free turbulent flow
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2014 ◽  
Vol 9 (2) ◽  
pp. JFST0014-JFST0014 ◽  
Author(s):  
Takuya KAWATA ◽  
Hoshito MAEDA ◽  
Shinnosuke OBI

2010 ◽  
pp. 327-356
Author(s):  
Meinhard T. Schobeiri

2007 ◽  
Vol 2007 ◽  
pp. 1-9 ◽  
Author(s):  
Tomomi Uchiyama ◽  
Tomohiro Degawa

This study is concerned with the two-dimensional simulation for an air-water bubbly flow around a hydrofoil. The vortex method, proposed by the authors for gas-liquid two-phase free turbulent flow in a prior paper, is applied for the simulation. The liquid vorticity field is discrerized by vortex elements, and the behavior of vortex element and the bubble motion are simultaneously computed by the Lagrangian approach. The effect of bubble motion on the liquid flow is taken into account through the change in the strength of vortex element. The bubbly flow around a hydrofoil of NACA4412 with a chord length 100 mm is simulated. The Reynolds number is2.5×105, the bubble diameter is 1 mm, and the volumetric flow ratio of bubble to whole fluid is 0.048. It is confirmed that the simulated distributions of air volume fraction and pressure agree well with the trend of the measurement and that the effect of angle of attack on the flow is favorably analyzed. These demonstrate that the vortex method is applicable to the bubbly flow analysis around a hydrofoil.


Author(s):  
R. Fesanghari ◽  
H. Basirat Tabrizi ◽  
F. Hamdullahpur

This paper is concerned with the two-dimensional gas-solid turbulent plane-mixing layer. The solid phase is considered a continuum and a two-fluid model, which is coupled by source terms due to particle drag and diffusion. Finite volume scheme has been employed for the governing equations. The simulation results show that the ratio of particle diffusion coefficient and kinematics viscosity of the carrier gas, have significant influence on the prediction of particles trend. In addition, it is observed that the loading ratio has no significant effect on the gas-solid flow prediction. The results are compared with the existed experimental data’s of others. This kind of modeling will ease the time consuming, stochastic approach of the Eulearian-Lagrangian methods but needs further investigation on the particle diffusivity term.


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