Script for solving the 1D diffusion equation - T(t) at x meters from dikeΒΆ

We will solve for the cooling of hot dike that was emplaced into cooler country rock. The method we are using is a simple explicit 1D finite differences scheme. This script also shows how we can record the temperature throught time at a certain distance from the dike country rock interface

First we load some useful libraries

[1]:
import numpy as np
import matplotlib.pyplot as plt
from matplotlib import animation
from matplotlib.patches import Rectangle
from IPython.display import HTML

Next we define some physics constants

[2]:
L       = 100           # Length of modeled domain [m]
Tmagma  = 1200          # Temperature of magma [C]
Trock   = 300           # Temperature of country rock [C]
kappa   = 1e-6          # Thermal diffusivity of rock [m2/s]
W       = 5;            # Width of dike [m]
day     = 60*60*24       # # seconds per day
dt      = 1*day         # Timestep [s]

and some numerical constants constants

[10]:
nx      = 201                                          # Number of gridpoints in x-direction
nt      = 500                                          # Number of timesteps to compute
Xvec,dx = np.linspace(-L/2, L/2, nx,  retstep=True)    # X coordinate vector, constant spacing
beta    = kappa*dt/dx**2
Time    = np.arange(0,nt*dt, dt)

Set the initial conditions

[11]:
T_init  = np.ones(nx)*Trock;              # everything is cold initially
T_init[np.nonzero(np.abs(Xvec) <= W/2)] = Tmagma   # and hot where the dike is
time    = 0

Make a function that computes temperature

[12]:
# hide: the code in this cell is hidden by the author
[13]:
# write a function that solves for temperature!

#def fdm_solve(Told):
#    Tnew=Told.copy()
#    for i in range(1,len(Xvec)-1):
#        Tnew[i] = ???
#    return Tnew
[14]:
# temperature close to dike
# x_test = 5 + W/2
# idx = ??? find index closest to 5m from dike/country rock interface
# T_x     = np.empty(Time.shape) # initialize T_x array for storing temp at this point through time
# T_x[:]  = np.nan
[15]:
# hide: the code in this cell is hidden by the author

Compute and visualize everything

[16]:
# First set up the figure, the axis, and the plot element we want to animate
fig, (ax1, ax2) = plt.subplots(2, 1, figsize=(10,7.5))

# prepare axes

# temperature (space)
ax1.set_xlim(-L/2, L/2)
ax1.set_ylim(0, Tmagma)

ax1.add_patch(Rectangle((-W/2, 0), W, 1200, alpha=0.5, color='tab:red'))
line, = ax1.plot([], [], lw=1)
marker, = ax1.plot(Xvec[idx], Trock,  marker='o', markersize=5, color="red", alpha=0.5)

timeLabel=ax1.text(0.02,0.98,'Time: ',transform=ax1.transAxes,va='top')
ax1.set_xlabel('X (m)')
ax1.set_ylabel('Temperature ($^{\circ}$C)')


#temperature (time)
ax2.set_xlim(0, Time[-1]/day)
ax2.set_ylim(0, Tmagma)
evo,  = ax2.plot([],[],lw=1)
ax2.set_xlabel('Time (day)')
ax2.set_ylabel('Temperature ($^{\circ}$C)')
tempLabel=ax2.text(0.02,0.98,'Marker temperature: ',transform=ax2.transAxes,va='top')

# Initialization function: plot the background of each frame
def init():
    line.set_data([], [])
    evo.set_data([],[])
    marker.set_data([],[])
    return line,evo,marker

# Initialize Tnew
Tnew=T_init
T_x[0] = T_init[idx]

# Animation function which updates figure data.  This is called sequentially
def animate(i):
    timeLabel._text='Time: %.1f day'%(i*dt/day)

    # use global keyword to store the latest solution and update it using fdm_solve function
    global Tnew

    Tnew=fdm_solve(Tnew)
    line.set_data(Xvec, Tnew)
    T_x[i] = Tnew[idx]
    evo.set_data(Time/day, T_x)
    marker.set_data(Xvec[idx], T_x[i])
    tempLabel._text='Marker temperature: %.1f ($^{\circ}$C)'%(T_x[i])

    return line,evo,marker

# Call the animator.  blit=True means only re-draw the parts that have changed.
anim = animation.FuncAnimation(fig, animate, init_func=init,
                               frames=nt, interval=30, blit=True)

plt.close(anim._fig)

# Call function to display the animation
#HTML(anim.to_html5_video())  # lower resolution
HTML(anim.to_jshtml())  # higher resolution

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