lbm_solver_3d_Macro_Sukop

This solver is almost similar to lbm_solver_3d expect several difference as follows:

  1. Some parameter is different

#grid resolution
nx,ny,nz = 60,50,5
#external force
fx,fy,fz = 1.0e-6,0.0,0.0
#viscosity
niu = 0.1
#import geometry
geo_name = './BC.dat'
#maximum timestep
max_timestep = 5000
#output frequency
output_fre = 100
#vtk file output frequency
vtk_fre = 500

  1. There are two array for solid flag data.

ns_np = init_geo(geo_name)
solid_np = ns_np.astype(int)
#solid_np = init_geo('./img_ftb131.txt')
solid.from_numpy(solid_np)
ns.from_numpy(ns_np)

  1. The streaming function is different

@ti.kernel
def streaming0():
    for i in ti.grouped(rho):
        if (solid[i] == 0):
            for s in ti.static(range(19)):
                ip = periodic_index(i+e[s])
                #if it is fluid f2=f otherwise apply bounce-back f2[i,s]=f[ip,LR[s]]
                f2[i,s] = f[i,s] + ns[i]*(f[ip,LR[s]] - f[i,s])


@ti.kernel
def streaming1():
    for i in ti.grouped(rho):
        if (solid[i] == 0):
            #if it is fluid apply streaming
            for s in ti.static(range(19)):
                ip = periodic_index(i+e[s])
                F[ip,s] = f2[i,s]

                #if (solid[ip]==0):
                #    F[ip,s] = f[i,s]
                #else:
                #    F[i,LR[s]] = f[i,s]
                    #print(i, ip, "@@@")
#not used
@ti.kernel
def streaming2():
    for i in ti.grouped(rho):
        for s in ti.static(range(19)):
            f[i,s] = F[i,s]

streaming3() calculates the macroscopic variable