Visualizing Test on the Distribution Rule of Coarse Particles in a Double Blade Pump

2019 ◽  
Author(s):  
Xianfang Wu ◽  
Xiao Tian ◽  
Minggao Tan ◽  
Houlin Liu
Keyword(s):  
Particle Concentration ◽  
Two Phase Flow ◽  
Particle Density ◽  
Particle Diameter ◽  
Phase Flow ◽  
Coarse Particles ◽  
Two Phase ◽  
Solid Liquid ◽  
Blade Pump ◽  
Flow Pump

Abstract As a typical fluid mechanics problem, pump blockage has always been a hot research topic. The obtaining of the distribution of coarse particles in the solid-liquid two-phase flow pump is the basis of improving its non-blocking performance. High-speed photography technique is applied to do visualizing test and research on the distribution of coarse particles in a double blade pump. The effects of particle concentration, particle density and particle diameter on the distribution of coarse particles in the solid-liquid two-phase flow pump at different phases are studied. Besides, the variation of hydraulic performance of the double blade pump under different parameters is also analyzed. The results show that the particles in the impeller mainly located in the vicinity of the blade pressure surface, and the distribution of the particles in each section of the volute is quite different. The great difference in particle density can result in obviously uneven distribution of particles. With the increase of particle diameter, particle density and particle concentration, the pump head and efficiency both decrease while the shaft power increase on the contrary. This research results can also provide a basis for the optimization design of solid-liquid two-phase flow pumps.

Experimental Resistance Measurement on Solid-Liquid Two-Phase Flow in Microchannel

2012 ◽  
Vol 239-240 ◽  
pp. 353-358
Author(s):  
Yong Hong Liu ◽  
Je Eun Choi ◽  
Masahiro Takei ◽  
Xian Tao Wang
Keyword(s):  
Rate Control ◽  
Particle Concentration ◽  
Single Phase ◽  
Two Phase Flow ◽  
Measuring Instruments ◽  
Phase Flow ◽  
Two Phase ◽  
Flow Phenomena ◽  
Flow Rate Control ◽  
Solid Liquid

Monitoring the flow behaviour on the micro-scale is very important in many industrial and biochemical process, the multiphase coexistence in microchannel provide many attractive characteristics compared to a single-phase flow. The precise flow rate control and well-defined channel geometries make it possible for us to make detailed investigation on multiphase flow phenomena. This paper aims at the measurement of resistance distribution in the cross-section of a novel microchannel based on the Agilent measuring instruments. Experimental results verified the possibility of estimation on particle concentration in the solid-liquid two-phase flow by the measurement of resistance distribution in the microchannel.

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.

scholarly journals Investigations of Gas–Particle Two-Phase Flow in Swirling Combustor by the Particle Stokes Numbers

Processes ◽  
2021 ◽  
Vol 9 (6) ◽  
pp. 951
Author(s):  
Yang Liu ◽  
Guohui Li
Keyword(s):  
Two Phase Flow ◽  
Particle Diameter ◽  
Tangential Direction ◽  
Stokes Number ◽  
Order Moment ◽  
Frictional Stress ◽  
Phase Flow ◽  
Two Phase ◽  
Close Relationship ◽  
Experimental Validations

Gas turbulence modulations and particle dispersions of swirling gas–particle two-phase flow in the combustor is investigated under the large spans of the particle Stokes numbers. To fully consider the preferential concentrations and anisotropic dispersions of a particle, a kinetic frictional stress model coupled with a second-order moment two-phase turbulent model and granular temperature equation is improved. The proposed modeling and simulations are in good agreement with the experimental validations. Results show turbulent modulations and particle dispersions exhibit strongly anisotropic characteristics, keeping a close relationship with flow structure. The axial gas velocity and RMS fluctuation velocity of 45.0-μm EGP was approximately 5.0 times and 3.0 times greater than 1000.0 μm Copper particles, and their axial particle velocity was 0.25 times and twice greater than those of 45.0 μm EGP. The degree of modulation in the axial–radial direction is larger than those of radial–tangential and axial–tangential direction. Particle dispersions are sensitive to particle diameter parameters and intensified by higher Stokes number.

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