A New Method to Describe Two-Phase Solvent Extraction Based on Net Transport Potential Derived as Linear Combinations of Forward and Reverse Constituents

1998 ◽  
Vol 35 (2) ◽  
pp. 120-129 ◽  
Author(s):  
Masahiro NABESHIMA
Keyword(s):  
Solvent Extraction ◽  
New Method ◽  
Linear Combinations ◽  
Two Phase ◽  
Transport Potential

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.

Experimental Study of Two-Phase Compulsive Circulation Flows Finishing

2010 ◽  
Vol 135 ◽  
pp. 149-153 ◽  
Author(s):  
Wen Hui Li ◽  
Sheng Qiang Yang ◽  
Xiu Hong Li
Keyword(s):  
Numerical Simulation ◽  
Experimental Study ◽  
Liquid Flow ◽  
New Method ◽  
Surface Finishing ◽  
Two Phase ◽  
Nozzle Position ◽  
Main Factors

For the precise hole surface, the burr severely affects products’ performance. Considering the specific conditions of the precise hole surface finishing, a new method of two-phase compulsive circulation flows finishing is brought up. Nozzle number, nozzle position, liquid flow, etc. are main factors, which would directly influence finishing effect and efficiency. Affecting rules of main factors are studied by experiments and numerical simulation, which provide basis for thorough research.

A new method of detoxification of cottonseed by means of mixed solvent extraction

1981 ◽  
Vol 58 (2) ◽  
pp. A93-A96 ◽  
Author(s):  
Fu-Kuang Liu ◽  
S. Y. Jou ◽  
L. Y. Jung
Keyword(s):  
Solvent Extraction ◽  
Mixed Solvent ◽  
New Method

A New Method of Fault Phase Identification for High Voltage Transmission Lines Based on the Fault Component of Phase Voltage

2013 ◽  
Vol 732-733 ◽  
pp. 1056-1064
Author(s):  
Yang Chen ◽  
Yan Hu ◽  
Neng Ling Tai
Keyword(s):  
Kalman Filter ◽  
High Voltage ◽  
Transmission Lines ◽  
High Sensitivity ◽  
New Method ◽  
Phase Identification ◽  
Phase Voltage ◽  
Two Phase ◽  
Kalman Filter Algorithm ◽  
High Voltage Transmission

Since the existing fault phase identification methods can not identify all fault types quickly and accurately for high voltage transmission lines, this article proposed a new method of fault phase identification based on the fault component of phase voltage difference and the kalman filter algorithm. The method defined the fault components ratio of one phase voltage to the difference of the other two phase voltages as a fault phase identification factor. By analyzing the characteristics of fault phase identification factors in each fault type, the fault phase can be identified. Simulation results show that using the kalman filter algorithm to extract fundamental component is faster and more accurate. Meanwhile, the method can identify fault phases within half a cycle and is scarcely influenced by fault resistances, fault locations and fault initial phase angles. It also has a high sensitivity when the fault is on the side of strong source.

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