Energy equation in nanoFluidX is implemented so that it accommodates for conduction and convection heat transfer with initial or Dirichlet boundary
conditions.
Direct export of the heat transfer coefficient on provided .stl surfaces is possible in nanoFluidX. This section clarifies some of the theoretical aspects of the implementation.
Standard SPH interpolation heavily depends on the basic premise that each particle has the so called full support.
Full support implies that the owner particles can see particles all around itself within the smoothing length of the
particle, which mathematically implies that the sum of the kernel, also known as Shepard coefficient, is equal
to one.
New viscosity-temperature coupling (viscTempCoupling) has been introduced into the nanoFluidX code as an option. Three models were implemented: polynomial, Sutherland, and power law.
Aeration-viscosity models were depracated in the 2022 release because the models involved required a set of parameters
which were difficult to obtain and/or required calibration.
Both single phase surface tension and adhesion modeling is based on the work of
Akinci et al.
Both models are capable of reproducing qualitatively realistic results, but are in
principle unphysical and cannot be generalized for an arbitrary case/simulation.
Because of this, trial-and-error tuning of the surface tension coefficient and the
adhesion coefficient is necessary if realistic fluid behavior is to be achieved.
Both adhesion and single phase surface tension models rely on a form inter-particle
force, which binds the particles together. The way the force is modeled is through a
specific kernel shape which mimics a potential energy well. In that sense, particles
tend to keep a certain distance from each other and introduce elastic forcing if the
particles get too close or too far from each other.
The equation that dictates the adhesion force is given by:(1)
While the single phase surface tension is defined by:(2)
Where,
Indicies and stand for adhesion and cohesion.
is the appropriate kernel used for each of the
forces.
is the mass of the particle.
is the distance between two interacting
particles.
and are instantaneous particle densities.
is the default density value of the particle
phase.
is the adhesion coefficient.
is the cohesion or surface tension coefficient.
The parameter is specified for each
WALL or MOVINGWALL phase. That means that the
level of adhesion can be different for every WALL or
MOVINGWALL phase. The same applies to the value for the surface tension forces. The balance
between surface tension and adhesion forces can replicate qualitatively the physical
contact angles between the fluid and the solid elements. An example of balancing
adhesion and surface tension forces is shown in Figure 1.
The adhesion model can be used in conjunction with the more physical multiphase
surface tension model. In that situation, the surface tension forces are physical
and only the adhesion model is left to be tuned, which can be a significantly easier
exercise.
Modeling Physical Behavior of Single Phase Surface Tension and Adhesion
The nanoFluidX team has performed a number of tests
resulting in the development of consistent single phase surface tension and adhesion
behavior. By consistency it is meant that if appropriate/desired behavior is found
for a given resolution and a given surface tension or adhesion coefficient such
behavior can be replicated for other resolutions by following the below
methodology.
The simulation data show that the variations of surface tension coefficient and adhesion coefficient due to particle spacing changes can be modeled as . and are case dependent and will take different values
depending on the resolution and specific phenomena of the simulation. It is
recommended to set and for surface tension and adhesion, respectively.
The procedure to obtain new or when changes is as follows:
Assume your current values are , , and .
You have a new and want to find and .
Set for surface tension and use for adhesion.
Use and or and solve for .
For example:(3)
or (4)
Use the computed above to find or .
For example,(5)
or (6)
These approximations are to save time when you want to change . They are not perfect fits and some iteration maybe
needed to find the adequate values.