Python Thermal lattice Boltzmann model ignoring source term -- python code help please

AI Thread Summary
The discussion centers on implementing a Lattice Boltzmann Model (LBM) for simulating phase change in a thermal system using a D2Q5 lattice structure. The model addresses a one-dimensional, single-phase phase change scenario with specified boundary conditions, including constant temperature on the left wall and adiabatic conditions on the right. Key parameters include the number of nodes in the x and y directions, heat diffusion coefficient, and the number of time steps for simulation.The code initializes temperature and enthalpy matrices, along with a liquid fraction matrix to represent the phase state. The main loop consists of collision and streaming processes, where the distribution function is updated based on equilibrium calculations and boundary conditions. The model calculates temperature, enthalpy, and liquid fraction iteratively until convergence is achieved, monitoring errors to ensure accuracy. A division by zero error is noted in the code, indicating a potential issue in the phase change boundary detection logic.
Gwen
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LBM model for phase change- relevant equations found here. Also here.

Code:
#Thermal LBM
#solves 1D 1 phase phase-change
#D2Q5 Lattice

nx=100                                   # the number of nodes in x direction lattice direction
ny=5                                    # the number of nodes in y direction lattice direction
alpha=.5/3                     # heat diffusion coefficient                                   # the dimension of the problem
mstep=1000                               # the number of time step
tau=3.*alpha+0.5

Tleft=0.0                                 # left wall temperature
Tright=1.0                                # right wall temperature
k=5 # k=0,1,2,3,4,5,6,8,9

x=numpy.linspace(0,1,nx+1) #start at zero, end at 1, fill with nx+1 even spaced intervals
y=numpy.linspace(0,1,ny+1)
t=np.zeros(mstep)
s=np.zeros(mstep)
w=numpy.ones(k)                              # witghting factor
T=numpy.ones((ny+1,nx+1) )         # Temperature matrix
f= numpy.ones((k, ny+1,nx+1))                # distribution function

Hl=1
Hs=0.5
H=numpy.ones((ny+1,nx+1) )                   # Enthalpy matrix
Fl=numpy.ones((ny+1,nx+1) )                  # Liquid fraction matrix (Fl=1 for liquid, Fl=0 for solid)

##================ Initial boundary condition
w[0]=1./3. #0.0
w[1:5]=1./6. #1./4.

##================== Initial value

T[0:ny+1,0:nx+1]=1.0   #temperature in the whole region (including bottom wall)
T[0:ny+1,0]=0        #temperature on the left wall
T[0:ny+1,nx]=1.0       #temperature one node in from the right wall
T[ny,1:nx]=1.0         #temp one node in from the top wall (and one node in from left and right sides)

for i in range(nx+1):
    for j in range(ny+1):
        for l in range (k): #k=0,1,2,3,4    
            f[l,j,i]=w[l]*T[j,i]
  
##   Main loop  : comprised two parts :collision and streaming
##=====================
for n in range(mstep) :
    t[n]=n  #track the time
    time=t[n]

    epsilon=1e-8
    error=1
    Fl_old=Fl
    while error>epsilon:
        Fl_old_iter=Fl
        T_old_iter=T

# collision process
# ==========================
        for i in range(nx+1):
            for j in range(ny+1):
                    for l in range (k):
                        feq=w[l]*T[j,i]  
                        f[l,j,i]=(1.-1/tau)*f[l,j,i]+(1/tau)*feq-w[l]*(Fl[j,i]-Fl_old[j,i])
 
 #streaming process
# ==========================
        for i in range(nx):
            for j in range(ny,0,-1):  #backwards from top to bottom
                f[2,j,i]=f[2,j-1,i]

        for i in range(nx,0,-1):   #backwards from right to left
            for j in range(ny,0,-1):  #backwards from top to bottom
                f[1,j,i]=f[1,j,i-1]

        for i in range(nx,0,-1):   #backwards from right to left
            for j in range(0,ny):     #forward from bottom to second-to-top lattice node
                f[4,j,i]=f[4,j+1,i]

        for i in range(0,nx):      #forward from left to second-to-right lattice node
            for j in range(0,ny):     #forward from bottom to second-to-top lattice node
                f[3,j,i]=f[3,j,i+1]

# Boundary conditions
#  =============================
        for j in range(0,ny+1) :               #left Boundary. Dirichlet boundary condition: constant temperature.
            f[1,j,0]=( Tleft*(w[1]+w[3]) )-f[3,j,0]

        for j in range(0,ny+1):                #right Boundary. adiabatic
            f[3,j,nx]=f[1,j,nx]

        for i in range(0,nx+1):                # bottom and top Boundary
            f[4,ny,i]=f[2,ny,i]                  #adiabatic
 #================================ #calculate temperature
        for i in range(nx+1):
            for j in range(ny+1):
                sum=0.0
                for l in range (k):
                    sum=sum+f[l,j,i]
                T[j,i]=sum
        T[0:ny+1,0]=Tleft           #Dirichlet BC      
        T[0:ny+1,nx]=T[0:ny+1,nx]   #adiabatic BC        
        T[ny,1:nx]=T[ny-1,1:nx]     #adiabatic BC        
        T[0,1:nx]=T[1,1:nx]         #adiabatic BC       
#==============================   #calculate nodal enthalpy and liquid fraction
        for i in range(nx+1):
            for j in range(ny+1):
                H[j,i]=0.5*T[j,i]+0.5*Fl[j,i]
        for i in range(nx+1):
            for j in range(ny+1):
                if H[j,i]<=Hs:
                    Fl[j,i]=0
                elif H[j,i]>Hs and H[j,i] < Hl:
                    Fl[j,i]=(H[j,i]-Hs)/(Hl-Hs)
                else:
                    Fl[j,i]=1
#==============================   #convergence? If no, go back
        for i in range(nx+1):
            for j in range(ny+1):
                error_Fl=abs(np.max(np.max((Fl[j,i]-Fl_old_iter[j,i])/Fl[j,i])))
                error_T=abs(np.max(np.max((T[j,i]-T_old_iter[j,i])/T[j,i])))
                error=np.max([error_Fl, error_T])      
#find position of phase change boundary (where Fl<=0.5)  
    Fl_col=Fl[3,:]<=0.5
    max = Fl_col[0]
    index = 0
    for i in range(1,len(Fl_col)):
        if Fl_col[I] >= 0.5:
            max = Fl_col
            index = i[/I][/I]
 
        s[n]=index/nx   
#==============================[/I][/I]
 
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