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I am trying to solve a problem with 2D Convection-Diffusion equation with U = Concentration ($mg/m^{2}$) using Implicit Upwind Finite Difference Method like this

$$ \frac{\partial U}{\partial t} + v_{y}\frac{\partial U}{\partial y} = D(\frac{\partial^{2} U}{\partial x^{2}}+ \frac{\partial^{2} U}{\partial y^{2}}) $$

Set $\sigma_D = D\frac{\Delta t}{\Delta x^{2}} = D\frac{\Delta t}{\Delta y^{2}}$ and $\sigma_{C} = \frac{v_{y}\Delta t}{\Delta y}$

I have dicretized the equation above using Implicit Upwind scheme as I have vy = -0.01 m/s going down towards the ground:

$$ U_{i,j}^{m+1}(1+4\sigma_D+\sigma_{C})-\sigma_{D}(U_{i+1,j}^{m+1}+U_{i-1,j}^{m+1} + U_{i,j+1}^{m+1})-(\sigma_{C}+\sigma_{D})U_{i,j-1}^{m+1} = U_{i,j}^{m} $$ with domain [x,y] = [10km,4km]. Dirichlet BCs are at the top, left and right of the domain and Robin BC is at the bottom (modelled as ground):

$$ D\frac{\partial U}{\partial y} - v_{y}U = 0 $$

Set $\sigma_{R} = \frac{v_{y}\Delta y}{D}$

Dicretized Robin BC using downwind method (since the wind is going down):

$$ v_{y}U_{i,1}^{m+1}-D(\frac{U_{i,1}^{m+1} - U_{i,0}^{m+1}}{\Delta y}) $$

Rearrange the equation above gives:

$$ U_{i,1}^{m+1}(\sigma_{R}-1)+U_{i,0}^{m+1}=0 $$

Initial Conditon: 1000kg of chemical is dropped in the middle of domain [5km,2km] ( U = Concentration [mg/m2] ):

$$ U_{init} = \frac{1000E6}{\Delta x \Delta y} $$

This is my sample code to run with this method:

Lx = 10E3
Ly = 4E3
dx, dy = 20, 20
nx = int(Lx/dx + 1)
ny = int(Ly/dy + 1)
D = 0.5 
x = np.linspace(0.0, Lx, nx)
y = np.linspace(0.0, Ly, ny)
mid_x = int(nx/2)
mid_y = int(ny/2)
mass = 1000E6 #mg
vy = -0.01
sigma_D = 1
dt = sigma_D * min(dx, dy)**2 / D
sigma_c = vy*dt/dy
day = 4
time = 3600*24*day
nt = int(time/dt)
def IC(nx, ny, mass, dx, dy, mid_x, mid_y):
    Dis = np.zeros((ny, nx))
    Con = mass / (dy*dx)
    Dis[mid_y, mid_x] = Con
    return Dis, Con
U0, C = IC(nx, ny, mass, dx, dy, mid_x, mid_y)

def Implicit(U0, nt, dx, dy, D, vx, vy, frn, dt, nx, ny):
    sigma_D = D*dt/(dx)**2
    sigma_c = vy*dt/dy
    sigma_R = vy*dy/D
    AA = csr_matrix((nx*ny, nx*ny)).tolil(copy = True)
    #Boundary Condition
    #Dirichlet
    for j in range(ny):
        for i in range(nx):
            AA[i + j*nx, i + j*nx] = 1
    #Inner nodes 
    for j in range(1, ny - 1):
        for i in range(1, nx - 1):
            #n + 1 side
            AA[i + j*nx, i + j*nx]     = 1 + 4*sigma_D + sigma_c
            AA[i + j*nx, i+1 + j*nx]   = -sigma_D
            AA[i + j*nx, i-1 + j*nx]   = -sigma_D
            AA[i + j*nx, i + (j+1)*nx] = -sigma_D 
            AA[i + j*nx, i + (j-1)*nx] =  -(sigma_D +sigma_c)
    #Robin BC
    for j in range(0, 1):
        for i in range(nx):
            AA[i + j*nx, i + j*nx] = -1
            AA[i + j*nx, i + (j+1)*nx] = -sigma_R + 1
    Matrix_1 = AA.tocsr()
    for n in tqdm(range(nt)):
        U0[0] = 0
        U0 = csr_matrix(U0.reshape(ny*nx, 1))
        U1 = scipy.sparse.linalg.bicgstab(Matrix_1, U0.todense())[0]

        U0 = U1.copy().reshape((ny, nx)) 
    return U0

This is what I got from the code after 4 days (3600*24*4 seconds):
Concentration Plot in 3D Concentration Plot

Total concentration over time
Total Concentration

I am not sure why my total concentration keeps losing over time. Theoretically, it should stay the same over time since when it hits the ground, it is stuck there.

I believe my boundary condition for Robin BC might be wrong but I am not sure where I went wrong. Any suggestions?

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  • $\begingroup$ I believe both your boundary conditions are not conservative. Neumann boundary conditions would be. Robin boundary condition models a heat exchange with the surroundings $\endgroup$ – VorKir Oct 21 at 0:11
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I think you have some confusion about convection-diffusion equation (CDE) as well as assuming a non-physical velocity profile here. Let's rewrite your CDE as:

$$\frac{\partial \phi}{\partial t} + \nabla \cdot (-D \nabla \phi + \mathbf{u} \phi) = 0$$

Where $\phi$ is concentration, $D$ is diffusion coefficient, and $\mathbf{u}$ is velocity profile of your fluid. You said you have three Dirichlet boundary conditions at the top, left, and right, so they are formulated as:

top: $\phi(x,y_{top}) = \phi_{top}$

left: $\phi(x_{left},y) = \phi_{left}$

right: $\phi(x_{right},y) = \phi_{right}$

and finally, as far as I understand from your description, you want to have zero flux ($\mathbf{J} = -D \nabla \phi + \mathbf{u} \phi$) at the bottom. But you need to know that putting a constant velocity in $y$ direction, is somewhat unphysical. Why? Cause you know that at the walls (left and right), your velocity must be zero, but constant velocity does not satisfy these conditions. I suggest you replace constant velocity in $y$ direction with this formula:

$$\mathbf{u} = u_{max} (x-x_{left}) (x - x_{right}) \mathbf{j}$$

You want to make sure this new velocity profile is incompressible:

$$\nabla \cdot \mathbf{u} = \frac{\partial u_{x}}{\partial x} + \frac{\partial u_{y}}{\partial y} = 0$$

Finally, you want to have outflow boundary condition at the bottom. The most popular assumption at the outflow is: diffusive flux ($-D \nabla \phi$) is negligible at the outlet in comparison to convective flux ($\phi \mathbf{u}$), So:

bottom: $-D \frac{\partial \phi}{\partial y}|_{y = y_{bottom}} = 0$

But, you need to know that the thing which will remain constant is the total mass in the region, so:

$$\frac{d\Phi}{d t} = \frac{d}{dt} \int_{\Omega} \phi d^{2} \mathbf{r} = 0$$

So, in order to check the correctiveness of your implementation, you could find $\Phi$ the total mass in the computational domain ($\Omega$) and you should not see any drift or increase in total mass.

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