock strata,and it provides theoretical guidance for stability analysis of the overburden rock strata,goaf roof control and the support movements in the mining face.     

废水的反歧化生物脱氮技术研究进展

自荷兰学者Strous等在反硝化过程中发现了生物反歧化脱氮(厌氧氨氧化)现象之后,该技术在近十余年中已经成为废水脱氮领域的研究热点问题之一.并由于低廉的运行成本和快速的脱氮效率,而使其在高氨氮废水脱氮领域中具有广阔的应用前景.本文总结了生物反歧化脱氮技术的研究与应用发展过程,并对该技术的实际工程运用前景进行了展望.     

ADC14C080在高速数据采集电路中的应用

介绍了采样速率达到80MPSP,精度为14bit的模数转换芯片ADC14C080的性能指标.设计了其ADC前端电路.在FPGA中讨论了其控制和存储逻辑.     

WSN中一种新的基于蚁群优化的路由算法

针对无线传感器网络路由中网络节点能量和生存时间受限问题,提出了一种基于蚁群优化的WSN分簇路由算法.算法引入蚁群优化,对网络覆盖区域内的节点进行分簇处理,簇内利用蚁群优化算法进行最优路径搜索.仿真结果表明:该算法能有效平衡网络节点间能耗,延长网络生存期,蚁群增强了最优路径的可靠性,进一步降低了网络能耗.     

基本地貌形态数学模型的改进

以邻域、边界等拓扑学概念为基础,引入环状邻域和分离型邻域等概念,根据任意点对地貌特征点的高差所满足的不同条件,分别推导了山、洼地、鞍部、盆地、高原、岛屿等基本地貌形态的数学模型.     

An improved strategy to synthesize graphite oxide with controllable interlayer spacing as coatings for anticorrosion application

A facile method to synthesize nanoscale graphene oxide (GO) with controllable interlayer spacing was carried out using two-step oxidation process and much less acid to improve the efficiency of the oxidation. The X-ray diffraction results demonstrated that GO had been successfully prepared from graphite because of disappearance of characteristic peaks of pristine graphite at about 2θ = 26.5° along with appearance of a sharp major peak of GO at about 2θ = 9.4°. The increased basal spacing d₀₀₁ of as-prepared GO could reach as high as 9.39 Å, suggesting higher degree of oxidation than that prepared by the classical Hummers' synthesis, and characterization results from Fourier transform infrared spectrometer, X-ray photoelectron spectroscopy, Raman spectroscopy, scanning electron microscopy and transmission electron microscopy further confirmed this conclusion. The influence of GO on anti-corrosion performance of nanocomposite coatings composited with the 2,5-dimethoxyaniline (DMA) conductive polymer was examined via potentiodynamic polarization curve tests in 3.5 wt% NaCl aqueous solution. The results demonstrated that the incorporation of GO significantly decreased the corrosion current density (i_corr = 2.62 μA/cm²) in the case of GO-PDMA coating, reflecting excellent physical isolation of GO and its synergistic effect with PDMA against the infiltration of water and corrosive electrolyte.     

Removal behavior and mechanism of silver from low concentration wastewater using cellulose aerogel modified by thiosemicarbazide

Due to the low concentration of silver in water, most of the cellulose adsorbents exhibited low removal efficiency, which greatly limited their practical applications. Herein, a cellulose aerogel modified by thiosemicarbamide (CAT) was fabricated for reducing and adsorbing silver ions from low concentration wastewater. The characterization results concluded that CAT owned a three-dimensional spongy structure with many circular microspheres and a better specific surface area (19.37 m² g⁻¹), as well as the functional groups of ─C═N⁺─H and ─(C═S)─N. The static batch adsorption experiments demonstrated that CAT could reached the maximum removal percentage of 94.94% and adsorption capacity of 42.12 mg g⁻¹ under the initial concentration of Ag(I) was 15 mg L⁻¹ and the pH value was 7. Meanwhile, the adsorption of Ag(I) on CAT was second-order reaction, and the Langmuir model could better fit the adsorption process. In addition, CAT exhibited wide pH values (1–9) adaptability and excellent adsorption performance for silver through electrostatic interaction, chelation, and reduction. This study probably provides a new method as well as important experimental data and theoretical reference for the removal of silver ions and other metals.     

Improving classification-based diagnosis of batch processes through data selection and appropriate pretreatment

This work considers the application of classification algorithms for data-driven fault diagnosis of batch processes. A novel data selection methodology is proposed which enables online classification of detected disturbances without requiring the estimation of unknown (future) process behavior, as is the case in previously reported approaches.The proposed method is benchmarked in two case studies using the Pensim process model of Birol et al. (2002) implemented in RAYMOND. Both a simple k Nearest Neighbors (k-NN) and complex Least Squares Support Vector Machine (LS-SVM) are employed for classification to demonstrate the generic nature of the proposed approach. In addition, the influence of different data pretreatment methods on the classification performance is discussed, together with a motivation for selecting the correct pretreatment steps. Finally, the influence of the number of available training batches is studied.The results demonstrate that a good classification performance can be achieved with the proposed data selection method even with a low number of faulty training batches by exploiting knowledge on the nature of the to-be-diagnosed faults in the data pretreatment. This provides a proof of concept for classification-based batch diagnosis and demonstrates the importance of incorporating process insight in the construction of data-driven process monitoring and diagnosis tools.     

Predictive control of an activated sludge process: An application to the Viikinmäki wastewater treatment plant

In this work, we discuss the application of multivariable predictive control for the activated sludge process in a full-scale municipal wastewater treatment plant. Emphasis is given to the selection of a control configuration that contributes to minimising the economic costs while improving the removal efficiency of the nitrogen compounds. For this task, a simple dynamic matrix control algorithm is favoured for controlling the nitrogen concentrations at the end of the biological process. The behaviour of the activated sludge process is reproduced in a commercial simulator that acts as a real-time testing platform and that is also used for identifying the multivariable input–output models for the predictive controller. For demonstrating the effectiveness of the proposed approach, different control configurations are considered and compared against the aeration control strategies currently used at the plant. Based on the simulation results, this work shows the potentiality of the dynamic matrix control which is able to decrease the energy consumption costs and, at the same time, reduce the ammonia peaks and nitrate concentration in the effluent.     

基于多端元混合光谱模型与Landsat影像的北京不透水层动态研究

中国正在经历快速地城市化过程,及时又准确地掌握城市化过程对我国社会经济发展具有重要的实际意义。以Landsat-TM和ETM+为主要数据源,通过多端元光谱混合分析法(MESMA)提取北京建成区不透水层的时空演变信息。在Ridd的V-I-S(植被—不透水层—土壤)概念模型框架下,基于最小噪音变换(MNF)将TM或ETM+的6个光谱波段转换成MNF空间,并定义4种端元光谱分别代表植被、高反射率地表、低反射率地表和土壤,同时构建北京建成区端元光谱数据库。然后在MATLAB软件包中实现MESMA模型程序,依次提取北京市6个时段的不透水层信息。研究结果表明:MESMA方法能够提高植被、土壤和不透水层提取精度,相对误差分别为14.6%、17.3%和11.9%。研究结论充分说明MESMA方法应用到一个时间序列的中分辨率多光谱遥感影像是非常有效的。MESMA光谱分解方法能高效实现北京城市动态变化和城市扩张的监测。