[Canesin]

Hi all, I have tried to use cellZoneInjection to put particles in my case but I'm not understanding the behavior of the "numberDensity".

I was in the believe that the numberDensity was the number of particles per cell. Or the number of particles for the cellZone.

But reading the source file .C, it looks like it is "the number of particles per cubic meter".

http://foam.sourceforge.net/docs/cpp/a05068_source.html


Is it right ??

So, my question relies. If I provide: flowrate (kg/s), diameter (distribution) and the density is know.. why the hell do I need some particle density O.o ??

injectionModel cellZoneInjection; //Inject particles at the cloudZone

cellZoneInjectionCoeffs
{
numberDensity 5.87E+06;//Number density of particles in one cell
massFlowRate 0.0024585;//Mass per second
massTotal 0.0024585;
parcelBasisType mass;//Reference propertie
cellZone myCloud;//Cell zone to realize injection
SOI 1e-6; //Start of injection
U0 (89.4 0 0); //Initial particle velocity
sizeDistribution //Used to infere the diameter
{
type uniform;
uniformDistribution
{
minValue 1.9e-5;
maxValue 2.1e-5;
}
}
}

Is that right ?? Can someone please confirm the behavior.

[vidyadhar]

Hello Fábio César Canesin,

I have seen this post recently. I, also, want to use cellZoneInjection in openfoam4.0 or caelus.

If you have used it successfully, I request you to help me how to execute the same.
Like, I need help in setting the injection models and parameters involved in it. I am using toposetDict to create the cellZone.

Thanks in advance.

Regards,
vidyadhar

[alexlupo]

Hi,

In this type of injection, numberDensity is equal to the number of desired particles in the celZone divided by the cellZone volume. The setup is as follows (just an example for a random case):


model1
{
type cellZoneInjection;
numberDensity 2.22e11;//Number of desired particles divided by the cellZone Volume
SOI 0; //Star of Injection
cellZone cellZoneInject;//cellZone defined for injection
massTotal 3.686e-5;
parcelBasisType fixed;
nParticle 1;
U0 (0 0 0.1);
sizeDistribution
{
type normal;
normalDistribution
{
expectation 40e-6;
variance 10e-6;
minValue 30e-6;
maxValue 50e-6;
}
}
}