Rising Bubble

This example simulates a two-dimensional rising bubble [1].

Features

• Solver: lethe-fluid

• Two phase flow handled by the Volume of fluids (VOF) approach with phase filtering, phase sharpening, and surface tension force

• Calculation of filtered phase fraction gradient and curvature fields

• Unsteady problem handled by an adaptive BDF1 time-stepping scheme

• Post-processing of a fluid barycentric coordinate and velocity

Files Used in This Example

Both files mentioned below are located in the example’s folder (examples/multiphysics/rising-bubble).

• Parameter file: rising_bubble.prm

• Postprocessing Python script: rising_bubble.py

Description of the Case

A circular bubble with density of \(100\) and kinematic viscosity of \(0.01\) (all the units in this example are dimensionless) is defined at an initial location \((0.5, 0.5)\) in a rectangular column filled with a denser fluid (with a density of \(1000\) and kinematic viscosity of \(0.01\)). At \(t = 0\) the bubble is released to rise inside the denser fluid column. The corresponding parameter file is rising-bubble.prm.

The following schematic describes the geometry and dimensions of the simulation in the \((x,y)\) plane:

Note

On the upper and bottom walls slip boundary conditions are applied, and on side walls the boundary conditions are noslip. An external gravity field of \(-0.98\) is applied in the \(y\) direction.

Parameter File

Simulation Control

Time integration is handled by a 1st order backward differentiation scheme (bdf1), for a \(3~\text{s}\) simulation time with an initial time step of \(0.001~\text{s}\).

Note

This example uses an adaptive time-stepping method, where the time-step is modified during the simulation to keep the maximum value of the CFL condition below a given threshold. Using output frequency = 20 ensures that the results are written every \(20\) iterations. Consequently, the time increment between each vtu file is not constant.

subsection simulation control
  set method           = bdf1
  set time end         = 3
  set time step        = 0.001
  set adapt            = true
  set max cfl          = 0.8
  set output name      = rising-bubble
  set output frequency = 20
  set output path      = ./output/
end

Multiphysics

The multiphysics subsection enables to turn on (true) and off (false) the physics of interest. Here VOF is chosen. The phase filtration, interface sharpening, and surface tension force are enabled in the VOF subsection.

subsection multiphysics
  set VOF = true
end

Source Term

The source term subsection defines the gravitational acceleration:

subsection source term
  subsection fluid dynamics
    set Function expression = 0; -0.98; 0
  end
end

VOF

In the VOF subsection, three features are enabled : the interface sharpening, the phase filtration and the surface tension force.

The interface sharpening method and its parameters are explained in the Dam-Break example. The phase filtration filters the phase field used for the calculation of physical properties by stiffening the value of the phase fraction. We refer the reader to The Volume of Fluid (VOF) Method theory guide for more explanation on the phase filtration. Finally, the surface tension force computation is explained in the Static Bubble example.

subsection VOF
  subsection interface sharpening
    set enable              = true
    set threshold           = 0.5
    set interface sharpness = 1.5
    set frequency           = 50
  end

  subsection phase filtration
    set type      = tanh
    set verbosity = quiet
    set beta      = 10
  end

  subsection surface tension force
    set enable                                = true
    set phase fraction gradient filter factor = 4
    set curvature filter factor               = 1
    set output auxiliary fields               = true
  end
end

Initial Conditions

In the initial conditions, the initial velocity and initial position of the liquid phase are defined. The light phase is initially defined as a circle with a radius \(r= 0.25\) at \((x,y)=(0.5, 0.5)\). We enable the use of a projection step to ensure that the initial phase distribution is sufficiently smooth, as explained in the Static Bubble example.

subsection initial conditions
  set type = nodal
  subsection uvwp
    set Function expression = 0; 0; 0
  end
  subsection VOF
    set Function expression = if ((x-0.5) * (x-0.5) + (y-0.5) * (y-0.5) < 0.25 * 0.25 , 1, 0)

    subsection projection step
      set enable           = true
      set diffusion factor = 1
    end
  end
end

