Numerical Analysis of Solid−Liquid Two-Phase Flow on Sandstone Wastewater of Hydropower Stations in a Rectangular Sedimentation Tank

2010 ◽  
Vol 49 (22) ◽  
pp. 11714-11723 ◽  
Author(s):  
X. Ling Wang ◽  
Tao Li ◽  
Jian Lang ◽  
S. Sha Zhou ◽  
L. Liang Zhang ◽  
...  
Keyword(s):  
Numerical Analysis ◽  
Two Phase Flow ◽  
Phase Flow ◽  
Two Phase ◽  
Sedimentation Tank ◽  
Solid Liquid ◽  
Hydropower Stations

scholarly journals Numerical Analysis of Bed-Load Layer As Solid/Liquid Two-Phase Flow.

1994 ◽  
pp. 11-19
Author(s):  
Hitoshi Gotoh ◽  
Tetsuro Tsujimoto ◽  
Hiroji Nakagawa
Keyword(s):  
Numerical Analysis ◽  
Two Phase Flow ◽  
Bed Load ◽  
Phase Flow ◽  
Two Phase ◽  
Solid Liquid

scholarly journals Unsteady numerical analysis of solid-liquid two-phase flow in stirred tank with double helical ribbon impeller

2017 ◽  
Author(s):  
He Bai ◽  
Xiangshan Chen ◽  
Guangyu Zhao ◽  
Chenglei Xiao ◽  
Chen Li ◽  
...  
Keyword(s):  
Numerical Analysis ◽  
Two Phase Flow ◽  
Stirred Tank ◽  
Phase Flow ◽  
Two Phase ◽  
Helical Ribbon ◽  
Solid Liquid

Numerical Analysis of Solid-Liquid Two-Phase Flow with Interaction

2003 ◽  
Vol 2003 (0) ◽  
pp. 151-152
Author(s):  
Kazuki KURODA ◽  
Fumio SHIMIZU ◽  
Kazuhiro TANAKA ◽  
Hiroshi SHIGEFUJI
Keyword(s):  
Numerical Analysis ◽  
Two Phase Flow ◽  
Phase Flow ◽  
Two Phase ◽  
Solid Liquid

scholarly journals Clustering-Based Component Fraction Estimation in Solid–Liquid Two-Phase Flow in Dredging Engineering

Sensors ◽  
2020 ◽  
Vol 20 (19) ◽  
pp. 5697
Author(s):  
Chang Sun ◽  
Shihong Yue ◽  
Qi Li ◽  
Huaxiang Wang
Keyword(s):  
Clustering Algorithm ◽  
Two Phase Flow ◽  
Low Cost ◽  
Fast Response ◽  
New Method ◽  
Phase Flow ◽  
Reference Distribution ◽  
Two Phase ◽  
Long Time ◽  
Solid Liquid

Component fraction (CF) is one of the most important parameters in multiple-phase flow. Due to the complexity of the solid–liquid two-phase flow, the CF estimation remains unsolved both in scientific research and industrial application for a long time. Electrical resistance tomography (ERT) is an advanced type of conductivity detection technique due to its low-cost, fast-response, non-invasive, and non-radiation characteristics. However, when the existing ERT method is used to measure the CF value in solid–liquid two-phase flow in dredging engineering, there are at least three problems: (1) the dependence of reference distribution whose CF value is zero; (2) the size of the detected objects may be too small to be found by ERT; and (3) there is no efficient way to estimate the effect of artifacts in ERT. In this paper, we proposed a method based on the clustering technique, where a fast-fuzzy clustering algorithm is used to partition the ERT image to three clusters that respond to liquid, solid phases, and their mixtures and artifacts, respectively. The clustering algorithm does not need any reference distribution in the CF estimation. In the case of small solid objects or artifacts, the CF value remains effectively computed by prior information. To validate the new method, a group of typical CF estimations in dredging engineering were implemented. Results show that the new method can effectively overcome the limitations of the existing method, and can provide a practical and more accurate way for CF estimation.

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