Application of Computational Fluid Dynamics to Multiphase Flow in Bubble Columns

2002 ◽  
Vol 1 (1) ◽  
Author(s):  
Francesco Bertola ◽  
Marco Vanni ◽  
Giancarlo Baldi
Keyword(s):  
Fluid Dynamics ◽  
Computational Fluid Dynamics ◽  
Bubbly Flow ◽  
Liquid System ◽  
Bubble Columns ◽  
Bubble Plume ◽  
Computational Fluid Dynamics Cfd ◽  
2D And 3D ◽  
Two Fluid ◽  
Present Ability

The application of Computational Fluid Dynamics (CFD) to the simulation of bubble columns devices is discussed. A comparison between different modeling approaches has been carried out in order to understand which is the present ability of CFD codes to predict the flow in a gas–liquid system. The effect of different options of simulation, such as 2D and 3D grids with different density of cells, order of discretization, turbulence closure, has been studied for systems characterized by different values of gas hold-up. The analysis is restricted to bubbly flow conditions. Eulerian-Eulerian two fluid models have been used to describe both the time–dependent motion of the bubble plume and the time-averaged flow pattern in the column. The systems considered are those experimentally characterized by the group of Eigenberger (Becker et al., 1994), by Mudde et al. (1997), by the group of Dudukovic (Sanyal et al., 1999) and by Ho Yu and Kim (1991).

Richardson Extrapolation-Based Discretization Uncertainty Estimation for Computational Fluid Dynamics

2014 ◽  
Vol 136 (12) ◽  
Author(s):  
Tyrone S. Phillips ◽  
Christopher J. Roy
Keyword(s):  
Fluid Dynamics ◽  
Computational Fluid Dynamics ◽  
Convergence Rates ◽  
Richardson Extrapolation ◽  
Local Solution ◽  
Navier Stokes ◽  
Grid Convergence ◽  
Computational Fluid Dynamics Cfd ◽  
Grid Convergence Index ◽  
2D And 3D

This study investigates the accuracy of various Richardson extrapolation-based discretization error and uncertainty estimators for problems in computational fluid dynamics (CFD). Richardson extrapolation uses two solutions on systematically refined grids to estimate the exact solution to the partial differential equations (PDEs) and is accurate only in the asymptotic range (i.e., when the grids are sufficiently fine). The uncertainty estimators investigated are variations of the grid convergence index and include a globally averaged observed order of accuracy, the factor of safety method, the correction factor method, and least-squares methods. Several 2D and 3D applications to the Euler, Navier–Stokes, and Reynolds-Averaged Navier–Stokes (RANS) with exact solutions and a 2D turbulent flat plate with a numerical benchmark are used to evaluate the uncertainty estimators. Local solution quantities (e.g., density, velocity, and pressure) have much slower grid convergence on coarser meshes than global quantities, resulting in nonasymptotic solutions and inaccurate Richardson extrapolation error estimates; however, an uncertainty estimate may still be required. The uncertainty estimators are applied to local solution quantities to evaluate accuracy for all possible types of convergence rates. Extensions were added where necessary for treatment of cases where the local convergence rate is oscillatory or divergent. The conservativeness and effectivity of the discretization uncertainty estimators are used to assess the relative merits of the different approaches.

Experimental Study of Horizontal Bubble Plume With Computational Fluid Dynamics Benchmarking

2016 ◽  
Vol 138 (11) ◽  
Author(s):  
Shao-Wen Chen ◽  
Christopher Macke ◽  
Takashi Hibiki ◽  
Mamoru Ishii ◽  
Yang Liu ◽  
...  
Keyword(s):  
Fluid Dynamics ◽  
Computational Fluid Dynamics ◽  
Cfd Simulation ◽  
Fluid Velocity ◽  
Experimental Tests ◽  
Water Tank ◽  
Bubble Plume ◽  
Two Phase ◽  
Ansys Cfx ◽  
Computational Fluid Dynamics Cfd

In order to study the two-phase flow behaviors of a horizontal bubble plume in a tank, experimental tests along with computational fluid dynamics (CFD) simulations were carried out in this paper. An experimental facility was designed and constructed which allows air–water bubble jet being injected horizontally into a water tank by three-parallel injector nozzles with different gas and liquid superficial velocities (〈jg〉in = 2.7–5.7 m/s and 〈jf〉in = 1.8–3.4 m/s). Two sizes of injector nozzles (D = 0.053 m and 0.035 m) were tested to examine the injector size effect. Important parameters including void fraction, fluid velocity, bubble Sauter mean diameter, and their distributions in the tank were measured and analyzed. In addition to the experimental work, selected flow conditions were simulated with ANSYS CFX 13.0. Compared with the experimental data, the present CFD simulation can predict the general trends of void and flow distributions and the recirculation fluid velocity with an accuracy of ±30%. The present CFD simulation methodology has been validated by the experimental results and can be applied to bubble plume analyses and design.

scholarly journals Using a Dynamic and Constant Mesh in Numerical Simulation of the Free-Rising Bubble

Fluids ◽  
2019 ◽  
Vol 4 (1) ◽  
pp. 38 ◽  
Author(s):  
Zlatko Rek
Keyword(s):  
Fluid Dynamics ◽  
Numerical Simulation ◽  
Computational Fluid Dynamics ◽  
Bubbly Flow ◽  
Process Industry ◽  
Computational Grids ◽  
Two Phase ◽  
Efficient Operation ◽  
Rising Bubble ◽  
Computational Fluid Dynamics Cfd

A two-phase bubbly flow is often found in the process industry. For the efficient operation of such devices, it is important to know the details of the flow. The paper presents a numerical simulation of the rising bubble in a stagnant liquid column. The interFOAM solver from the open source Computational Fluid Dynamics (CFD) toolbox OpenFOAM was used to obtain the necessary data. The constant and dynamic computational grids were used in the numerical simulation. The results of the calculation were compared with the measured values. As expected, by using the dynamic mesh, the bubble trajectory was closer to the experimental results due to the more detailed description of the gas–liquid interface.

Efficiency prediction for storage chambers using computational fluid dynamics

1996 ◽  
Vol 33 (9) ◽  
pp. 163-170 ◽  
Author(s):  
Virginia R. Stovin ◽  
Adrian J. Saul
Keyword(s):  
Fluid Dynamics ◽  
Computational Fluid Dynamics ◽  
Shear Stress ◽  
Particle Tracking ◽  
Critical Value ◽  
Complex Geometries ◽  
Bed Shear Stress ◽  
Breadth Ratio ◽  
Computational Fluid Dynamics Cfd ◽  
Simulated Flow

Research was undertaken in order to identify possible methodologies for the prediction of sedimentation in storage chambers based on computational fluid dynamics (CFD). The Fluent CFD software was used to establish a numerical model of the flow field, on which further analysis was undertaken. Sedimentation was estimated from the simulated flow fields by two different methods. The first approach used the simulation to predict the bed shear stress distribution, with deposition being assumed for areas where the bed shear stress fell below a critical value (τcd). The value of τcd had previously been determined in the laboratory. Efficiency was then calculated as a function of the proportion of the chamber bed for which deposition had been predicted. The second method used the particle tracking facility in Fluent and efficiency was calculated from the proportion of particles that remained within the chamber. The results from the two techniques for efficiency are compared to data collected in a laboratory chamber. Three further simulations were then undertaken in order to investigate the influence of length to breadth ratio on chamber performance. The methodology presented here could be applied to complex geometries and full scale installations.

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