Physical Properties

We define two fluids here simply by setting the number of fluids to be \(2\). In subsection fluid 0, we set the density and the kinematic viscosity for the phase associated with a VOF indicator of \(0\). A similar procedure is done for the phase associated with a VOF indicator of \(1\) in subsection fluid 1. Then a fluid-fluid type of material interaction is added to specify the surface tension model. In this case, it is set to constant with the surface tension coefficient \(\sigma\) set to \(24.5\).

subsection physical properties
  set number of fluids = 2
  subsection fluid 0
    set density             = 1000
    set kinematic viscosity = 0.01
  end
  subsection fluid 1
    set density             = 100
    set kinematic viscosity = 0.01
  end
  set number of material interactions = 1
  subsection material interaction 0
    set type = fluid-fluid
    subsection fluid-fluid interaction
      set first fluid id              = 0
      set second fluid id             = 1
      set surface tension model       = constant
      set surface tension coefficient = 24.5
    end
  end
end

Mesh

We start off with a rectangular mesh that spans the domain defined by the corner points situated at the origin and at point \([1,2]\). The first \(1,2\) couple defines that number of initial grid subdivisions along the length and height of the rectangle. This makes our initial mesh composed of perfect squares. We proceed then to redefine the mesh globally six times by setting set initial refinement = 6.

subsection mesh
  set type               = dealii
  set grid type          = subdivided_hyper_rectangle
  set grid arguments     = 1, 2 : 0, 0 : 1, 2 : true
  set initial refinement = 6
end

Mesh Adaptation

In the mesh adaptation subsection, adaptive mesh refinement is defined for phase. min refinement level and max refinement level are \(6\) and \(9\), respectively. Since the bubble rises and changes its location, we choose a rather large fraction refinement (\(0.99\)) and moderate fraction coarsening (\(0.01\)). To capture the bubble adequately, we set initial refinement steps = 5 so that the initial mesh is adapted to ensure that the initial condition is imposed for the VOF phase with maximal accuracy.

subsection mesh adaptation
  set type                     = kelly
  set variable                 = phase
  set fraction type            = fraction
  set max refinement level     = 9
  set min refinement level     = 6
  set frequency                = 1
  set fraction refinement      = 0.99
  set fraction coarsening      = 0.01
  set initial refinement steps = 5
end

Post-processing: Fluid Barycenter Position and Velocity

To compare our simulation results to the literature, we extract the position and the velocity of the barycenter of the bubble. This generates a vof_barycenter_information.dat file which contains the position and the velocity of the barycenter of the bubble.

subsection post-processing
  set verbosity            = quiet
  set calculate barycenter = true
  set barycenter name      = vof_barycenter_information
end

Running the Simulation

Call lethe-fluid by invoking:

mpirun -np 8 lethe-fluid rising-bubble.prm

to run the simulation using eight CPU cores. Feel free to use more.

Warning

Make sure to compile lethe in Release mode and run in parallel using mpirun. This simulation takes \(\sim \,7\) minutes on \(8\) processes.

Results and Discussion

The following image shows the shape and dimensions of the bubble after \(3\) seconds of simulation, and compares it with results of [1].

A python post-processing code (rising-bubble.py) is added to the example folder to post-process the data files generated by the barycenter post-processing. Run

python3 ./rising-bubble.py output

to execute this post-processing code, where output is the directory that contains the simulation results. The results for the barycenter position and velocity of the bubble are compared with the simulations of Zahedi et al. [1] and Hysing et al. [2]. The following images show the results of these comparisons. The agreement between the two simulations is remarkable considering the coarse mesh used within this example.

Animation of the rising bubble example:

References

[1] (1,2,3)

S. Zahedi, M. Kronbichler, and G. Kreiss, “Spurious currents in finite element based level set methods for two-phase flow,” Int. J. Numer. Methods Fluids, vol. 69, no. 9, pp. 1433–1456, 2012, doi: 10.1002/fld.2643.

[2]

S. Hysing et al., “Quantitative benchmark computations of two-dimensional bubble dynamics,” Int. J. Numer. Methods Fluids, vol. 60, no. 11, pp. 1259–1288, 2009, doi: 10.1002/fld.1934.

[3]

J. U. Brackbill, D. B. Kothe, and C. Zemach, “A continuum method for modeling surface tension,” J. Comput. Phys., vol. 100, no. 2, pp. 335–354, Jun. 1992, doi: 10.1016/0021-9991(92)90240-Y.