文献类型：期刊文献

英文题名：Flow patterns of pulverized coal pneumatic conveying and time-series analysis of pressure fluctuations

作者：Cong, Xingliang[1];Guo, Xiaolei[1];Lu, Haifeng[1];Gong, Xin[1];Liu, Kai[1];Sun, Xiaolei[1];Xie, Kai[1]

机构：[1]E China Univ Sci & Technol, Key Lab Coal Gasificat & Energy Chem Engn, Minist Educ, Shanghai Engn Res Ctr Coal Gasificat, Shanghai 200237, Peoples R China

年份：2013

卷号：101

起止页码：303

外文期刊名：CHEMICAL ENGINEERING SCIENCE

收录：;EI(收录号：20133116560928);WOS:【SCI-EXPANDED(收录号:WOS:000323603700030)】；

基金：This work was supported by the National Natural Science Foundation of China (21006027, 21206041), "the Fundamental Research Funds for the Central Universities", and "Chen Guang" project supported by Shanghai Municipal Education Commission and Shanghai Educational Development Foundation.

语种：英文

外文关键词：Transport processes; Powders; Multiphase flow; Tomography; Pressure fluctuations; Flow patterns

摘要：Flow instability is a key question which needs to be solved for the development of dense-phase pneumatic conveying. Flow patterns are closely related with flow instability. There is a gap in our knowledge of gas solid flow patterns in the dense-phase pneumatic conveying due to the lack of advanced measure technology and analysis methods. Electrical Capacitance Tomography (ECT) is an effective and advanced measure method which was used to research flow patterns in pulverized coal dense phase pneumatic conveying with solid gas ration of 60-560 kg/kg. With stack of ECT images in order of time, different How patterns were defined and classified in the horizontal and vertical pneumatic conveying systems. Plug flow, fluidized flow, slug flow and stratified flow were observed in the horizontal pneumatic conveying; there were plug flow, fluidized flow, slug flow and annular How in the vertical pneumatic conveying. The relationship between Reynolds number and Archimedes number was used to predict transition of these flow patterns. The prediction is in good agreement with experimental results in the experimental range. In addition, some analysis methods were introduced to research the flow patterns, such as the Standard Deviation (SD), Power Spectrum Density (PSD) and wavelet analysis. We found that flow stability can be represented with SD and PSD. PSD is preferred to SD for its higher resolution ratio and noise immunity. The wavelet analysis can reflect flow characteristics and energy distributions in the different scales for different flow patterns. (C) 2013 Elsevier Ltd. All rights reserved.