sandbox/Antoonvh/test.c
Internal Waves
In a stratified fluid so-called internal waves can exist (also reffered to as gravity waves). An interesting feature of these waves is the so-called dispersion relation between the angle of wave propagation (\theta), stratification strength (N^2) and the freqency of the wave (\omega), according to,
\displaystyle \omega = N^2 \cos(\theta).
Numerical set-up
The Navier-Stokes equantions under Boussinesq approximation are solved on a 256 \times 256 miltigrid. In the centre of the domain an oscillating force exites the internal waves with a freqency corresponding to \theta = 45^o.
#include "grid/multigrid.h"
#include "navier-stokes/centered.h"
#include "tracer.h"
scalar b[];
scalar * tracers = {b};
face vector av[];
double sqN = 1,omega=pow(2,0.5)/2;
b[top]=neumann(sqN);
b[bottom]=neumann(-sqN);
int main(){
L0=30;
X0=Y0=-L0/2;
init_grid(256);
run();
}
Initialization
We initialize the simulation with a small tolerance for the Poisson problems and a very short timestepping. This is chosen so that the pressure field (p) can be ‘found’ by the solver before the rest of the simulation is done. Note that p=\frac{N^2}{2}y^2 + c with c an arbitrarry constant. In the acceleration event during the 100-th iteration the timestepping and tolerance is altered to more sensible values.
event init(i=0){
TOLERANCE=1e-10;
DT=0.000000001;
a=av;
foreach()
b[]=sqN*y;
}
event acceleration(i++){
coord del = {0,1};
foreach_face(){
av.x[]= del.x*((b[]+b[-1])/2 + 0.1*(sin(omega*t)*((sq(x)+sq(y))<1)));
}
if (i==100){
DT=0.05;
TOLERANCE=1e-5;
}
}
Output
We output a .gif file showing the evolution of the magnitude of the gradient of the buoyancy field (|\nabla b|).
event output(t+=0.5;t<=75){
fprintf(ferr,"i = %d, t = %g\n",i,t);
scalar grb[];
foreach(){
grb[]=0;
foreach_dimension()
grb[]+=sq((b[1]-b[-1])/(2*Delta));
grb[] = pow(grb[],0.5);
}
static FILE * fp = popen ("ppm2gif > grbMG2.gif", "w");
output_ppm (grb, fp, min = 0.8, max = 1.2);
}
Results
The dispersion relation appears to be statisfied. So thats good.
The next step is to perform this simulation using adaptive grids. See here.